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MALDI-TOFMS Based Protein Profiling as a Diagnostic Tool for the Analysis of Bacillus Spores and Cells


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MALDI-TOFMS BASED PROTEIN PROFILING AS A DIAGNOSTIC TOOL FOR THE ANALYSIS OF Bacillus SPORES AND CELLS By DANIELLE NICOLE DICKINSON A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2004

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Copyright 2004 by Danielle Nicole Dickinson

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For my inspiration. My grandfather, the smartest man I have ever known. You are my light and my strength, and are always in my heart. Shine on. And for my biggest fan. My mother, for everything she has sacrificed and for making me into who I am. I cant thank you enough. I am not bound to win, but I am bound to be true. I am not bound to succeed, but I am bound to live up to what light I haveAbraham Lincoln

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ACKNOWLEDGMENTS It is difficult to know where to begin to thank all of the people who made my graduate career worthwhile and helped to make my dissertation project possible. I ask them to forgive me ahead of time for the length and breadth of this list but I want an opportunity to thank everyone. I must start first with the three whom I consider my cochairs, regardless of whether UF recognizes them as such: Dr. James D. Winefordner, Dr. David H. Powell, and Dr. Kasthuri Venkateswaran. I thank Dr. Winefordner for his faith and courage in taking me under his wing and allowing me to go willy-nilly on a project that was somewhat beyond the scope of his repertoire of work. His enthusiasm and love for science I will forever try to imitate. I thank Dr. Powell, aka the leader of the mass spectrometry orphanage. His patience, love, kindness, and guidance will never be forgotten, and neither will dark matter. I thank him for allowing me the privilege to work in his facility and with his instrumentation. I dont know if he realizes what a true friend and mentor he is for us in both science and life. And I do apologize for the ambulance ride I took him on. I dont think many advisors have had to endure a ride like that! In thanking Venkat, I dont even know where to begin! This project came as far as it did thanks to him. I dont know if he even realizes its impact in the mass spectrometry arena and without his microbial guidance and spores it would have never happened. I thank him for having the patience to turn an iv

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analytical chemist into a microbiologist, for never giving up on me, and for the constant supply of wit and banter. I must pause to thank the funding sources, scarce as they seemed sometimes! I thank the NASA Graduate Student Research Program for 3 years of support on this project; and the Planetary Protection and Biotechnology Group at the Jet Propulsion Laboratory for all the funding they provided. I owe much gratitude the people in the Biotechnology and Planetary Protection Group at the Jet Propulsion Laboratory and the contacts I have made through them. I thank Karen Buxbaum for having the faith to bring me out again after a rather interesting first round. I thank Wayne, Roger, Cecilia, Shirley, and Gayan for their help and guidance the first summer I was there. I thank Mike Kempf for providing some of the first spore samples we worked on and for his help in learning the ropes of making spores myself. Most especially I thank Myron LaDuc, a guy with some of the most interesting personality quirks I have ever encountered. Turning an analytical chemist into a microbiologist was not an easy task, but he did it patiently, as long as we could listen to Dave and not my hillbilly music. I am honored to call him a colleague and friend. I thank Dr. Adam Driks at Loyola University for the spore coat mutants of B. subtilis and for being such a great wealth of knowledge on spore coats and sporulation procedures. My last trip to California would also not have been possible without a free place to camp out for 8 weeks. I thank Nay and Alicia for opening their home to me and for taking me out on the town. It was surreal and crazy to live in Hollywood for a time. I especially thank them for not being too scared when the geek was wandering around the house muttering things to herself! v

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At Kennedy Space Center (KSC), I also send thanks to Drs. Ray Wheeler, Jay Garland, Mike Roberts, and Langfang Levine, who were always willing to listen, give advice, and get me passes onto KSC where I got to run around like a kid in a candy store (oh I dont think they were supposed to know that). Back on the UF front, there are also a lot of great people and resources that deserve an abundance of praise. First and foremost I thank Kenny, aka the Bruker Reflex II. He might be old, but he works like a charm when hes in a good mood, and the picture of Kevin in the crown is present. Long live the BK crown! I thank the electronics and machine shop guys, who are incredible. In the end, they are the only reason Kenny stayed in a good mood for any length of time. I apologize to Steve for still being unable to translate the schematics. Big thanks go to all the support staff (Bev, Maribel, Beth, Lisa, Gracie, Jill, Jim, Joe, Darrius, and Matt) in the department for their help and encouragement along the way. They are the backbone that keeps this place going. I cannot forget my three favorites, Jeanne, Lori, and Romaine. On many days that I dont know what I would have done without their help and laughter. They have kept me going and tried their best to keep me on the straight, narrow, and focused path (and yes I know I am not good at it). I thank them tremendously for it all. On the technical side, I had a great deal of assistance at UF as well. Dr. Jodie Johnson, Dr. William Haskins, and Regina Wolper helped with the HPLC analysis. Igor Gornushkin developed the linear correlation software and library searching algorithms that were used. Scott and Stan in the protein core helped me get through my lengthy database searches. Dr. Denslow offered extremely helpful discussions on proteins and allowed me to use the instrumentation and database search tools in the ICBR. I thank vi

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Danielle Anderson and Qian Li for taking some SEM images of the spores. Stephanie, Greg, and Nicole offered helpful discussion on microbiology and gel electrophoresis. Dr. Rasche, initially took on the task of turning me into a microbiologist and provided me with an incubator I could use in my lab for cell growth. Her faith in me and constant encouragement have were a source of inspiration on many a frustrating day. She was so willing to give me time and assistance, both in the lab and out, and I cant thank her enough for what it has meant to me and the respect I have for her because of it. Last but certainly not least, I thank all of my family for putting up with me while I came on this journey. Most especially I thank my husband Owen, for he by far has dealt more with my graduate school blues than anyone else. I thank him for being there and for just being himself and for not running for the hills, despite my temperament during this tenure. I thank Owens family, Martin and Lonna. I am so blessed to have them as a second set of parents. I also thank PaJ, Dick, and the Sallys, for their endless encouragement and praise; it has helped me press on, each step along the way. And I thank little Ms. Lindsey for being a source of spiritual inspiration for me whether she knows it or not. I also thank all my family who has taught me the perfected art of putting the fun in dysfunction. I thank Mom, Jim, Deb, and Mike for believing in me and for making the journey all the more interesting, even while having no idea where I was heading. I love them more than they know or that I have had time to show over the last few years. My Mom is the strongest, most stubborn person alive and I am proud to be just like her. Jim, for his wisdom and guidance over the years I am deeply indebted. Mike, keep up the good work bro, you will get here one day too. To the greatest cook in the US, my sister vii

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Debbie, I am so proud of you, cooking is much more difficult than chemistry and you a doctor of Pi. E. in that area! And to the rest of my family, Grandma and Grandpa, June, Judy, Don, Cindy, and Heather, I thank them for their love and support. I also have to step back a few years and thank Dr. Pat Saulson, Dr. Brad Herbert, and Dr. Karen Sentell for steering me down this path. They are the greatest of mentors. Graduate school was made more pleasant by the presence of many good friends and colleagues. I thank the members of the Winefordner group, past and present, for your friendship. I thank my fellow orphans in the mass spec laboratory and Lydia and Jodie. I will miss the entertainment and excitement of working in the orphanage with them; it has been such a treat! I remember starting in the MS lab a lost soul. Then one at a time I got all these sisters and a brother to work with. I hope I have inspired them as much as they have inspired me. No more spore talks or blue cupcakes! Gabby, Chad, Kelly, Danielle, Tracy, Kristen, Romaine, Lori, Lani, and Violeta all made my bad days good, and my good days better, for that I cant thank them enough. If there is anyone I have arbitrally left off, I thank them from the bottom of my heart. viii

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TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................iv LIST OF TABLES ...........................................................................................................xiii LIST OF FIGURES ...........................................................................................................xv ABSTRACT ...................................................................................................................xviii CHAPTER 1 INTRODUCTION......................................................................................................20 The Genus Bacillus.....................................................................................................21 Spore Architecture and Composition..........................................................................23 Sporulation and Germination......................................................................................25 Microbial Identification and Classification................................................................27 Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOFMS).................................................................................................28 MALDI-TOFMS for Bacterial Fingerprinting...........................................................29 Research Overview.....................................................................................................32 2 OPTIMIZATION OF MATRIX AND SOLVENT CONDITIONS FOR THE EXTRACTION OF PROTEINS FROM SPORES.....................................................34 Materials and Methods...............................................................................................36 Chemicals and Reagents......................................................................................36 Sample Preparation and Mass Spectrometry.......................................................37 Results and Discussion...............................................................................................38 Initial Studies.......................................................................................................38 Acidic Modifier...................................................................................................39 Organic Modifier.................................................................................................50 Detergent Additives.............................................................................................54 Characteristics of Optimized Solvent Extraction System...................................56 Limit of Detection Study for MALDI Spore Preparations..................................57 3 SPECIES DIFFERENTIATION OF A DIVERSE SUITE OF Bacillus SPORES AND CELLS WITH MASS SPECTROMETRY BASED PROTEIN PROFILING.60 ix

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Introduction.................................................................................................................60 Materials and Methods...............................................................................................61 Bacterial Strains...................................................................................................61 Sporulation of Bacillus isolates...........................................................................62 Preparation of Vegetative Cells...........................................................................63 Sample Preparation for Mass Spectrometry........................................................63 Mass Spectrometry Analysis...............................................................................64 Spectral Processing and Statistical Methodology................................................65 Results and Discussion...............................................................................................67 Incidence of Spore-Forming Microbes from Spacecraft Associated Environments...................................................................................................67 Molecular Phylogeny of Spore-Forming Microbes.............................................67 MALDI-TOFMS Spore Profiles..........................................................................69 MALDI-TOFMS Vegetative Profiles..................................................................76 Conclusion..................................................................................................................91 4 MALDI-TOFMS COMPARED WITH OTHER POLYPHASIC TAXONOMY APPROACHES FOR THE IDENTIFICATION AND CLASSIFICATION OF Bacillus pumilus SPORES..........................................................................................93 Introduction.................................................................................................................93 Materials and Methods...............................................................................................95 Bacterial Strains...................................................................................................95 Sporulation of Bacillus isolates...........................................................................95 Vegetative Cell Growth.......................................................................................96 Metabolic profiling..............................................................................................97 16S rDNA and gyrB sequencing.........................................................................97 DNA-DNA hybridization....................................................................................97 MALDI-TOFMS protein profiling......................................................................98 Statistical processing of MALDI-TOFMS profiles.............................................99 Results.........................................................................................................................99 Metabolic fingerprinting of B. pumilus strains....................................................99 16S rDNA and gyrB sequencing.......................................................................100 DNA-DNA hybridization..................................................................................101 MALDI-TOFMS protein profiling of spore samples........................................102 MALDI-TOFMS Protein Profiling of Vegetative Cells....................................109 Discussion.................................................................................................................110 Conclusion................................................................................................................116 5 MALDI-TOFMS PROTEIN PROFILING OF Bacillus anthracis-cereus-thuringiensis GROUP SPORES...............................................................................117 Introduction...............................................................................................................117 Materials and Methods.............................................................................................119 Bacterial Strains.................................................................................................119 Sporulation of Bacillus Isolates.........................................................................119 Preparation of Vegetative Cells.........................................................................120 x

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Fatty Acid Methyl Ester (FAME) Analysis.......................................................121 MALDI-TOFMS Protein Profiling....................................................................122 Statistical Processing.........................................................................................122 Results.......................................................................................................................124 Sporulation of Bacillus Isolates.........................................................................124 FAME Analysis.................................................................................................124 MALDI-TOFMS Protein Profiling of BACT Spores........................................125 MALDI-TOFMS Protein Profiling of BACT Vegetative Cells........................141 Discussion.................................................................................................................149 Conclusion................................................................................................................153 6 PEPTIDE PROFILING AND BIOMARKER IDENTIFICATION FOR SELECTED Bacillus SPECIES................................................................................156 Introduction...............................................................................................................156 Materials and Methods.............................................................................................159 Bacterial Strains.................................................................................................159 Protein Extraction and Digestion.......................................................................159 Peptide profiling................................................................................................160 1-D Gel Electrophoresis....................................................................................160 Proteomic Analysis............................................................................................161 Results and Discussion.............................................................................................162 Peptide Profiling................................................................................................162 1-D Gel Electrophoresis....................................................................................163 Proteomic Analysis for Biomarker Identification.............................................166 Conclusions...............................................................................................................176 7 IMPACT OF ENVIRONMENTAL FACTORS AND STERILIZATION ON THE MALDI-TOFMS PROTEIN PROFILE OF SPORE SPECIES.......................178 Introduction...............................................................................................................178 Materials and Methods.............................................................................................180 MALDI-TOFMS Protein Profiling and Statistical Analysis.............................180 Bacterial Strains.................................................................................................180 Standard Sporulation in Liquid Media..............................................................181 Sporulation on Solid Media...............................................................................181 Spore Purification..............................................................................................182 Storage Conditions and Aging...........................................................................182 Radiation Exposure...........................................................................................182 Hydrogen Peroxide Exposure............................................................................183 Autoclave Exposure...........................................................................................184 Preparation of B. subtilis Sporulation Mutants..................................................184 Results and Discussion.............................................................................................185 Initial Sporulation and Purification Conditions.................................................185 Storage Conditions and Spore Aging................................................................187 Radiation Exposure...........................................................................................190 H 2 O 2 Exposure...................................................................................................193 xi

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Autoclave Exposure...........................................................................................195 Sporulation Mutants..........................................................................................202 Conclusion................................................................................................................211 8 CONCLUSIONS AND FUTURE WORK...............................................................213 LIST OF REFERENCES.................................................................................................217 BIOGRAPHICAL SKETCH...........................................................................................225 xii

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LIST OF TABLES Table page 3-1. List of Bacillus species used in this study.................................................................62 3-2. 16S rDNA sequence similarities for the various Bacillus species studied................68 3-3. Correlation values based on MALDI-TOFMS protein profiling of the spores of the Bacillus species in this study..............................................................................74 3-4. Correlation values based on MALDI-TOFMS protein profiling of the vegetative cells of the Bacillus species in this study.................................................................83 3-5. Correlation values based on MALDI-TOFMS protein profiling of vegetative cells of select Bacillus species incubated on three different growth media.............85 4-1. Strain designation, grouping, and source of Bacillus species in this study...............96 4-2. DNA-DNA hybridization of B. pumilus isolates.....................................................101 4-3. Linear correlation values obtained when comparing the Bacillus species library with the B. pumilus strains in this study.................................................................103 4-4. Correlation results based on MALDI-TOFMS protein profiles of the B. pumilus spore strains in this study.......................................................................................104 4-5. Correlation results based on MALDI-TOFMS protein profiles of selected B. pumilus vegetative cells in this study................................................................109 5-1. List of B. cereus serotype strains.............................................................................120 5-2. Results of FAME analysis for selected BACT strains............................................125 5-3. MALDI-TOFMS correlation values for BACT spore strains versus the type strain reference library using 30% formic acid as a solvent...................................132 5-4. MALDI-TOFMS correlation values for BACT spore strain library using 30% formic acid as a solvent..........................................................................................133 5-5. MALDI-TOFMS correlation values for BACT spore strain library using TFA as a solvent.............................................................................................................139 xiii

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5-6. MALDI-TOFMS correlation values for BACT vegetative cells versus the vegetative type strain reference library using30% formic acid as a solvent..........146 5-7. MALDI-TOFMS correlation values for BACT vegetative cells using 30% formic acid as a solvent..........................................................................................147 5-8. DNA:DNA Hybridization values of the BACT strains examined in this study......149 6-1. Correlation values based on the peptide profiles.....................................................163 6-2. Proteins identified from B. subtilis 168 using CLC-MS 2 ........................................167 6-3. Proteins identified from B. licheniformis using CLC-MS 2 ......................................171 6-4. Proteins identified from B. thuringiensis using CLC-MS 2 ......................................171 6-5. Proteins identified from FO-11 using CLC-MS 2 .....................................................171 6-6. Proteins identified from FO-36b using CLC-MS 2 ...................................................172 6-7. Proteins identified from SAFN-036 using CLC-MS 2 ..............................................172 6-8. Proteins identified from SAFN-029 using CLC-MS 2 ..............................................173 6-9. Proteins identified from SAFR-032 using CLC-MS 2 ..............................................173 6-10. Proteins identified from B. pumilus 7061 using CLC-MS 2 ...................................174 7-1. List and description of strains used in this study.....................................................181 7-2. Correlation values for aged spores and spores stored under different conditions...188 7-3. Correlation values for mutated B. subtilis strains....................................................206 xiv

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LIST OF FIGURES Figure page 1-1. Transmission electron microscopy image showing typical spore architecture.........24 1-2. Sporulation and germination cycle............................................................................26 2-1. Comparison of TFA versus formic acid....................................................................40 2-2. Formic acid extraction effect.....................................................................................41 2-3. Comparison of different matrix compounds and 17% formic acid modifier............42 2-4. Signal-to-noise versus solvent for calibration mix....................................................44 2-5. Signal-to-noise versus solvent for the B. subtilis 168 spore suspension...................45 2-6. Signal-to-noise versus formic acid concentrations from 10 to 60% for B. subtilis 168...........................................................................................................47 2-7. Spectra showing enhancement of biomarker signal for B. subtilis 168 when increasing formic acid concentration.......................................................................48 2-8: 1-D Gel showing the effects of increasing formic acid concentration on extraction of proteins from B. subtilis 168 spores.........................................................................49 2-9. Signal-to-noise versus formic acid concentrations from 10-60% for FO-36b spores........................................................................................................................51 2-10. Spectra showing enhancement of biomarker signal for FO-36b spores when increasing formic acid concentration.......................................................................52 2-11. Signal-to-noise versus formic acid concentrations: organic modifier effects.........53 2-12. Treatment of spores with OGP detergent................................................................55 2-13. Treatment of spores with Rapigest detergent..........................................................58 2-14. Limit of detection for B. subtilis 168 spores...........................................................59 3-1. MALDI-TOFMS protein profiles of 14 Bacillus spore species................................71 xv

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3-2. Correlation results of the 20 individual B. atrophaeus ATCC 9372 spectrum.........77 3-3. Correlation results of the 20 individual B. subtilis 168 spectrum.............................78 3-4. Visualization of the spectra in-line with the dendrogram for 14 Bacillus species....79 3-5. MALDI-TOFMS protein profiles of the 14 Bacillus vegetative cells.......................81 3-6. Visualization of the spectra in-line with the dendrogram for the vegetative cells....84 3-7. MALDI-TOFMS protein profiles of B. anthracis 34F2 vegetative cells on different growth media.............................................................................................87 3-8. MALDI-TOFMS protein profiles of B. subtilis 168 vegetative cells on different growth media............................................................................................................88 3-9. MALDI-TOFMS protein profiles of B. thuringiensis ATCC 10792 vegetative cells on different growth media................................................................................89 3-10. MALDI-TOFMS protein profiles of B. pumilus 7061 vegetative cells on different growth media.............................................................................................90 4-1. MALDI-TOFMS protein profiles of the B. pumilus type strain group spores......105 4-2. MALDI-TOFMS protein profiles from selected spores in the FO-36b cluster. ....106 4-3. MALDI-TOFMS protein profiles comparing B. pumilus ATCC 7061T, FO-36b and the two outlier strains......................................................................................107 4-4. Dendrogram and visualization of the B. pumilus spore strains...............................108 4-5. MALDI-TOFMS protein profiles of the B. pumilus type strain group vegetative cells.........................................................................................................................111 4-6. MALDI-TOFMS protein profiles of the FO group vegetative cells.......................112 5-1. Average spectra from the BACT spores using 30% formic acid as a solvent. ......126 5-2. Clustering and visualization of the BACT spores obtained using 30% formic acid as a solvent......................................................................................................134 5-3. Average spectra from the BACT spores using 5% TFA as a solvent......................135 5-4. Clustering and visualization of the BACT spores protein profiles obtained using TFA as a solvent.....................................................................................................140 5-5. Average spectra from the BACT vegetative cells using 30% formic acid as a solvent....................................................................................................................142 xvi

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5-6. Clustering and visualization of the BACT vegetative cells using formic acid as a solvent....................................................................................................................148 6-1. Peptide profiles obtained for Bacillus species.........................................................164 6-2. 1-D gel electrophoresis for 6 Bacillus strains..........................................................165 6-3. Comparison of the protein profile of the cotT protein using a cotT mutant............169 7-1. MALDI-TOFMS protein profiles of aged FO36b spores........................................189 7-2. MALDI-TOFMS protein profiles of B. subtilis 168 spores under different storage conditions...................................................................................................191 7-3. MALDI-TOFMS protein profiles of 1 month old FO36b spores under different storage conditions...................................................................................................192 7-4. MALDI-TOFMS protein profiles of UV treated B. subtilis 168 spores..................194 7-5. MALDI-TOFMS protein profiles of H 2 O 2 vapor treated B. subtilis 168 spores.....196 7-6. MALDI-TOFMS protein profiles of H 2 O 2 vapor treated B. pumilus 7061 spores..197 7-7. MALDI-TOFMS protein profiles of H 2 O 2 vapor treated FO36b spores.................198 7-8. MALDI-TOFMS protein profiles of H 2 O 2 liquid treated B. subtilis 168 spores.....199 7-9. MALDI-TOFMS protein profiles of H 2 O 2 liquid treated B. pumilus 7061 spores..200 7-10. MALDI-TOFMS protein profiles of H 2 O 2 liquid treated FO36b spores...............201 7-11. MALDI-TOFMS protein profiles of autoclaved B. subtilis 168 spores................203 7-12. MALDI-TOFMS protein profiles of autoclaved B. pumilus 7061 spores.............204 7-13. MALDI-TOFMS protein profiles of autoclaved FO36b spores............................205 7-14. MALDI-TOFMS protein profiles of B. subtilis sporulation mutants....................207 7-15. MALDI-TOFMS protein profiles of the cells of the B. subtilis spore coat mutants at T6..........................................................................................................208 7-16. MALDI-TOFMS protein profiles of the spores of the B. subtilis spore coat mutants at T24........................................................................................................210 xvii

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy MALDI-TOFMS BASED PROTEIN PROFILING AS A DIAGNOSTIC TOOL FOR THE ANALYSIS OF Bacillus SPORES AND CELLS By Danielle Nicole Dickinson August 2004 Chair: James D. Winefordner Major Department: Chemistry This research focuses on the development of Matrix-Assisted Laser Desorption/Ionization Time-of -Flight Mass Spectrometry (MALDI-TOFMS)-based protein profiling as a rapid diagnostic tool to detect and discriminate microbial species. MALDI-TOFMS is well suited for this task because of its rapid analysis time (<1 minute), low sample requirement, sensitivity, reproducibility, and resolving power. Analysis of whole bacterial cells and spores with this technique has given rise to unique protein fingerprints that can be used for identification at the species and strain level. Identification can be accomplished by using statistical algorithms to find the best match in a database containing fingerprints from previously analyzed bacterial species. The diversity found within bacterial species and the effects of environmental conditions on protein profiles from identical strains have proven to be a challenge for the statistical analysis of the spectra. To this end, we have sought an understanding of the variability in the protein profiles among strains of the same species and have evaluated the factors xviii

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affecting the expression and extraction of the proteins used as biomarkers. Systematic evaluation of these factors is crucial for bringing this technology into fruition as a viable diagnostic tool for microbial analysis. We have demonstrated the versatility and efficacy of MALDI-TOFMS protein profiling for bacterial identification by examining over 50 different spore strains of Bacillus, the most diverse study of the genus reported to date. A one-step sample treatment and MALDI-TOFMS preparation was designed to obtain spectra rapidly with a wide range of protein biomarkers, including several higher molecular weight (10-25 kDa) protein species not reported in other MALDI spore preparations. Linear correlation analysis, hierarchal cluster analysis, and spectral visualization were used to identify and catalog all Bacillus spores evaluated. To validate the use of MALDI-TOFMS protein profiling for species and strain differentiation, result of the protein profiling were compared with 16S rDNA sequences and DNA:DNA hybridization for their bacterial systematics and molecular phylogenetic affiliations. The effect of strain variation and environmental conditions (such as age, storage conditions, and exposure to radiation and sterilization) were examined to facilitate identification of invariant and omnipresent biomarkers in the spectra. The biomarkers needed for species delineation were targeted for further proteomic identification. xix

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CHAPTER 1 INTRODUCTION This research focuses on the development of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) protein profiling as a rapid diagnostic tool for identification of bacteria and bacterial spores. Analysis of whole bacterial cells and spores with this technique gives rise to unique protein fingerprints that can be used for the identification at the species and strain level. Identification can be accomplished by using statistical algorithms to find the best match in a database containing fingerprints from previously analyzed bacterial species. The algorithms have been tested with both a large diversity of bacterial species and strains and by the effect of environmental conditions on the resulting spectra of identical strains. To this end, we have sought an understanding of the variability in the protein profiles among strains of the same species; evaluated the factors affecting the expression and extraction of the proteins used as biomarkers; and identified omnipresent genus-, species-and strain-specific protein biomarkers. The systematic evaluation of these factors is crucial for bringing this technology into fruition as a viable diagnostic tool for microbial analysis. Our interest in investigating this technology is two-fold. The primary interest stems from the fact the Bacillus spores are the major source of contamination found in spacecraft assembly facility (SAF) clean rooms. The planetary protection requirements of space missions destined to contact the surface of other planets require technologies for validating decontamination processes and archiving the bioburden of flight hardware and 20

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21 facilities. These technologies must be sensitive, accurate, rapid, and cost-effective, and must be able to provide an organic signature of the organism that could allow scientists to distinguish it as forward contamination in the search for extraterrestrial life. The MALDI-TOFMS methodology developed here provides one possible answer to these challenges, and could record in the form of a protein fingerprint, the microbial diversity associated with space missions. Our more general interest is in rapid, sensitive, and selective microbial detection and identification at the species and strain level, which is a necessity for the differentiation of viable pathogenic and nonpathogenic microbial species. The development of technologies that accomplish this level of distinction would have a significant impact in the areas of occupational and health care, homeland defense, and environmental monitoring. The Genus Bacillus The genus Bacillus is one of the largest and most ubiquitous genera of bacteria containing 65 valid species, with new species continually being described. 1 The type species of Bacillus, Vibrio subtilis was first described by Ehrenberg in 1835 and was renamed Bacillus subtilis in 1872 by Cohn. The genus has become the graveyard for all aerobic or facultatively anaerobic, spore-forming, rod-shaped bacteria. Taxonomic characterization and systematics of Bacillus have been an area of great debate for over a century. The genus has been classified into six RNA groups based on 16S rDNA sequence similarity, spore morphology, spore position in the mother cell, and the presence or absence of mother cell swelling during sporulation. 2 The genus has gained notoriety with taxonomists for its extreme phenotypic diversity and heterogeneity. As a result, this is one of the most animated areas in systematic bacteriology studies.

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22 Most Bacillus species are regularly encountered and cultivated from soil samples, their primary habitat, from which they can contaminate anything. Bacillus species are particularly important in the medical, veterinary, military, and industrial fields. They are probably most noted for their negative effects, which include food spoilage, clean room contamination, biodeterioration, and causing various infections and foodborne illnesses in humans and many animals. The most infamous member is B. anthracis, the bioterrorism agent that causes anthrax. Although notorious for the negative effect they can have on human health in particular, Bacillus species possess redeeming qualities. They are rich sources of extracellular enzymes (such as proteases and amylases); of peptide antibiotics such as bacitracin; and of insecticides such as the widely used toxins from the species such as B. thuringiensis and B. popilliae. 2 The most distinguishing characteristic of the genus is the ability to produce a resistant endospore. The spore is formed within the mother cell in response to nutrient deprivation and can be oval, spherical, or cylindrical. Spores are highly resistant to agents such as heat and radiation, and cannot be easily destroyed even by harsh chemical treatment, disinfectants, or desiccation. 1,3 The increased resistance of spores, although not completely understood, has been partly explained by the impermeability of the spore coat, dehydration of the core, and the protective proteins that bind to the DNA. In the metabolically inert spore form, these bacteria can remain dormant for hundreds of thousands of years. Within the spore the essential macromolecules (and a variety of other substances) are stored until conditions become favorable for survival; at which point they are triggered to return to an active vegetative state. The resiliency they exhibit enables

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23 the genus to be ubiquitous in the environment, a common source of contamination, sterilization resistant, and an ideal bioterrorism agent. 1,3 Spore Architecture and Composition A closer look at the spore shows significant differences in the composition and location of many biomolecules when compared to a vegetative cell. The cell wall of a gram-positive vegetative cell is characterized by a rigid layer of peptidoglycan. This layer is relatively easy to penetrate, either through the use of enzymes such as lysozyme (which breaks the 1,4-glycosidic bonds in the peptidoglycan), or by extreme changes in osmotic pressure or pH. Vegetative cells are also susceptible to desiccation, heat, radiation, and sterilization. The spore, in comparison, is more complex with several outer layers that are believed to contribute to its increased resistance. Spore species may contain an outermost layer called the exosporium (Figure 1-1A). All species contain a spore coat, typically comprising an inner and outer layer (Figure 1-1A, B). The exosporium and spore coat are mainly comprised of proteins and glycoproteins. The cortex, a peptidoglycan layer similar to that found in a vegetative cell, is the next layer of the spore. Within the cortex is the dehydrated spore core. The core contains the same parts as the vegetative cell (including the cell wall, cytoplasmic membrane, ribosomes, and DNA). A high concentration of a calcium-dipicolinic acid complex is present in the core of all spores. Bound to the DNA (and unique to spores) are proteins known as small acid soluble proteins (SASPs), which protect the DNA against damage from radiation, desiccation, and dry heat. 4

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24 Figure 1-1. Transmission electron microscopy image showing typical spore architecture. A) B. odysseyi PTA-4993 which contains an exosporium (EX). B) B. subtilis 168 which does not contain an exosporium. The core, cortex, and spore coat (SC) are shown for both spore species.

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25 Sporulation and Germination Sporulation occurs in a series of stages (0, II, and III-VII) that can be monitored by phase contrast microscopy. A pictorial representation of the sporulation and germination stages is shown in Figure 1-2. The end of exponential growth is considered time 0 for sporulation, and occurs when the cells reach stage II and the cell divides into two asymmetric compartments, each with its own chromosome. The larger division is termed the mother cell or sporangium; the smaller compartment is the forespore. In stage III and IV, the forespore becomes engulfed by the mother cell, the peptidoglycan cortex layer is deposited on the outside of the developing spore, and the SASPs are synthesized within the forespore. During stage V and VI, the spore coat proteins are deposited and the spore reaches maturity with a full arsenal of resistances. Finally, the mother cell lyses, releasing the mature spore during stage VII. This results in the appearance of phase-bright refractile bodies which are observed when using phase contrast microscopy. The entire process of spore formation takes 6-8 hours. 5-7 When nutrients are returned to the medium, the spore undergoes a process called activation, whose mechanism is not well understood. Germination begins within minutes and can be characterized by a rehydration of the spore core, release of cations and dipicolinic acid, degradation of the SASPs by the germination protease protein (GPR), and the loss of refractility and resistance. Later in germination, the cortex undergoes hydrolysis followed by metabolism and protein synthesis. This is followed by outgrowth, when emergence and elongation occur, during which normal cell division resumes and the coat remnants are discarded. The time for completion of this process is under 1.5 hours. 5-7

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26 Figure 1-2. Sporulation and germination cycle.

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27 Microbial Identification and Classification The biologist is attuned to the vagarities of living things and does not expect an experiment to be exactly repeatable . is surprised by the expected and astounded by the fulfillment of a forecast of prediction. The bacteriologist must never forget that genera and species are artificial concepts and that the bacteria show no interest in their classificationSam Cowan, 1978 When developing technology for the identification of microbial species, consideration should be given to the biological system itself, the processes it can undergo, and the chemicals and biomolecules available for analysis. One of the most challenging aspects of any biological system (in analytical terms) is its almost constant potential for change and adaptation. Analytical chemists strive for reproducibility, specificity, selectivity, and detection limits. Traditional analytical approaches are not attuned to dealing with biological flux or the vast expanse of diversity that can exist. To be successful, we must do what is less traditional, and accept that biological samples have a mind of their own. The definition of a successful biological analysis may or may not concur with traditional analytical measures of success. Traditional techniques for the characterization and identification of microorganisms have relied on lengthy biochemical, nutritional, and physiological testing. Often these tests are inconvenient to prepare and perform, difficult to standardize and interpret, and can be challenging to reproduce. 8-10 Modern techniques for microbial classification and identification have focused on the development of chemotaxonomic and molecular-based methods. These techniques can be classified broadly as genotypic or phenotypic. Examples of genotypic techniques include PCR-based analysis, DNA hybridization, genetic fingerprinting, direct sequencing, and nucleic acid probing. Fatty acid methyl ester analysis, pyrolysis mass spectrometry, whole-cell protein profiling via gel electrophoresis or mass spectrometry, antibody-based methods, and various miniaturized

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28 test kits for determining biochemical and nutritional requirements are examples of phenotypic techniques. 8-10 Genotypic methods are faster and are usually more reliable than traditional biochemical methods, though they have drawbacks, including the stability of consumables, availability of specific probe sequences, and the associated cost and time required for gene sequencing. Commercially available identification kits and other newly developed technologies, mentioned above for phenotypic analysis, have the advantage of speed and convenience when compared to most traditional methodologies, but still require an incubation period and may have difficulties associated with reproducibility. Protein expression, metabolic profiles, and fatty acid profiles can fluctuate dramatically based on environmental and nutritional variables during different stages of growth. 8-10 Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOFMS) MALDI-TOFMS has become an essential tool for analyzing a wide array of biomolecules, particularly proteins. The explosion in genomic and proteomic research in the past two decades has placed high demands on instrumentation and techniques for analysis. MALDI-TOFMS has become a primary player in both of these arenas due to its high throughput, sensitivity (femtomole range for most proteins), and handling of complex biological samples. In MALDI-TOFMS, a solid organic matrix compound is dissolved in an appropriate solvent and combined with a protein sample solution. A small volume (typically 0.5-3.0 L) is spotted on a stainless-steel target plate and allowed to dry. The target is placed (via a probe) into the vacuum chamber of a time-of-flight mass spectrometer. The sample is irradiated with a pulsed laser, resulting in the desorption and

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29 ionization of the analyte molecules. The laser is most often a nitrogen laser which produces photons in the ultraviolet range (337 nm), although infrared lasers are also used. The matrix acts as the vehicle to desorb and ionize the sample molecules with little or no fragmentation. The matrix molecules absorb most of the energy from the photons, and vaporize to form an expanding plume that carries the sample molecules into the gas phase. Ions are accelerated by an electrostatic potential (V) to a certain velocity (v) and a total kinetic energy (E). The ions traverse a field-free drift region where they are separated based on differences in their velocity. A channel electron multiplier detects the ions. The time-of-flight of the ions is recorded and converted to a mass-to-charge ratio, using the TOF relationship: 222/ L Vtzm where t = time, L = length of flight tube, z = charge, V = accelerating voltage, and m = mass of the ion. 11 To increase the resolving power of the time-of-flight mass spectrometer, a reflectron can be added to focus the kinetic energy of the ions. The reflectron is most effective at relatively low masses, and is more frequently used for peptide analysis below 4 kDa. MALDI-TOFMS for Bacterial Fingerprinting MALDI-TOFMS has demonstrated great promise for interrogating microbial species and for identifying proteins using comparative and clinical proteomic approaches. 11-14 Microbial analysis with MALDI-TOFMS dates back to the late 1980s. 15 Many groups have demonstrated the versatility of this technique, from analysis of cell lysates to whole-cells to the analysis of PCR products. 16 MALDI-TOFMS is well-suited for this task due to its rapid analysis time (<1 min/sample), low sample requirements,

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30 sensitivity, and resolving power. Analysis of whole bacterial cells and spores with this technique has given rise to unique protein fingerprints that can be used for identification at the species and (at times) strain level. 16-33 All of the studies rely on the growth and/or sporulation of cells in the laboratory; none are sampled directly from the environment. Vegetative cells generally produce a relatively large number of biomarker proteins that can be used for subsequent pattern recognition or correlation analysis. However, the proteins expressed in vegetative cells are dynamic, and can vary dramatically based on cultural conditions. In contrast, extraction of proteins from spores has been more challenging, providing only a limited number of biomarker peaks when compared to their vegetative counterparts. The spore associated biomarker peaks detected using MALDI-TOFMS with a UV laser are reported in the range of 3-10 kDa. Various sample pretreatments including the use of infrared (IR) laser irradiation, 34-37 corona plasma discharge, 19,26 sonication, 26 and the addition of 5% trifluoroacetic acid (TFA) 34 or 1M HCl, 38 have been used on spores to increase the number and intensity of biomarkers observed in the spectra. These methods have had some success; however, in most cases, these treatments require longer sample preparation times and visualization of peaks above 10 kDa is still limited. Fenselau et al. 39 reported detection limits as low as 5,000 cells/spot; however, only a single protein biomarker was reported. Most conventional MALDI-TOFMS bacterial research has focused on species differentiation without the identification of protein biomarkers, and therefore, the ability to extract strain-specific and pathogen-specific biomarkers has not been thoroughly investigated. In the case of spores, recent studies have identified a limited number of biomarker peaks as SASPs; however, these proteins alone do not allow

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31 for differentiation at the species level. This is evident in the case of B. thuringiensis and B. cereus. 32,38,40 In addition to the direct MALDI-TOFMS analysis of whole spores, various groups have recently been engaged in full-scale proteomic analysis of B. anthracis 37,41 and B. subtilis 37,42 using one or two-dimensional gel electrophoresis in conjunction with MALDI-TOFMS or liquid chromatography mass spectrometry. While these extensive studies improve our understanding of the spore coat and allow for limited species comparisons, they are very time consuming and have not been applied to other Bacillus strains. These studies are also limited to species with sequenced genomes. Published studies show that MALDI-TOFMS of whole bacterial spores is feasible and of practical value, lending speed and higher accuracy to the analysis. MALDI-TOFMS for microbial analysis provides a rapid, relatively simple analysis that is amenable to all species, and is not reliant on previous knowledge of DNA sequences or antibody interactions. MALDI-TOFMS protein profiling is well-suited for high throughput and automation, requires minimal sample preparation, has superior reproducibility, and has much higher resolution than gel-based techniques. To prove MALDI-TOFMS fingerprinting as a useful technology for bacterial identification, the technique must be able to rapidly differentiate and identify genus-, species-, and strain-specific biomarkers over a wide variety of spores. More importantly, it must be able to identify biomarkers that can differentiate pathogenic strains from nonpathogenic strains. To this end, this research was performed on over 50 species, including 21 type strains and 25 wild-type environmental isolates, and 17 B. cereus serovars. To our knowledge, this is the largest collection of Bacillus spores ever

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32 evaluated with MALDI-TOFMS protein profiling. This large collection of Bacillus affords us several advantages. First, it allowed elucidation of the protein differences that are present at both the species and strain level. Second, it allowed evaluation of the reliability of the biomarkers over a wide range of isolates. Third, it allowed for the determination of the level of distinction needed to differentiate pathogens from other similar nonpathogens that are of the same or related species. This highly specific level of discrimination is required to differentiate nonpathogenic strains (B. anthracis Sterne) from pathogenic strains (B. anthracis Ames). These biomarkers allowed rapid identification of proteins as targets for molecular probes and other biosensors that are field-portable, robust, small, and both sensitive and highly specific. This could decrease the time and cost of identifying targets for sensor-based counterterrorism systems. Research Overview This body of research begins with a description of the optimization of the conditions for the extraction of proteins from spores. Using the optimized extraction conditions the research moved into the analysis phase where over 50 different spore species were analyzed. Chapter 3 addresses the successful differentiation of 11 different Bacillus species, the most diverse study of the species to date. This chapter also describes in detail the statistical processing of the spectra using linear correlation and hierarchal cluster analysis. The effect of strain variation within a species is addressed in Chapters 4 and 5 and the criteria for including a strain within a species using linear correlation were established. Chapter 4 deals specifically with using MALDI-TOFMS protein profiling in a polyphasic taxonomy approach for the identification and classification of B. pumilus isolates. MALDI-TOFMS protein profiling proved to be more accurate than metabolic profiling and was complementary to gyrB sequencing and

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33 DNA hybridization for the identification of these isolates, which included the possible identification of a new species of Bacillus. Chapter 5 tackles the differentiation of the B. anthracis-B. cereus-B. thuringiensis (BACT) group spores and cells. This is the first investigation of a wide variety of BACT group bacteria (20 strains) with MALDI-TOFMS protein profiling where the results are compared directly with genetic analysis for their bacterial systematics and molecular phylogenetic affiliations. The next portion of the research focused on the identification of the protein biomarkers that were found to be species specific in the studies outlined in Chapters 3-5. MALDI protein extracts from several Bacillus species were analyzed by tandem mass spectrometry techniques to obtain peptide mass tag data in Chapter 6. The first report of the identification of coat proteins from a MALDI extract is included for the B. subtilis 168 strain in the study. For organisms that did not have sequenced genomes most of the proteins identified are SASP associated due to the high sequence conservation among these proteins, although some surface associated proteins are identified in several B. pumilus species. The final chapter, Chapter 7, addressed the effect of environmental exposures on Bacillus spores and demonstrated that species specific biomarker peaks were maintained over most of the conditions analyzed. The additional information provided by the appearance and disappearance of other peaks in the spectra was shown to be useful for source tracking, forensic investigations, and epidemiological studies.

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CHAPTER 2 OPTIMIZATION OF MATRIX AND SOLVENT CONDITIONS FOR THE EXTRACTION OF PROTEINS FROM SPORES Matrix and solvent selection is a critical factor in the success of MALDI-TOFMS. Selection of matrix compounds is empirical and must be evaluated for each application. Solvent systems for MALDI must balance the organic and aqueous phase to maintain solubility of both the matrix and sample, and must optimize crystal formation. An acidic modifier must also be present to maintain a pH less than 4 to promote crystallization of the matrix in the free acid form. The number, quality, and intensity of peaks in a MALDI spectrum can also be affected by the matrix compound, the solvent, and the acidic modifier chosen for the analysis. Both the enhancement and suppression of peaks have been observed in MALDI by changing various components. The selection of the solvent system in the case of spores is complicated by the presence of a wide range of hydrophobic and hydrophilic proteins in the exosporium, coat layers, and core of bacterial spores, as well as by the rigidity and chemical resistance of the spores. Two main families of proteins are present in spores at relatively high concentrations: the SASPs and the spore coat proteins. SASPs have recently been evaluated as biomarkers for the identification of spores. Targeting the SASPs requires that the spores be disrupted, allowing for the release of SASPs from the spore core. This is accomplished by using high concentrations of strong acids, such as trifluoroacetic acid (TFA) and hydrochloric acid, to lyse open the spore. Post release, the SASPs are digested with trypsin and are identified using post-source 34

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35 decay or ion-trap technologies. Although this approach has allowed for identification of SASPs that are species-specific, it is limited to the species that have sequenced genomes, and it fails to differentiate closely related species such as B. cereus and B. thuringiensis effectively. 32,38,40 This failure is likely due to the high level of sequence homology among the SASP proteins. The spore coat proteins have not been identified in any direct whole-cell analysis experiments. They possess a high level of sequence divergence, which should allow for higher levels of discrimination. To effectively extract and analyze the spore coat proteins, it is necessary to target mainly hydrophobic proteins. On average, 75% of the known proteins located in the spore coats are hydrophobic. 43 In addition, it would be ideal to use a gentle extraction scheme that would not lyse the spore open during treatment, releasing SASP proteins that would dominate the spectra. Spores are more resilient and difficult to destroy than vegetative cells, making it difficult to design an efficient protein extraction scheme. Most of the published MALDI-TOFMS spore spectra have used a mixture of acetonitrile/water with various concentrations of TFA. 25-27,32,38 Components used to analyze vegetative cells are far more varied, with past studies using -cyano-4-hydroxycinnamic acid (HCCA), ferulic acid, and sinapinic acid with a variety of solvents including ethanol, isopropanol, and acetonitrile. 16,20,27,29,31,33,44,45 Voorhees et al. 46 and Chait et al. 47 recommended using a mixture of 17% formic acid, 30% acetonitrile, and ferulic acid to enhance the high mass signal in whole-cell analysis. This mixture has also been shown to be more tolerant of salts and surfactants, an important factor when considering possible contamination from using crude cell samples. Procedures for analyzing hydrophobic proteins also regularly employ the use of a detergent additive to increase the solubility of the proteins. 48-51

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36 Detergents typically used include low levels of sodium dodecyl sulfate (SDS), Triton X-100, and octylglucoside. However, various studies show that adding detergents can have negative impacts on the MALDI signal. 52 The goal of this research was to develop a simple, one-step extraction protocol that provides for the maximum availability of biomarkers for analysis. To this end, we systematically evaluated the extraction of proteins from spores by MALDI-compatible solvents. Several common MALDI matrices, acidic modifiers, and organic solvents for analysis spores were evaluated. Detergent additives were also examined as a method of increasing the number of biomarkers extracted from the spore coat. Spectra generated were evaluated based on the following criteria: signal-to-noise ratio, number of discernable peaks, molecular weight range, suppression effects, reproducibility, and homogeneity of crystal formation. The limits of detection of the optimized extraction system were also investigated. Materials and Methods Chemicals and Reagents The evaluated MALDI matrices, purchased from Sigma Chemical Co. (St. Louis, MO), included sinapinic acid (SA), ferulic acid (FA), dihydroxybenzonic acid (DHB), and -cyano-4-hydroxycinnamic acid (HCCA). All matrices were used as received except HCCA. The HCCA was further purified by preparing a saturated solution of HCCA in warm ethanol, to which 3 parts water was added. The solution was allowed to stand at 4C overnight. The HCCA precipitate was then filtered and the matrix was allowed to dry in a desiccators. Organic solvents used included acetonitrile (ACN), methanol, ethanol, and isopropanol. All solvents were HPLC grade from Fisher Scientific Co. (Fairlawn, NJ).

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37 Trifluoroacetic acid (TFA) was from Sigma-Aldrich Chemical (St. Louis, MO). Aldehyde-free formic acid was obtained from Fisher Scientific Co. (Fairlawn, NJ). The two detergents evaluated included N-octylglucoside (OGP) from Sigma-Aldrich Chemical Co. and the acid labile Rapidgest from Waters (Milford, MA). Cytochrome C, myoglobin, bovine serum albumin (BSA), and insulin were used in calibration mixtures and were purchased from Sigma-Aldrich Chemical Co. The spore suspensions used for analysis were provided by the Biotechnology and Planetary Protection Group at the Jet Propulsion Laboratory. Three strains were used in the extraction protocol development: B. subtilis 168, B. pumilus 7061, and the wild-type FO-36b, which has been putatively identified as B. pumilus. All spore suspensions were between 1 x 10 8 and 1 x 10 9 spores/mL. The spores were stored in sterile water at 4C before use. Sample Preparation and Mass Spectrometry Saturated solutions of the MALDI matrices (typically 10-20 mg/mL) were prepared in the selected solvent system for analysis. Unless otherwise indicated, standard dried-droplet sample preparation was used to prepare the MALDI spots for analysis. The optimum ratio for mixing was found to be 10 parts matrix to 1 part sample, where the initial concentration of spores was 1 x 10 8 to 1 x 10 9 spores/mL. The spore suspension was premixed 1:10 with the matrix solution and 1 L of the resultant solution was spotted on the MALDI plate. Samples were allowed to air dry, and no further treatments were applied to the spot post deposition. MALDI analysis was performed on a Bruker Reflex II TOFMS (Bruker Daltonics, Billerica, MA) retrofitted with delayed extraction. The instrument uses a pulsed nitrogen laser (337 nm) for ionization. Ions were collected in the linear mode and were detected

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38 with a HIMASS detector (Bruker Daltonics, Billerica, MA). An acceleration voltage of 20 kV was used in conjunction with a 50 ns delay time. For deflecting matrix and other low molecular weight ion signals, a deflector was set at 2,000 Da. All spectra were obtained by the accumulation of 50 laser shots in positive mode. A three point external calibration was performed daily using either a mixture of insulin, myoglobin, and BSA; or insulin and the doubly and singly charged ions of cytochrome C. Results and Discussion Initial Studies Initial studies focused on the use of sinapinic acid as a matrix compound. Sinapinic acid was typically used in combination with 0.1% TFA and 30% ACN for the analysis of proteins. When this combination was applied to the B. subtilis 168 spores in this study, very few biomarkers were observed (Figure 2-1A). Changing the acidic modifier to 17% formic acid had a profound effect on the spectrum, increasing the observable number of biomarker peaks from 6-8 barely discernable peaks to approximately 15 well-resolved peaks (Figure 2-1B). Because the addition of formic acid increased the organic content of the solvent system, a 50% ACN/ 0.1% TFA solvent was also evaluated (Figure 2-2A) and demonstrated little improvement over the previous TFA solvent system (Figure 2-1A). The spectrum in Figure 2-2B represents an analysis where a 0.1%TFA/50% ACN solvent was first deposited and allowed to dry. A mixture of the spore sample with 10 parts 17% formic acid/30% ACN was deposited on top of the matrix layer. This gave a similar spectrum to the premixed dried droplet approach used above (Figure 2-1B), indicating that the effect of the formic acid is likely an enhancement in protein solubility more than an effect of the mechanics of the MALDI deposition.

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39 Using the 17% formic acid/30% acetonitrile solvent system as a base solvent, several matrix compounds other than sinapinic acid were evaluated. All matrix compounds were dissolved in the base solvent. DHB, unlike the other 2 matrices, was water soluble, and was also tested in 17% formic acid/83% water. Representative spectra from each matrix are shown in Figure 2-3. Ferulic acid (not shown) gave an identical spectrum to the sinapinic acid, and the effects of these 2 matrices will be discussed separately. When compared with DHB and HCCA, sinapinic and ferulic acid matrices gave higher signal-to-noise ratios and the largest range of biomarkers. The higher molecular weight proteins were not evident in the DHB samples (Figure 2-3B and C). However, the 17% formic acid/83% water sample (Figure 2-3C) highlighted additional biomarker peaks found in the 5-10 kDa range. Acidic Modifier To further characterize the discrepancy between the two matrix solutions a study was performed to evaluate the effects of the acidic modifier on the resultant MALDI spectra. The following solvent systems were prepared: 30% ACN, 70% 0.1%TFA (pH=1.90) 30% ACN, 53% H2O, 17% formic acid (pH=1.56) 30% ACN, 55% H2O, 15% formic acid (pH=1.58) 30% ACN, 60% H2O, 10% formic acid (pH=1.67) 30% ACN, 65% H2O, 5% formic acid (pH=1.82) Sinapinic acid and ferulic acid were dissolved in each of the solvent systems. A calibration mixture (CM-IMB) was prepared containing insulin, myoglobin, and bovine serum albumin at concentrations of 15, 100, and 100 pmole/L, respectively. A 1 L aliquot of the calibration mixture was mixed with 24 L matrix solution. The calibration mixture was used to ascertain suppression effects that do not result from differences in

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40 Figure 2-1. Comparison of TFA versus formic acid. A) B. subtilis 168 spores in 0.1% TFA/30% acetonitrile. B) B. subtilis 168 spores in 17% formic acid/30% acetonitrile.

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41 Figure 2-2. Formic acid extraction effect. A) B. subtilis 168 spores in 0.1% TFA/50% ACN dried droplet preparation. B) 0.1% TFA/50% ACN matrix layer applied first followed by deposition of B. subtilis 168 spores in 17% formic acid/30% acetonitrile.

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42 Figure 2-3. Comparison of different matrix compounds and 17% formic acid modifier. A) Sinapinic acid in 17% formic acid/30% ACN B) DHB in 17% formic acid/30% ACN C) DHB in 17% formic/83% water D) HCCA in 17% formic acid/30% ACN

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43 extraction efficiency. Each sample (CMIMB and B. subtilis 168) was spotted in triplicate on the MALDI plate. The signal-to-noise ratio was determined for peaks of interest in each spectrum. In the CM-IMB spectrum, the three peaks of interest were at masses 5,734, 16,952, and 66,432 Da. In the spore spectrum, the peaks of interest were the biomarker peaks at 3,950, 6,648, and 7,760 Da. Data analysis was performed by averaging 3 spectra per spot and obtaining the standard deviation within the spot. The signal-to-noise values from each of the samples were averaged and the standard error was calculated. The resulting data can be seen in Figure 2-4 for the calibration mix and Figure 2-5 for the spore samples. The plots are of the signal-to-noise versus solvent composition for each peak of interest in the spectra. Sinapinic acid gave higher signal-to-noise ratios overall except in the case of high molecular weight proteins like BSA. The solvent system 30% ACN, 70% 0.1%TFA produced superior results for the calibration mix in both matrices; however, neither produced significant signals from the spore sample. In contrast, both matrices produced superior signals for the spore biomarkers when dissolved in the 30% ACN, 53% H2O, 17% formic acid solvent system. For both matrices, the biomarker signal detected decreased as the percent formic acid was decreased in the solvent mixture. In the formic acid series, there was a decrease in signal for all the proteins in the calibration mix as the percent formic acid increased. These results were in opposition to the spore samples, as signal increased with increasing formic acid. These trends suggested the formic acid aids in the extraction of proteins from the spore coat.

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44 Figure 2-4. Signal-to-noise versus solvent for calibration mix. A) Sinapinic acid matrix. B) Ferulic acid matrix. The solvents, from left to right in each graph are 0.1% TFA, 5% formic acid, 10% formic acid, 15% formic acid, and 17% formic acid in 30 % acetonitrile. The error bars represent the standard error of 9 measurements.

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45 Figure 2-5. Signal-to-noise versus solvent for the B. subtilis 168 spore suspension with varying acidic modifier concentrations. A) Sinapinic acid matrix. B) Ferulic acid matrix. The solvents, from left to right in each graph are 0.1% TFA, 5% formic acid, 10% formic acid, 15% formic acid, and 17% formic acid in 30 % acetonitrile. The error bars represent the standard error of 9 measurements.

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46 Because increasing the formic acid concentration seemed to increase the extraction efficiency of the protein biomarkers from the spores, higher concentrations of formic acid were investigated. The percentage of acetonitrile was kept at 30% while the percent formic acid was increased from 10 to 60%. The results are shown in Figure 2-6 for both sinapinic and ferulic acid matrices. Sample spectra from the sinapinic acid samples for each concentration are shown in Figure 2-7. Higher concentrations of formic acid (30 to 40%) enhanced extraction, giving rise to higher molecular weight biomarkers (> 15 kDa) not seen at lower concentrations. This observation was supported by a 1-D gel electrophoresis studies (Figure 2-8) where bands emerged at higher molecular weights with increasing formic acid concentrations. However, MALDI spectral quality declined as formic acid concentrations above 30-40% were used. This decline was attributed to inhomogenieties in crystal formation; as the solvent became more hydrophobic, crystal homogeneity suffered due to spreading of the spot. Using formic acid as a modifier resulted in spectra with higher signal-to-noise ratios and a significantly greater number of biomarker peaks. The visualization of these higher molecular weight proteins has not typically been seen in other MALDI-TOFMS analyses of whole spores. 25,26,34,35,38 When comparing the two matrices, sinapinic acid clearly was advantageous due to enhanced signal-to-noise ratios. However, the ferulic acid matrix produced spots which were more reproducible. Since the long term goals of this project deal with the statistical treatment of spectra, reproducibility was a critical factor in the success of this methodology. Therefore, signal-to-noise was sacrificed in exchange for better reproducibility and the ferulic acid matrix was used in all subsequent studies.

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47 Figure 2-6. Signal-to-noise versus formic acid concentrations from 10 to 60% for the m/z 7,760 peak from B. subtilis 168. Ferulic acid is shown in blue and sinapinic acid is in red. The error bars represent the standard error across 9 measurements.

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48 Figure 2-7. Enhancement in biomarker signal for B. subtilis 168 by increasing formic acid concentration. From top to bottom, B. subtilis in 60%, 40%, 30%, 20%, 10% formic acid. The scale is from m/z 2,000-20,000. Note the emergence of higher molecular weight proteins as formic acid concentration increased.

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49 Figure 2-8: 1-D Gel showing the effects of increasing formic acid concentration on extraction of B. subtilis 168 spores compared to SDS solublized extract. This is shown for 2 organic solvents, 30% acetonitrile and 30% methanol.

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50 The higher formic acid concentrations also had a significant impact on the biomarkers that were extracted, possibly due to differences in the hydrophobicities of the proteins. This was highlighted when analyzing the FO-36b spore sample. As formic acid concentration increased, the biomarker peak at 7,620 peak was favored over the 7,250 peak (Figure 2-9 and 2-10). This peak was one of the few peaks that differed between spores of FO-36b and B. pumilus 7061 and was critical for differentiation of these two strains. Organic Modifier The effect of the organic solvent was also investigated. The acetonitrile preparation was compared with methanol, ethanol, and isopropanol. A range of formic acid concentrations was studied with each of the different solvents. Similar results were obtained for all three of the spore lines evaluated. A graph of the results for B. subtilis 168 is shown in Figure 2-11 for methanol and isopropanol with acetonitrile for comparison. Results with ethanol were nearly identical to those with isopropanol and are not shown in the graph. Overall, the effect of the organic modifier on the spectra was minimal. Similar trends were noted for the formic acid concentrations as seen with ACN before. The signal increased for samples with up to ~30% formic acid, and then decreased again due to poor MALDI spot formation at higher formic acid concentrations. Methanol shows an advantage in signal-to-noise ratio but, as indicated by the error bars, didnt give results as reproducible as when acetonitrile was used. Isopropanol and ethanol were very similar to acetonitrile in signal-to-noise, although the MALDI spots were less reproducible and tended to spread over the plate. Therefore, acetonitrile was generally used as the organic solvent in our studies.

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51 Figure 2-9. Signal-to-noise versus formic acid concentrations from 10-60% for 4 biomarker peaks from FO-36b spores. Ferulic acid was used as a matrix and 30% acetonitrile is the organic solvent. The error bars represent the standard error of 9 measurements.

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52 Figure 2-10. Enhancement in biomarker signal for FO-36b spores by increasing formic acid concentration. From top to bottom, FO-36b in 20%, 30%, 40%, and 60% formic acid. Each spectrum is displayed from m/z 2,500-40,000. At 20% formic acid the 7,250 Da peak is the base peak in the spectra. As the formic acid concentration increased to 30% and higher, the 7,620 Da peak became the base peak in the spectra.

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53 Figure 2-11. Signal-to-noise versus formic acid concentrations: organic modifier effects. Comparison of acetonitrile (ACN), methanol (MeOH), and isopropanol (IPA) as the organic modifier in the MALDI solvent using B. subtilis 168 as the sample.

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54 Detergent Additives Detergent additives were also examined as a mechanism for increasing the number of biomarkers extracted from the spores. Two MALDI compatible detergents were examined, N-octylglucoside (OGP) and the acid labile Rapigest. Sodium dodecyl sulfate (SDS) was not evaluated as a detergent additive because MALDI compatible concentrations of SDS are less than 0.01%. During the purification of a spore preparation, 0.05% SDS was used to clean the spores and did not disrupt the spore coat proteins. 7 Therefore, lower concentrations of SDS would have no effect on protein solubilization. A 0.1% TFA/50% ACN solution was used as the matrix solution instead of formic acid in order to ascertain whether it was the detergents which improved solubilization,. OGP was added directly to the matrix solution at concentrations ranging from 0.425-68 mM. Figure 2-12 shows sample spectra from B. subtilis 168 spores treated with 0.1%TFA/50% ACN matrix preparation alone in A, and with increasing OGP concentrations of 13.6 mM OGP added in B, and 68mM OGP added in C. Spores treated with a 30% formic acid/30% acetonitrile solvent are shown for comparison in D. OGP enhanced the extraction of proteins from the spores as indicated by the higher signal-to-noise in the spectra with OGP added. However, even with the highest level of OGP, this enhancement was still lower than the formic acid treatment (D). The OGP also did not allow for the detection of the higher molecular weight peaks in the spectra. Rapigest was also evaluated at a concentration of 0.1% and was used per the manufacturers instructions. This involved boiling the spore sample in the detergent and then adding 50 mM hydrochloric acid to degrade the Rapigest. As a control, a spore sample in water was also boiled and added to the formic acid matrix. The Rapigest

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55 Figure 2-12. Treatment of spores with OGP detergent. A) B. subtilis 168 spores in 0.1% TFA/50% ACN. B) B. subtilis 168 spores in 0.1% TFA/50% ACN with 13.6 mM OGP. C) B. subtilis 168 spores in 0.1% TFA/50% ACN with 68 mM OGP. D) B. subtilis 168 spores in 30% formic acid/30% acetonitrile. The OGP improved extraction from the spores; however the formic acid treatment was still superior.

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56 treatment significantly altered the visible biomarkers spectra (Figure 2-13, top). The dominating biomarker became the 9,130 peak, which had not been previously observed. This spectrum is similar to that obtained when concentrated TFA or HCl treatments were used to lyse spores for SASP extraction, and these peaks correspond to the molecular weights of the major SASPs in B. subtilis 168. Since Rapigest required degradation with high acid concentrations prior to analysis, the SASPs would be expected to dominate the spectra. In the formic acid matrix, the boiled spores gave rise to an even higher molecular weight protein at ~43 kDa that had not been previously discernable, indicating that a boiling step might aid in the solubilization of additional proteins. Characteristics of Optimized Solvent Extraction System The best combination of solvents evaluated for the analysis of spore was a 30% formic acid/30% ACN solvent system with ferulic acid as the matrix. This solvent system represented a compromise between signal-to-noise, reproducibility, and the availability of a wide range of low and high molecular weight biomarkers for analysis. Higher formic acid concentrations allowed for the extraction of higher molecular weight proteins; however, inconsistencies in the MALDI spot formation were detrimental to analysis. At a concentration of 30% formic acid, the MALDI spot formation was homogeneous and consistently gave a good crystal layer for the analysis. This treatment was rapid and did not require any additional sample preparation or spot treatment. It was also relatively inexpensive in comparison to the use of detergents such as Rapigest and OGP. Unlike other sample preparation procedures, such as treatments for SASP extractions, in which the spores were not viable post-treatment, the B. subtilis 168 and FO-36b spores in our studies remained viable for up to 1 hour in 30% formic/30%

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57 acetonitrile. After 1 hour in the solvent there was a 2 decade reduction in growth. In contrast, spores from B. pumilus 7061 were affected by the formic acid treatment and there was a 2 decade reduction in growth after only 10 minutes of treatment. The difference in viability between the three spore strains might be explained by differences in the permeability of the spore coats by the MALDI solvent. This could also be a result of storage conditions and storage times. Limit of Detection Study for MALDI Spore Preparations Although a limit of detection for bacterial cells has been reported in the literature (5,000 cells/spot), no comprehensive study has been compiled. To assess a more realistic limit of detection for whole-cell analysis of spores by MALDI, an experiment was designed to determine the minimum number of spores necessary to obtain useful spectra. Obtaining a useful spectrum depends on a number of factors including the signal-to-noise ratio and the number of biomarker peaks discernable in the spectrum. Dilutions of the spore suspension were made in water and the resulting solutions were mixed with the ferulic acid matrix described above. Figure 2-14 is an overlay of the spectra collected for the spore sample at each of the dilutions in the series. The results from the spore samples show a drastic decrease in spectral information very early in the dilution series. Nearly all spectral information is lost when there are fewer than 50,000 cells on the spot. The peak at approximately 7,760, the most abundant biomarker for the spores, remains barely discernable at 5,000 cells/spot; and no other peaks are seen in the spectrum. The ability to identify the spores at lower concentrations will be dependent on the statistical approaches used.

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58 Figure 2-13. Treatment of spores with Rapigest detergent. A) B. subtilis 168 spores in boiled with Rapigest and analyzed in 0.1% TFA/50% ACN matrix solvent. B) B. subtilis 168 spores boiled in water and analyzed in 30% formic/ 30% ACN. The Rapigest treatment resulted in the release of SASP proteins from the spores. With the additional boiling step, a 43 kDa protein was also extracted with the formic acid treatment.

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59 Figure 2-14. Limit of detection for B. subtilis 168 spores. The dilution series runs from 100,000 cells/spot to 100 cells/spot. At 5,000 cells/ spot the 7,760 Da biomarker is barely discernable in the spectra.

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CHAPTER 3 SPECIES DIFFERENTIATION OF A DIVERSE SUITE OF BACILLUS SPORES AND CELLS WITH MASS SPECTROMETRY BASED PROTEIN PROFILING Introduction In order to overcome the problems involved with phenotypic characterization, 16S ribosomal RNA (16S rDNA) analysis has been used for decades to more accurately define the phylogenetic affiliation of the given test microorganism. 53 However, being highly conserved, the 16S rDNA molecule at times cannot differentiate closely related microbial species. 54,55 Therefore, alternative biomarkers 56 or a suite of protein profiling methods would be useful to effectively differentiate closely related microbial species. In this chapter, the versatility of Matrix-Assisted Laser Desorption/Ionization Time-of-flight Mass Spectrometry (MALDI-TOFMS) protein profiling for the species differentiation of a diverse suite of Bacillus cells and spores is demonstrated. MALDI-TOFMS protein profiles of fourteen different strains of Bacillus, encompassing eleven different species, were evaluated. Bacillus species selected for MALDI-TOFMS analysis represented the spore-forming bacterial diversity of typical class 100K clean-room spacecraft assembly facilities. A majority of the MALDI-TOFMS research directed at Bacillus has focused on only a few spore species. These include B. anthracis and its closely related species B. thuringiensis, B. cereus, 55 B. atrophaeus (formally called B. globigii) 57 an anthrax surrogate, and B. subtilis, whose genome has been completely sequenced and has been thoroughly examined by molecular biological methods. 25,26,38,58 Very little research 60

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61 attention has been given to other Bacillus species, which naturally occur in the environment. The nonpathogenic Bacillus spores, which are ubiquitous in the environment, are the most likely source of interference for any detection technique and have the highest potential to produce false positives. To demonstrate the versatility of MALDI-TOFMS protein profiling for the identification of a variety of spores and cells, a subset of Bacillus species isolated from various NASA spacecraft assembly facilities (class 10 to 100K clean rooms) was used in this study. The optimized one-step sample treatment and MALDI-TOFMS preparation was used to obtain spectra rapidly with a wide range of protein biomarkers, including several higher molecular weight (10-25kDa) protein species for the spores. A library of MALDI-TOFMS spectra was created from the 16 different spores and vegetative cells of the Bacillus species, the most diverse study of the genus reported to date. Linear correlation analysis was used to identify all Bacillus species evaluated. The results obtained from MALDI-TOFMS protein profiling of these Bacillus species were compared with 16S rDNA sequences for their bacterial systematics and molecular phylogenetic affiliations. Materials and Methods Bacterial Strains Bacillus strains used in this study and their source are listed in Table 3-1. Fourteen strains consisting of 11 Bacillus species were studied. The type strains of B. atrophaeus, B. licheniformis, B. megaterium, B. mojavensis, B. thuringiensis, B. pumilus, and B. subtilis were procured from the American Type Culture Collection (ATCC, Manassas, Virginia). B. subtilis 168 was received from Wayne Nicholson, Univ. of Arizona and the B. anthracis 34F2 vaccine strain was from M. Satomi, National Institute of Fisheries,

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62 Japan. B. odysseyi, B. licheniformis KL-196, B. niacini 51-8C, B. megaterium FO-38, and B. psycrodurans were isolated from several NASA spacecraft and assembly facilities surfaces. Bacterial isolation procedures from spacecraft and assembly facilities surfaces were described elsewhere 59,60 Identity of the test organisms was determined based on 16S rDNA sequencing for the environmental isolates; for the ATCC strains, those sequences available in the GenBank database were used 61 The 16S rDNA sequences of the environmental isolates have been deposited in the GenBank nucleotide sequence database. Table 3-1. List of Bacillus species used in this study NameStrain NumberSourceRemarksB. anthracis34F2Inst. of Fisheries, JapanVaccine strainB. atrophaeus9372ATCCSurrogate to B. anthracisB. licheniformis14580ATCCMost predominate species in clean room facilitiesB. licheniformisKL-196JPL-SAFClass 100K clean room floor, JPLB. megaterium14581ATCCB. megateriumFO-38JPL-SAFClean room air particulateB. mojavensis51516ATCCB. niacini51-8CKSC, SAEF-IIMars Odyssey assembly facility floorB. odysseyi34hs1KSC, SAEF-IIMars Odyssey spacecraft surfaceB. psycroduransVSE1-06KSC, PHSFMars Exploration Rover assembly facility air particlesB. pumilus7061ATCCSecond most predominate species in clean room facilitiesB. subtilis168University of ArizonaGenome fully sequencedB. subtilis6051ATCCType species of Bacillus genusB. thuringiensis10792ATCCInsecticide producing bacteria and phylogenetically unseparable from B. anthracisAbbreviations: ATCC, American type culture collection; SAF, Spacecraft assembly facility; SAEF-II, Spacecraft assembly and encapsulation facility-II; PHSF, Payload handling and spacecraft assembly facility; JPL, Jet Propulsion Laboratory; KSC, Kennedy Space Center Sporulation of Bacillus isolates A nutrient broth sporulation medium (NSM) was used to produce spores. 7,62 A single purified colony of the strain to be sporulated was inoculated into the NSM liquid medium. After 1 to 3 days of incubation at 32 o C under shaking conditions, cultures were

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63 examined using phase-contrast microscopy to determine the level of sporulation. Microcosms that attained >99% of spores were further purified to remove vegetative cells or cell debris as previously reported. 7 The purified spores were suspended in sterile deionized water and stored at 4 o C in glass tubes until analyzed. Before the analysis, spore suspensions were adjusted to give an optical density of 0.6 at 600 nm, which resulted in suspensions that were between 10 8 to 10 9 spores/mL. Preparation of Vegetative Cells A stock culture of each Bacillus species was streaked for isolation on tryptic soy agar (TSA) plates. B. anthracis 34F2, B. subtilis 168, B. pumilus 7061, and B. thuringiensis were also streaked on nutrient agar (NA) plates and Luria-Bertani (LB) plates for a study of the effect of different growth media on the spectra. The plates were incubated at 32 o C for 16 hours except in the case of the media study where the plates were incubated for 24 hours. Single purified colonies were removed from the plate with a sterile loop and were placed in 100 L of a phosphate buffered saline (PBS) solution. Most colonies were approximately 2 mm in diameter. If larger colonies were present only a 2 mm portion was removed for washing and analysis. The cells were vortexed in PBS for 15 minutes and then were pelleted by centrifugation for 10 minutes at 9600 x g. The supernatant was removed and the cell pellet was used for subsequent analysis. Sample Preparation for Mass Spectrometry A saturated matrix solution was prepared by dissolving 20 mg of ferulic acid into a 1 mL solution of 30% acetonitrile, 30% formic acid. As described in Chapter 2, this solvent system was selected due to the higher signal-to-noise, consistent crystallization, and better ability to differentiate across the various bacterial species. This effect was due to a combination of an increased number of biomarker peaks and the higher molecular

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64 weight range of these peaks in the spectra. 63,64 A 2.5 L aliquot of the spore suspension (0.6 OD 660 ) was added to 22.5 L of the matrix solution. This mixture was vortexed briefly and then 1 L of the sample containing both spores and matrix compound was removed and spotted on a SCOUT26 MALDI plate (Bruker Daltonics; Billerica, Ma). For the preparation of vegetative cells, 25 L of the matrix solution was mixed directly with the cell pellet. This solution was sonicated for 3 minutes and then vortexed for 3 minutes. A 1 L aliquot of the vegetative sample was then placed on the MALDI plate for analysis. Spots were allowed to air dry. No further treatments were applied to the spots once dried. Spots were prepared in duplicate for each sample mixture. Sample preparation required only a few minutes per sample. Mass Spectrometry Analysis MALDI-TOFMS analysis was performed on a Bruker Daltonics Reflex II Mass Spectrometer (Bruker Daltonics, Billerica, Ma) retrofitted with delayed extraction. The instrument was operated in the linear mode. A nitrogen laser (337 nm) pulsed at a frequency of 5 Hz irradiated the sample. Spectra were obtained in positive ion mode with a delay time of 50 ns. The acceleration voltage was 20 kV. An ion deflector was used to deflect low mass ions that would saturate the detector. The deflector was set at 2,500 Da. The laser intensity was adjusted to just above the threshold for ion formation for each sample. The instrument was calibrated daily using external calibration with a mixture of bovine insulin and equine cytochrome C. All spectra represent the accumulation of 50 laser shots. Ten spectra were collected from each spot on the MALDI plate. A total of 20 spectra were collected per sample.

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65 Spectral Processing and Statistical Methodology Prior to statistical analysis, each spectrum was baseline-corrected and smoothed using a ten point Savitzky-Golay smoothing algorithm. Normalized spectra were converted into ASCII files for statistical processing. Because linear correlation is invariant with respect to a linear transformation of spectra, the relative, not absolute, intensities were important for correlation analysis. Statistical analysis of the data was performed using linear correlation software developed in house using Visual Basic 6.0. 65-67 Spectra from the mass spectrometer were imported into the software as ASCII files and libraries were created using the average of the 20 spectra collected per sample (10 spectra per spot). Correlation analysis was performed on a point-to-point basis based on the following equation for the Pearson correlation coefficient, r: 22)()())((yyxxyyxxriiiii where x is the mean of s and ix y is the mean of s. The s and s are the intensities at the i-th pixel of the detector which in this case corresponds to the m/z (i=1.N; for the m/z range 2,500-60,000 N is approximately 16,000 points). The s, belong to an analyzed spectrum, and the s belong to one of the library spectra. The spectrum consisting of s is correlated against each spectrum in the library (different sets of s) and the closest match with the highest correlation coefficient indicated a similarity of this spectrum with the corresponding library spectrum. Conversely, the difference between this and other correlation coefficients signified spectral dissimilarities. To quantify the level of significance of these differences, a Students tiy ix iy ix iy ix iy

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66 test was applied. Student t values were calculated differently depending on whether the two distributions had the same or different variances. To check this, an F-test was applied (F denoting the ratio of the variances) as the basis of t-values. The probabilities that two distributions of correlation coefficients had different means were calculated. A reference library of spores and vegetative cells, consisting of the average spectrum created from the 20 spectra collected for each sample, was produced for all of the fourteen species evaluated in this study. The individual spectrum and the average spectrum obtained for each of the 14 strains were then compared to the MALDI-TOFMS spectra stored in the library to elucidate the bacterial speciation. To evaluate the reproducibility of the technique, a separate set of MALDI-TOFMS spectra were collected and averaged for all of the different species of spores in this study. The averages of these separate analyses were compared with the library spectra. To address batch-to-batch variability, B. subtilis 168 spore cultures prepared at different times over the course of two years were analyzed and compared to the library spectra. In the case of vegetative cells, colonies from 3 different agar plates were analyzed to ascertain the effect of different growth media and incubation times on the spectra. In conjunction with the correlation analysis, hierarchal cluster analysis (HCA) was used to help visualize and categorize the different species. The HCA analysis was performed using the commercially available statistical software SPSS (Chicago, IL). Dendrograms were produced based on the Pearson correlation value between the spectra using the nearest neighbor method (single linkage). To help visualize the peak patterns for the spectra, Surfer 8.0 from Golden software (Golden, CO) was used to create an image map with 10 Da resolution from the average spectra for each species. The image

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67 map provided a 3D representation of the spectra where the color of the band was indicative of peak intensity. Results and Discussion Incidence of Spore-Forming Microbes from Spacecraft Associated Environments Among several hundred aerobic spore-forming bacteria isolated from several spacecraft and associated facility surfaces, >90% of the isolates were found to be phylogenetically affiliated with the members of the genus Bacillus. 59-61 B. licheniformis (25%) and B. pumilus (16%) were the most prevalent Bacillus species isolated. Since B. licheniformis was the most prevalent Bacillus species in the environment and B. subtilis is the type species of the Bacillus genus, multiple strains of these species were included in this study. An additional wild-type strain of B. megaterium was included as well. To avoid confusion about the identity of the bacterial species, wherever possible, authentic type strains were procured from the culture collection and used. All tested Bacillus species fall into the RNA group I except B. psychrodurans and B. odysseyi, which are in RNA group II. 68,69 Group I includes aerobic Bacillus species that produce acid from a variety of sugars including glucose and whose spores are ellipsoidal and do not swell the mother cell. Group II Bacillus species are also aerobic; however, they do not produce acids from sugars and even though they also produce ellipsoidal spores, they swell the mother cell. As the Bacillus species of other rDNA groups were not isolated from class 100K clean-room facilities, 59-61,70 the characterization of the species by MALDI-TOFMS was restricted to the sixteen members of these two rDNA groups. Molecular Phylogeny of Spore-Forming Microbes The sequence similarities based on 16S rDNA sequences of the various Bacillus species tested are shown in Table 3-2. These sequences were either obtained from the

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68 GenBank database or were sequenced in previous studies. 59-61,70 The similarities in 16S rDNA nucleotide sequence between the tested Bacillus species, recognized by GenBank BLAST searches, were between 91 and 99%. A sequence variation of ~9% was found between rDNA groups 1 and 2 Bacillus species. A very high sequence variation within a well-described genus is not uncommon. Further analyses indicated that B. atrophaeus shares a close phylogenetic relationship with several Bacillus species such as B. mojavensis, B. pumilus and B. subtilis (>97.5%). Similarly, B. licheniformis wild-type Table 3-2. 16S rDNA sequence similarities for the various Bacillus species studied BacteriaB atrophaeus X60607B licheniformis AF387515B licheniformis X68416B megaterium X60629B mojavensis AB021191B odysseensis AF526913B psychrodurans VSE1 06B pumilus AB020208B subtilis 168 rrnAB subtilis X60646B thuringiensis X55062B atrophaeus X60607100B licheniformis AF38751596.9100B licheniformis X6841698.598.3100B megaterium X6062994.492.794.1100B mojavensis AB02119199.396.798.494.1100B odysseyi AF52691392.090.191.593.491.8100B psychrodurans VSE1 0691.890.591.592.991.595.4100B pumilus AB02020897.694.996.394.396.991.892.4100B subtilis 168 rrnA99.496.998.694.199.791.691.497.2100B subtilis X6064699.396.798.394.199.691.691.296.999.8100B thuringiensis X5506295.292.994.294.794.392.892.094.394.294.3100 strain KL-196 and B. mojavensis, as well as two B. subtilis strains tested in this study showed >98% 16S rDNA sequence similarities. Such high 16S rDNA sequence similarities was also noticed (>99%) in the case of the two B. subtilis strains sequenced and B. mojavensis. This clearly showed that 16S rDNA sequence analysis was not useful in differentiating these closely-related species of the genus Bacillus. The species

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69 identities of all these strains were confirmed by DNA-DNA hybridization (M. Satomi, personal communication). The two strains of B. licheniformis and B. subtilis showed >70% DNA-DNA hybridization dissociation values and exhibited >98.5% 16S rDNA sequence similarities. When all these species were grouped together, the maximum-likelihood based phylogenetic tree showed two major clusters (M. LaDuc, K. Venkateswaran, personal communication). One cluster consists of B. megaterium, B. odysseyi, B. psychrodurans, and B. thuringiensis, where the spores of these species contained an additional structure called exosporium around the spore outer coat. The second cluster formed by the other species tested did not contain an exosporium. MALDI-TOFMS Spore Profiles A representative spectrum from each Bacillus species analyzed in this study is shown in Figure 3-1 A-N. The mass spectra are presented with m/z values from 3,000-25,000. The m/z region from 9,500-25,000 is amplified (see inset of each spectrum) to aid in visualization of the less abundant peaks present at higher m/z. The observation of proteins at higher m/z is seldom reported in other MALDI-TOFMS analyses of whole spores. 25,26,34,35,38 We hypothesize that the appearance of large proteins at high m/z is due to optimization of the solvent system used in this study. From the spectra, we were unable to identify an obvious Bacillus-ubiquitous biomarker with the sample preparation protocol adapted in this study. A peak at 14,500 m/z was present in most of the spore spectra obtained except for that of the B. licheniformis ATCC 14580 type strain, its wild-type strain KL-196, and B. anthracis 34F2. The absence of a genus specific biomarker might be due to the extraction protocol used in this study, post translational modifications of proteins that may differ between the strains, or the need for more sophisticated spectral comparisons of the different species.

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70 All of the spores have a group of peaks in the m/z region from 6,500-8,000. B. licheniformis ATCC 14580, B. licheniformis KL-196, B. psychrodurans, B. odysseynsis and B. megaterium ATCC 14581, and B. megaterium FO-38 all have an additional group of peaks between m/z 5,000-6,500 that was not observed in the other spectra. It was challenging to obtain good spectra from the B. odysseyi samples as shown by the lower signal-to-noise in the spectra. This could have been a result of glycoproteins present in the exosporium layers. Glycoproteins can be challenging to analyze due to difficulty in the ionization of the sugar moieties and the inherent heterogeneity of glycosolations. An expected result was the level of similarity between the strains of the same species. B. licheniformis ATCC 14580 type strain (Figure 3-1C) and its wild-type strain KL-196 (Figure 3-1B), B. subtilis 168 (Figure 3-1I) and ATCC 6051 (Figure 3-1J), and B. megaterium ATCC 14581 (Figure 3-1D) and B. megaterium FO-38 (Figure 3-1M) have very comparable MALDI-TOFMS profiles upon visual inspection. The spectra for the B. licheniformis pair were very similar except for a difference in intensity of the m/z 7,260 peak and the presence of different higher molecular mass species in B. licheniformis 14580. The B. subtilis pair has the same pattern in that there was a difference in peak intensity for the peak at m/z 6,936 and variation in the masses observed above m/z 10,000. Similar patterns were also observed in the B. megaterium pair. This observation supports the theory that it is important to examine a wide variety of Bacillus spores before assigning definitive genus, species, and strain specific protein biomarkers. Linear correlation analysis provided a means of statistical comparison of the spectra. Correlation values close to 1 indicate that the fingerprint patterns of two organisms are very similar. Table 3-3 shows the linear correlation values for the

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71 Figure 3-1. MALDI-TOFMS protein profiles of the 14 Bacillus spore species analyzed in this study. The mass range depicted is from m/z 3,000-25,000. The higher molecular mass region from m/z 9,500-25,000 is amplified 4x (see inset of each spectrum) in order to visualize the higher molecular weight peaks that are present but are at much lower abundance in the samples. A) B. atrophaeus ATCC 9372. B) B. licheniformis KL-196. C) B. licheniformis ATCC 14580. D) B. megaterium ATCC 14581. E) B. mojavensis ATCC 51516. F) B. odysseyi ATCC PTA-4993. G) B. psycrodurans VSE1-06. H) B. pumulis ATCC 7061. I) B. subtilis 168. J) B. subtilis ATCC 6051. K) B. thuringiensis ATCC 10792. L) B. anthracis 34F2. M) B. megaterium FO-38. N) B. niacini 51-8C.

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72 Figure 3-1. Continued.

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73 Figure 3-1. Continued.

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74 MALDI-TOFMS spectra of the various Bacillus spore species evaluated when compared to the library spectra. Each of the 20 individual spectra from each species was searched against the user generated average library spectra. All individual spectra were successfully identified as their corresponding species and strain. These results were verified by applying a Students t-test to the data. Using the t-test, we confirmed that we could differentiate all the species studied at the 95% confidence level. Figure 3-2 shows the correlation results of the 20 individual B. atrophaeus spectra when searched against Table 3-3. Correlation values based on MALDI-TOFMS protein profiling of the spores of the Bacillus species in this study 34F2ATCC 9372ATCC 14580KL-196ATCC 14581FO-38ATCC 5151651-8C34hs1VSE1-06ATCC 7061168ATCC 6051ATCC 10792B. anthracisB. atrophaeusB. licheniformisB. licheniformisB. megateriumB. megateriumB. mojavensisB. niaciniB. odysseyiB. psychroduransB. pumulisB. subtilisB. subtilisB. thuringiensisB. anthracis34F21B. atrophaeusATCC 93720.051B. licheniformisATCC 145800.010.091B. licheniformisKL-1960.010.030.901B. megateriumATCC 14581-0.010.140.300.091B. megateriumFO-380.000.160.140.000.741B. mojavensisATCC 515160.010.200.230.070.370.451B. niacini51-8C0.020.050.130.120.060.030.021B. odysseyi34hs10.010.350.150.050.260.280.210.171B. psychroduransVSE1-060.000.040.450.420.350.190.050.060.161B. pumulisATCC 70610.000.140.270.040.450.480.440.020.340.071B. subtilis168-0.010.090.040.010.110.410.07-0.010.05-0.010.021B. subtilisATCC 60510.010.230.050.010.110.360.070.030.290.010.050.881B. thuringiensisATCC 107920.110.520.060.030.070.050.050.030.330.080.090.020.131Bacterial spores the library spectra. The y axis represents the linear correlation values obtained and the x-axis represents the 1 st -5 th ranks (hits) from the library. At each rank, the standard deviation of the measurement across the 20 spectra is represented by the error bars. The graph demonstrates that for rank 1 (B. atrophaeus), we have very high correlation values (0.96.02). For the next best hit, B. thuringiensis, the correlation values are much lower (0.51.02). Since none of the correlation values approach the B. atrophaeus hit, we can confirm the differentiation of B. atrophaeus from all of the other strains in the library.

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75 The linear correlation method applied here also allows for differentiation of the species whose MALDI-TOFMS profiles are almost indistinguishable upon visual inspection, including the type strain and wild-type strains of B. subtilis, B. megaterium, and B. licheniformis. Figure 3-3 shows the correlation results of B. subtilis 168 versus the library spectra as described above. The 2 nd rank (or hit) is much closer than in the case of B. atrophaeus, the values for the first rank are 0.98.02 and the second rank are 0.86.02. The second rank represents B. subtilis 6051, the other B. subtilis strain in this study. With statistical treatment of the data, the 2 strains were still able to be differentiated at the 95% confidence interval. The close correlation values of 0.88.02 for the B. licheniformis pair and 0.86.02 for the B. subtilis pair illustrate that close correlation values indicate a relationships between the organisms. However, with statistical treatment of the data, differentiation at the strain level in these two examples can still be obtained. To ascertain the robustness of the technique, separate spectra collected and averaged from the same spore culture were examined. All 16 species were correctly identified by comparison to the library spectra (r=0.85-0.98). This result was consistent whether the individual spectra themselves or averages of the individual spectra were used to search the library. In addition to the new preparations from the same culture, four batches of spores of B. subtilis 168, prepared at different times over the course of 2 years, were also compared against the library spectra. All of the B. subtilis 168 spores were correctly identified as the B. subtilis 168 from the library, regardless of the batch or storage time (r=0.92-0.98).

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76 Aligning the correlation results from the MALDI-TOFMS profiles (Table 3-3) with the 16S rDNA sequence analysis (Table 3-2) shows that the MALDI-TOFMS profiles were complementary to 16S rDNA analysis. Using MALDI-TOFMS spore profiles of these organisms, we were able to differentiate all of the species studied confidently, whereas there are several species including B. subtilis 168, B. licheniformis, B. mojavensis, and B. atrophaeus that 16S was unable to differentiate at the species level. MALDI-TOFMS analysis on these species would allow for differentiation at the species level. Comparing the MALDI protein profiles with the phenotypic groupings was challenging due to the large diversity in the number and range of the peaks across the spectra for all of the species studied. In general, spores with an exosporium resulted in spectra that had more peaks over a broader range than the non-exosporium organisms. On average, the phenotypic group IV organisms had more peaks than the group II organisms, with the exception of B. megaterium and its wild-type FO-38. Cluster analysis was applied to the data to allow the relationships based on protein profiles between the different species to be visualized. The results of the single linkage cluster analysis using the SPSS software package are shown in Figure 3-4 combined with an image map of the spectra for visualization. MALDI-TOFMS Vegetative Profiles The bulk of this work was focused on the analysis of spores; however, the same technology was applicable for the analysis of vegetative cells. For routine analysis and identification (not direct environmental sampling), samples would likely be cultured prior to analysis. One of the advantages, other than speed, of the MALDI technique developed

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77 Figure 3-2. Correlation results of the 20 individual B. atrophaeus ATCC 9372 spectrum when searched against the library. The y axis represents the linear correlation values obtained and the x-axis represents the 1 st -5 th ranks (hits) from the library. At each rank, the standard deviation of the measurement across the 20 spectra is represented by the error bars.

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78 Figure 3-3. Correlation results of the 20 individual B. subtilis 168 spectrum when searched against the library. The y axis represents the linear correlation values obtained and the x-axis represents the 1 st -5 th ranks (hits) from the library. At each rank, the standard deviation of the measurement across the 20 spectra is represented by the error bars.

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79 Figure 3-4. Visualization of the spectra in-line with the dendrogram for the spores in this study. The dendrogram is based on a single linkage scheme. Peak intensity is indicated by brighter colors in the image map. The dendrogram is highlighted to show that the closest clusters are between strains of the same species.

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80 here was the amenability to the presence of numerous cultures on a single plate, which could be removed individually with a sample loop for analysis. This could eliminate the need for several incubation steps while trying to isolate a single organism. To determine the scope of the current methodology the vegetative cells of the different species were also examined. The same extraction protocol with no modifications was used on the vegetative cells and should be effective since spores should present the more difficult challenge for protein extraction. The vegetative cell spectra for each of the species analyzed are shown in Figure 3-5 from m/z 2,500-60,000. The region from m/z 20,000-60,000 is amplified by 4x to highlight the upper molecular weight region of the spectra. Profiles of the vegetative cells have protein biomarker peaks that extend to a much higher range than their corresponding spore spectra. The vegetative profiles also have a greater number of peaks than the spores. The spectra obtained in this study have similar numbers of peaks as vegetative cell spectra in other studies where formic acid and ferulic acid were used in the matrix. No protein peaks were observed to overlap between the vegetative and spore spectra from the same strain, particularly due to the presence of peaks above 30 kDa in most the vegetative cell spectra. Correlation analysis of the vegetative cells gave us very similar results to those of the spores. Complete differentiation of the different strains examined was possible and the highest correlation values were found between the B. subtilis and B. licheniformis pair (Table 3-4). Repeat analysis of different colonies from the plates gave correlation values of 0.71-0.85 with their corresponding library spectra. Since the vegetative cell spectra

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81 Figure 3-5. MALDI-TOFMS protein profiles of the 14 Bacillus vegetative species analyzed in this study. The mass range depicted is from m/z 2,500-60,000. The higher molecular mass region from m/z 20,000-60,000 is amplified 4x (see inset of each spectrum) in order to visualize the higher molecular weight peaks that are present in the samples. A) B. atrophaeus ATCC 9372. B) B. licheniformis KL-196. C) B. licheniformis ATCC 14580. D) B. megaterium ATCC 14581. E) B. mojavensis ATCC 51516. F) B. odysseyi ATCC PTA-4993. G) B. psycrodurans VSE1-06. H) B. pumilus ATCC 7061. I) B. subtilis168. J) B. subtilis ATCC 6051. K) B. thuringiensis ATCC 10792. L) B. anthracis 34F2. M) B. niacini 51-8C.

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82 Figure 3-5. Continued.

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83 are more complex than the spore spectra, hierarchical cluster analysis (HCA) in conjunction with visualization using image mapping was used to observe patterns in the spectra (Figure 3-6). The HCA analysis divided the vegetative cells into two clusters, one consisting of B. atrophaeus, B. mojavensis, the B. licheniformis pair, and B. subtilis pair and the second cluster containing the other species. B. thuringiensis had fewer peaks in comparison with the other vegetative cells and, therefore, was not similar to either cluster. The second cluster had more peaks overall than the first cluster and contained the RNA group 2 organisms. All of the species in the first cluster contained a biomarker peak at 9,890 Da which was not present in the second cluster. In addition, all the species in the first cluster except the B. licheniformis pair had a biomarker peak at 3,405. There were no obvious biomarker peaks observed in the second cluster. Table 3-4. Correlation values based on MALDI-TOFMS protein profiling of the vegetative cells of the Bacillus species in this study 34F2ATCC 9372ATCC 14580KL-196ATCC 14581ATCC 5151651-8C34hs1VSE1-06ATCC 7061168ATCC 6051ATCC 10792B. anthracisB. atrophaeusB. licheniformisB. licheniformisB. megateriumB. mojavensisB. niaciniB. odysseyiB. psychroduransB. pumulisB. subtilisB. subtilisB. thuringiensisB. anthracis34F21B. atrophaeusATCC 93720.231B. licheniformisATCC 145800.160.141B. licheniformisKL-1960.090.070.931B. megateriumATCC 145810.370.270.250.151B. mojavensisATCC 515160.160.210.220.190.211B. niacini51-8C0.400.320.200.130.610.241B. odysseyi34hs10.370.250.150.060.530.210.571B. psychroduransVSE1-060.370.260.200.100.490.230.490.631B. pumulisATCC 70610.310.210.180.100.450.290.490.520.391B. subtilis1680.180.530.290.240.280.670.250.320.300.341B. subtilisATCC 60510.220.320.430.350.300.580.200.290.330.300.801B. thuringiensisATCC 107920.270.01-0.02-0.020.03-0.010.040.070.060.03-0.010.001Bacteria (vegetative)

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84 Figure 3-6. Visualization of the spectra in-line with the dendrogram for the vegetative cells in this study. The dendrogram is based on a single linkage scheme. Peak intensity is indicated by brighter colors in the image map.

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85 Four strains (B. subtilis 168, B. anthracis 34F2, B. pumilus ATCC 7061, and B. thuringiensis ATCC 10792) were chosen to further study the variability of growth media on the spectra from vegetative cells. These strains were cultured on 3 media, TSA, NA, and LB, under identical incubation conditions. Upon observation, there was a significant difference in the size of the colonies on the different plates. The largest colonies were on the TSA plates, followed by NA and then LBA plates. Every effort was made to remove similar size samples for each strain by only using a small portion from the edges of the larger colonies. Table 3-5 shows the results of the correlation analysis of these samples with each other. Figure 3-6, 3-7, 3-8, and 3-9 show the average spectra from each species on each of the growth plates. Table 3-5. Correlation values based on MALDI-TOFMS protein profiling of vegetative cells of select Bacillus species incubated on three different growth media LBNATSALBNATSALBNATSALBNSTSAB. anthracis 34F2B. anthracis 34F2B. anthracis 34F2B. pumilus 7061B. pumilus 7061B. pumilus 7061B. subtilis 168B. subtilis 168B. subtilis 168B. thuringiensis 10792B. thuringiensis 10792B. thuringiensis 10792B. anthracis 34F2LB-B. anthracis 34F2NA0.75-B. anthracis 34F2TSA0.730.77-B. pumilus 7061LB0.310.350.58-B. pumilus 7061NA0.290.310.440.78-B. pumilus 7061TSA0.320.340.560.820.78-B. subtilis 168LB0.140.100.140.240.270.25-B. subtilis 168NA0.460.550.370.060.070.070.03-B. subtilis 168TSA0.150.140.180.230.270.250.800.05-B. thuringiensis 10792LB0.560.560.700.480.400.480.120.210.17-B. thuringiensis 10792NS0.440.460.370.110.110.120.040.450.090.39-B. thuringiensis 10792TSA0.410.400.370.140.100.140.030.340.060.630.64-Bacteria (vegetative)MediaAbbreviations: LB, Luria-Bertani Agar; NA, Nutrient Agar; TSA, Tryptic Soy Agar

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86 In the case of B. anthracis (Figure 3-6) and B. pumilus (Figure 3-9), the spectra from all 3 of the growth media maintained correlation values of above 0.70 when compared with each other. In both cases, visual observation of the spectra revealed that the 3 samples had several biomarker peaks in common but the NA sample (middle) had additional biomarker peaks not seen in the TSA (top) or LB (bottom) samples. In B. subtilis 168 (Figure 3-7), the TSA and LB samples were similar to each other (r = 0.80); however, the NA sample had few biomarkers in common with the other two samples and was significantly different. The B. subtilis 168 sample grown on NA also demonstrated the presence of higher molecular weight biomarkers not seen in the other samples. The B. thuringiensis cells grown on the different media (Figure 3-8) were very dissimilar, supported by very low correlation values and visual observation of the spectra. The most significant difference in these samples is seen in the range above 30 kDa and below 7 kDa. Several biomarkers, including 2,891 Da, 10,010 Da, and 19,046 Da are common across all B. thuringiensis samples in this study. Therefore, it is still possible to identify species specific biomarkers present in several growth media. Notably, the B. thuringiensis cells grown on the LB plates had a correlation value of 0.70 with the B. anthracis cells grown on TSA even though they do not share the above mentioned biomarkers. The B. anthracis and B. thuringiensis samples have the 7,350 Da biomarker in common. The differences in the protein profiles on the 3 media could be an effect of the difference in growth phase of the organism or the differences in the proteins expressed due to the nutrients available in the different media. The cells in the media study were grown for 8 hours longer than the cells in which the initial comparisons of the vegetative cells were done. The media samples (20 hour

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87 Figure 3-7. MALDI-TOFMS protein profiles of B. anthracis 34F2 vegetative cells from different growth media: tryptic soy agar (top), nutrient agar (middle), and Luria Bertani agar (bottom). The mass range is from m/z 2,500-60,000. The higher molecular mass region from m/z 20,000-60,000 is amplified 4x (see inset of each spectrum) to aid in the visualization of the higher molecular weight peaks that are present.

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88 Figure 3-8. MALDI-TOFMS protein profiles of B. subtilis 168 vegetative cells from different growth media: tryptic soy agar (top), nutrient agar (middle), and Luria Bertani agar (bottom). The mass range depicted is from m/z 2,500-60,000. The higher molecular mass region from m/z 20,000-60,000 is amplified 4x (see inset of each spectrum) to aid in the visualization of the higher molecular weight peaks that are present.

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89 Figure 3-9. MALDI-TOFMS protein profiles of B. thuringiensis ATCC 10792 vegetative cells from different growth media: tryptic soy agar (top), nutrient agar (middle), and Luria Bertani agar (bottom). The mass range depicted is from m/z 2,500-60,000. The higher molecular mass region from m/z 20,000-60,000 is amplified 4x (see inset of each spectrum) to aid in the visualization of the higher molecular weight peaks that are present.

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90 Figure 3-10. MALDI-TOFMS protein profiles of B. pumilus 7061 vegetative cells from different growth media: tryptic soy agar (top), nutrient agar (middle), and Luria Bertani agar (bottom). The mass range depicted is from m/z 2,500-60,000. The higher molecular mass region from m/z 20,000-60,000 is amplified 4x (see inset of each spectrum) to aid in the visualization of the higher molecular weight peaks that are present.

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91 incubation) were compared with the vegetative cell library above (16 hour incubation) to ascertain the difference that growth time can make on the spectra. In the case of B. pumilus 7061 and B. anthracis 34F2, all of the media samples were positively identified with the B. pumilus 7061 and B. anthracis 34F2, samples from the previous day. The correlation values for the TSA, NA, and LB samples with the type strain sample on TSA from the previous day were 0.85, 0.76, and 0.83 respectively for the B. pumilus 7061 and 0.68, 0.62, and 0.88 for the B. anthracis 34F2. In the case of B. thuringiensis, the TSA and NA samples were correctly identified with correlation values of 0.88 and 0.58; however, the LB sample again had the highest correlation with the B. anthracis sample from the previous day (r = 0.57). Only B. subtilis 168 grown on LB was properly identified, with a correlation value of 0.71. The NA sample was closest to B. thuringiensis (r = 0.40) and the TSA sample was closest to B. atrophaeus (r = 0.68), both grown on TSA from the previous study. Although not all of the species type out properly, the robustness of the technique was highlighted, as cells grown on different media and incubation times still gave relatively high correlation values to a library strain of the same species under different conditions. To determine if the absolute value of r was significant (i.e., does an r of 0.40 indicate a good match?), a more detailed study was needed to determine the range of correlation values encountered when considering the strain variation across a species. Conclusion MALDI-TOFMS based protein profiling is a useful, rapid, and sensitive technology to differentiate spores and vegetative cells from closely related microbial species. Although a standardized sample preparation protocol is required, it is obvious that this

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92 technology is promising for species differentiation of a wide variety of bacterial spores and cells.

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CHAPTER 4 MALDI-TOFMS COMPARED WITH OTHER POLYPHASIC TAXONOMY APPROACHES FOR THE IDENTIFICATION AND CLASSIFICATION OF Bacillus pumilus SPORES Introduction To verify the efficacy of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) protein profiling for identifying and differentiating bacterial species, several strains of Bacillus pumilus were examined in a thorough taxonomic study incorporating a polyphasic approach. MALDI-TOFMS protein profiling is rapid, sensitive, and has higher resolution and better reproducibility than gel-based protein or DNA fingerprinting, and has proven effective for bacterial identification. 16,31,33 By carefully controlling extraction conditions combined with suitable software for data analysis, MALDI-TOFMS has the potential to identify and classify previously unidentified environmental isolates. The realization of this potential is dependent on the availability of standardized MALDI-TOFMS profile libraries for comparison of unknown isolates with reference strains. Verification of this microbial classification scheme has not been thoroughly explored, and published studies on this technique have focused solely on bacteria from culture collections and/or blind studies using strains already represented within user generated libraries. 20,71,72 These studies have included members of Enterobacteriaceae, Bacillus, Staphylococcus, Streptococcus, and other medically important species. Similar MALDI-TOFMS studies have been reported on the species and strain differentiation of Bacillus spores; 25,26,29,32,73 however, protein profile variation in spores 93

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94 of a single species by examining several strains isolated from various sources has not been reported to our knowledge. Such research will support the application of MALDI-TOFMS in field applications. In the current study, 16 isolates of putative B. pumilus from different spacecraft assembly facilities, the Mars Odyssey spacecraft, and the International Space Station, were characterized using the Biolog system, DNA techniques, and MALDI-TOFMS protein profiling. B. pumilus is one of the predominant spore-forming microbes in spacecraft and associated clean room environments. 60 Moreover, resistance of B. pumilus spores to various stressors is strain-specific 74 and might be influenced by the environmental factors resulting in the expression of different proteinaceous compounds for protection. 75,76 A one-step sample treatment and MALDI-TOFMS preparation was used to obtain spectra for the creation of a library of spectra from the different isolates of putative B. pumilus, providing the most diverse study of a single bacterial spore species using protein profiling reported to date. The results obtained from MALDI-TOFMS protein fingerprinting of these B. pumilus isolates was compared with DNA-DNA hybridization for their bacterial systematics and molecular phylogenetic affiliations. MALDI-TOFMS protein profiling was more accurate than Biolog metabolic profiling, more discriminating than 16S rDNA sequence analysis, and complemented the results of gyrB sequence analysis and DNA-DNA hybridization for the identification of the B. pumilus spores. This is the first report whereby MALDI-TOFMS generated protein profiles from a set of microbes are compared directly with DNA-DNA hybridization yielding a positive correlation. Unique, cluster-specific biomarker peaks have been identified in the spores of the B. pumilus examined in this study. MALDI-TOFMS protein profiling is a rapid and simple analysis

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95 and is demonstrated as a useful taxonomic tool for differentiating spores of the genus Bacillus. For practical purposes, it would be ideal (and necessary) to have a publicly available, standardized MALDI profile database, to facilitate the use of the technique as a diagnostic method to differentiate bacterial species. Materials and Methods Bacterial Strains Table 4-1 contains a list of the wild-type bacterial strains used in this study. All ATCC strains were procured from the American Type Culture Collection (Manassas, VA), including the type strains of B. atrophaeus, B. subtilis, B. megaterium, B. mojavensis, B. pumilus, and B. licheniformis. The B. odysseyi type strain was from our culture collection and B. subtilis 168 was obtained from Dr. Wayne Nicholson at the University of Florida. The source, location, and date of isolation of the 16 wild-type isolates of putative B. pumilus are indicated in Table 1 along with the other isolate species used in this study. Bacterial isolation procedures from spacecraft assembly facility surfaces are described elsewhere 59,61 Sporulation of Bacillus isolates A standard protocol for the production of spores was used in this study 7 A single purified colony of the strain to be sporulated was inoculated into nutrient broth sporulation medium (NSM) and incubated at 32 o C with shaking for ca. 2-4 days, until the cultures reached >99% spores as examined by phase-contrast microscopy. Spore cultures were harvested by centrifugation and purified to remove remnant vegetative cells and cellular debris, as previously reported 7 The purification protocol involved a lysozyme treatment followed by salt and detergent washes to remove vegetative cellular debris.

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96 Purified spores were adjusted to an optical density of 0.6 at 600 nm and were stored in sterile deionized water at 4 o C in glass vials until analyzed. Table 4-1. Strain designation, grouping, and source of Bacillus species in this study B. pumilus type strain groupB. pumilusATCC 7061TATCC-AB020208Type strainB. pumilusATCC 27142ATCC-n/aGamma radiation resistant strainB. pumilus0105342-2ISS-hardware2000n/aInternational Space Station hardwareB. pumilusSAFN-029JPL-SAF2001AY167883Air-lockB. pumilusSAFR-032JPL-SAF2001AY167879Air-lockB. pumilus FO-036b groupB. pumilusFO-033JPL-SAF1999AF234851Clean room air particulateB. pumilusFO-036bJPL-SAF1999AF234854Clean room air particulateB. pumilusSAFN-001JPL-SAF2001AY167886Entrance floorB. pumilusSAFN-027JPL-SAF2001AY167884Ante-roomB. pumilusSAFN-036JPL-SAF2001AY167881Clean room floorB. pumilusSAFN-037JPL-SAF2001AY167880Clean room floorB. pumilusKL-052JPL-SAF2000AY030327Clean room cabinet topB. pumilus51-3CMars Odyssey2002AF526907Mars Odyssey spacecraft surfaceB. pumilus81-4CKSC-SAEF II2002AF526903Mars Odyssey assembly facility floorB. pumilus82-2CKSC-SAEF II2002AF526902Mars Odyssey assembly facility floorB. pumilus84-1CKSC-SAEF II2002AF526898Mars Odyssey assembly facility floorB. pumilus84-3CKSC-SAEF II2002AF526896Mars Odyssey assembly facility floorB. pumilus84-4CKSC-SAEF II2002AF526895Mars Odyssey assembly facility floorWild-type strains of other Bacillus speciesB. cereusFO-11JPL-SAF1999AY461790 Clean room air particulateB. licheniformisKL-196JPL-SAF2000AF387515Clean room cabinet topB. niacini51-8CKSC-SAEF II2002AF526905 Mars Odyssey assembly facility floorB. odysseyiPTA-4399Mars Odyssey2002AF526913Mars Odyssey spacecraft surfaceB. psychroduransVSE-01KSC-PHSF2002n/aMars Exploration Rovers assembly facility air particles b Included sequences reported in various publications were used for comparison (LaDuc et. al. 2003b; Venkateswaran et. at. 2001)SpeciesaAbbreviations: JPL, Jet Propulsion Laboratory, KSC, Kennedy Space Center, SAF, Spacecraft Assembly Facility, PHSF, Payload Hazardous Servicing Facility, SAEF, Spacecraft Assembly and Encapsulation Facility, ATCC, American Type Culture Collection16S rDNA Genbank Accession NumberbCommentsStrain #SourceaYear of Isolation Vegetative Cell Growth To produce vegetative cells for analysis, cultures were first streaked out on tryptic soy agar plates and incubated overnight at 32C. A single, isolated colony was then used to inoculate a 5 mL tryptic soy broth culture. This culture was incubated at 32C with shaking at 250 rpm for 8 hours. A milliliter of the culture was removed from the tube and spun down for 10 minutes at 9,600 x g. The supernatant solution was removed and the pellet was resuspended in phosphate buffered saline solution. The culture was again centrifuged the supernatant removed, and the remaining cell pellet used for the MALDI analysis.

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97 Metabolic profiling All isolates were subjected to Gram staining and the presence of spores was confirmed using light microscopy. Metabolic profiling was performed on the various isolates using the Biolog system (Biolog, Foster City, CA). This 96-well microplate method tests for the oxidation of 95 different carbon sources. Protocols for the preparation and analysis of Bacillus species were followed per the manufacturers directions. Microplates were read after 6 and 20 hours of incubation in the 96 well plates. The Microstation hardware was used to read the plates and Microlog 3 software was used to analyze the data. 16S rDNA and gyrB sequencing Chromosomal DNA from each of the isolates was extracted by standard PCIAA and ethanol precipitation protocols 77 and was used as the template for PCR amplification (ca. 10 ng). Universal primers (Eub 8f and Univ.1492r) were used to amplify 16S rDNA fragments, as per established protocols 53 Procedures developed by Yamamoto and Harayama 56 were followed for gyrB amplification. Amplicons were gel-excised, purified with Qiagen columns (Qiagen, Valencia, CA), and sequenced as described elsewhere 59,61 The phylogenetic relationships of organisms covered in this study were determined by comparison of individual 16S rDNA (www.ncbi.nlm.nih.gov) or gyrB (www.mbio.co.jp) sequences to other existing sequences in the public databases. Evolutionary trees were constructed with PAUP software, following maximumparsimony parameters 78 DNA-DNA hybridization Bacterial strains were cultivated in tryptic soy broth (Difco, St. Louis, MO) containing 1.5% glycine by shaking at 30 o C for 16 hours. Cells were harvested by centrifugation, resuspended in TE buffer (pH 8.0), and lysed by the addition of 50 g/mL

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98 labiase (Seikagaku Corporation, Japan) and 1mg/ mL achromopeptidase (Wako Pure Chemicals, Japan). Cell suspensions were incubated at 37 o C until they became viscous, at which time chromosomal DNA was purified per standard methods 77 DNA-DNA homology was performed using the microplate hybridization method 79 with photobiotin labeling and colorimetric detection as described previously 80 Cluster analysis based on DNA hybridization was performed via the neighbor-joining method 81 using PHYLIP software 82 MALDI-TOFMS protein profiling Purified spores were diluted one to ten in a saturated solution of ferulic acid matrix using a 30% formic acid, 40% water, and 30% acetonitrile mixture as the solvent 73 The mixture was vortexed briefly and 1L of the sample containing both spores and matrix was deposited on the MALDI plate. For vegetative cell samples, 50 L of the matrix solution was used to resuspend the cell pellet. The mixture was vortexed briefly and 1L of the sample containing both vegetative cells and matrix was spotted. Spots were allowed to air dry and no further treatment was applied to the spots post drying. The sample preparation was done in duplicate from each spore and vegetative cell suspension. MALDI-TOFMS protein profiling was performed on a Bruker Daltonics Reflex II Mass Spectrometer (Bruker Daltonics, Billerica, MA) retrofitted with delayed extraction. Positive ion mass spectra were collected in the linear mode using a delay time of 50 ns, an acceleration voltage of 20kV, and a deflector set at 2,500 Da. All spectra represent the accumulation of 50 laser shots. Ten spectra were collected across each spot for a total of 20 spectra per sample. Each spectrum was baseline corrected and smoothed using a ten-point Savitzky-Golay smoothing algorithm prior to statistical analysis.

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99 Statistical processing of MALDI-TOFMS profiles Linear correlation analysis was performed on software developed in-house with Visual Basic 6.0 as described previously 73 A library of isolate spore spectra was complied by averaging the 20 spectra collected from each spore sample. The individual and the average spectrum obtained from the strains in this study were compared to MALDI-TOFMS profiles stored in this library and to a user generated library of eleven Bacillus species. Higher correlation coefficients are indicative of spectral similarity. To quantify the level of significance of these differences, a simple t-test was applied. A similar procedure was used for the vegetative cells except they were compared only with themselves, rather than with another library. In addition to the linear correlation analysis, SPSS software (Chicago, IL) was used for performing a hierarchal cluster analysis (HCA) on the average spectrum obtained from each strain in this study. The HCA analysis was based on the Pearson correlation and dendrograms were produced using a single linkage (nearest neighbor) scheme. Spectral visualization is accomplished through the use of Surfer 8.0 mapping software from Golden Software (Golden, CO). Using this mapping software, an image map with 10 Da resolution is produced from the average spectrum from each species. The intensity of the peaks is represented by the color of the bands in the image. Results Metabolic fingerprinting of B. pumilus strains Among the 95 carbon substrates tested, N-acetyl-D-glucosamine, inosine, and thymidine were oxidized by all the B. pumilus strains but were not oxidized by B. subtilis 168. Alphaand -cyclodextrin and L-lactic acid were oxidized by B. subtilis 168 but were not oxidized by any of the B. pumilus strains. All of the 16 wild-type B. pumilus

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100 isolates, B. pumilus ATCC 27142, and B. subtilis 168 reduced maltose, methyl-D-glucoside, palatinose, turanose, pyruvic acid methyl ester and cellibose whereas B. pumilus ATCC 7061 T did not. The Biolog identification system was not able to discriminate the spore forming aerobic bacteria in this study. The system correctly identified only 3 out of 18 strains tested, ATCC 7061 T SAFN-036, and SAFN-037 as B. pumilus. Eight of the B. pumilus strains (FO-36b, SAFN-001, SAFN-027, 51-3C, 82-2C, 84-1C, 84-3C, and 84-4C) were incorrectly identified as B. subtilis (44%). Metabolic fingerprinting profiles of the remaining 7 B. pumilus strains (ATCC 27142, FO-033, KL-052, SAFN-029, SAFR-032, 81-4C, and 015342-2) did not match with any of the species contained in the Biolog metabolic fingerprinting database (39%). 16S rDNA and gyrB sequencing The results of 16S rDNA sequencing and maximum-parsimony analysis rendered no apparent phylogenetic clustering pattern among the isolates tested. All of the B. pumilus examined, excluding 84-1C, 82-2C, 84-3C, and SAFR-032, had greater than 97.5% sequence similarity with each other. Strains 84-1C and SAFR-032 exhibited 16S rDNA sequence similarities of >99% with B. pumilus ATCC 7061 T and ~96.5% similarities with FO-36b group of isolates. Likewise, 82-2c and 84-3c isolates showed 16S rDNA similarities of ~96.5% with both ATCC 7061 T and the FO-36b group. Sensu lato, the strains examined in this study were indistinguishable by 16S rDNA sequence analysis. The gyrB analysis of 12 strains sequenced exhibited two distinct clusters based on maximum-parsimony analysis. The first cluster showed >96.5% sequence similarities among 5 strains, B. pumilus ATCC 7061 T ATCC 27142, 0105342-2, SAFN-029, and

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101 SAFR-032. Likewise, >97.6% sequence similarities was noted among the other 7 strains analyzed, FO-033, FO-036b, SAFN-001, SAFN-027, SAFN-036, SAFN-037, and KL-052. Furthermore, only 90 to 92% gyrB sequence similarities were observed between the strains of these two groups. DNA-DNA hybridization The results of DNA-DNA hybridization among the B. pumilus strains are shown in Table 4-2. The strains tested diverged into two groups when DNA-DNA hybridization Table 4-2. DNA-DNA hybridization of B. pumilus isolates SAFN-001FO-033FO-036b81-4C84-3C51-3C82-2C84-1C84-4CSAFN-027KL-052SAFN-036SAFN-037SAFN-029SAFR-0320105342-2ATCC 7061TATCC 27142B. pumilusSAFN-001-B. pumilusFO-03392-B. pumilusFO-036b9293-B. pumilus81-4C969096-B. pumilus84-3C98909192-B. pumilus51-3C9593959494-B. pumilus82-2C959393909390-B. pumilus84-1C94929394939596-B. pumilus84-4C9390939393959590-B. pumilusSAFN-027868082828481828280-B. pumilusKL-05284808484858581818296-B. pumilusSAFN-0368889868987868084858882-B. pumilusSAFN-037918086878486888488848396-B. pumilusSAFN-02961585860616163586061586062-B. pumilusSAFR-0325854546263575357545961575497-B. pumilus0105342-2615562626364606060606160617979-B. pumilusATCC 7061T65636161606360616266596166818485-B. pumilusATCC 271425959605863605863625963576079769085-SpeciesStrain #Percentage DNA reassociation values to labelled DNA from B. pumilus that are: values were examined by cluster analysis. The type strain group consisted of 5 strains as seen in gyrB analysis, B. pumilus ATCC 7061 T ATCC 27142, 0105342-2, SAFN-029, and SAFR-032, which showed more than 76% DNA relatedness within the group. The FO-36b group consists of the remaining 13 strains, FO-033, FO-036b, 51-3C, 81-4C, 82-2C, 84-1C, 84-3C, 84-4C, SAFN-001, SAFN-027, SAFN-036, SAFN-037, and KL-052 where >80% DNA relatedness was observed within this group. Strains of the FO-36b

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102 group formed a much more cohesive cluster than the type strain group. The DNA-DNA reassociation values between the type strain group and the strains in the FO-36b group were less than 66%. Even though the DNA-DNA hybridization values between the strains of the FO-36b group and the B. pumilus type strain ATCC 7061 T were 59-66%, we are still deeming this group B. pumilus. MALDI-TOFMS protein profiling of spore samples The averaged MALDI-TOFMS spectrum from each of the sixteen putative B. pumilus isolates and ATCC 27142 were compared sequentially with a user created library containing spectra from 12 strains (10 different type species) of Bacillus spores. The results from the correlation analysis are shown in Table 4-3. The 16 B. pumilus isolates tested in this study had low correlation values (0-0.48) with type strains of the ten other Bacillus species examined. Typically, a correlation value of >0.75 together with visual pattern recognition of the protein profiling were considered to define the bacterial species identity. Using MALDI-TOFMS protein profiling as a tool for phenotypic analysis all but 2, or 89% of the spores tested had correlation values of greater than 0.62 with the type strain, B. pumilus ATCC 7061T (Table 4-3). FO-033, FO-36b, and SAFN-037 had correlation values ranging from 0.62-0.71 with the type strain. All the other strains examined, except SAFN-029 and SAFN-036, had correlation values of >0.75 with the type strain. The highest correlation value (0.98) was found between the averaged spectra from ATCC 7061T in the library and a fresh batch of ATCC 7061T spores. Strains SAFN-029 and SAFN-036, had correlation values of 0.31 and 0.27 respectively indicating a low degree of spectral similarity with the B. pumilus type strain.

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103 Table 4-3. Linear correlation values obtained when comparing the Bacillus species library with the B. pumilus strains in this study ATCC 9372 T FO-11ATCC 14580 TKL-196ATCC 14581 TATCC 51516 T 51-8CPTA-4399 TVSE1-06ATCC 7061 T 168ATCC 6051 TATCC 10792 TB. atrophaeusB. cereus B. licheniformisB. licheniformisB. megateriumB. mojavensisB. niacini B. odysseyiB. psychroduransB. pumilusB. subtilisB. subtilisB. thuringiensisB. pumilusSAFN-0010.220.020.250.050.390.330.000.280.100.850.060.080.11B. pumilusFO-0330.250.020.280.060.400.390.000.280.060.710.150.150.10B. pumilusFO-036b0.260.010.200.040.390.310.000.260.060.620.170.160.09B. pumilus81-4C0.310.010.210.030.410.340.000.300.050.750.140.150.14B. pumilus84-3C0.270.010.270.040.440.450.000.320.060.860.100.130.14B. pumilus51-3C0.290.020.280.060.430.410.010.300.090.790.130.140.13B. pumilus82-2C0.280.010.260.040.450.440.000.320.050.860.110.130.14B. pumilus84-1C0.330.020.230.030.440.380.010.330.060.850.100.130.16B. pumilus84-4C0.250.010.260.050.440.380.010.340.080.870.090.100.11B. pumilusSAFN-0270.310.020.230.040.430.360.010.310.070.890.080.100.15B. pumilusKL-0520.270.010.210.030.410.330.000.290.050.790.120.120.12B. pumilusSAFN-0360.190.010.110.060.260.16-0.010.150.110.270.210.160.01B. pumilusSAFN-0370.350.020.200.050.390.310.030.300.090.680.140.170.16B. pumilusSAFN-0290.130.010.110.020.160.120.020.140.040.310.260.270.07B. pumilusSAFR-0320.130.010.170.040.410.340.040.370.150.75-0.010.030.11B. pumilus0105342-20.190.010.300.040.420.440.030.380.070.940.010.090.12B. pumilusATCC 271420.120.010.210.040.450.390.030.370.080.830.000.040.09B. pumilusATCC 7061T0.130.000.270.040.480.460.010.320.070.980.010.030.08Species/Strain Furthermore, the average and individual MALDI-TOFMS spectra from all of the B. pumilus isolates were compared with themselves using the user created library, and the correlation results are shown in Table 4-4. MALDI-TOFMS spectra (m/z 2,500 to 35,000) of representative strains of type strain group (Figure 4-1), FO-36b group (Figure 4-2) and outlier group (Figure 4-3) are shown. The molecular mass region from approximately 10,000 to 35,000 Da is amplified by 10x to highlight the higher molecular weight peaks which are present at lower intensities. These higher molecular weight proteins may prove important as they are sometimes a strain level distinguishing feature in the spectra obtained from the spores. Using MALDI-TOFMS protein profiling with linear correlation and HCA analysis, the B. pumilus isolates in this study are clustered

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104 into two groupings as seen with the gyrB and DNA-DNA hybridization analyses. The dendrogram and image map for all of the strains is shown in Figure 4-4. Table 4-4. Correlation results based on MALDI-TOFMS protein profiles of the B. pumilus spore strains in this study SpeciesStrainSAFN-001FO-033FO-036b81-4C84-3C51-3C82-2C84-1C84-4CSAFN-027KL-052SAFN-036SAFN-037SAFN-029SAFR-0320105342-2ATCC 7061ATCC 27142B. pumilusSAFN-001-B. pumilusFO-0330.96-B. pumilusFO-036b0.820.90-B. pumilus81-4C0.930.980.95-B. pumilus84-3C0.940.990.860.96-B. pumilus51-3C0.950.990.900.980.98-B. pumilus82-2C0.950.990.880.970.990.99-B. pumilus84-1C0.940.960.880.970.960.970.98-B. pumilus84-4C0.950.970.860.950.970.970.970.97-B. pumilusSAFN-0270.950.940.820.940.940.960.960.980.96-B. pumilusKL-0520.940.970.920.990.950.980.960.960.960.96-B. pumilusSAFN-0360.550.650.900.730.590.650.620.600.600.520.69-B. pumilusSAFN-0370.890.940.960.980.920.960.940.950.920.910.950.80-B. pumilusSAFN-0290.280.280.230.270.290.280.280.290.290.300.270.100.24-B. pumilusSAFR-0320.630.570.420.550.620.590.640.680.650.700.560.170.530.30-B. pumilus0105342-20.840.830.550.740.870.820.850.820.850.840.760.200.660.330.71-B. pumilusATCC 70610.850.820.580.760.860.820.860.850.870.890.800.240.690.320.750.93-B. pumilusATCC 271420.690.650.460.610.700.660.720.740.720.760.630.160.570.320.940.820.84The first grouping, the type strain group, contains B. pumilus ATCC 7061 T and includes ATCC 27142, 0105342-2, and SAFR-032 with one outlier (SAFN-029). Strains in this group have characteristic peaks in their spectra at m/z 6,860 Da, 7,230 Da, and 9,605 Da (Figure 4-1). SAFN-029 (Figure 4-3D), has a correlation value of less than 0.32 for all of the strains examined and is considered an outlier. It is contained within the type strain cluster because of the presence of the three characteristic peaks described above. All of the strains in this type strain group can be differentiated from other B. pumilus strains tested at the 97% confidence interval using the Students t-test. The second FO-36b group contains the remaining B. pumilus strains tested in this study. This FO-36b group also has peaks at m/z 6,860, 7,230, and 9,605 Da but all strains in this group have an additional peak at m/z 7,620 (Figure 4-2). The outlier strain,

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105 Figure 4-1. MALDI-TOFMS protein profiles of the B. pumilus type strain group spores. The mass range depicted is from m/z 3,000-35,000. The higher molecular mass region from m/z 9,500-25,000 is amplified 10x (see inset of each spectrum) in order to visualize the higher molecular weight peaks that are present but are at much lower abundance in the samples. A) ATCC 27142, B) SAFR-032, C) B. pumilus ATCC 7061 T D) 0105342-2.

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106 Figure 4-2. MALDI-TOFMS protein profiles from selected spores from the FO-36b cluster. A) FO-36b, B) 82-2C, C) KL-052, D) SAFN-037. Explanations are as given in Fig. 4-1.

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107 Figure 4-3. MALDI-TOFMS protein profiles comparing B. pumilus ATCC 7061T, FO-36b and the two outliers found in this study. A) FO-36b, B) SAFN-036, C) B. pumilus ATCC 7061T, D) SAFN-029. Explanations are as given in Fig. 4-1.

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108 Figure 4-4. Dendrogram and visualization of the spore strains in this study. The spectra are represented as an image map where the intensity is indicated by the band color. The figure is highlighted to show the 2 clusters formed in this study as well as the outliers. The arrows indicate the presence and absence of peaks in the outliers.

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109 SAFN-036, is also included in this FO-36b group. The SAFN-036 profile (Figure 4-3B) does not exhibit the peak at 9,605 Da, which is found in all of the other B. pumilus strains examined, but contains the 7,620 peak which is characteristic of this group. Correlation values of 0.52-0.90 are found between SAFN-036 and strains in this second cluster. In contrast to the type strain group, the FO-36 group is very tightly clustered. Many of the isolates in FO-36b group cannot be differentiated at the 97% confidence interval from the other strains in this cluster. However, strains of FO-36b group can be differentiated from strains in the type strain group. MALDI-TOFMS Protein Profiling of Vegetative Cells To further characterize the outliers from the spore form of the organism, 8 strains were cultured into vegetative cells and the correlation and HCA analysis was repeated on the spectra from the vegetative cells. B. pumilus ATCC 7061 T ATCC 27142, 0105342-2, FO-36b, 82-2C, SAFN-037, and the outliers, SAFN-029 and SAFN-036 were selected for this analysis. The correlation results are shown in Table 4-5. As with the spore Table 4-5. Correlation results based on MALDI-TOFMS protein profiles of selected B. pumilus vegetative cells in this study SpeciesStrainFO-036b82-2CSAFN-036SAFN-037SAFN-0290105342-2ATCC 7061ATCC 27142B. pumilusFO-036b-B. pumilus82-2C0.74-B. pumilusSAFN-0360.500.63-B. pumilusSAFN-0370.460.550.90-B. pumilusSAFN-0290.380.370.350.37-B. pumilus0105342-20.290.370.280.280.78-B. pumilusATCC 70610.400.410.370.350.930.77-B. pumilusATCC 271420.460.490.430.440.840.670.90

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110 samples the vegetative cells are clustered into 2 groups, although the groupings are not as close as the spore clusters. One cluster contains the type strain B. pumilus ATCC 7061 T along with ATCC 27142, 0105342-2, and SAFN-029 (Figure 4-5). Among these samples the correlation values ranged from 0.67-0.93. The second group contains FO-36b, 82-2C, SAFN-037, and SAFN-036 (Figure 4-6). The correlation values for this grouping were slightly lower ranging from 0.46-0.90 with the lowest values being evident for SAFN-037 and SAFN-036 with FO36b. SAFN-037 and SAFN-036 have a correlation value of 0.90 with each other. The spectra of all the vegetative cells are very similar in the region below 11 kDa (Figure 4-5 and 4-6). All of the spectra have biomarker peaks at 9,810 Da and approximately 10,716 Da. In this region the type strain group has a distinct biomarker peak at 5,350 Da while in the FO group the peak is at 5,390 Da. This is one of the most profound differences between the 2 groups in the vegetative cell state. In the higher molecular weight region there are no biomarker peaks observed that are common within the groupings. There appears to be significant within-group variation in this region. Replicate culturing of the vegetative cells gave nearly identical results to the initial trial. Comparison of the replicate trials gave correlation values of above 0.80 for strains within the type strain group and above 0.60 for those within the FO group. Discussion To adopt MALDI-TOFMS as a new methodology for identifying closely related bacterial species, it is necessary to compare this technique with several existing genotypic and phenotypic methods. Biolog metabolic fingerprinting did not correctly identify most of the B. pumilus isolates tested. Of the genotypic analyses performed, 16S rDNA proved to be the least discriminating for the tested B. pumilus isolates. Unlike the slowly

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111 Figure 4-5. MALDI-TOFMS protein profiles of the B. pumilus type strain group vegetative cells. The mass range depicted is from m/z 2,500-60,000. The higher molecular mass region from m/z 20,000-60,000 is amplified 4x (see inset of each spectrum) in order to visualize the higher molecular weight peaks. A) B. pumilus ATCC 7061 T B) SAFN-029. C) B. pumilus ATCC 27142. D) 0105342-2.

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112 Figure 4-6. MALDI-TOFMS protein profiles of the FO group vegetative cells. The mass range depicted is from m/z 2,500-60,000. The higher molecular mass region from m/z 20,000-60,000 is amplified 4x (see inset of each spectrum) in order to visualize the higher molecular weight peaks. A) FO-36b. B) SAFN-036. C) 82-2C. D) SAFN-037.

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113 evolving ribosomal RNA gene, the more rapidly evolving gyrB gene allowed for distinct clustering of the tested strains into two groups, which are in strong agreement with both the DNA-DNA hybridization and MALDI-TOFMS protein profiling. To identify the unknown isolates based on MALDI-TOFMS protein profiling, both the linear correlation value and visual peak comparisons were used as a diagnostic tool for differentiating a group of strains. Although high correlation values (typically >0.75) are desirable for definitive species differentiation, low correlation values do not unambiguously exclude an isolate. Rather the delta value for the first and second highest hits should be considered the significant measure of the validity of the bacterial species assignment. The MALDI-TOFMS protein profile from the unknown strains was compared with a library of type strains of different species. The B. pumilus type strain was the species with the highest correlation value for every putative B. pumilus isolate tested including SAFN-029 and SAFN-036. In all cases except SAFN-029 and SAFN-036, the delta value between the first and second hit was >0.23 (Table 3). As seen in the gyrB and DNA-DNA hybridization methodologies, MALDI-TOFMS analysis exhibited two very distinct and consistent groups among the B. pumilus isolates tested. According to the Ad Hoc Committee on Bacterial Systematics, 83 DNA-DNA re-association values of >70% between the type strain and the unknown strain are considered as the same species. The 53 to 66% DNA:DNA hybridization values as well as groupings exhibited by MALDI-TOFMS among the isolates tested in this study suggest that these two groups represent a different species of Bacillus. However, description of a novel species is beyond the scope of this study.

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114 The most notable difference in the MALDI-TOFMS protein profile between the type strain and FO-36b group is the presence of a peak at 7,620 Da, found only in the FO-36b group strains. Another difference between the two groups is that the FO-36b group forms a tight cluster, which cannot be differentiated at the strain level based solely on MALDI-TOFMS protein profiling. In contrast, the type strain group can be differentiated at the strain level indicating a higher level of strain variation within this cluster. To determine the reproducibility of the MALDI-TOFMS analysis, duplicate analysis of spores from each isolate was performed and gave correlation values ranging from 0.87-0.98 for strains within the FO-36b group and 0.89-0.96 from the type strain group. Analysis of duplicate batches of 10 different strains prepared by various technicians yielded a correlation values of >0.75 for strains within the same group. SAFN-036 and SAFN-029 are the two species not convincingly identified as either a member of the B. pumilus type strain group or the FO-36b group solely by the linear correlation analysis and visual interpretation of the peaks in the spectra was required. In both cases, there is not another type strain within the library that was a closer match to these isolates (Table 4-3). The 9,605 Da peak, absent in the initial SAFN-036 spore batch, was observed at low intensities in subsequent analysis of this isolate from a different batch of spores. The absence of it in the first analysis could be due either to a difference in spore formation or more likely to a problem with the concentration of spores in the first analysis. Although SAFN-036 had a very low correlation value (0.27) with the type strain, ATCC 7061 T it had correlation values ranging from 0.52-0.90 (Table 4-4) for strains in the FO-36b group. The spectrum from SAFN-029 (Figure 4-3D) has the 3 biomarker peaks in common with ATCC 7061 T cluster; however, its most intense peak at

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115 7,929 Da, not found in any of the other B. pumilus spectra, contributes to its low correlation values thus making it an outlier. This intense 7,929 Da peak has not been observed in the spectra of any of the other Bacillus species we have examined. Subsequent analysis including a different sporulation of this isolate produced spectra that contained the intense 7,929 Da peak and had correlation values ranging from 0.83-0.91 with the SAFN-029 spectra in the library. Analysis of a subset of these strain as vegetative cells supported the assignment of the spore outliers to the groupings above. In the vegetative state, SAFN-029 was clearly clustered with the type strain group and had a correlation value of 0.93 (Table 4-5) with B. pumilus ATCC 7061 T SAFN-036 was more loosely associated with FO-36b, r = 0.50, but was closely clustered with SAFN-037. Both strains were within the FO-36b cluster due to the presence of the biomarker at 5,390 Da (Figure 4-6). The vegetative cell spectra appear to have more strain variability than the spore spectra for the strains analyzed. Although not addressed in the current study, the intra-species with vegetative cells variation may necessitate a different acceptance number for the correlation value; perhaps r < 0.50 for vegetative cells with a delta value of 0.1 would be more indicative of the variation seen in vegetative cell spectra. Further investigation of this is warranted. The linear correlation analysis and HCA used was sufficient for the confident classification of 14/16 of the spores in this study. It proved critical to take into account the correlation value and the presence and absence of certain biomarker peaks to understand the placement of the two outliers. This limitation and the variability of the absolute correlation value presents a challenge for determining definitive species classification based solely on linear correlation analysis. Software developed at the

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116 Pacific Northwest National Laboratory is currently being implemented in an attempt to overcome these limitations. 84,85 This software uses a peak-picking based algorithm to differentiate MALDI-TOFMS protein profiles and has been shown to be effective for bacterial differentiation of single isolates and of mixtures. 72,86 In addition to improved pattern recognition, the identification of protein peaks which are useful for bacterial systematics, such as the 7,620 Da peak, would be valuable for the definitive differentiation of a given species. Conclusion MALDI-TOFMS protein profiling has been demonstrated as a useful taxonomic tool for differentiating spores and vegetative cells of the genus Bacillus. This methodology is far more accurate than metabolic profiling, more discriminating than 16S rDNA sequence analysis, and complements the results of gyrB sequence analysis and DNA-DNA hybridization. When compared with the genotypic methods used here, the MALDI-TOFMS analysis is much more rapid for isolate differentiation, taking only a few minutes to prepare and analyze. In addition, new isolates can be compared with established libraries to obtain species level identification and to elucidate relationships between bacterial strains, eliminating the necessity of maintaining and growing reference strains for subsequent studies. The addition of automated peak picking algorithms that recognize species-specific biomarker peaks will further strengthen the diagnostic power of this tool.

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CHAPTER 5 MALDI-TOFMS PROTEIN PROFILING OF Bacillus anthracis-cereus-thuringiensis GROUP SPORES Introduction A great deal of attention has been focused recently on the MALDI-TOFMS analysis of B. anthracis spores. B. anthracis, the causative agent of the disease anthrax, is closely related to a group of bacteria that includes B. cereus and B. thuringiensis. B. cereus is often the organism implicated in food poisoning outbreaks and causes great concern in the food processing and dairy industries. B. thuringiensis, by contrast, is of great importance in the agricultural industry as an insecticide used in crop sprays and pesticide treatments and is generally though to be harmless to humans. The precise discrimination and classification of this group of bacteria remains a topic of great debate. The debate is fueled on one side by taxonomists who seek to establish evolutionary relationships and lineages between bacteria. On the other side are practitioners and bacteriologists who are primarily concerned with the ability to deduce the pathogenic, spoilage, or ecological properties associated with a new isolate. 2 Phenotypic identification of these species depends on virulence factors, including the genes encoding for the Cry toxin crystals in B. thuringiensis, the toxin and capsule of B. anthracis, and the emetic and enterotoxin genes of B. cereus. 2 These genes are encoded by extrachromosomal mobile genetic elements such as plasmids that can be lost or involved in lateral gene transfer between species. 2,87,88 Sequence analysis of the 16S rDNA is not able to differentiate the species within this group. 55,88,89 The use of modern 117

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118 genotypic methods such as PCR of virulence factors, 90,91 restriction fragment length polymorphisms, 92,93 pulsed-field gel electrophoresis, 2 and analysis of intergenic spacer regions 94 are able to differentiate B. anthracis from B. cereus but are unable to differentiate B. cereus from B. thuringiensis. Because of the ambiguities in the phenotypic and genotypic characterization of these organisms, it has been suggested that the three species be considered as one species evolved from a common ancestor. 89,95 The need to differentiate this group of bacteria, and particularly discriminate potential pathogenic and nonpathogenic strains, regardless of their correct phylogenetic classification, lingers as the goal of most rapid, phenotype-based identification techniques. The many attempts to design rapid methods for this task such as commercial identification tests (API, Biolog, Vitek, and the Microbial ID system) have fallen short in their ability to effectively differentiate this closely related group of bacteria. 2 The clear, unambiguous identification and characterization of members in this group is currently an unmet diagnostic challenge. MALDI-TOFMS-based protein profiling has demonstrated the ability to differentiate closely related groups of bacteria for a set of B. pumilus isolates. 96 However, MALDI-TOFMS based investigations of whole spores from the BACT group to date have been limited in both scope and in the number of strains examined. 25,29,32 The most prominent biomarker peaks highlighted in these studies were in the 6,000-8,000 Da range, with lower weight biomarkers observed in some cases between 2,000-4,000 Da. The lower molecular weight components have been attributed to microbial lipopeptides and spore cortex peptidoglycan while the 6,000-8,000 Da peaks are from small acid soluble proteins (SASPs). 25,32,40,97,98 Little similarity can be seen in the biomarker peaks,

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119 even for identical strains between the different studies. All have failed to effectively differentiate the group, although biomarkers unique to B. anthracis strains are reported using both whole proteins and trypsin digests of SASPs. 25,29,32,38,99,100 However, the B. cereus and B. thuringiensis strains are not differentiated. This chapter reports on an attempt to validate the use of MALDI-TOFMS protein profiling as a phenotypic discriminator for this group of bacteria. A set of 26 unique strains of B. anthracis, B. cereus, and B. thuringiensis (BACT) were examined for their proteomic-based affiliations. Materials and Methods Bacterial Strains Table 5-1 contains a list of the B. cereus isolate and serotype strains used in this study with both the DNA:DNA hybridization and 16S rDNA results reported by LaDuc et al. 88 All ATCC strains were procured from the American Type Culture Collection (Manassas, VA) which included B. cereus ATCC 14579, B. mycoides ATCC 6462, B. thuringiensis Berliner ATCC 10792 T and the type strains contained in the reference libraries. B. thuringiensis Kurstaki HD-1, B. thuringiensis Aizawai, B. thuringiensis Galleriae, B. thuringiensis Israeliensis, B. anthracis 34F2, and the collection of B. cereus serotypes were provided by M. Satomi at the National Institute of Fisheries, Japan. Sporulation of Bacillus Isolates Two protocols were used for the productions of spores in this study. For the first protocol, production of spores was performed as described previously. 7,101 Briefly, a single purified colony of the strain to be sporulated was inoculated into nutrient broth sporulation medium (NSM) and was incubated at 32 o C under shaking conditions for 2-4 days. Spore cultures were harvested once they attained >99% spores as examined using

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120 phase-contrast microscopy. In a second protocol, tryptic soy agar (TSA) plates or nutrient agar (NA) plates were inoculated and the plates were allowed to sit at room Table 5-1. List of B. cereus serotype strains B. cereusB. anthracisB. cereusB. anthracisJPLFO-11Air particlesUSAJPL-SAF-17999.099.05371H5186Fried riceGreat BritainPHLS, Great Britain99.399.85571H6CAN30Barbecued chickenCanadaE. Todd, FRI, Health & Welfare Canada99.199.25378H7277Curry powderGreat BritainPHLS, Great Britain99.399.75375H17202Uncooked riceGreat BritainPHLS, Great Britain99.299.75675H24433Meat loafUSAJ.M. Goepfert, FRI, UW-Madison99.399.95967H3214Boiled riceGreat BritainPHLS, Great Britain99.199.74969H84431Indonesian rice dishNetherlandsJ.M. Goepfert, FRI, UW-Madison99.299.75271H94429Vanilla puddingNetherlandsJ.M. Goepfert, FRI, UW-Madison98.298.45566H12118RisottoGreat BritainPHLS, Great Britain99.299.74976H16RR43Uncooked RiceGreat BritianPHLS, Great Britain99.299.75675H104432Indonesian rice dishNetherlandsJ.M. Goepfert, FRI, UW-Madison99.399.77250H112140Neonatal brain abscessGreat BritainPHLS, Great Britain99.499.87748H13167Prawn curry and riceGreat BritainPHLS, Great Britain99.599.77053H14262Fried riceGreat BritainPHLS, Great Britain99.499.88856H15RR60Uncooked riceGreat BritainPHLS, Great Britain99.399.98156H186833Uncooked riceGreat BritainPHLS, Great Britain99.299.75840*These strains were originally classified as B. cereus based on 16S rDNA sequence analysis. Highlighted are the strains which DNA hybridization showed higher similarities with B. anthracis or B. cereus. Further studies on the toxigenic properties of thesa Taylor et al., 1975; b Original strain designiation; c LaDuc et al., 2004SerotypeaStrain #bSourceCountryOrigin% similarity in 16S rDNAc% similarity in DNA:DNAc temperature for 1-2 weeks until the plates contained >90% spores. The center of the colonies were removed with a sterile loop and placed in sterile water. After harvesting, spores were further purified to remove remnant vegetative cells or cell debris as previously reported. 102 The purified spores were adjusted to give an optical density of 0.6 at 600 nm and were suspended in sterile deionized water and stored at 4 o C in glass tubes until analyzed. Preparation of Vegetative Cells A stock culture of each Bacillus strain was streaked for isolation on tryptic soy agar (TSA) plates and/or nutrient agar (NA) plates. The plates were incubated at 32 o C for 16 hours. Single purified colonies were removed from the plate with a sterile loop and were

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121 placed in 100 L of a phosphate buffered saline solution. Most colonies were approximately 2 mm in diameter. Cells were removed from the agar with a sterile loop and were vortexed in phosphate buffered saline for 15 minutes and pelleted by centrifugation for 10 minutes at 9600 x g. The supernatant was removed and the cell pellet was used for subsequent analysis. Fatty Acid Methyl Ester (FAME) Analysis FAME analysis was performed on the following strains in this study: B. anthracis 34F2, B. thuringiensis Berliner ATCC 10792 T B. thuringiensis Kurstaki HD-1, and the B. cereus serotypes H3, H5, H7, H10, H15, H16, H18. FAME analysis was performed using the commercially available Sherlock Identification System by MIDI, Inc. (Newark, DE). The Sherlock Identification System is a fully automated gas chromatographic system which identifies bacteria based on their unique fatty acid profiles. To ensure accurate and reproducible results, protocols for FAME analysis were followed according to the technical note #101 available on the manufacturers website ( www.midi-inc.com/media/pdfs/TechNote_101.pdf last viewed on April 12 2004). Cells were cultured for analysis on TSA infused with 5% defibrinated sheep blood for 24 hours at 35C. FAME analysis was performed on an Agilent technologies 6890N gas chromatograph with a flame ionization detector (FID). An Agilent Ultra 2 (cross linked 5% PH ME Siloxane) capillary column (25 M long, 0.2 mm ID) was used for separation of the fatty acid methyl esters. The peaks from the chromatograph were integrated on a PC and the fatty acid methyl ester composition of the sample is compared with the bioterrorism database using Sherlock pattern recognition software. The bioterrorism library provided by MIDI contained B. cereus, B. anthracis, and B. thuringiensis species and 6 other Bacillus challenge organisms.

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122 MALDI-TOFMS Protein Profiling Samples were prepared and analyzed using MALDI-TOFMS as described previously. 101 Briefly, a saturated matrix solution was prepared by dissolving 20 mg of ferulic acid in a solution of 30% acetonitrile, 30% formic acid. For the spore suspensions (normal and autoclaved), a 2.5 L aliquot of the spore suspension (0.6 OD660) was added to 22.5 L of the matrix solution. For the preparation of vegetative cells, 25 L of the matrix solution was mixed directly with the cell pellet. This solution was sonicated for 3 minutes and then vortexed for 3 minutes. A 1 L aliquot of the spore or vegetative sample was then placed on the MALDI plate for analysis. Spots were allowed to air dry. No further treatments were applied to the spots once dried. The sample preparation was done in duplicate. An additional MALDI analysis was performed as described above except a 5% trifluoroacetic acid (TFA) and 70% acetonitrile solution was used as the matrix solvent to facilitate the release and analysis of small acid soluble proteins (SASPs) from the spores. MALDI-TOFMS protein profiling was performed on a Bruker Daltonics Reflex II Mass Spectrometer (Bruker Daltonics, Billerica, MA) retrofitted with delayed extraction. Positive ions were collected in the linear mode using a delay time of 50 ns, an acceleration voltage of 20kV, and a deflector set at 2,500 Da. All spectra represent the accumulation of 50 laser shots. Ten spectra were collected across each spot for a total of 20 spectra per sample. Statistical Processing Protocols for spectral processing, library spectra creation, and statistical analysis have been described elsewhere. 101 A library of BACT group spore or vegetative cell spectra was created by taking the average spectra from the 20 spectra collected for each

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123 strain. The individual and the average spectrum obtained from the BACT strains were compared to MALDI-TOFMS profiles stored in the BACT library and to a user generated library of eleven Bacillus species. Based on previous analysis of B. pumilus isolates, correlation values (r) of 0.75 with a delta value between the first and second hit of 0.1 are regarded as a good match for inclusion of a strain within a species. 96 Correlation values between 0.50-0.75 with delta values 0.1 may be considered for inclusion within a species providing peaks identified as species specific biomarkers are preserved. Strains with correlation values <0.50 that maintain sufficient delta values and biomarkers may be acceptable but represent an atypical strain of a species and at present require additional manual analysis for species-specific biomarker peaks. In addition to the linear correlation analysis, SPSS software (Chicago, IL) was used for performing a hierarchal cluster analysis (HCA) on the data. The HCA analysis was based on the Pearson correlation and dendrograms were produced using a single linkage (nearest neighbor) scheme. To help visualize the peak patterns for the spectra, Surfer 8.0 from Golden software (Golden, CO) was used to create an image map with 10 Da resolution from the average spectra for each species. The image map provides a 3-D representation of the spectra where the color of the band is indicative of peak intensity. Clustering and visualization of the spectra was helpful for addressing atypical strains and could be used to justify the inclusion of a strain with low correlation values within a species.

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124 Results Sporulation of Bacillus Isolates The efficient sporulation of many of the BACT strains proved to be difficult using the standard NSB sporulation protocol. In most cases, engulfed spores within the mother cell could be visualized with phase contrast microscopy. Subsequent lysozyme treatment did not efficiently break the peptidoglycan bonds in the mother cell to allow for release of the spores. Allowing the cell cultures to sit on culture medium for 1-2 weeks resulted in spores that were completely released from the mother cells. Therefore, the plate preparation with TSA media was used for most of the spores in this study. We were unable to obtain spores from B. mycoides ATCC 6462 T and the B. cereus serotypes H6, H9, and H16 using both protocols and only vegetative cell MALDI data is presented for these strains. FAME Analysis FAME analysis was performed on 10 of the strains is this study and the resulting similarity index values obtained against organisms in the bioterrorism library are shown in Table 5-2. Criteria that were considered for a good library match were a similarity index of >0.5 and a difference between the first and second match of >0.1, as recommended by the manufacturer. Of the 10 strains analyzed, only 4 met the criteria for consideration as a good library match; the delta values for these strains were above 0.1 and are highlighted in black in the table. These four stains were B. anthracis 34F2 identified as B. anthracis, the B. cereus type strain identified as B. cereus subgroup A, the B. thuringiensis serotype Kurstaki HD-1 identified as B. cereus subgroup B, and the B. cereus serotype H7 identified as B. thuringiensis subgroup A. The remaining B. cereus serotypes and the B. thuringiensis type strain did not meet the criteria for a good library

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125 match and generally have high similarity indices with at least two of the species in the reference library. Cluster analysis of the FAME data using the Sherlock system produced two clusters (data not shown). One contained B. anthracis 34F2, H5, and H18. The second cluster contained the B. thuringiensis type strain, B. cereus type strain, B. thuringiensis Kurstaki, H10, H16, H3, H15, and H7. Table 5-2. Results of FAME analysis for selected BACT strains EntryNameB. anthracis GC subgroup AB. anthracis GC subgroup BB. cereus GC subgroup AB. cereus GC subgroup BB. thuringiensis GC subgroup BB. mycoidesDelta ValueB. anthracis 34F20.9160.3080.2780.2910.608B. cereus serotypeH50.5380.5320.3650.006H70.4740.5350.7450.4740.210H30.5950.660.5210.065H160.7860.6330.7510.035H100.8420.6930.7670.075H150.3810.4660.6250.6170.4250.008H180.5050.3070.4580.047B. cereus ATCC 14579 T0.6190.8730.6130.254B. thuringiensis serotypes:Berliner IAM 12077T 0.7770.6340.6930.084Kurstaki HD-10.5280.7980.5810.217 MALDI-TOFMS Protein Profiling of BACT Spores Using 30% formic acid and 30% acetonitrile as a solvent for analysis, spores in this study produced spectra with diagnostic peaks in the molecular weight range 2-35 kDa. Average spectra from each of the species in this study are shown in Figure 5-1. The most intense peaks in the spectra were typically found from 3-5 kDa although some species, notably the B. thuringiensis type strain and several of the serotypes including Galleriae, Aizawaii, and Kurstaki, all had a significant contribution to the spectra from a peak at ~19kDa. The molecular weight peaks above 10 kDa were not observed in these strains in other published studies. 25,29,32

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126 Figure 5-1. Average spectra from the BACT spores using 30% formic acid as a solvent. The mass range depicted is from m/z 2,500-35,000. The higher molecular weight region from m/z 13,00035,000 is amplified 6x in the inset of each spectrum to help visualize the higher molecular weight proteins. A) B. cereus serotype H2. B) B. cereus serotype H3. C) B. cereus serotype H5. D) B. cereus serotype H7. E) B. cereus serotype H8. F) B. cereus serotype H10. G) B. cereus serotype H11. H) B. cereus serotype H12. I) B. cereus serotype H14. J) B. cereus serotype H15. K) B. cereus serotype H17. L) B. cereus serotype H18. M) FO-11. N) B. thuringiensis serotype Israeliensis. O) B. thuringiensis serotype Aizawai. P) B. thuringiensis serotype Kurstaki HD-1. Q) B. thuringiensis serotype Galleriae. R) B. cereus ATCC 14579 T S) B. anthracis 34F2. T) B. thuringiensis Berliner ATCC 14579 T

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127 Figure 5-1. Continued.

PAGE 128

128 Figure 5-1. Continued.

PAGE 129

129 Figure 5-1. Continued.

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130 The profiles from the BACT group of spores were remarkably different from those seen with other spore species. 101 All of the BACT spores had negligible correlation values when compared with other Bacillus type species (Table 5-3), confirming this low degree of spectral similarity. B. anthracis 34F2, FO-11, H7, H17, H2, H8, and H12 were all found to have r values from 0.71-0.97 with the B. anthracis 34F2 strain in the library. H3, H11, and the B. cereus type strain had correlation values of 0.78, 0.72, and 0.92 respectively with the B. cereus type strain in the library. B. thuringiensis Galleriae had a correlation value of 0.56 with a delta of 0.2 with the B. cereus type strain and therefore was considered as a possible B. cereus type organism. The B. thuringiensis type strain had an r value of 0.80 with the library reference spectra of the same strain. The remaining species H5, H10, H14, H15, and H18, B. thuringiensis Aizawai, Kurstaki, and Israeliensis did not have significant correlation values or delta values with any of the species in the type strain library. Closer analysis of the relationship between the profiles is accomplished by comparing the profiles within the BACT library using linear correlation. The correlation values reveal a fairly well defined B. anthracis group and a poorly defined B. cereus/B. thuringiensis group (Table 5-4). This was supported by the clustering and visualization of the spectra as seen in Figure 5-2. H14 and B. thuringiensis Israeliensis are considered outliers in the cluster analysis and have r values less than 0.36 with all of the strains in the study. Within the B. anthracis cluster are FO-11, H8, H12, H7, H17, and H2. All of these species contain a peak at m/z 4, 335 and the r values for organisms within this cluster are all above 0.71. The next cluster is very diverse and contains both B. cereus and B. thuringiensis strains. The B. thuringiensis type strain grown in broth, and on TSA

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131 and NA plates, formed its own resolved group within this cluster branch and has its next highest, well separated, correlation value with the B. cereus types strain (r = 0.44). The B. cereus/B. thuringiensis cluster can further be split into 2 subclusters, one containing H10, H18, H15, H5, and B. thuringiensis Aizawai and Kurstaki HD-1, of which all but the H5 and H15 strains contain a peak at 3,805 Da. H5 and H15 share a biomarker peak at m/z 3,751. H5 and H15 also have peaks around 10kDa which are not seen in the other strains in this subcluster. This is highlighted in the correlation values as well with H5 and H15 having r of 0.57 with each other and H10 but less than 0.28 with the B. thuringiensis Aizawai and Kurstaki strains. The other subcluster contains H11, H3, the B. cereus type strain, and B. thuringiensis Galleriae. These spectra all contain a peak at 4,360 Da and have r values of >0.56 with the B. cereus type strain. These subclusters should not be considered as true groupings. Overall, the B. cereus/B. thuringiensis cluster is poorly defined and profiles contain a great deal of variation making it very difficult to outline clear group boundaries. Protein profiles produced after treatment with 5% TFA and 70% ACN produced more prominent peaks in the 6-9 kDa range and fewer peaks larger than 10 kDa (Figure 5-3). The peaks in this range are believed to be SASP associated proteins based on their identification in other studies. 38,99,100 The biomarkers in the 3-5 kDa range seen with the formic acid treatment are suppressed in many of the TFA treated samples. These profiles were not compared with the type strain library since it is made with 30% formic acid which produces very different spectral profiles. Comparison of the strains treated with TFA using linear correlation produced Table 5-5 and the visualization and clustering is shown in Figure 5-4. Two clusters are formed with the TFA treatment, one coherent

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132 cluster containing the B. thuringiensis Aizawai and Galleriae serotypes and H10 and H15. The other cluster is very diverse and contains the remaining strains and splitting of this cluster into any subgroups was not clear-cut. Examination of the spectral profiles, particularly of the SASP associated proteins in the m/z range 6,500-7,500 highlights some differences in the spectra. None of the SASP protein extracted from the other strains matches those in B. anthracis 34F2 which has an intense SASP at 6,684 Da. The remaining strains can be classified into two groups based on the presence of either a ~6,700 Da peak (H2, H3, H7, H8, H12, H17, H18 and the B. thuringiensis type strain) or a ~6,720 Da peak (B. cereus type strain, H5, H10, H11, H14, H15, FO-11, and B. thuringiensis Aizawai, Galleriae, Kurstaki, and Israeliensis). These grouping based on the SASPs are not clearly defined in the HCA. Table 5-3. MALDI-TOFMS correlation values for BACT spore strains versus the type strain reference library using 30% formic acid as a solvent 34F2ATCC 14579 T ATCC 10792 T ATCC 9372 T KL-196ATCC 14580 T ATCC 14581 T ATCC 51516 T 51-8CPTA-4399 TVSE1-06ATCC 7061 T 168ATCC 6051 TB. anthracisB. cereusB. thuringiensisB. atrophaeusB. licheniformisB. licheniformisB. megateriumB. mojavensisB. niacini B. odysseyiB. psychroduransB. pumilusB. subtilisB. subtilisB. anthracis 34F2 0.970.220.170.020.020.020.010.010.010.000.000.000.010.01FO110.790.310.100.020.050.050.020.030.030.010.040.010.000.01B. cereus serotypes:H50.030.280.060.130.100.260.200.320.080.190.100.330.040.04H70.920.250.190.050.030.060.050.070.020.040.020.060.010.03H170.940.280.200.070.050.090.070.070.040.050.050.060.020.04H20.710.270.210.020.050.070.030.070.040.030.060.020.010.01H30.300.780.440.100.050.080.060.070.110.060.050.050.030.05H80.840.260.180.060.060.090.080.120.040.070.060.060.050.05H120.950.230.180.050.030.040.030.050.060.020.010.030.020.03H100.020.090.000.030.020.040.010.030.020.020.020.010.020.02H110.230.720.310.040.030.040.020.020.080.020.030.010.010.02H140.060.170.330.270.000.030.080.060.040.120.050.090.020.11H150.020.100.010.030.040.060.030.060.110.030.020.020.010.01H180.010.050.010.060.030.040.030.020.040.030.030.010.030.02B. cereus ATCC 14579 T0.200.920.450.300.060.180.170.280.050.180.070.280.050.12B. thuringiensis serotypes:Aizawai0.020.070.020.060.040.040.030.030.030.030.020.010.020.02Galleriae0.060.560.330.360.070.150.170.170.050.180.040.260.030.17Kurstaki0.020.080.240.290.030.050.060.060.060.140.030.060.070.15Israeliensis0.070.220.100.090.020.050.030.040.060.040.040.050.010.04Berliner ATCC 10792 T 0.090.440.80-0.010.100.090.030.050.04-0.010.010.060.000.0130% Formic/ 30% ACN

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133 Table 5-4. MALDI-TOFMS correlation values for BACT spore strain library using 30% formic acid as a solvent BACT group Spores 30% Formic/30% ACNB. anthracis 34F2 FO11H5H7H17H2H3H8H12H10H11H14H15H18B. cereus JCM 2152TAizawaiGalleriaeKurstakiIsraeliensisBerliner IAM 12077T B. anthracis 34F2 -FO110.79-B. cereus serotypes:H50.030.24-H70.920.910.09-H170.940.880.170.95-H20.710.890.180.810.80-H30.300.390.150.300.340.42-H80.840.950.200.940.910.870.34-H120.950.860.070.960.960.780.310.90-H100.020.090.110.030.080.190.090.060.05-H110.230.240.070.200.230.300.880.230.220.14-H140.060.110.120.060.070.100.160.080.070.090.15-H150.020.150.570.030.100.230.110.090.060.500.150.10-H180.010.100.130.020.100.060.070.080.030.600.040.030.12-B. cereus ATCC 14579 T 0.200.310.280.250.280.270.780.260.230.090.720.170.100.05-B. thuringiensis serotypes:Aizawai0.020.090.120.030.100.110.070.070.040.760.080.050.280.930.07-Galleriae0.060.140.200.140.150.060.220.090.110.070.100.110.080.030.560.07-Kurstaki0.020.100.130.030.100.080.080.080.040.670.060.040.170.980.080.970.08-Israeliensis0.070.130.100.090.110.210.190.100.110.350.180.070.300.070.220.210.260.12-Berliner ATCC 10792 T 0.090.110.050.090.130.120.360.100.080.030.250.050.040.020.440.060.330.030.06

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134 Figure 5-2. Clustering and visualization of the BACT spore protein profiles obtained using 30% formic acid as a solvent.

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135 Figure 5-3. Average spectra from the BACT spores using 5% TFA as a solvent. The mass range depicted is from m/z 2,500-35,000. The higher molecular weight region from m/z 13,00035,000 is amplified 6x in the inset of each spectrum to help visualize the higher molecular weight proteins. A) B. cereus serotype H2. B) B. cereus serotype H3. C) B. cereus serotype H5. D) B. cereus serotype H7. E) B. cereus serotype H8. F) B. cereus serotype H10. G) B. cereus serotype H11. H) B. cereus serotype H12. I) B. cereus serotype H14. J) B. cereus serotype H15. K) B. cereus serotype H17. L) B. cereus serotype H18. M) FO-11. N) B. thuringiensis serotype Israeliensis. O) B. thuringiensis serotype Aizawai. P) B. thuringiensis serotype Kurstaki HD-1. Q) B. thuringiensis serotype Galleriae. R) B. cereus ATCC 14579 T S) B. anthracis 34F2. T) B. thuringiensis Berliner ATCC 14579 T

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136 Figure 5-3. Continued.

PAGE 137

137 Figure 5-3. Continued.

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138 Figure 5-3. Continued.

PAGE 139

139 Table 5-5. MALDI-TOFMS correlation values for BACT spore strain library using TFA as a solvent BACT group Spores 5% TFA/70% ACNB. anthracis 34F2FO11H5H7H17H2H3H8H12H10H11H14H15H18B. cereus JCM 2152TAizawaiGalleriaeKurstakiIsraeliensisBerliner IAM 12077T B. anthracis 34F2-FO110.66-B. cereus serotypes:H50.600.69-H70.760.720.81-H170.770.730.830.93-H20.410.380.290.460.33-H30.630.730.870.820.840.29-H80.790.690.680.900.830.600.70-H120.570.540.410.620.500.770.460.75-H100.210.370.320.220.230.490.250.230.25-H110.320.460.350.330.310.510.500.360.370.58-H140.540.850.660.610.650.230.680.510.350.420.51-H150.150.250.240.160.150.500.170.180.250.820.620.35-H180.600.810.790.700.770.250.820.600.370.410.410.780.26-B. cereus ATCC 14579 T 0.370.510.380.380.380.320.560.390.320.270.760.500.220.40-B. thuringiensis serotypes:Aizawai0.170.280.250.190.190.490.200.190.220.830.480.300.570.390.24-Galleriae0.440.660.530.470.510.470.520.430.350.570.580.640.490.570.480.52-Kurstaki0.570.840.680.640.750.170.690.520.310.390.370.810.190.860.420.400.60-Israeliensis0.610.880.720.690.800.200.720.570.350.300.380.830.190.830.450.240.640.95-Berliner ATCC 10792T0.290.320.420.370.340.470.420.370.310.430.610.320.410.350.490.450.480.270.29

PAGE 140

140 Figure 5-4. Clustering and visualization of the BACT spores protein profiles obtained from using TFA as a solvent.

PAGE 141

141 MALDI-TOFMS Protein Profiling of BACT Vegetative Cells Vegetative cells were extracted with 30% formic acid/30% ACN and were subjected to MALDI-TOFMS protein profiling. Spectra obtained for the vegetative cells were significantly different from their sporulated counterparts. Vegetative cell spectra are characterized by a larger number of biomarkers as well as the presence of higher molecular weight protein peaks (Figure 5-5). All of the vegetative strains in this study were found to have a biomarker peak at 6,425 Da, a triplet of peaks centered at 9,600 Da, and a peak at ~19.1 kDa. The results for the BACT vegetative cells with the type strain library for vegetative cells using linear correlation analysis are shown in Table 5-6. Highlighted in black are those values that make both the r>0.75 and >0.1 delta values and highlighted in gray are those strains where the r>0.50 and the delta value is >0.1. H15, H18, the B. thuringiensis type strain and the Kurstaki serotype, and B. mycoides do not have correlation values with any of the reference strains that meet either criterion. Of the strains that meet the criteria, all of them except the B. cereus type strain and B. thuringiensis Kurstaki had the closest match being the B. anthracis type strain. The results of the correlation analysis of these strains with themselves are in Table 5-7 and the clustering and visualization is shown in Figure 5-6. The cluster analysis does little to differentiate this group into distinct clusters and does not mimic the correlation analysis very effectively. This is likely due to the greater complexity of peaks in the vegetative spectra.

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142 Figure 5-5. Average spectra from the BACT vegetative cells using 30% formic acid as a solvent. The mass range depicted is from m/z 2,500-60,000. A) B. cereus serotype H2. B) B. cereus serotype H3. C) B. cereus serotype H5. D) B. cereus serotype H7. E) B. cereus serotype H8. F) B. cereus serotype H10. G) B. cereus serotype H11. H) B. cereus serotype H14. I) B. cereus serotype H15. J) B. cereus serotype H17. K) B. cereus serotype H18. L) FO-11. M) B. thuringiensis serotype Israeliensis. N) B. thuringiensis serotype Aizawai. O) B. thuringiensis serotype Kurstaki HD-1. P) B. cereus ATCC 14579 T Q) B. anthracis 34F2. R) B. thuringiensis Berliner ATCC 14579 T S) B. mycoides ATCC 6462 T T) B. cereus serotype H16. U) B. cereus serotype H6. V) B. cereus serotype H9.

PAGE 143

143 Figure 5-5. Continued.

PAGE 144

144 Figure 5-5. Continued.

PAGE 145

145 Figure 5-5. Continued.

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146 Table 5-6. MALDI-TOFMS correlation values for BACT vegetative cells versus the vegetative type strain reference library using30% formic acid as a solvent 34F2ATCC 14579 T ATCC 10792 TATCC 9372 T KL-196ATCC 14580 TATCC 14581 TATCC 51516 T 51-8CPTA-4399 TVSE1-06ATCC 7061 T 168ATCC 6051 TB. anthracisB. cereusB. thuringiensisB. atrophaeusB. licheniformisB. licheniformisB. megateriumB. mojavensisB. niacini B. odysseyiB. psychroduransB. pumilusB. subtilisB. subtilisB. anthracis 34F20.830.140.210.210.100.180.430.180.130.360.380.380.200.18FO-110.760.130.330.160.130.200.360.140.130.320.330.350.170.18B. cereus serotypes:H50.470.070.160.090.050.090.220.060.050.190.200.230.080.08H60.760.150.260.160.100.160.300.160.130.220.310.180.170.18H70.680.130.460.110.040.070.190.070.060.170.200.180.100.08H170.730.280.320.110.060.100.160.100.080.150.210.120.100.12H20.630.100.390.090.020.070.170.060.040.140.220.130.070.08H30.630.110.300.090.060.110.210.090.150.160.260.120.130.20H90.760.150.220.130.070.130.200.100.080.170.240.140.110.13H160.620.120.220.140.080.130.290.140.100.230.290.200.140.15H100.630.100.360.120.090.140.290.090.050.260.260.290.110.08H110.650.420.240.160.210.260.420.150.110.410.340.450.190.15H140.580.130.330.080.250.240.220.100.090.180.230.150.110.12H150.270.330.390.00-0.03-0.020.030.02-0.010.090.050.100.00-0.01H180.470.030.390.100.080.120.280.070.040.260.250.300.110.06B. cereus ATCC 14579 T 0.360.790.110.070.020.050.110.080.020.120.150.100.040.04B. thuringiensis serotypes:Aizawai0.530.080.370.090.070.100.190.070.150.170.250.130.080.15Galleriae0.450.050.500.060.000.040.110.040.110.150.140.120.060.07Kurstaki0.570.430.200.120.120.160.300.120.290.280.280.260.120.16Israeliensis0.560.070.540.090.020.050.160.040.130.170.170.090.050.09Berliner ATCC 10792T0.390.100.820.050.000.030.110.020.120.140.130.110.030.05B. mycoides ATCC 6462 T 0.190.160.220.030.040.030.060.010.050.060.050.040.010.0230% Formic/ 30% ACN Vegetative Cells

PAGE 147

147 Table 5-7. MALDI-TOFMS correlation values for BACT vegetative cells using 30% formic acid as a solvent Vegetative Cells in 30%Formic/30%ACNB. anthracis 34F2FO-11H5H6H7H17H2H3H9H16H10H11H14H15H18B. cereus ATCC 14579 T AizawaiGalleriaeKurstakiIsraeliensisBerliner ATCC 10792TB. mycoides ATCC 6462TB. anthracis 34F2-FO-110.87-B. cereus serotypes:H50.520.57-H60.840.850.51-H70.670.730.480.67-H170.710.730.420.840.65-H20.650.750.440.750.700.69-H30.700.780.460.830.640.730.72-H90.810.810.480.930.600.790.710.77-H160.740.710.420.830.430.660.570.670.79-H100.680.730.430.610.640.560.590.560.590.48-H110.690.760.450.600.510.580.530.520.560.520.65-H140.650.780.430.730.590.650.650.680.700.600.780.66-H150.220.340.180.260.480.540.410.310.230.110.360.480.34-H180.450.570.470.410.740.390.510.430.300.220.590.530.490.43-B. cereus ATCC 14579 T 0.440.420.240.440.300.430.330.370.460.400.310.580.400.370.14-B. thuringiensis serotypes:Aizawai0.610.680.390.700.610.620.630.680.660.540.800.500.820.370.480.37-Galleriae0.450.520.290.420.660.470.530.450.390.250.520.390.460.460.520.200.52-Kurstaki0.680.690.410.640.490.570.530.560.620.570.560.760.630.380.370.790.560.36-Israeliensis0.510.600.340.560.730.580.630.560.540.350.570.430.560.500.520.260.620.690.42-Berliner ATCC 10792T0.450.540.320.390.590.420.500.410.330.250.560.500.450.440.590.220.480.580.400.60-B. mycoides ATCC 6462T0.100.130.070.130.200.170.120.100.110.090.130.140.180.090.080.160.110.130.140.120.45-B. thuringiensis serotypesB. cereus serotypes

PAGE 148

148 Figure 5-6. Clustering and visualization of the BACT vegetative cell protein profiles obtained from using formic acid as a solvent.

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149 Discussion All of the BACT strains examined using 16S rDNA analysis had greater than 97.5% sequence similarity with both of the type strains, B. cereus and B. anthracis 34F2 (Table 5-1). Therefore, 16S rDNA did not allow for the differentiation of these isolates. The DNA:DNA hybridization data is reproduced in part for the strains analyzed by MALDI-TOFMS in Table 5-8. Clustering based on DNA:DNA hybridization resulted in Table 5-8. DNA:DNA Hybridization values of the BACT strains examined in this study. Adapted from LaDuc, et al. 2004 and M. Satomi personal communication B. anthracis Sterne 7702FO-11H5H6H7H17H2H3H8H9H12H16H10H11H14H15H18B. cereus JCM 2152TAizawaiGalleriaeKurstakiIsraeliensisBerliner IAM 12077TB. mycoides ATCC 646 2 -FO-1171B. cereus serotypes:-H560na-H678na97-H775na8281-H1775na868282-H267na72747066-H369na6569616070-H871na666966627468-H966na72697657776783-H1276na7172667078807780-H1684na797577805863626967-H1050na54595563504754585161-H1148na4351424640475448355480-H1456na585663445449465654597678-H1556na56476066554953535757788384-H1840na4542414141423745354459666063-5653555353565949525549527277888158-B. thuringiensis serotypes:Aizawai51na57606058575451596055827572826273-Galleriae51na5848566158445558665380746367566969-Kurstaki47na545452545546495750556460637173586458-Israeliensis37na48495147523836444849473956584055506452-Berliner IAM 12077T45585140375235464440404363525646515456575243-4855534056524746554849495045474043525458434151-B. cereus JCM 2152TB. mycoides ATCC 6462TB. thuringiensis serotypesB. cereus serotypesB. anthracis Sterne 7702 the organization of these strains into 4 groups. The B. anthracis group consisted of the B. anthracis strain and the B. cereus serotypes H02, H09, H08, H01, H03, H12, H05, H06, H07, H16, and H17 and the laboratory strain FO-11. The second group consisted of the B. cereus type strain, the serotypes H14, H11, H04, H15, H10, H18, and H13 and the B. thuringiensis serotypes Kurstaki HD-1, Galleriae, and Aizawai. The B. thuringiensis

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150 serotypes Kurstaki HD-1, Galleriae, and Aizawai had DNA reassociation values of 58%, 69%, and 73% with the B. cereus type strain. The third grouping consisted of the B. thuringiensis serotype Israeliensis and the type strain, Berliner which had less than 60% hybridization with all of the other strains. The sole member of the fourth group was B. mycoides (personal communication, M. Satomi and K. Venkateswaran). 88 Since DNA:DNA hybridization is considered the gold-standard for bacterial speciation it is used as the benchmark for comparison of the analyses performed in this study. FAME analysis was only able, at a high confidence level, to assign 4 of the strains in this study to a reference strain. Based on the DNA:DNA hybridization studies the assignment of the 3 of strains (B. anthracis 34F2, B. thuringiensis Kurstaki, and the B. cereus type strain) is correct, however H7 is misidentified as B. thuringiensis. The FAME analysis was not useful for identifying the other 6 species analyzed as they had high similarity indices with 2 or more of the reference strains. The cluster analysis of this data also resulted in several misclassifications, including H16, H3, H7 to the B. cereus/B. thuringiensis cluster and H18 to the B. anthracis cluster. MALDI-TOFMS protein profiling with a 30% formic acid/30% ACN solvent split the spores into several groupings which somewhat mimicked the DNA-based molecular characterization of these strains. The B. anthracis group is well defined and contains H02, H07, H08, H12, H17, FO-11, and the B. anthracis 34F2 strain which all agree with the hybridization assignment. The other groupings based on protein profiling are not as clearly defined as the B. anthracis group and are characterized by having strains within them that are well below the 0.75 cutoff typically used in our analyses. The second grouping contains the B. cereus type strain, H3, H10, H11, H18, H15, H5, and B.

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151 thuringiensis Aizawai and Kurstaki HD-1. H18, Aizawai Galleriae and Kurstaki HD-1 have r > 0.93 with each other; H11, H3 have correlation values >0.70 with the B. cereus type strain while the Galleriae strain has a lower r value of 0.56. H5 and H15 have r of 0.57 with each other but overall very low correlation values with the other strains. The third group contains what can be considered outliers as the B. thuringiensis type strain forms its own well defined cluster and B. thuringiensis Israeliensis and H14 do not fall within any of the clusters in this study. This is expected for the B. thuringiensis type strain and Israeliensis as hybridization studies showed less than 60% hybridization with the other BACT strains. H3 is identified as a B. cereus type organism based on the linear correlation analysis (r=0.78) and according to the hybridization data it should fall out closer to the B. anthracis group (69% hybridization with B. anthracis 7702). Galleriae, H5, and H15 are in the same misclassification predicament; however, the linear correlation values for these strains are below 0.56, 0.28, and 0.10 respectively with the B. cereus type species and most of the other strains in this cluster. So their inclusion in the cluster would need to be justified by the presence of additional species-specific biomarker peaks, and neither have the 3,805 Da or 4,360 Da peaks that are characteristic in this cluster. H10 and H18 also have low correlation values with the B. cereus type strain but have r > 0.76 with Aizawai and contain the biomarker peak at 3,805 Da. Therefore it is proposed that Galleriae, H5, H15, and H14 are considered outliers as there is not sufficient evidence to include them in either cluster. The inclusion of the H10 and H18 are justified by additional biomarker evidence.

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152 Because of the misclassification of H3 and the lack of classifications for H5, H15, and H14, additional MALDI-TOFMS profiles were collected. These profiles were collected on spores that were treated with 5%TFA/70% ACN in lieu of the formic acid solvent to determine if better classification could be obtained using a different solvent system. Using the TFA treatment, even less classification was obtained than with the formic acid system as evidenced by the poor HCA clustering and the higher correlation values that were found between most of the strains. This can be attributed to the similarities in the SASP proteins that are released using the TFA treatment. Interestingly, the B. anthracis strain had a unique set of SASPs while the rest of the strains were divided into two SASP groups, one containing a 6,700 Da SASP (B. thuringiensis type strain group) and the other a 6,720 Da SASP (B. cereus type strain group). Whereas in the formic acid study, there was ambiguity between the B. thuringiensis and B. cereus group, in the TFA analysis, strains classified by hybridization as B. anthracis and B. thuringiensis showed more overlap and higher correlation values than with the B. cereus strains. To further characterize the BACT strains in this study, MALDI-TOFMS protein profiling was performed on the vegetative cells using formic acid as a solvent. The vegetative cells proved to be the least discriminating of the MALDI-TOFMS studies. Several group specific biomarkers were identified at 6,425 Da and 19.1 kDa, and a triplet of peaks was found in all the strains around 9,600 Da. Most of the variation in the vegetative profiles was found above 20 kDa. In looking strictly at the classification of these strains as B. anthracis, B. cereus, or B. thuringiensis in the type strain library, 14 of 26 strains met one of the two criteria to be included as B. anthracis. These included

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153 several of the B. thuringiensis ( Aizawai and Kurstaki) and B. cereus serotypes (H10, H11, and H14) that were not classified as B. anthracis based on the hybridization study. The proper classifications of the strains described thus far have been based on DNA hybridization analysis. Although this is the gold standard for species differentiation, it does not effectively identify differences in the phenotypes or toxins that may exist in these isolates which are plasmid encoded. This direction leaves the classification of these organisms based on evolutionary relationships and goes for the more applied identification of these strains. In looking at these properties, B. cereus H3 (reassociation values of 49% and 69% with B. cereus and B. anthracis respectively) was the only serotype which produced the cereuride toxin characteristic of B. cereus. B. cereus H17 (reassociation values of 56% and 75% with B. cereus and B. anthracis respectively) and H6 (reassociation values of 53% and 78% with B. cereus and B. anthracis respectively) tested positive for the genes encoding the protective antigen (pag) from B. anthracis. 88 H17 was classified as B. anthracis and H3 was classified as B. cereus using the formic acid treatment and linear correlation analysis. We were unable to obtain spores for H6 but the vegetative cells had one of the highest correlation values with the B. anthracis reference strain (r = 0.84). Based on toxigenic properties, the identification of these strains would be correct; however the converse would also be true. Strains that lack the toxins should also be distinguishable, which with the current analysis they clearly are not. Conclusion The MALDI-TOFMS-based protein profiling method using formic acid as a solvent proved to be the most successful for the differentiation and classification of the BACT group spores in this study. MALDI-TOFMS protein profiles using TFA were less

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154 discriminatory than those with formic acid solvent, instead causing an improper grouping of the B. anthracis strains with B. thuringiensis. Analysis of vegetative cells was the least discriminatory and most of the strains in the study would be assigned to the B. anthracis group. MALDI-TOFMS protein profiling also proved to be more discriminating than both FAME and 16S rDNA analysis. This is the first investigation of this many BACT group bacteria with MALDI-TOFMS protein profiling where the results are compared directly with genetic analyses. Using formic acid as a solvent, only 1 misclassification was made according to DNA hybridization results (H3) and this organism could arguable be identified properly based on pathogenic properties. There were several species that could not with certainty be assigned to any of the species in the library. These missed assignments, or false negatives, may highlight the fact that the small number of type strains or reference strains that are used are not representative of the microbial diversity within this group. 2 Additionally, to improve the analysis of this group of spores it would be beneficial to test to determine if better biomarker extraction could be facilitated by higher formic acid concentrations. Initial optimization experiments were carried out on B. subtilis 168, which does not contain an exosporium, and is less hydrophobic than the BACT group bacteria. 2 The increased hydrophobicity and exosporium layer may make the protein extraction step more challenging and a different solvent system may prove better for this group of spores. It may also be feasible and necessary to target the expressed toxin proteins for effective differentiation of this group. The use of MALDI-TOFMS protein profiling as a true diagnostic tool for the BACT group organisms has not been solidified and its effectiveness would be based on

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155 the goal of the classification or identification. The MALDI analysis tracks closely with the DNA hybridization results but has not been shown to be an effective discriminator of pathogen versus nonpathogen strains. Put simply, the MALDI analysis lends itself more towards the taxonomists goals of classification and perhaps slightly away from a pragmatic approach based on pathogenic properties. To ascertain the ability of the technique to do both, the profile library should be expanded to include more strains with and without toxin proteins. The ultimate goal could then be shifted to identify both speciesand pathogen-specific biomarkers in each strain.

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CHAPTER 6 PEPTIDE PROFILING AND BIOMARKER IDENTIFICATION FOR SELECTED Bacillus SPECIES Introduction MALDI-TOFMS protein profiling of proteins extracted from whole spores and cells has proven useful for the differentiation and identification of microorganisms. The profiles obtained from such analyses can be used in several ways. Profiles can be analyzed by statistical methods for comparing them with standardized libraries of microbial profiles in order to identify the organism at the species and strain level. 20,71,72,101,103 In another approach, peak masses extracted from the profiles can be matched to protein masses predicted from the genome. 104-106 In both cases, the analyses are hindered by the inherent variation among microbial species and by the low mass accuracy, lower resolution and sensitivity, and variability of protein profiles obtained with MALDI-TOFMS. To overcome these limitations, several groups have explored using bioinformatics-based approaches, using proteolytic peptides generated by tryptic digestion of proteins from intact microorganisms for identification purposes. 29,107-111 Using peptide fragments allows for higher sensitivity, mass resolution, and mass accuracy than can be obtained for the precursor proteins. Tandem mass spectrometry of peptides to obtain peptide mass tags has also been performed using collision induced dissociation (CID) or post source decay (PSD). Recent studies of the genus Bacillus have been focused on the release and digestion of small acid soluble proteins (SASPs). 99,100 Fenselau, et al. have shown that treatment 156

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157 with 10% TFA followed by digestion using trypsin immobilized on agarose beads results in the production of tryptic peptides from SASPs in under 30 minutes. 99,100 Using this approach, combined with a specially designed database of in silico produced tryptic peptides from the sequences of all SASP proteins available in the NCBI database, they were able to differentiate B. anthracis Sterne from closely related species. However, they were unable to differentiate B. cereus T from B. thuringiensis Kurstaki HD-1 based on the tryptic peptides generated from the SASPs. While SASPs do allow for some species differentiation, they do not account for all the peaks observed nor do they allow for differentiation at the species level as in the case of B. thuringiensis and B. cereus. 32,38,40,99,100 Therefore, the ability to visualize and identify coat proteins as well as small acid soluble proteins in the spore is critical for complete and effective species differentiation of the Bacillus genus. A solvent extraction system for protein profiling of whole spores has been developed that targets the more hydrophobic coat protein constituents instead of the SASPs. Using this system, the differentiation of over 50 strains encompassing 15 species of Bacillus species has been accomplished. Additionally, strain variation in the protein profiles from a group of B. pumilus and B. cereus and B. thuringiensis serotypes has been evaluated. These studies, which use linear correlation analysis to compare profiles, have not been directed at assigning identities to the peaks in the profile spectra. The goal of this chapter of the research is to identify the proteins which produce peaks in the MALDI profile to confirm the presence of spore coat proteins in the spectra and to begin to eliminate proteins that are expressed only in response to external stimuli. Armed with this additional information, a subset of peaks, which is species specific, can be identified as solid

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158 biomarkers for analysis, allowing for identification regardless of experimental and environmental factors. The identification of the proteins in the spectra is the backbone needed to bring this technique into fruition as a viable microbial analysis tool. Spores were extracted using the MALDI protocol described previously. 101 MALDI extracts from several species of Bacillus, including four putative B. pumilus isolates, were digested with trypsin. Profiles of the tryptic peptides were obtained using MALDI-TOFMS and were compared using linear correlation analysis. Peptide profiles obtained for the different species analyzed were distinguishable from each other but had higher correlation values than their corresponding protein profiles. Identification of the peaks in the MALDI profiles was pursued by using capillary liquid chromatography-tandem mass spectrometry (CLC-MS 2 ) to obtain peptide fragment information from the digested proteins in the MALDI extracts. The fully sequenced, B. subtilis 168 had the greatest number of coat proteins identified with 4 coat associated proteins identified in the MALDI extract. Other species examined resulted in the identification of mainly SASP associated proteins due to their high sequence conservation. Additional proteins identified include proteases, hydrolases, transport and membrane associated proteins, and several hypothetical proteins with no known function. A PE-PGRS family protein from Mycobacterium was also found in all of the B. pumilus group organisms except the type strain ATCC 7061. The only additional coat proteins identified include the spoIVA protein in B. pumilus 7061 and a cotT homologue in FO-36b. The ability to rectify the identified protein masses from the CLC-MS 2 analysis with the MALDI protein profiles proved to be difficult. This is most likely due to post translational modifications of

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159 proteins prior to deposition in the spore coat and lack of complete sequence information for the species studied. Materials and Methods Bacterial Strains The type strains of B. licheniformis, B. mojavensis, B. thuringiensis, and B. pumilus were procured from the American Type Culture Collection (ATCC, Manassas, Va). B. subtilis 168 was a gift from Dr. Wayne Nicholson at the University of Florida and B. subtilis NB200 and JH642 were a gift from Dr. Arnold Aronson at Purdue University. B. odysseyi PTA-3499, B. niacini 51-8C, FO-11, FO-36b, SAFN-029, SAFN-036, SAFR-032, and B. psycrodurans VSE1-06, were isolated from several NASA spacecraft and assembly facilities surfaces. Identity of the test organisms was determined based on 16S rDNA sequencing for the environmental isolates; whereas for the ATCC strains, those sequences available in the GenBank database were used. 61 Preparation of spores followed standard protocols described previously. 7,73 Protein Extraction and Digestion A 10 L aliquot of each spore suspension (0.6 OD 660 ) was diluted in 100 L of 30% formic acid/30% acetonitrile. This sample was vortexed briefly and then centrifuged for 5 minutes at 9600 x g. The supernatant (MALDI extract) was removed and placed in a clean microfuge vial. The solvent was removed with a speed vac and the sample was reconstituted in 50 L of 50 mM ammonium bicarbonate with 0.1 g/L sequencing grade trypsin (Promega). This concentration was found to be optimal for the efficient digestion of the extracts as less trypsin resulted in incomplete digestion. The proteins were digested overnight at 37C.

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160 Peptide profiling To perform the peptide profiling, 2.5 L of the digested sample from each spore species was diluted into 10 L of a MALDI matrix solution containing 10 mg/mL HCCA matrix in 50% ACN/ 0.1% TFA. A 1 L aliquot of this solution was then spotted onto a MALDI plate for analysis. MALDI-TOFMS analysis was performed on a Bruker Daltonics Reflex II Mass Spectrometer (Bruker Daltonics, Billerica, Ma) retrofitted with delayed extraction. The instrument was operated in the linear mode. A nitrogen laser (337 nm) pulsed at a frequency of 5 Hz irradiated the sample. Spectra were obtained in the positive ion mode with a delay time of 50 ns. The acceleration voltage was 20 kV. External calibration was performed using a mixture of angiotensin I and II and ACTH I and II. All spectra represent the accumulation of 50 laser shots. Ten spectra were collected from each spot on the MALDI plate. A total of 20 spectra were collected per sample. Each spectrum was baseline corrected and smoothed using a ten-point Savitzky-Golay smoothing algorithm prior to statistical analysis. Linear correlation analysis was performed on software developed in-house with Visual Basic 6.0 as described previously. 73 A library of the peptide spectra was complied by averaging the 20 spectra collected from each digest sample. Average spectra obtained from the peptide profiling of strains in this study were compared to MALDI-TOFMS profiles stored in this library. Higher correlation coefficients are indicative of spectral similarity. 1-D Gel Electrophoresis 1-D gel electrophoresis was performed on both a whole spore coat extract (SDS) and a MALDI extract. To prepare the extract, approximately 500 L of spores (0.6 OD 660 ) was centrifuged and the supernatant was removed. The whole spore extract was

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161 prepared by extracting the spores with 50 L of a tricine sample buffer (Biorad, Hercules, CA) containing 200 mM Tris-HCl at pH 6.8, 2% SDS, 40% glycerol, and 0.04% Coomassie Brilliant Blue G-250. For the MALDI extract, 1 mL of MALDI solvent (30% formic acid/30% acetonitrile) was first added to the spores. The spores were vortexed for 30 seconds and centrifuged in order to remove the supernatant. The spore-free supernatant was then evaporated in a speed vac, leaving behind only those proteins extracted by the MALDI solvent. These proteins were reconstituted in 50 L of tricine sample buffer. Both samples were then boiled for 10 minutes, with a 1 minute vortexing step in the middle. For the whole coat extract, the solution was centrifuged and the supernatant removed for loading onto a gel; the MALDI extract could be loaded directly. Samples were loaded onto a Criteron precast 16.5% Tris-tricine gel (Biorad, Hercules, CA) and were run at 150 V for 1.5 hours. The gel was subsequently stained with Coomassie R-250. Proteomic Analysis The MALDI protein extracts from the spores of B. subtilis 168, B. pumilus 7061, FO-11 (wild-type B. cereus), B. thuringiensis 10792, FO-36b, SAFN-036, SAFN-029, SAFR-032 and B. licheniformis 14580 were subjected to proteomic analysis. Tryptic peptides were analyzed by capillary liquid chromatography-tandem mass spectrometry (CLC-MS 2 ) using a system similar to that described elsewhere. 112 Sequence information was obtained for tryptic peptides via collision-induced dissociation. The mass-to-charge (m/z) ratio of the precursor ion and product ions for each tryptic peptide were searched against the NCBI (National Center for Biotechnology Information) protein database using the Sequest 113 and Mascot 114 algorithms for protein identification. All searches used a peptide mass tolerance of 1.8 Da and a fragment mass tolerance of 1 Da. Only the

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162 oxidation of methionine was considered as a modification. Initial database searches were performed against the entire database (all organisms) using trypsin for enzyme specificity, allowing for 1 missed cleavage. Because of the unique structure of many of the proteins identified in this study, it was necessary in subsequent searches to use no enzyme specificity. In these searches, the database search was limited to the gram positive bacteria in order to decrease the search time. Results and Discussion Peptide Profiling Peptide profiling was performed on the 10 Bacillus species in this study. The peptide profiling was performed in linear mode on the MALDI-TOFMS. The correlation results of the peptide profiling are shown in Table 6-1. Correlation values between the different species were higher than those seen with whole-cell protein profiling studies 73 and several were above the 0.75 correlation value used for species differentiation in protein profiling studies. However, using the Students t-test, complete differentiation of the peptide profiles was possible. For all species, the difference (delta value) between the first and second hit was >0.1. The applicability of the same criteria used for protein profiling (r >0.75) needs to be further evaluated using peptide profiling. Average spectra from each sample are shown in Figure 6-1. B. pumilus, B. thuringiensis, and B. odysseyi resulted in spectra that were very similar from m/z 600-2000 but had differences in the higher m/z range (m/z 2000-5000) and had correlation values ranging from 0.81-0.85 with each other. B. licheniformis and B. psychrodurans, with a correlation value of 0.85, are characterized by an absence of high intensity peptide peaks that were seen in the spectra of the other species. A notable similarity between all the spectra is the presence of biomarker peaks at m/z 1330 and 1185. Though the identity

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163 of these peptides is presently unknown, they could be genus-specific peptide biomarkers as they are not known contaminants resulting from keratin or trypsin autolysis peaks. Table 6-1. Correlation values based on the peptide profiles B. subtilisB. cereusB. licheniformisB. mojavensisB. niaciniB. odysseyiB. psychroduransB. thuringiensisB. pumulisSAFN-029SAFR-032FO36bSAFN-036B. subtilis1681.00B. cereusFO-110.381.00B. licheniformisATCC 145800.450.771.00B. mojavensisATCC 515160.330.440.531.00B. niacini51-8C0.120.230.250.191.00B. odysseyi34hs10.300.740.600.360.191.00B. psychroduransVSE1-060.430.750.850.520.250.591.00B. thuringiensisATCC 107920.200.670.460.280.140.810.421.00B. pumulisATCC 70610.270.680.530.310.160.730.500.851.00B. pumulisSAFN-0290.190.380.480.250.110.310.420.270.321.00B. pumulisSAFR-0320.230.470.540.290.140.380.500.330.400.951.00B. pumulis/FO groupFO-36b0.250.640.670.330.150.410.560.360.370.430.441.00B. pumulis/FO groupSAFN-0360.370.710.870.440.190.500.700.390.490.370.410.641.00Trypsin Digest Fingerprint From 1-D Gel Electrophoresis 1-D gel electrophoresis was used to ascertain the effectiveness of the MALDI extraction when compared to a whole spore coat (SDS) extract. Figure 6-2 shows the results of this experiment for the type strains of B. subtilis, B. pumilus, B. licheniformis, and B. atrophaeus, B. megaterium, and B. subtilis 168. The lanes alternate across the gel showing the whole coat extract next to the MALDI extract (30% formic acid/30% acetonitrile) for each species. Clearly, the MALDI solvent is only able to extract a subset of proteins from the spores when contrasted with the SDS extract. The higher concentration of formic acid used in this experiment did allow us to extract and subsequently visualize, by MALDI-TOFMS, a more diverse set of proteins from the spores. However, the resolution obtained in the gel based method is far less than that obtained using the MALDI-TOFMS protein profiling. Many of the proteins visualized in the protein profile are not resolved in the gel analysis.

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164 Figure 6-1. Peptide profiles obtained for the different species examined in this study. The scale is from m/z 500-5,000.

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165 Figure 6-2. 1-D gel electrophoresis showing the whole spore coat extract (WS) and MALDI extract (M) for 6 Bacillus strains

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166 In examining the gel, it is also interesting to note the difference in the number and amount of proteins that are extracted from each species using both the SDS and formic acid treatment. The extraction of protein from the spore coat can be affected by the number of coat proteins, by cross linking of the proteins, and by the presence or absence of an exosporium. These effects were species specific, as can be seen in the gel, where species such as B. subtilis 6051, B. globgii, and B. licheniformis appeared to have more coat proteins than the other species. B. pumilus 7061 is characterized the lowest number of coat proteins extracted using the formic acid treatment. Proteomic Analysis for Biomarker Identification Peptide profiling, while useful as an alternate method for the characterization and classification of spore species, still does not explain the source of the peptides and thus the source of the biomarkers in the MALDI spectra from the whole spores. To accomplish this goal, CLC-MS 2 has been employed to obtain peptide mass tag on the tryptic peptides from the MALDI extracts. Since the genome of B. subtilis 168 is completely sequenced, this organism was selected first for further proteomic studies directed at identifying which proteins are represented by the biomarker peaks observed by MALDI-TOFMS. Fourteen proteins were identified in the extract of the B. subtilis 168 spore sample using CLC-MS 2 The protein description, sequence coverage, molecular weight, and database searching scores are shown in Table 6-2. Four small acid soluble proteins, A, B, C, and D, one DNA binding protein, hypothetical protein ymfJ, ribosomal protein L12, a phosphocarrier protein, a protein similar to 1-pyrroline-5-carboxylate dehydrogenase, and 4 proteins

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167 associated with the spore coat and spore coat formation, coat JB, coat F, coat T, and spoIVA were identified. Table 6-2. Proteins identified from B. subtilis 168 using CLC-MS2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage16080009small acid-soluble spore protein (major alpha-type SASP) sspA B. subtilis706637568.716078040small acid-soluble spore protein (major beta-type SASP) sspB B. subtilis697528761.216081105spore coat protein cotF B. subtilis1871417637.516078751conserved hypothetical protein ymfJ B. subtilis964211456.516077757spore coat peptide assembly protein cotJB B. subtilis117457626230576Histidine-Containing Phosphocarrier Protein Hpr Mutant With Met 51 Replaced By Val And Ser 83 Repl90378832.632468826small acid-soluble spore protein [B. subtilis]51597716077390similar to 1-pyrroline-5-carboxylate dehydrogenase [B. subtilis]564547151.21075916Spore Coat Protein PrecursorcotT B. subtilis101256959.716078411small acid-soluble spore protein (minor alpha/beta-type SASP) sspD B. 68006743.716077173ribosomal protein L12 (BL9) [B. subtilis]127436716.39630297small acid-soluble spore protein C B. subtilis 77536527.816079336DNA-binding protein HU B. subtilis98785841.316079337coat morphogenesis sporulation protein spoIVA B. subtilis55140504.3B. subtilis 168 4.6 Relating these proteins to the peaks observed in the MALDI-TOFMS profile for B. subtilis 168 was challenging. It is important to note that the masses contained within the database include the methionine residue as the start of the protein, which is in most cases removed during processing. Therefore, when looking for intact proteins in the protein profiles, 131 Da should be subtracted from the molecular weight given in the databases. Proteins in the lower molecular mass region (under m/z 10,000) include the small acid soluble proteins, the DNA binding protein, the ribosomal protein, and smaller spore coat polypeptides processed from larger precursors. We postulate that the higher m/z peaks represent other processed and intact spore coat proteins such as cotJB at m/z 11,638 Da. The large peak at m/z 7,758 is the processed form of cotT, which starts as a 10kDa protein in which the first 19 residues (termed the propeptide) are removed to leave behind a ~7,800 Da spore coat protein. 115 To confirm this identification, two additional B. subtilis strains, JH 642 and NB 200, were examined. NB 200 is a cotT knockout mutant

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168 derived from the parent strain JH 642. Figure 6-3 shows the average spectrum of B. subtilis 168 compared with JH 642 and NB 200. As expected, the large 7,758 Da peak is present in both B. subtilis 168 and B. subtilis JH 642 but is missing from the cotT mutant NB200. This evidence confirms the assignment of the 7,758 Da peak to the processed from of the cotT protein. The molecular mass listed in the protein database for the remaining proteins identified, including spoIVA, ymfJ, cotF, and sspB, did not directly match with the m/z of singly charged ions observed in the MALDI spectra. Separations of the proteins prior to proteomic analysis is required in order to reduce the complexity of the biomarker protein extract and confidently assign protein identifications made by CLC-MS 2 to peaks in the MALDI spectra. This is the first time that proteins associated with the spore coat have been identified from direct spore analysis using a MALDI extract, as previous studies have only identified small-acid soluble proteins found in the spore cortex as the source of the biomarker peaks. Rectifying proteins identified in the CLC-MS 2 study for B. subtilis 168, a fully sequenced and highly annotated species, with peaks in the MALDI-TOFMS protein profile proved to be very difficult. This difficulty resulted from the post-translational processing and modifications that occur in proteins. Therefore, the success of doing this for species that do not have full sequence information available will be limited. The only currently available, fully sequenced genomes for Bacillus include B. subtilis 168 and B. anthracis Ames. Limited database entries exist for B. megaterium, B. halodurans, B. stearothermophilus, and B. cereus. Further proteomic analysis of several other species was pursued in order to ascertain what kind of proteins would be identified using the

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169 Figure 6-3. Comparison of the protein profile of the cotT protein using a cotT mutant. On the top is the B. subtilis 168 genetic strain, the middle is the JH-642 strain which is the parent strain, and NB-200 on the bottom which is the mutant with the cotT protein deleted from its sequence. Note the absence of the large 7,760 Da biomarker in the NB-200 mutant strain.

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170 CLC-MS 2 approach. The proteins identified from the analysis of B. licheniformis, FO-11, B. thuringiensis, and several of the B. pumilus group bacteria including the type strain 7061 and FO36b, SAFN-029, SAFN-036, and SAFR-032 are given in Table 6-3 through 6-10. The majority of the proteins identified from the unsequenced species were SASP associated proteins. This is expected due to the high sequence conservation among the SASP proteins. Spore coat proteins, on the other hand, have high sequence divergence, and a significant overlap with other species is not expected. We believe this is why no coat proteins are identified. Even though no spore coat proteins were identified, the analysis did result in the identification of other functional categories of proteins in these spores which have been observed in other proteomic analyses. 37,41,42 These categories of proteins included enzymes responsible for transport, translation, and various metabolic processes, including proteases, hydrolases, and synthases. The presence of these types of proteins in spores is not surprising as they function in protein synthesis and degradation and other cellular processes that allow the spore to adapt to atypical conditions. Many of these proteins are believed to be active in the signaling of the spore to break dormancy and return to a vegetative state. In B. thuringiensis, a hypothetical protein identified (NCBI accession number 21401766) shows high homology to the ymfJ protein predicted and detected in B. subtilis 168. Unfortunately, none of the adjusted molecular weights from the databases matched the m/z of peaks in the spectra for any of these other species. This is likely due to the fact that although there are peptides identified from these proteins, the coverage is by no means complete. The variable regions of protein in these species likely remain unidentified in the database search. In addition to the precursor

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171 Table 6-3. Proteins identified from B. licheniformis using CLC-MS 2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage13676638small acid-soluble protein gamma-type [Bacillus subtilis]933916247.116079336non-specific DNA-binding protein HBsu [Bacillus subtilis]987815130.480156DNA-binding protein HB Bacillus sp989115030.430022721 Small acid-soluble spore protein [Bacillus cereus ATCC 14579]683711352.3134246small acid-soluble protein gamma-type SASP90151106121399863Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]72088923.530020123 Small acid-soluble spore protein [Bacillus cereus ATCC 14579]74388923.523019957COG0168: Trk-type K+ transport systems, membrane components [Clostridium thermocellum ATCC 27405]37836766.73015572gamma-type small, acid-soluble spore protein [Bacillus aminovorans]153517138.616078040small acid-soluble spore protein (beta-type SASP) [Bacillus subtilis]69757029.4B. licheniformis Table 6-4. Proteins identified from B. thuringiensis using CLC-MS 2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage21402693Small, acid-soluble spore proteins, alpha/beta type [B. anthracis A2012]680542270.821399863Small, acid-soluble spore proteins, alpha/beta type [B. anthracis A2012]720830960.330020123Small acid-soluble spore protein [Bacillus cereus ATCC 14579]743830860.321398813Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]696125953.71710854small acid-soluble spore protein 2 (SASP) Sporosarcina Ureae717222928.3134241small acid-soluble spore protein C-5 Bacillus Mmgaterium767522926134242small acid-soluble spore protein A Bacillus megaterium638722041.921401766hypothetical protein predicted by GeneMark [Bacillus anthracis A2012]933311530.530021283IG hypothetical 17224 [Bacillus cereus ATCC 14579]17520516.721397483hypothetical protein predicted by GeneMark [Bacillus anthracis A2012]70085021.3B. Thuringiensis Table 6-5. Proteins identified from FO-11 using CLC-MS2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage30022721Small acid-soluble spore protein [Bacillus cereus ATCC 14579]68371856021398813Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracisA2012]696118073.521399863Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]720817039.730020123Small acid-soluble spore protein [Bacillus cereus ATCC 14579]743817021401004Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracisA2012]729011131.432266031conserved hypothetical protein [Helicobacter hepaticus ATCC 51449]76791661.930021283Uncharacterized conserved protein, YLXR B.subtilis homolog [Clostridium acetobutylicum]10276415.4FO11

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172 Table 6-6. Proteins identified from FO-36b using CLC-MS 2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage134224small acid-soluble spore protein 1 Bacillus Stearothermophilus 72232706021402693Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]680526449.221399863Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]720825339.730020123Small acid-soluble spore protein [Bacillus cereus ATCC 14579]743825039.7134243small acid-soluble spore protein C Bacillus megaterium755024238.83688809sspA Bacillus firmus715221934.316078040small acid-soluble spore protein (beta-type SASP) [Bacillus subtilis]697520935.816080009small acid-soluble spore protein (alpha-type SASP) [Bacillus subtilis]706620835.821398813SASP, Small, acid-soluble spore proteins, alpha/beta type [B. anthracis A2012]696120044.81710854small acid-soluble spore protein 2 (SASP) Sporosarcina ureae717219826.8134241small acid-soluble spore protein C-5 Bacillus megaterium767522924.6134246small acid-soluble spore protein, gamma type B. Stearothermophilus 901513564.621633218HlbB [Lactobacillus delbrueckii subsp. bulgaricus]974011024.431794684PE-PGRS Family Protein [Mycobacterium bovis subsp. bovis AF2122/97]1131219411.83015572gamma-type small, acid-soluble spore protein [Bacillus aminovorans]153519319.413676638small acid-soluble protein gamma-type [Bacillus subtilis]9330871075916Spore Coat Protein PrecursorcotT Bacillus subtilis101257836.637522475ATP synthase delta chain of CF(1) [Gloeobacter violaceus]21005777.637522856photosystem I subunit VII [Gloeobacter violaceus]87927516077202 ribosomal protein L30 (BL27) [Bacillus subtilis]66347237521939protochlorophyllide reductase iron-sulfur ATP-binding protein [Gloeobacter 29977694.331793669PE-PGRS Family Protein [Second Part] [Mycobacterium bovis subsp. bovis AF2122/97]910096825.630248366hypothetical protein [Nitrosomonas europaea ATCC 19718]371396810.8FO36b 54.113.625.4 Table 6-7. Proteins identified from SAFN-036 using CLC-MS 2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage21402693Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]680518561.521398813Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]696114379.1134224small acid-soluble spore protein 1722310834.3134246small acid-soluble spore protein, gamma type90157931.7134246small acid-soluble spore protein 1 [Oceanobacillus iheyensis HTE831]68837341.7134229small acid-soluble spore protein 177856741.721399863Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]72087044.130020123Small acid-soluble spore protein [Bacillus cereus ATCC 14579]74387044.1159235062-amino-4-hydroxy-6-hydroxymethyldihydropteridin e pyrophosphokinase Staphylococcus aureus subsp. 17990696.3160800009small acid-soluble spore protein (alpha-type SASP) [Bacillus subtilis]70666428.928868478conserved hypothetical protein [Pseudomonas syringae pv. tomato str. DC3000]37335633.8SAFN-036

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173 Table 6-8. Proteins identified from SAFN-029 using CLC-MS 2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage30022721Small acid-soluble spore protein [Bacillus cereus ATCC 14579]68372258621402693SASP, Small, acid-soluble spore proteins, alpha/beta type [B. anthracis A2012]68052178621399863SASP, Small, acid-soluble spore proteins, alpha/beta type [B. anthracis A2012]72082104130020123Small acid-soluble spore protein [Bacillus cereus ATCC 14579]7438209134243small acid-soluble spore protein C75501785516078040small acid-soluble spore protein (beta-type SASP) [Bacillus subtilis]697514536160800009small acid-soluble spore protein (alpha-type SASP) [Bacillus subtilis]70661421710854small acid-soluble spore protein 2 (SASP)71721454321398813Small, acid-soluble spore proteins, alpha/beta type [B. anthracis A2012]696113846143652Hbsu Protein26601091616079336non-specific DNA-binding protein HBsu [Bacillus subtilis]987810880156DNA-binding protein HB Bacillus sp989110622537119NADH oxidase [Streptococcus agalactiae 2603V/R]49823853.937519783unknown protein [Gloeobacter violaceus]78729811.815608383PE_PGRS [Mycobacterium tuberculosis H37Rv]47258702315608210echA8 [Mycobacterium tuberculosis H37Rv]27256685.4538879Ig light chain-binding protein precursor Peptostreptococcus magnus78935653.317986643ABC Transporter ATP-Binding Protein/ ABC Transporter Permease Protein [Brucella melitensis]40568623.927365336Acetyl-CoA carboxylase beta subunit [Vibrio vulnificus CMCP6]33994597.431792838PE-PGRS Family Protein [Mycobacterium bovis subsp. bovis AF2122/97]88941596.823113959COG0015: Adenylosuccinate lyase [Desulfitobacterium hafniense]49281575.628897257glutamate synthase, small subunit [Vibrio parahaemolyticus RIMD 2210633]53348571115614888BH2325~unknown conserved protein in B. subtilis [Bacillus halodurans]197735712.315805864hypothetical protein [Deinococcus radiodurans]239985611.1SAFN-029 Table 6-9. Proteins identified from SAFR-032 using CLC-MS 2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage16078040small acid-soluble spore protein (beta-type SASP) [Bacillus subtilis]697513555.2160800009small acid-soluble spore protein (alpha-type SASP) [Bacillus subtilis]706613355.2134243small acid-soluble spore protein C755012051.42956709839K protein [Adoxophyes honmai nucleopolyhedrovirus]30218864.232474990hypothetical protein-putative transmembrane protein [l.]30698754.315615456BH2893~unknown conserved protein in bacilli [Bacillus halodurans]68197130.521400449Peptidase_M4, Thermolysin metallopeptidase, catalytic domain [B. anthracis 40054683.631794687PE-PGRS FAMILY PROTEIN [Mycobacterium bovis subsp. bovis AF2122/97]151940686.7515610447hypothetical protein Rv3311 [Mycobacterium tuberculosis H37Rv]45704672.922991783COG0636: F0F1-type ATP synthase, subunit c/Archaeal/vacuolar-type H+-ATPase, subunit K [Enterococcus sp.]7295673132265695hypothetical protein [Helicobacter hepaticus ATCC 51449]25991643.415925035conserved hypothetical protein [Staphylococcus aureus subsp. aureus Mu50]39273632.220808467hypothetical protein [Thermoanaerobacter tengcongensis]33693603.916081074yydB [Bacillus subtilis]56425591.6SAFR-032

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174 Table 6-10. Proteins identified from B. pumilus 7061 using CLC-MS 2 Accession NumberProtein DescriptionMolecular WeightMascot Score% Coverage30022721Small acid-soluble spore protein [Bacillus cereus ATCC 14579]683724861.521398813Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]696124877.621399863Small, acid-soluble spore proteins, alpha/beta type [Bacillus anthracis A2012]720819357.330020123Small acid-soluble spore protein [Bacillus cereus ATCC 14579]743819257.380126small acid-soluble spore protein C-1 Bacillus megaterium720110532.3134223small acid-soluble spore protein C1 B acillus megaterium732910532.3134239small acid-soluble spore protein C4Bacillus megaterium734310532.380127small acid-soluble spore protein C-2 B acillus megaterium759810432.3134232small acid-soluble spore protein C-2 Bacillus megaterium772610432.321401004SASP, Small, acid-soluble spore proteins, alpha/beta type [ B anthracisA2012]729091309630126site-specific recombinase [Bacteriophage SPBc2]63099703.330021283hypothetical protein [Bacillus cereus ATCC 14579]17520516.816079337coat morphogenesis sporulation protein spoIVA B acillus subtilis55140504.3B. pumilus 7061 protein masses not matching with peaks in the protein profile, very few of the peptides identified in the tandem mass spectrometry experiment match to peaks in the peptide profiles obtained by MALDI-TOFMS (Figure 6-1). This difference in the peptides identified can be attributed to differences in the ionization mechanisms between MALDI and electrospray and/or to the fact that the most intense peptide peaks in the MALDI profiles do not match to sequence data in the databases. Of particular interest are the differences noticed in the B. pumilus strains analyzed. Based on the DNA-DNA hybridization data and the MALDI-TOFMS protein profile analysis, the B. pumilus group is split into two groups, the FO group and the type strain group. Spectra of the peptides from the FO group strains were very similar to one another, with >0.90 correlation values among them. The type strain group strains had more diversity in their spectral profiles. SAFN-036 and FO36b are members of the FO group and SAFN-029, SAFR-032, and ATCC 7061 belong to the type strain group. When looking at the peptide profiles in Table 6-1, the B. pumilus type strain and FO-36b have very low correlation values (<0.50) with all of the other strains in this study. The

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175 highest correlation value (0.95) is found between SAFN-029 and SAFR-032, which are both in the type strain group. The proteins identified from each of the B. pumilus strains are shown in Table 6-3. The type strain ATCC 7061 had the fewest number of proteins identified (eight). Five of these proteins were SASPs and one was the coat protein, spoIVA. FO36b had the largest number of unique proteins identified with 21 followed by SAFN-029 with 19, SAFR-032 with 13, and SAFN-036 with nine. All five of the B. pumilus group strains had high homology with the B. megaterium SASP C protein. All of the species except SAFR-032 also had peptides matching to SASPs associated with B. anthracis and B. cereus (21399863, 30020123, and 21398813). FO36b, SAFR-032, and SAFN-029 all had peptides identified from PE-PGRS family proteins. These are surface associated antigens with high glycine content found in Mycobacteria. Since these are surface associated antigens in another organism, it is possible these have similar functions and loci in the spores as well. It is interesting to note that although the SAFN-029 and SAFR-032 had very similar peptide profiles via MALDI-TOFMS, they resulted in the identification of many different proteins when compared to each other. The only overlaps between the strains were for SASPs and the PE-PGRS proteins described above. FO36b had peptides which were identified as arising from the cotT protein from B. subtilis. This is the first report of the cotT protein being present in another organism. Other species that have been examined have not had a cotT-like protein and it was thought to be unique to B. subtilis. 116 The FO36b strain also had high homology with 13 SASPs including gamma type SASPs and SASPs from the extremophile B. stearothermophilus. This is interesting in light of the increased resistance of FO-36b in

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176 comparison with other Bacillus strains. Further evaluation of the unique resistances and properties associated with the FO group strains and with SAFR-032 and SAFN-029 is necessary to correlate protein identification with the differing properties. Conclusions Profiling of the tryptic peptides obtained from the species in this study produced unique peptide spectra for each species. Possible genus specific peptides were observed at m/z 1330 and 1185. Correlation values between peptide profiles for the different species were above 0.75 in some cases. However, complete differentiation using the Students t test was possible. The applicability of the same criterion used for protein profiling (r >0.75) needs to be further evaluated for use with peptide profiling. The peptide profiling experiment requires additional sample processing and time. Little additional information was obtained when compared to the protein profiling study. The better resolution and sensitivity that can be achieved for peptide fragments may decrease the absolute limit of detection and the differentiation of closely related strains may be feasible using this approach. Ultimately the goal of this study was to identify the biomarker peaks in the MALDI-TOFMS protein profiles. One dimensional gel electrophoresis of the MALDI extracts was attempted and abandoned based on the decreased resolution obtained on gels, strongly indicating the co-elution of multiple proteins in a single band. Instead, the MALDI extract containing all the extracted proteins was digested with trypsin and analyzed using CLC-MS 2 Using this proteomics approach, we were able to identify a number of proteins in the different species. However, correlation of this information to peaks in the MALDI profiles proved challenging due to post translational processing of proteins and due to the high sequence divergence expected for spore coat proteins.

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177 Proteins identified in this study included 4 coat proteins in B. subtilis and a cotT type protein in FO-36b. This is the first time coat proteins have been identified as a source of the peaks observed in the MALDI profiles of whole spores. The cotT protein was also observed in an organism other than B. subtilis for the first time. The majority of proteins identified across the different species and strains were SASPs. The identification of SASPs and not coat proteins in the unsequenced organisms was expected due to the high sequence conservation among the SASPs. Little else can be said about the protein identifications that is not speculation at this point. Additional research on the resistances and unique properties of these organisms is needed to gain an understanding of the presence and absence of proteins in certain strains.

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CHAPTER 7 IMPACT OF ENVIRONMENTAL FACTORS AND STERILIZATION ON THE MALDI-TOFMS PROTEIN PROFILE OF SPORE SPECIES Introduction Spores are highly resistant to many sterilization treatments and can withstand a wide range of environmental conditions. These conditions include desiccation, heat, radiation, and harsh chemical treatments. Although the exact mechanism for these resistances is not completely understood, many of them are protein-based. An example of this is the small acid soluble proteins (SASPs), which are known to play a role in DNA repair and radiation survival. Spore coat proteins, which provide structural integrity to the spore, can also serve as an additional barrier between the spore and challenges present in the outside world. If disruption, alteration, and/or removal of these proteins results from environmental exposure, there may be a detectable change in the protein biomarkers found in the spore species. MALDI-TOFMS protein profiling has been established as a rapid diagnostic tool for bacterial differentiation of laboratory cultured isolates. In the field, real-time spore samples will be exposed to a wide variety of both controlled and uncontrolled environmental conditions. To translate this technology into a field-based analysis technique, the impact of these environmental conditions on the protein profiles should be evaluated. A comprehensive study on the impact of environmental factors and sterilization on the MALDI-TOFMS protein profile of spores could have several consequences. Spectral differences resulting from environmental conditions may prove 178

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179 useful in providing forensic and epidemiology information for source tracking. Profile differences may also help to explain elevated resistance levels and may be able to provide viability information for an unknown sample. Additionally, having the option to first inactivate a pathogenic strain prior to transport, analysis, and cataloging is significant from a personnel safety standpoint. The study reported in this chapter focused on a subset of environmental conditions including differences in the growth/sporulation state of the organism, initial sporulation conditions, storage conditions, aging of the spore crop, and exposure to radiation, heat, and chemical agents. Sporulation mutants were used as a model for differences in the sporulation state and incomplete spore formation that could be encountered in the environment. Lyophilized and desiccated spores were compared to spores stored in water. The aging effect of spores stored in water was also considered. Gamma and UV radiation, liquid and vapor hydrogen peroxide treatments, and autoclaving were used to mimic possible environmental exposures and to ascertain the effect of sterilization treatment on protein profiles. Spore strains that were resistant to select treatments are included to see if the profiles would provide information on viability. Spores grown on agar plates were compared with spores prepared with the standard preparation to determine if initial sporulation conditions might impact protein profiles. Using these different factors with the optimized extraction conditions established for the analysis of spores, several questions will be asked and answered. Primarily, we sought to determine whether species-specific biomarkers were still present under the exposure conditions such that differentiation of the spore strains would still be possible. We then asked whether additional biomarkers provide evidence that could be used for

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180 source tracking, forensic investigations, or epidemiology studies. We also evaluated whether differences observed in the protein spectra could be translated into viability information on the spore samples, as well as whether there are unique biomarkers present or variable alterations in resistant strains that may help to explain elevated resistances. The answers to these questions, discussed in this chapter, will provide a basis for the use of MALDI-TOFMS protein profiling as a rapid diagnostic tool for real-time bacterial identification. Materials and Methods MALDI-TOFMS Protein Profiling and Statistical Analysis Samples were prepared and analyzed by MALDI-TOFMS using the optimized matrix solution and instrumental parameters as described previously.73 Spore samples were combined with the matrix solution consisting of ferulic acid in 30% acetonitrile, 30% formic acid. Sample preparation was done in duplicate. All spectra represented the accumulation of 50 laser shots. Ten spectra were collected across each spot for a total of 20 spectra per sample. Protocols for spectral processing, library spectra creation and statistical analysis have also been described in a previous chapters. The average spectrum for each sample was put into a library and compared using linear correlation. The treated samples were compared with previously created reference libraries containing 14 species to determine if the different exposures affected the identification. Visual observation was necessary to understand the quantitative and qualitative changes in the protein profiles caused by the various treatments and exposures. Bacterial Strains Table 7-1 contains a list of the bacteria, source, and description of strains and known resistances used in this study. B. subtilis 168 was obtained from Dr. Wayne

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181 Nicholson at the University of Florida. All the sporulation mutants were provided by Dr. Adam Driks at Loyola University. Table 7-1. List and description of strains used in this study. ATCC 7061TATCCType strainFO-036bJPL-SAFClean room air particulate, H2O2 resistant168NicholsonGenome fully sequencedPY79 (ADL18)Driks"wild type" parent strain for mutantsAGS232 (ADL392)Driksblocks sporulation very early around stage IPM806 (ADL201)Driksblocks sporulation at stageIISC500 (ADL40)Driksblocks sporulation at stage IIISAB50 (ADL58)Driksblocks sporulation at stage IVPE241 (ADL956)Driksblocks cortex synthesisAD17 (ADL56)Driksprevents some mother cell gene expression and formation of the inner coat to a lar g e de g reeAD28 (ADL77)Driks prevents outer coat assemblyAD142 (ADL57)Driksprevents core assembly and some mother cell gene expression but cortex is lar g el y norma l B. subtilisB. subtilisaAbbreviations: JPL, Jet Propulsion Laboratory, SAF, Spacecraft Assembly Facility, ATCC, American Type Culture CollectionB. pumilusB. subtilisB. subtilisB. subtilisB. subtilisSpeciesCommentsStrain #SourceaB. subtilisB. subtilisB. subtilisB. subtilisB. pumilus Standard Sporulation in Liquid Media The standard protocol for the production of spores in this study followed the procedure outlined by Nicholson and Setlow7 and has been described previously.73 Briefly, a single purified colony was inoculated into nutrient broth sporulation medium (NSM), and incubated at 32oC with shaking for ca. 2-4 days until the cultures reached >99% spores. Sporulation on Solid Media A second protocol utilized in this study involved streaking a tryptic soy agar plate with purified cells of the strain to be sporulated. The plate was incubated at 32oC for 12 hours and was then kept at room temperature. The center portions of the colonies on the plate were periodically checked with phase contrast microscopy for the appearance of

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182 spores. After approximately 2 weeks of storage at room temperature, the colonies reached >90% spores. A sterile loop was used to scrape and remove the middle portion of the colonies on the plate. The scrapings were resuspended in 5 mL of sterile water until a milky solution was obtained. Spore Purification Spore cultures were harvested by centrifugation and purified to remove remnant vegetative cells and cellular debris using either the water washing or the lysozyme treatment with salt and detergent washing.7 Purified spores were adjusted to an optical density of 0.6 at 600 nm and were suspended in sterile deionized water and stored at 4oC in glass vials until exposure and/or analysis. Storage Conditions and Aging Freshly prepared B. subtilis 168, B. pumilus 7061, and FO-36b spores were compared with spores that had been stored in sterile water at 4C for 1 year. Additionally 25 L from the stock solution of B. subtilis 168, B. pumilus 7061, and FO-36b was centrifuged down at 9,600 x g for 10 minutes and the supernatant solution removed. The remaining spore pellets were lyophilized, desiccated, or resuspended in sterile water and stored for 1 week under these conditions. The lyophilized and desiccated samples were reconstituted in sterile water and the resulting solutions were diluted 1:10 with the matrix solution for MALDI analysis. Radiation Exposure Radiation dosimetry was performed using a cobalt 60 source in an ion chamber. B. subtilis 168, B. pumilus 7061, and FO-36b spores were exposed to gamma radiation at 1 MRad (50 rad/sec for 330 minutes) and 0.5 MRad (25 rad/sec for 330 minutes). Prior to gamma exposure, the concentration of the spores was adjusted to 108 cells/mL and 1mL

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183 of this dilution was placed in a 1.5 mL glass vial for exposure. Controls (unexposed spores) were also prepared and stored under the same conditions. For the MALDI analysis, the solutions were removed and spun down at 9,600 x g for 10 minutes. The supernatant was discarded and a 100 L aliquot of the MALDI matrix solution was used to resuspend the pellet. Survival of the spores after the radiation treatment was quantitatively determined by growing the gamma irradiated samples in tryptic soy broth at 32C. B. subtilis 168, B. pumilus 7061, and FO-36b spores were exposed to UVC irradiation at 254nm. Prior to exposure, the concentration of the spores was adjusted to 106 cells/mL using phosphate buffered saline. Spores were placed into an uncovered Petri dish and were exposed to UVC radiation at 254 nm using a low pressure hand held mercury arc UV lamp (UV Products Inc., model #UGV-11, Upland, CA). Spores were exposed for 169.8 seconds, the time needed to produce 1 kJ of energy at the sample surface based on measurements using a radiometer. Control (unexposed) spores were also diluted and stored under the same conditions. One mL of the exposed and control solutions were centrifuged at 9,600 x g for 10 minutes. The supernatant was discarded. No pellet was observed in the bottom of the microfuge tubes, however 10 L of the MALDI matrix solution was added to the tubes and was used for analysis. Hydrogen Peroxide Exposure B. subtilis 168, B. pumilus 7061, and FO-36b spores were exposed to hydrogen peroxide vapor sterilization. A vial containing 1mL of a desiccated solution of 107 cells/mL of each spore strain was place an appropriate sealed bag. The bags were placed inside a Sterrad 100 vapor H2O2 chamber (Advanced Sterilization Products, Irvine, CA). The vials were exposed to 2 cycles of H2O2 injections. Each injection

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184 cycle resulted in the exposure of the spores to 3 mg/mL vapor H2O2. Controls consisted of desiccated spores in vials not exposed to the vapor treatment. To recover the spores from the vial, 1 mL of water was added and the vial was vortexed for 1 hour. After 1 hour of shaking, the solution was centrifuged at 9,600 x g for 10 minutes. The supernatant was discarded. Again, no pellet was observed but 10 L of MALDI matrix solution was added to the tubes for analysis. B. subtilis 168, B. pumilus 7061, and FO-36b spores were exposed to a 5% liquid hydrogen peroxide treatment. An 833 L aliquot of a 107 cells/mL culture was combined with 167 L of 30% hydrogen peroxide which resulted in a final concentration of 5% hydrogen peroxide. Controls were prepared by adding 167 L of water to the spores. The solutions were incubated for 1 hour at room temperature (25C) with gentle mixing. After 1 hour the treated solutions were centrifuged and the supernatant solution was discarded. A 10 L aliquot of the MALDI matrix solution was added to the remaining spore pellets and the solution was deposited directly onto the MALDI plate. Autoclave Exposure Aliquots (100 Ls) of and both freshly prepared and 1 year old B. subtilis 168, B. pumilus 7061, and FO-36b spores were autoclaved for 30 minutes at 15 psi and 220C. No dilutions were performed on the original OD 0.6 spore solutions prior to autoclaving. For MALDI analysis, 2.5 L of the autoclaved sample was combined with 22.5 L of the MALDI matrix solution. Preparation of B. subtilis Sporulation Mutants Sporulation mutants were incubated in Luria Bertani (LB) media until turbid. A 10 L aliquot of the culture was then inoculated onto LB agar plates containing antibiotics to isolate cells with the mutation of interest. SAB50, AD142, and AD28 were

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185 grown on LB containing 5 g/mL choloramphenicol; AGS232 was grown with 5 g/mL choloramphenicol and 50 g/mL spectinomycin and PE241 was grown on 5 g/mL tetracycline. PM806, SC500, and AD17 had no drug resistance markers and were grown on LB with no drug. Single isolated colonies from the LB plates were used to prepare glycerol stocks. The glycerol stocks were then used to streak tryptic soy agar (TSA) plates for sporulation. The sporulation was prepared as described by Driks.117-119 It was necessary to harvest the mutants with different blocks in sporulation at different times to prevent lysing of the cells in solution. The mutants were harvested shortly after the time at which the blocks occurred. AGS232 was harvested at T2 (hour 2 of sporulation), PM806 at T3, SC500 at T4, and SAB50 and PE241 were harvested at T5. The cell pellets (consisting mostly of vegetative cells and protoplasts) were collected by centrifugation and were used for MALDI analysis with no further purification. For the remaining strains, including the parent strain PY79, AD28, AD17, and AD142, a 1 mL aliquot was taken at T6 and then the culture was completely harvested at T24. The T6 samples consisting of vegetative looking cells were pelletized and were used with no further purification. The T24 samples were further purified using a Renografin gradient.7 All of the cell pellets were resuspended in 50 L of sterile water and were diluted 1:10 with the matrix solution for MALDI analysis. Results and Discussion Initial Sporulation and Purification Conditions To date, standardized protocols for the laboratory culture of vegetative cells have been necessary for obtaining reproducible MALDI-TOFMS protein profiles. However, very few studies have been done on the reproducibility of spores produced under different initial sporulation conditions. These limited studies have examined liquid

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186 sporulation media formulations and have shown that the same protein peaks are generally present across the samples.26 No studies have examined spores grown on solid media or with media that is not chemically altered to enhance sporulation. In the environment, spores are not likely to have the abundance of nutrients and ions available in broth cultures and will certainly not have a controlled temperature of incubation. To pseudo-mimic this type of formation, bacterial cultures were streaked on regular TSA plates. Following an initial incubation period to start colony formation, the plates were left at room temperature and checked for sporulation. After approximately 2 weeks, the center of the colonies from all the strains contained mainly sporulated cells which were removed for analysis. Spores of B. subtilis 168, B. pumilus 7061, and FO36b produced in this manner had linear correlation values of 0.96, 0.87, and 0.92, respectively, with spectra from the same species contained in the reference library. In addition to the initial sporulation conditions, there are several methods for the purification of spore crops. The lysozyme treatment with salt and detergent washes or Renografin gradients are typically rather than plain water washing to ensure the removal of mother cell components adsorbed to the forespore. These purification methods are not likely to be available in the environment and so an examination of the protein profiles obtained under different purification methods is warranted. Correlation values among B. subtilis spores purified in water, lysozyme, or Renografin were above 0.90 indicating there was no difference in the profiles. The MALDI-TOFMS protein profiling method proved to be robust enough to handle spores produced under different sporulation conditions and purification methods.

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187 Storage Conditions and Spore Aging The conditions and times for which spores are stored may also impact the protein profile of the sample. Storage in water is recommended as it does not present a radical change in the spore environment. Long term storage in water can be complicated by spore germination in response to small amounts of nutrients leaked by spores and by possible hydrolysis or degradation of spore coat components.7 Therefore, lyophilization is recommended for long-term storage. In the case of a bioagent release, spores will have been desiccated to maximize dispersal and obtain the optimal particle size for inhalation. Two spore crops were examined: one that was prepared 1 year ago and stored in water and the second which was less than 1 month old. Three storage conditions were also examined: storage in water at 4C, desiccated spores, and lyophilized spores. Storage conditions were examined for short term effects after 1 week of storage under the different conditions. Table 7-2 shows the correlation results for B. subtilis 168, B. pumilus 7061, and FO-36b spores under different storage conditions and different ages. The impact of the storage conditions on the MALDI protein profiles was minimal; however, the effect of aging for some of the spores was significant. For B. subtilis 168 and B. pumilus 7061 spores, aging had only a minimal effect on the protein profiles. The peaks in the range from 3-10 kDa were stable over time. For proteins above 10kDa, there was a loss in sensitivity noticed but it had minimal impact on the correlation values, with values of 0.90 and 0.84 for the different aged spores of B. subtilis and B. pumilus. FO-36b showed a significant difference in its protein profile even in the 3-10 kDa range and had a low correlation value of 0.56 with the older spores. Figure 7-1 shows the difference in the protein profiles for the 1 month old and 1 year old FO-36b spore crops. There is an

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188 appearance of intense biomarkers at 6,824, 7,240, and 9,620 Da in spores stored in water over long periods of time. In examining spectra taken over a 1 year period, the 7,630 Da peak was initially the most intense peak in the spectra with a small 7,240 Da peak. The relative intensity of the 7,240 Da peak increased compared to the 7,630 peak over the course of the year. Although the species and strain specific biomarkers identified previously were still present, the change in the relative intensities of these peaks would impact the correlation analysis. It is unknown whether these biomarkers are a result of the hydrolysis of spore coat proteins or are indicative of a change in the permeability of the spore coat. Table 7-2. Correlation values for aged spores and spores stored under different conditions. controlcontrollyophilizeddessicatedcontrolcontrollyophilizeddessicatedcontrolcontrollyophilizeddessicated1 year1 month1 month1 month1 year1 month1 month1 month1 year1 month1 month1 monthB. pumulis 7061B. pumulis 7061B. pumulis 7061B. pumulis 7061B. subtilis 168B. subtilis 168B. subtilis 168B. subtilis 168FO36bFO36bFO36bFO36bB. pumulis 70611 yearwater-B. pumulis 70611 monthwater0.84-B. pumulis 70611 monthlyophilized0.780.83-B. pumulis 70611 monthdessicated0.750.920.96-B. subtilis 1681 yearwater0.040.050.040.05-B. subtilis 1681 monthwater0.040.050.050.050.90-B. subtilis 1681 monthlyophilized0.020.030.020.020.940.80-B. subtilis 1681 monthdessicated0.020.030.020.020.920.850.97-FO36b1 yearwater0.090.080.070.060.140.150.150.16-FO36b1 monthwater0.680.740.720.740.140.160.110.120.56-FO36b1 monthlyophilized0.700.710.650.700.160.170.120.140.620.98-FO36b1 monthdessicated0.640.640.710.700.150.160.120.130.560.940.93-SpeciesAgeStorage

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189 Figure 7-1. MALDI-TOFMS protein profiles of aged FO36b spores. A) FO36b spores that are stored in water for 1 month. B) FO36b spores that were stored in water for 1 year. The mass range is shown from m/z 2,500-40,000.

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190 For the same age spores of each strain that had been lyophilized or desiccated, correlation values remained above 0.80, indicating a high degree of similarity. Upon closer observation, it was noted that the greatest impact of the different storage conditions were on the higher molecular weight proteins. Figure 7-2 shows the average spectra for the B. subtilis 168 spores that are 1 month old under the different storage conditions. Figure 7-3 is the average spectra for the FO36b spores that are 1 year old. The lyophilized spores overall had a lower signal to noise ratio and a loss in sensitivity was seen for the higher molecular weight proteins. This impact was more significant for lyophilized spores than desiccated spores and was more evident in freshly prepared spores than in older preparations where a loss in sensitivity for the higher molecular weight proteins was already present. Other freshly prepared spore strains from other species gave similar results for the lyophilized and desiccated spores (data not shown). Radiation Exposure Gamma and UV radiation are sterilants for most microbial organisms. Spores possess a unique ability to resist and/or repair the damage caused by ionizing radiation, which allows them to persist in the environment and be immune to the use of these technologies for sterilization. The level of resistance to radiation is strain-specific. All of the spore strains in this study had elevated resistances to UVC radiation. The LD90 for B. subtilis 168, B. pumilus 7061, and FO36 b are 200 J/m2, <200 J/m2, and 900 J/m2 respectively (K. Venkateswaran and D. Newcombe, personal communication). All of the spore strains were resistant to gamma irradiation at 0.5 MRad and both B. subtilis 168 and FO36b were resistant to 1MRad dose of gamma irradiation. The MALDI-TOFMS

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191 Figure 7-2. MALDI-TOFMS protein profiles of B. subtilis 168 spores under different storage conditions. A) Lyophilized spores. B) Desiccated spores. C) Water storage. The mass range is shown from m/z 2,500-40,000. The higher molecular mass region from m/z 10,000-40,000 is amplified 4x (see inset of each spectrum) in order to visualize the higher molecular weight peaks.

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192 Figure 7-3. MALDI-TOFMS protein profiles of 1 month old FO36b spores under different storage conditions. A) Lyophilized spores. B) Desiccated spores. C) Water storage. The mass range is shown from m/z 2,500-40,000. The higher molecular mass region from m/z 10,000-40,000 is amplified 4x (see inset of each spectrum) in order to visualize the higher molecular weight peaks.

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193 protein profiles of spores exposed to both irradiation sources were examined using linear correlation. Gamma exposed spores from all three species were nearly identical to the control and reference strains. For the 0.5 and 1 MRad exposure, correlation values (r) for B. subtilis 168 were 0.96 and 0.94, for B. pumilus 7061 r = 0.98 and 0.87, and for FO36b, r = 0.94 and 0.88 with the control strains. UV exposed spores of B. pumilus 7061 and FO36b were also not different from controls with correlation values of 0.90 and 0.94 respectively; however, an increase in intensity was noted in the spectra from treated spores. Profiles of B. subtilis 168 spores were significantly altered by the UV treatment. Figure 7-4 shows both the treated and control spectra from B. subtilis 168. There was a drop in overall sensitivity and there was a large peak at 5, 387 Da which had not been previously observed in B. subtilis spores. H 2 O 2 Exposure While intensely oxidizing conditions are not prevalent in the environment, H2O2 vapor sterilization is commonly used for the treatment of spacecraft parts and other heat sensitive medical equipment and devices. Of the three spore strains in this study, FO-36b was found to be resistant to both liquid and vapor H2O2 treatments. MALDI-TOFMS protein profiling of the vapor treated spores was hindered by the ability to efficiently recover the treated, desiccated spores from the inside of the vials used in the analysis. This combined with the molecular weight shifts caused by the oxidation of amino acids in the proteins resulted in very low correlation values when compared with reference and control strains. Visual interpretation of the spectra was necessary to interpret spectral differences.

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194 Figure 7-4. MALDI-TOFMS protein profiles of UV treated B. subtilis 168 spores. A) UV exposed spores. B) Unexposed (control) spores. The mass range is shown from m/z 2,500-40,000.

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195 Average spectra from the control and H2O2 vapor-treated spores of B. subtilis 168, B. pumilus 7061, and FO36b are shown in Figure 7-5, 7-6, and 7-7. Oxidation of the protein peaks is readily evident in the treated spectra where shifts in molecular weight between 60-100 Da are seen for the base peaks in the spectra. These shifts are combined with a decrease in peak resolution for the oxidized samples. The B. subtilis 168 and B. pumilus 7061 spectra also have an increase in intensity (and accompanying peak shift) for the 6,940 Da peak in B. subtilis and the 6,870 Da peak in B. pumilus. In FO36b, there is a decrease in intensity of the 6,830 Da peak and the 7,630 peak is missing from the treated spectra. Since the recovery of spores from the vial could have contributed to changes in the resulting protein profiles, a second H2O2 treatment, using a 5% liquid exposure directly on 1 month old spores was performed. Average spectra from the control and treated spectra from the liquid exposure are shown in Figure 7-8, 7-9, and 7-10. Treated spectra from B. subtilis 168 and B. pumilus 7061 again showed a shift in molecular weight of the base peak in the spectra. Interestingly, spores of FO36b showed no corresponding shift in molecular weight for the intensity 7,630 peak. This may have been a result of the protein not having oxidizable residues or the presence of a catalase protein in FO36b that quenches oxidizing species. The oxidation of residues in the proteins could alter the protein structure to the point that it would lose activity or function and inhibit germination. Autoclave Exposure Autoclaving at high temperatures and high pressure is the most reliable method to inactivate spore strains. The 1 month old spores from the three strains were autoclaved.

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196 Figure 7-5. MALDI-TOFMS protein profiles of H 2 O 2 vapor treated B. subtilis 168 spores. A) H 2 O 2 exposed spores. B) Unexposed (control) spores. The mass range is shown from m/z 2,500-40,000.

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197 Figure 7-6. MALDI-TOFMS protein profiles of H 2 O 2 vapor treated B. pumilus 7061 spores. A) H 2 O 2 exposed spores. B) Unexposed (control) spores. The mass range is shown from m/z 2,500-40,000.

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198 Figure 7-7. MALDI-TOFMS protein profiles of H 2 O 2 vapor treated FO36b spores. A) H 2 O 2 exposed spores. B) Unexposed (control) spores. The mass range is shown from m/z 2,500-40,000.

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199 Figure 7-8. MALDI-TOFMS protein profiles of H 2 O 2 liquid treated B. subtilis 168 spores. A) H 2 O 2 exposed spores. B) Unexposed (control) spores. The mass range is shown from m/z 2,500-40,000.

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200 Figure 7-9. MALDI-TOFMS protein profiles of H 2 O 2 liquid treated B. pumilus 7061 spores. A) H 2 O 2 exposed spores. B) Unexposed (control) spores. The mass range is shown from m/z 2,500-40,000.

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201 Figure 7-10. MALDI-TOFMS protein profiles of H 2 O 2 liquid treated FO36b spores that are 1 month old. A) H 2 O 2 exposed spores. B) Unexposed (control) spores. The mass range is shown from m/z 2,500-40,000.

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202 None of the spore strains were viable post-autoclaving. The average spectra from the control and autoclaved spores are shown in Figure 7-11, 7-12, and 7-13. Surprisingly, the spectra from B. subtilis 168 and B. pumilus 7061 are very similar to the control spectra as evident by the high correlation values of 0.86 and 0.85 respectively. Change in the relative intensity of the m/z 6,940 and 9,136 peaks are the most predominant changes in the B. subtilis pair. In B. pumilus 7061, there is not an obvious change in the spectra other than a change in overall signal-to-noise and the disappearance of the higher molecular weight peaks in the autoclaved samples. As Figure 7-13 shows, the FO36b sample had significant changes that caused the correlation value between the spectra to be 0.20. The autoclaved spores showed a similar spectral pattern to the aged FO36b samples with the appearance of intense biomarkers at 6,830 and 7,240, which are not observed in the fresh FO36b control samples. Sporulation Mutants In the environment or in a spore sample, it is possible that the sporulation process may start but not go through to completion. Accordingly, examining sporulation mutants may give us insight into the sporulation process and the cascade of gene and protein expression that occurs during spore formation. In this study, the MALDI-TOFMS protein profiles were obtained for sporulation mutants blocked at different stages of sporulation and for mutants which resulted in incomplete formation of the spore coat. Table 4-3 contains the results from the linear correlation analysis of these strains. Mutants which resulted in incomplete spore formation (ADL392, ADL201, ADL40, ADL58, and ADL956) resulted in spectra (Figure 7-14 A-E) which were drastically different from both the T6 (Figure 7-15 A) and T24 (Figure 7-16 A) samples from the parent strain (ADL18). Average spectra from these strains are shown in time

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203 Figure 7-11. MALDI-TOFMS protein profiles of autoclaved B. subtilis 168 spores. A) Autoclaved spores. B) Control spores. The mass range is from m/z 2,500-40,000.

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204 Figure 7-12. MALDI-TOFMS protein profiles of autoclaved B. pumilus 7061 spores. A) Autoclaved spores. B) Control spores. The mass range is from m/z 2,500-40,000.

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205 Figure 7-13. MALDI-TOFMS protein profiles of autoclaved FO36b spores. A) One month old autoclaved spores. B) One month old control spores. The mass range is from m/z 2,500-40,000.

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206 sequence in Figure 7-14 A-E. The 5 mutants were markedly similar to each other even though they were sampled at different time points and sporulation was blocked at different stages. Prominent biomarker peaks for these mutants were found at m/z 7,300, 9,870, 16,400, 17,700, 22,380, and 32, 630. In the late blocks, ADL58 and ADL956, additional biomarker peaks appear at 6,930 Da and 12.6 kDa. Table 7-3. Correlation values for mutated B. s ubtilis s tra ins StrainTime DescriptionAGS232 (ADL392) PM806 (ADL201) SC500 (ADL40) SAB50 (ADL58) PE241 (ADL956) PY79 (ADL18) AD17 (ADL56) AD28 (ADL77) AD142 (ADL57) PY79 (ADL18) AD17 (ADL56) AD28 (ADL77) AD142 (ADL57)AGS232 (ADL392) 2 blocks sporulation very early around stage I PM806 (ADL201) 3 blocks sporulation at stageII 0.82 SC500 (ADL40) 4 blocks sporulation at stage III 0.840.85 SAB50 (ADL58) 5 blocks sporulation at stage IV 0.550.660.63PE241 (ADL956) 5 blocks cortex synthesis 0.770.940.840.76 PY79 (ADL18) 6 "wild type" parent strain for mutants 0.410.560.560.690.59AD17 (ADL56) 6 prevents some mother cell gene expression and formation of the inner coat to a large degree 0.300.400.380.440.520.50AD28 (ADL77) 6 prevents outer coat assembly 0.200.270.290.640.400.60 0.78 AD142 (ADL57) 6 prevents core assembly and some mother cell gene expression but cortex is largely normal 0.360.500.480.510.610.55 0.980.75 PY79 (ADL18) 24 "wild type" parent strain for mutants 0.000.050.00-0.010.070.350.010.000.01AD17 (ADL56) 24 prevents some mother cell gene expression and formation of the inner coat to a large degree 0.110.120.070.100.140.320.260.220.250.57AD28 (ADL77) 24 prevents outer coat assembly 0.060.080.030.210.130.360.290.350.260.41 0.72 AD142 (ADL57) 24 prevents core assembly and some mother cell gene expression but cortex is largely normal 0.080.130.080.080.170.260.430.290.410.38 0.89 0.54For the mutants which continued through the complete sporulation cycle, samples were analyzed at T6 and T24. At T6, the spores should be entering stage V where they would begin formation of the spore coat. The average spectrum for each of the strains at T6 is shown in Figure 7-15 B-D. Spectra from the mutant strains (ADL56, ADL77, and ADL57) at T6 were more similar to each other than to the parent strain (Figure 7-15 A). The mutant strains and the parent strain have several biomarkers in common with the blocked mutants including m/z 6,930 (with a variation in relative intensity between the 2

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207 Figure 7-14. MALDI-TOFMS protein profiles of B. subtilis sporulation mutants. A) ADL392 at T2. B) ADL201 at T3. C) ADL40 at T4. D) ADL58 at T5. E) ADL956 at T5. The mass range is from m/z 2,500-40,000.

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208 Figure 7-15. MALDI-TOFMS protein profiles of the cells of the B. subtilis spore coat mutants at T6. A) ADL18 (parent strain). B) ADL56. C) ADL77. D) ADL57. The mass range is from m/z 2,500-40,000.

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209 groups), 12,600, 16,400, 17,700, 22,380, and 32, 630; however, this similarity did not translate into high correlation values between the two groups. At T24, the sporulation should be complete with the phase bright spore released from the mother cell. These spectra are shown in Figure 7-16 A-D with the parent strain normal spore shown in spectra A and the mutated strains in B-D. The parent strain spore in this study had a high correlation value (r=0.94)with the B. subtilis 168 reference strain in the library. The mutated spores which resulted incomplete coat formation had correlation values ranging from 0.38-0.57 with the parent strain spore indicating a low degree of spectral similarity. Visual observation of these mutants did reveal that all spores had the 7,760 Da biomarker peaks in common with the parent strain. The mutated spores also had several peaks in common with each other including m/z 6,695, 8,760 and 10, 112. ADL56 and ADL57 were very similar to each other (r=0.89) with additional peaks in common at 7,915 Da and 17.6 kDa. In general, the mutated spores had a greater number of peaks in the 3-10kDa range than normal B. subtilis spores. These peaks could be associated with SASPs or with polypeptide components of the spore coat that were now extracted due to the incomplete spore coat being more susceptible to the solvent extraction. Proteomic analysis and growth studies are needed to determine this. Follow-up studies on these mutants should also include analysis of vegetative cells in log phase growth (not entering the sporulation cycle) to determine if the biomarkers identified in the different mutants are specific to the sporulation process. Proteomic analysis of the samples in the different stages could then be focused on the sporulation specific proteins.

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210 Figure 7-16. MALDI-TOFMS protein profiles of the spores of the B. subtilis spore coat mutants at T24. A) ADL18 (parent strain). B) ADL56. C) ADL77, D) ADL57. The mass range is from m/z 2,500-40,000.

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211 Conclusion The B. pumilus 7061 spores were the least impacted by the different exposure conditions. This may be due to the fact that these spores are more susceptible to the initial formic acid extraction and thus no detectable change in the protein profile occurs for spores that have been treated. The B. subtilis 168 spores did show increases in SASP associated proteins (6,940 and 9,136 Da) particularly for the autoclaved and H 2 O 2 vapor treated samples indicating a change in spore coat permeability post treatment. Radiation exposed samples, except in the case of the UV treated B. subtilis 168, showed no difference that could be attributed to exposure or a change in spore coat permeability for any of the strains. The examination of the sporulation and spore coat mutants from B. subtilis provided insight into possible sporulation specific biomarkers that can be linked to spore formation, although further proteomic analysis is needed to identify the peaks. The FO-36b spores proved to be the most interesting group in this study. FO-36b spores exhibited significant changes in protein profiles when autoclaved and in long term storage in water. This change involved the appearance of biomarkers at 6,820 and 7,240 Da which we believe are SASP associated proteins that are also present in B. pumilus 7061. The presence of the biomarker peak at 7,620 is necessary for the differentiation of FO group spores from the B. pumilus type strain. 96 The 7,620 Da peak also proved interesting in the liquid H 2 O 2 treated spores. Unlike the other 2 species in this study, no evidence of protein oxidation was seen in the FO-36b spores. The reason for this warrants further studies but the lack of a molecular weight shift could be used as an indicator of H 2 O 2 resistant strains. This study sought to answer the following important question: are species-specific biomarkers still present under the exposure conditions such that differentiation of the

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212 spore strains is still possible? Except in the case of the mutated strains and H 2 O 2 treated spores, most of the exposures or differences in growth or storage conditions resulted in spectra that contained species-specific biomarkers. The linear correlation values obtained in some cases were low due to changes in the relative intensities of peaks in treated versus control spectra and/or the appearance of additional peaks in the treated spectra. To compensate for this, either different statistical analyses could be used which only consider peak location and not intensities, or spectral libraries could contain profile entries from treated spores. This study also indicated that it is possible to use the differences in the spectra to provide information on cell viability and explanations for increased resistances. The additional information provided by the appearance of these biomarkers can potentially provide evidence that can be used for source tracking, forensic investigations, and epidemiological studies. These results are encouraging and confirm the robustness of MALDI-TOFMS protein profiling methodology as a rapid diagnostic tool for both laboratory cultured strains and field samples.

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CHAPTER 8 CONCLUSIONS AND FUTURE WORK MALDI-TOFMS based protein profiling has been demonstrated as a rapid diagnostic tool for the analysis of Bacillus spores and cells. The success of the technique was realized through the combination of linear correlation and cluster analysis with an optimized one-step sample preparation. The technique was validated by its application for the analysis of over 50 different Bacillus strains, the largest and most thorough examination of the genus to date. Using a polyphasic approach for classification, we were able to substantiate the MALDI-TOFMS protein profiling technique with other well-established genotypic and phenotypic methods. MALDI-TOFMS protein profiling was shown to be more discriminating than other phenotypic tests, such as Biolog and FAME analysis, and was demonstrated to be complementary to genetic methods such as DNA:DNA hybridization and gyrB sequence analysis. The protein profiling experiment was rapid, reproducible, and sensitive, requiring less than 10,000 cells for species identification (data not shown). Using the criteria for species identification of a correlation value greater than 0.75 and a delta value of 0.1, the technique was shown to be robust and versatile for the analysis of environmentally challenged spores. Invariant and omnipresent species-specific biomarkers could be identified for almost all of the strains examined. Because of its reliability, discriminating power, speed, and sensitivity, the protein profiling technique using MALDI-TOFMS is far better than other phenotypic typing and chemotaxonomic methods that are in use today including whole-cell protein 213

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214 fingerprinting using gel electrophoresis. Since the MALDI analysis allows for better resolution of proteins, it can define more unique proteins in a sample which can allow for better differentiation. An example of this is seen in the analysis of the B. pumilus group isolates where the differentiation of the FO group bacteria required the resolution of the 7,640 Da biomarker peak. The rate at which analyses can be performed and the potential for automation is also a great advantage over genotypic techniques such as hybridization and sequence analysis. There is a significant initial capital cost associated with the purchase of a mass spectrometer; however, the long-term cost per sample is low, due mainly to the non-labile and inexpensive consumables. The technique also uses a reference library for comparison of new isolates, eliminating the time and effort needed to grow and maintain reference strains for each analysis as in DNA:DNA hybridization experiments. Limitations that still exist for this technique are the size and breadth of the MALDI protein profile database; the reliance on manual interpretation of the spectra in order to deal with atypical strains; the need for pure cultures; the lack of proteome information on Bacillus in databases for protein identification and the lack of understanding of the post translational modifications and divergence in spore coat proteins. Neill Logan put it best when he said Taxonomists can only be as good as their culture collections and identification systems can only be as good as their databases. Therefore, future work in this area must first be to continue to expand the Bacillus profile library with thoroughly characterized reference strains that represent the vast diversity of this genus. This will certainly mean using multiple strains of a given species for reference as opposed to type strains which do not always encompass all the phenotypic

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215 properties within a species as was evident in the BACT group analysis. The addition of strains to the database would be best managed by a multidisciplinary team which includes scientists from microbiology, chemistry, and statistics, where each member brings a different view of the analysis to the table. Changing the statistical treatment of the spectra for identification is also inevitable. While the linear correlation analysis has worked throughout the course of this research, the manual interpretation of the spectra is the limiting factor in the speed and analysis of these species. The liberal criteria used for the correlation analysis allowed for effective species discrimination but often ignored the finer points of strain differentiation which required manual interpretation of peaks. The solution is to move towards using peak picking algorithms for profile identification. The use of peak picking algorithms should allow us to weight species-specific biomarker peaks in the spectra, which, should in turn allow us to deal with strain variation and atypical strains more efficiently. The use of peak picking algorithms has also been shown to be successful for the analysis of spore mixtures. Preliminary investigation of the Algoworks statistical software developed at Pacific Northwest National Laboratories is currently underway for this purpose. To identify the species-specific biomarker peaks in the spectra, we have to patiently wait for more Bacillus genome projects to be completed and translated into protein information in the databases or perform de novo sequencing of the extracted proteins. Newly developed mass spectrometry techniques such as electron capture dissociation allow for the sequencing of whole proteins and could be utilized for this purpose. For this type of analysis however, it will be necessary to isolate the protein of interest prior to

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216 analysis. Because of the limited resolution of 1D gel electrophoresis, either 2D gel electrophoresis or chromatography will have to be developed for this purpose. The research here provides a platform for the design of diagnostics for a wide range of applications that can include source tracking, epidemiological studies, forensic investigations, determination of resistances, niche, and natural selection and direct environmental monitoring. While the ultimate design of the instrument and the sample requirements may vary in these different applications, the fundamental and polyphasic approach used here allows for the rapid identification of new characters that have diagnostic value for the differentiation of the Bacillus genus.

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LIST OF REFERENCES 1. Sonenshein, A. L.; Hoch, J. A.; Losick, R. Bacillus Subtilis and Other Grampositive Bacteria Biochemistry, Ph ysiology, and Molecular Genetics, American Society for Microbiology: Washington, D.C, 1993. 2. Logan, N. A. Applications and Systematics of Bacillus and Relatives, Blackwell Scientific Publica tions: Oxford, 2002. 3. Madigan, M. T. Brock Biology of Microorganisms, 8th ed.; Prentice-Hall: Upper Saddle River, New Jersey, 1997. 4. Nicholson, W. L.; Fajardo-Cavazos, P.; Rebeil, R.; Slieman, T. A.; Riesenman, P. J.; Law, J. F.; Xue, Y. M. Int. J. Gen. Mol. Microbiology 2002, 81, 27-32. 5. Driks, A. Microbiol. Mol. Biol. Rev. 1999, 63, 1-20. 6. Driks, A. Cell Mol. Life Sci. 2002, 59 389-91. 7. Nicholson, W. L.; Setlow P. in Molecular Biological Methods for Bacillus Harwood, C. R.; Cutting, S. M., Eds.; Wiley: Chichester, MA, 1990. 8. Towner, K. J.; Cockayne, A. Molecular Methods for Mi crobial Identification and Typing, 1st ed; Chapman & Hall: London, 1993. 9. Logan, N. A. Bacterial Systematics, Blackwell Scientific Publications: Oxford, 1994. 10. Busse, H. J.; Denner, E. B.; Lubitz, W. J. Biotechnol. 1996, 47, 3-38. 11. Dass, C. Principles and Practice of Bi ological Mass Spectrometry, John Wiley: New York, 2001. 12. Fung, E. T.; Wright, G. L.; Dalmasso, E. A. Cur. Opin. Mol. Ther. 2000, 2, 64350. 13. Fung, E. T.; Enderwick, C. Biotechniques 2002, Suppl 34-1. 14. Weinberger, S. R.; Dalmasso, E. A.; Fung, E. T. Cur. Opin. Chem. Biol. 2002, 6, 86-91. 217

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218 15. Cain, T. C.; Lubman, D. M.; Weber, W. J. Rapid Commun. Mass Spectrom. 1994, 8, 1026-30. 16. van Baar, B. L. M. FEMS Microbiol. Rev. 2000, 24, 193-219. 17. Goldman, R. C.; Tipper, D. J. J. Bacteriol. 1981, 147, 1040-48. 18. Fox, A.; Stewart, G. C.; Waller, L. N.; Fox, K. F.; Harley, W. M.; Price, R. L. J. Microbiol. Methods. 2003, 54, 143-52. 19. Birmingham, J.; Demirev, P.; Ho, Y. P.; Thomas, J.; Bryden, W.; Fenselau, C. Rapid Commun. Mass Spectrom. 1999, 13, 604-06. 20. Arnold, R. J.; Reilly, J. P. Rapid Commun. Mass Spectrom. 1998, 12, 630-36. 21. Holland, R. D.; Rafii, F.; Heinze, T. M.; Sutherland, J. B.; Voorhees, K. J.; Lay, J. O. Rapid Commun. Mass Spectrom. 2000, 14, 911-17. 22. Vaidyanathan, S.; Rowland, J. J.; Kell, D. B.; Goodacre, R. Anal. Chem. 2001, 73, 4134-44. 23. Welham, K. J.; Domin, M. A.; Scannell, D. E.; Cohen, E.; Ashton, D. S. Rapid Commun. Mass Spectrom. 1998, 12, 176-80. 24. Easterling, M. L.; Colangelo, C. M.; Scott, R. A.; Amster, I. J. Anal. Chem. 1998, 70, 2704-09. 25. Elhanany, E.; Barak, R.; Fisher, M.; Kobiler, D.; Altboum, Z. Rapid Commun. Mass Spectrom. 2001, 15, 2110-16. 26. Hathout, Y.; Demirev, P. A.; Ho, Y. P.; Bundy, J. L.; Ryzhov, V.; Sapp, L.; Stutler, J.; Jackman, J.; Fenselau, C. Appl. Environ. Microbiol. 1999, 65, 4313-19. 27. Holland, R. D.; Wilkes, J. G.; Rafii, F.; Sutherland, J. B.; Persons, C. C.; Voorhees, K. J.; Lay, J. O. Rapid Commun. Mass Spectrom. 1996, 10, 1227-32. 28. Krishnamurthy, T.; Ross, P. L. Rapid Commun. Mass Spectrom. 1996, 10, 1992-96. 29. Krishnamurthy, T.; Ross, P. L.; Rajamani, U. Rapid Commun. Mass Spectrom. 1996, 10, 883-88. 30. Lay, J. O. Trac-Tr. Anal. Chem. 2000, 19, 507-16. 31. Lay, J. O. Mass Spectrom. Rev. 2001, 20, 172-94. 32. Ryzhov, V.; Hathout, Y.; Fenselau, C. Appl. Environ. Microbiol. 2000, 66, 3828-34. 33. Fenselau, C.; Demirev, P. A. Mass Spectrom. Rev. 2001, 20, 157-71.

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225 BIOGRAPHICAL SKETCH Danielle N. Dickinson was born in St. Petersburg, Florida on December 23, 1974. She is the daughter of Connie Putman and Si dney P. Rowe who, at 2-year intervals, provided her with two siblings, a sister, De borah Shannon Rowe; and a brother, Michael Aaron Rowe. Her father passed away in 1986, and her mother later married James W. Hancock. At Brookwood High School her fascination with science began; thanks largely to the individual guidance and encouragement she received from her AP Chemistry instructor, Dr. Pat Saulson. When she gr aduated with honors in 1992 it was no surprise that she chose to attend Embry Riddle Aer onautical University (ERAU) on a full Air Force ROTC scholarship; ostensibly provi ding the opportunity to pursue her childhood dream of becoming an astronaut. While a ttending ERAU, she was active in Alpha Xi Delta Sorority and the Future Professional Wo men in Aviation, played several intramural sports including volleyball and softball, and served as a summer-camp counselor. Unable to retain her scholarship due to a medical misdiagnosis, and unable to remain at ERAU without the scholarship, in the fall of 1994 she departed ERAU and enrolled at North Georgia College to pursu e a degree in Chemistry. There, she was a member of the state championship flag f ootball team, the Fellowship of Christian Athletes, the Baptist Student Union, Gamm a Sigma Sigma Service Sorority, Omicron Delta Kappa leadership honor society, and Phi Kappa Phi Honor Sorority. She readily became an integral part of the chemistry department. As such, she was a teaching

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226 assistant for most of the chemistry classes, and rebuilt a donated cap illary electrophoresis instrument as an undergraduate research project. She spent a summer at Clemson University in the National Science F oundation Summer Undergraduate Research Program doing inorganic chemistry resear ch under Dr. Hwu. She received her baccalaureate degree in chemistr y, Magna Cum Laude, December 12th, 1997, and was recognized as the Chemistry Departments Outstanding Graduate for academic year 1996-1997. During her senior year, she was an intern working in research and development for Ciba Vision in Duluth, Ge orgia, and post-graduation continued with them full time as a scientist in the analyti cal, formulations, and st erilization technology groups. On July 4th of 1997 she met then Marine Corporal Owen Dickinson, who was to become her husband; they wed on February 27th, 1999. She joined the analytical division of the chemistry department at the Univers ity of Florida in the fall of 1999, and began working with personnel from both the Kennedy Space Center and Jet Propulsion Laboratory (JPL). While there she received guidance from Dr. James Winefordner, Dr. David Powell and JPLs Dr. Kasthuri Venkatesw aran. She was supported in her graduate education by a NASA Graduate Student Rese arch Program Fellowship, and was also a Grinter and a Rue-Gammer Fellow. In her spare time, she enjoyed participating in intramural sports, found time to begin an annual Women in Science Conference, and served as a chapter adviser to her sororit y. She received her Doctor of Philosophy degree in chemistry in August 2004. Danielle has been awarded an ORISE postdoctoral fellowship to work in the Counterterrorism and Forensics Unit at the FBI Academy in Quantico, Virginia.


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Title: MALDI-TOFMS Based Protein Profiling as a Diagnostic Tool for the Analysis of Bacillus Spores and Cells
Physical Description: Mixed Material
Copyright Date: 2008

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Holding Location: University of Florida
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Permanent Link: http://ufdc.ufl.edu/UFE0005202/00001

Material Information

Title: MALDI-TOFMS Based Protein Profiling as a Diagnostic Tool for the Analysis of Bacillus Spores and Cells
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0005202:00001


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MALDI-TOFMS BASED PROTEIN PROFILING AS A DIAGNOSTIC TOOL FOR
THE ANALYSIS OF Bacillus SPORES AND CELLS















By

DANIELLE NICOLE DICKINSON


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


2004

































Copyright 2004

by

Danielle Nicole Dickinson



























For my inspiration.
My grandfather, the smartest man I have ever known. You are my light and my strength,
and are always in my heart. Shine on.

And for my biggest fan.
My mother, for everything she has sacrificed and for making me into who I am. I can't
thank you enough.


"I am not bound to win, but I am bound to be true. I am not bound to succeed, but I am
bound to live up to what light I have"-Abraham Lincoln















ACKNOWLEDGMENTS

It is difficult to know where to begin to thank all of the people who made my

graduate career worthwhile and helped to make my dissertation project possible. I ask

them to forgive me ahead of time for the length and breadth of this list but I want an

opportunity to thank everyone.

I must start first with the three whom I consider my cochairs, regardless of whether

UF recognizes them as such: Dr. James D. Winefordner, Dr. David H. Powell, and Dr.

Kasthuri Venkateswaran.

I thank Dr. Winefordner for his faith and courage in taking me under his wing and

allowing me to go "willy-nilly" on a project that was somewhat beyond the scope of his

repertoire of work. His enthusiasm and love for science I will forever try to imitate. I

thank Dr. Powell, aka the leader of the mass spectrometry orphanage. His patience, love,

kindness, and guidance will never be forgotten, and neither will "dark matter." I thank

him for allowing me the privilege to work in his facility and with his instrumentation. I

don't know if he realizes what a true friend and mentor he is for us in both science and

life. And I do apologize for the ambulance ride I took him on. I don't think many

advisors have had to endure a ride like that! In thanking Venkat, I don't even know

where to begin! This project came as far as it did thanks to him. I don't know if he even

realizes its impact in the mass spectrometry arena and without his microbial guidance and

spores it would have never happened. I thank him for having the patience to turn an









analytical chemist into a microbiologist, for never giving up on me, and for the constant

supply of wit and banter.

I must pause to thank the funding sources, scarce as they seemed sometimes! I

thank the NASA Graduate Student Research Program for 3 years of support on this

project; and the Planetary Protection and Biotechnology Group at the Jet Propulsion

Laboratory for all the funding they provided.

I owe much gratitude the people in the Biotechnology and Planetary Protection

Group at the Jet Propulsion Laboratory and the contacts I have made through them. I

thank Karen Buxbaum for having the faith to bring me out again after a rather interesting

first round. I thank Wayne, Roger, Cecilia, Shirley, and Gayan for their help and

guidance the first summer I was there. I thank Mike Kempf for providing some of the

first spore samples we worked on and for his help in learning the ropes of making spores

myself. Most especially I thank Myron LaDuc, a guy with some of the most interesting

personality quirks I have ever encountered. Turning an analytical chemist into a

microbiologist was not an easy task, but he did it patiently, as long as we could listen to

Dave and not my "hillbilly" music. I am honored to call him a colleague and friend. I

thank Dr. Adam Driks at Loyola University for the spore coat mutants ofB. subtilis and

for being such a great wealth of knowledge on spore coats and sporulation procedures.

My last trip to California would also not have been possible without a free place to camp

out for 8 weeks. I thank 'Nay and Alicia for opening their home to me and for taking me

out on the town. It was surreal and crazy to live in "Hollywood" for a time. I especially

thank them for not being too scared when "the geek" was wandering around the house

muttering things to herself!









At Kennedy Space Center (KSC), I also send thanks to Drs. Ray Wheeler, Jay

Garland, Mike Roberts, and Langfang Levine, who were always willing to listen, give

advice, and get me passes onto KSC where I got to run around like a kid in a candy store

(oh I don't think they were supposed to know that).

Back on the UF front, there are also a lot of great people and resources that deserve

an abundance of praise. First and foremost I thank Kenny, aka the Bruker Reflex II. He

might be old, but he works like a charm when he's in a good mood, and the picture of

Kevin in the crown is present. Long live the BK crown! I thank the electronics and

machine shop guys, who are incredible. In the end, they are the only reason Kenny

stayed in a good mood for any length of time. I apologize to Steve for still being unable

to translate the schematics. Big thanks go to all the support staff (Bev, Maribel, Beth,

Lisa, Gracie, Jill, Jim, Joe, Darrius, and Matt) in the department for their help and

encouragement along the way. They are the backbone that keeps this place going. I

cannot forget my three favorites, Jeanne, Lori, and Romaine. On many days that I don't

know what I would have done without their help and laughter. They have kept me going

and tried their best to keep me on the straight, narrow, and focused path (and yes I know I

am not good at it). I thank them tremendously for it all.

On the technical side, I had a great deal of assistance at UF as well. Dr. Jodie

Johnson, Dr. William Haskins, and Regina Wolper helped with the HPLC analysis. Igor

Gornushkin developed the linear correlation software and library searching algorithms

that were used. Scott and Stan in the protein core helped me get through my lengthy

database searches. Dr. Denslow offered extremely helpful discussions on proteins and

allowed me to use the instrumentation and database search tools in the ICBR. I thank









Danielle Anderson and Qian Li for taking some SEM images of the spores. Stephanie,

Greg, and Nicole offered helpful discussion on microbiology and gel electrophoresis. Dr.

Rasche, initially took on the task of turning me into a microbiologist and provided me

with an incubator I could use in my lab for cell growth. Her faith in me and constant

encouragement have were a source of inspiration on many a frustrating day. She was so

willing to give me time and assistance, both in the lab and out, and I can't thank her

enough for what it has meant to me and the respect I have for her because of it.

Last but certainly not least, I thank all of my family for putting up with me while I

came on this journey. Most especially I thank my husband Owen, for he by far has dealt

more with my graduate school blues than anyone else. I thank him for being there and

for just being himself and for not running for the hills, despite my temperament during

this tenure. I thank Owen's family, Martin and Lonna. I am so blessed to have them as a

second set of parents. I also thank PaJ, Dick, and the Sallys, for their endless

encouragement and praise; it has helped me press on, each step along the way. And I

thank little Ms. Lindsey for being a source of spiritual inspiration for me whether she

knows it or not.

I also thank all my family who has taught me the perfected art of putting the fun in

dysfunction. I thank Mom, Jim, Deb, and Mike for believing in me and for making the

journey all the more interesting, even while having no idea where I was heading. I love

them more than they know or that I have had time to show over the last few years. My

Mom is the strongest, most stubborn person alive and I am proud to be just like her. Jim,

for his wisdom and guidance over the years I am deeply indebted. Mike, keep up the

good work bro, you will get here one day too. To the greatest cook in the US, my sister









Debbie, I am so proud of you, cooking is much more difficult than chemistry and you a

doctor of Pi. E. in that area! And to the rest of my family, Grandma and Grandpa, June,

Judy, Don, Cindy, and Heather, I thank them for their love and support. I also have to

step back a few years and thank Dr. Pat Saulson, Dr. Brad Herbert, and Dr. Karen Sentell

for steering me down this path. They are the greatest of mentors.

Graduate school was made more pleasant by the presence of many good friends and

colleagues. I thank the members of the Winefordner group, past and present, for your

friendship. I thank my fellow orphans in the mass spec laboratory and Lydia and Jodie. I

will miss the entertainment and excitement of working in the orphanage with them; it has

been such a treat! I remember starting in the MS lab a lost soul. Then one at a time I got

all these sisters and a brother to work with. I hope I have inspired them as much as they

have inspired me. No more spore talks or blue cupcakes! Gabby, Chad, Kelly, Danielle,

Tracy, Kristen, Romaine, Lori, Lani, and Violeta all made my bad days good, and my

good days better, for that I can't thank them enough.

If there is anyone I have arbitrally left off, I thank them from the bottom of my

heart.
















TABLE OF CONTENTS

page

A CK N O W LED G M EN T S ....................................................................... iv

LIST OF TABLES .................. .......................................... ...... ........xiii

LIST OF FIGURES .................. ............................. ....... ........ ....... ........ xv

ABSTRAC T ............. ............. ................ .......... xviii

CHAPTER

1 IN TR O D U C T IO N ..................................... ................................................................ 20

The Genus Bacillus............... ...... .. .... ...... ..................... ......... ......... ....21
Spore Architecture and Com position............................. ................... 23
Sporulation and Germination.........................................25
M icrobial Identification and Classification ............................... ..................... .. 27
Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry
(MALDI-TOFMS) .................... ............. .. .................. 28
MALDI-TOFMS for Bacterial Fingerprinting ................. .....................29
Research Overview............. ... ................32

2 OPTIMIZATION OF MATRIX AND SOLVENT CONDITIONS FOR THE
EXTRACTION OF PROTEINS FROM SPORES...................................34

M materials and M methods ............................................................36
Chem icals and Reagents.............................................................. .............36
Sample Preparation and M ass Spectrometry .....................................................37
Results and Discussion ............................................... ..... .. .38
Initial Studies..................... .............. ........ 38
Acidic Modifier ........................................ .........39
Organic M odifier ................... ........... .. ........ .......... ... ............ 50
Detergent Additives ................................... ............... .. .. ......... 54
Characteristics of Optimized Solvent Extraction System .................................56
Limit of Detection Study for MALDI Spore Preparations..............................57

3 SPECIES DIFFERENTIATION OF A DIVERSE SUITE OF Bacillus SPORES
AND CELLS WITH MASS SPECTROMETRY BASED PROTEIN PROFILING.60


Characteristics of Optimized Solvent Extraction System ..................................56
Limit of Detection Study for MALDI Spore Preparations...............................57

3 SPECIES DIFFERENTIATION OF A DIVERSE SUITE OF Bacillus SPORES
AND CELLS WITH MASS SPECTROMETRY BASED PROTEIN PROFILING.60









In tro d u ctio n .................................................................................. 6 0
M materials and M methods ....................................................................... ..................6 1
B acterial Strain s......................................................6 1
Sporulation of Bacillus isolates ................................ ......................... ....... 62
Preparation of Vegetative Cells.............. ................................... ................... 63
Sample Preparation for M ass Spectrometry ................................. ............... 63
M ass Spectrometry Analysis ....................... ........................... 64
Spectral Processing and Statistical Methodology....................................65
R results and D iscu ssion ............. ....................................................... ... ....... ....67
Incidence of Spore-Forming Microbes from Spacecraft Associated
Environm ents ................................................... .......... .. ............... 67
Molecular Phylogeny of Spore-Forming Microbes..............................67
M ALDI-TOFM S Spore Profiles...................................... ........................ 69
M ALDI-TOFM S Vegetative Profiles....................................... ............... 76
C conclusion ............. ................................................................................. 9 1

4 MALDI-TOFMS COMPARED WITH OTHER POLYPHASIC TAXONOMY
APPROACHES FOR THE IDENTIFICATION AND CLASSIFICATION OF
B acillus p um ilus SP O R E S ................. .............. .............. ....................................... 93

Introdu action ..................................................... .. .........................................93
M materials and M methods ....................................................................... ..................95
B acterial Strain s......................................................95
Sporulation of Bacillus isolates .................................. ............... ............... 95
V egetative C ell G row th ............................................................ ............. .96
M etabolic profiling .................. ......................... ....................... 97
16S rDN A and gyrB sequencing ........................................ ...... ............... 97
DN A-DN A hybridization ..............................................................................97
MALDI-TOFMS protein profiling.......... ................................98
Statistical processing of MALDI-TOFMS profiles................ ........... .......99
R e su lts .......... ... ................ ...... ... ....... ..................... ................ 9 9
Metabolic fingerprinting of B. pumilus strains.............................................99
16S rDN A and gyrB sequencing ............................................ ............... 100
D N A -D N A hybridization ............................ ................................ ............... 101
MALDI-TOFMS protein profiling of spore samples ................................102
MALDI-TOFMS Protein Profiling of Vegetative Cells.............. ............... 109
Discussion ........................ ..........................110
Conclusion ................ ......... ..................... ........ .... ..... ........ 116

5 MALDI-TOFMS PROTEIN PROFILING OF Bacillus aiun/ati i--cereus-
tiini iugie' ii s GR OU P SPORE S .................................... ........................... .......... 117

Introdu action ................................................................................................ ..... 117
M materials and M methods ................................................................. .. .................... 119
B a cterial S train s ................................................................................. 1 19
Sporulation of Bacillus Isolates ................. .. ..............119
Preparation of V egetative C ells........................................................................ 120


x









Fatty Acid Methyl Ester (FAME) Analysis...........................................121
MALDI-TOFMS Protein Profiling.......................................... ..............122
Statistical Processing ........ .............................. ............ ...... .......... 122
Results ............. .................... ...................................124
Sporulation of Bacillus Isolates ................. .. .............. 124
FA M E A analysis ....................................................... .............. .................. .. 124
MALDI-TOFMS Protein Profiling of BACT Spores.....................................125
MALDI-TOFMS Protein Profiling of BACT Vegetative Cells......................141
D discussion ............ .... ................................................................ 149
C onclu sion .................................................................................... .. 153

6 PEPTIDE PROFILING AND BIOMARKER IDENTIFICATION FOR
SELECTED Bacillus SPECIES........................................... ......................... 156

In tro du ctio n ................................................................................................ ..... 15 6
M materials and M methods ........................................... ....................................... 159
B acterial Strain s .............................................. ....................159
Protein Extraction and D igestion.................................................................... 159
Peptide profiling .................. ............................ .. .... .............. ... 160
1-D G el Electrophoresis ............................................................................. 160
P roteom ic A naly sis.......... ........................................................ ...... .... 16 1
R results and D discussion .............................................. ... .... ........... .... 162
P ep tid e P ro filin g ......... ......................................................... .... .. .................... 16 2
1-D Gel Electrophoresis .................................. ...... ...................... 163
Proteomic Analysis for Biomarker Identification ..........................................166
C o n clu sio n s.................................................... ................ 17 6

7 IMPACT OF ENVIRONMENTAL FACTORS AND STERILIZATION ON
THE MALDI-TOFMS PROTEIN PROFILE OF SPORE SPECIES.......................178

Introdu action ................................................................................................ ..... 17 8
M materials and M methods ......................................... ... ...................................... 180
MALDI-TOFMS Protein Profiling and Statistical Analysis...........................180
B bacterial Strains ........................................ ................. ........... 180
Standard Sporulation in Liquid Media ...................... ........ ................181
Sporulation on Solid M edia................................................................... ...... 18 1
Spore Purification .................. ............................. .. .. .... .. ........ .... 182
Storage Conditions and A ging.................................... .................................... 182
R radiation E exposure ....................... .. ...................... .... .... ........... 182
Hydrogen Peroxide Exposure...................................................................... 183
A utoclave Exposure.............................. .. ......................................... 184
Preparation of B. subtilis Sporulation Mutants....................... ............. 184
R results and D discussion ............. ...... .... ........ ........ ............... .. ............. 185
Initial Sporulation and Purification Conditions.....................................185
Storage Conditions and Spore Aging ..................................... ............... 187
R radiation E exposure ..................... .. .... .................. .... .... ...............190
H 202 Exposure .............. ........ ........... .... ....... ...... 193









Autoclave Exposure........................................ ....... 195
Sporulation M utants .................................................. .............................. 202
Conclusion ........................ ..................... .... 211

8 CONCLUSIONS AND FUTURE WORK .........................................................213

L IST O F R E F E R E N C E S ...................... .. ............. .. ..................................................2 17

BIOGRAPH ICAL SKETCH ...................................................... 225
















LIST OF TABLES


Table p

3-1. List of Bacillus species used in this study ...................................... ............... 62

3-2. 16S rDNA sequence similarities for the various Bacillus species studied ..............68

3-3. Correlation values based on MALDI-TOFMS protein profiling of the spores of
the B acillus species in this study ...................................................................... .. 74

3-4. Correlation values based on MALDI-TOFMS protein profiling of the vegetative
cells of the Bacillus species in this study ........................................................... 83

3-5. Correlation values based on MALDI-TOFMS protein profiling of vegetative
cells of select Bacillus species incubated on three different growth media .............85

4-1. Strain designation, grouping, and source of Bacillus species in this study ..............96

4-2. DNA-DNA hybridization of B. pumilus isolates..................................................... 101

4-3. Linear correlation values obtained when comparing the Bacillus species library
with the B. pumilus strains in this study ...... ......... ...................................... 103

4-4. Correlation results based on MALDI-TOFMS protein profiles of the B. pumilus
spore strains in this study ............................................... ............................ 104

4-5. Correlation results based on MALDI-TOFMS protein profiles of selected
B. pum ilus vegetative cells in this study ..................................... ............... ..109

5-1. List of B. cereus serotype strains .................... ..... ................................. 120

5-2. Results of FAME analysis for selected BACT strains .........................................125

5-3. MALDI-TOFMS correlation values for BACT spore strains versus the type
strain reference library using 30% formic acid as a solvent.............................. 132

5-4. MALDI-TOFMS correlation values for BACT spore strain library using 30%
form ic acid as a solvent .................. .. .......... .. ................... .... 133

5-5. MALDI-TOFMS correlation values for BACT spore strain library using TFA
as a solvent ............... .. ..... ................... .......... 139









5-6. MALDI-TOFMS correlation values for BACT vegetative cells versus the
vegetative type strain reference library using30% formic acid as a solvent ..........146

5-7. MALDI-TOFMS correlation values for BACT vegetative cells using 30%
form ic acid as a solvent......... ....................................................... ............... 147

5-8. DNA:DNA Hybridization values of the BACT strains examined in this study......149

6-1. Correlation values based on the peptide profiles.........................................163

6-2. Proteins identified from B. subtilis 168 using CLC-MS2 .....................................167

6-3. Proteins identified from B. licheniformis using CLC-MS2 ................................. 171

6-4. Proteins identified from B. ithin iigie'\i\, using CLC-MS2................................. 171

6-5. Proteins identified from FO-11 using CLC-MS2 ............................................171

6-6. Proteins identified from FO-36b using CLC-MS2................................. ...........172

6-7. Proteins identified from SAFN-036 using CLC-MS2........................................172

6-8. Proteins identified from SAFN-029 using CLC-MS2..........................................173

6-9. Proteins identified from SAFR-032 using CLC-MS2................................ .....173

6-10. Proteins identified from B. pumilus 7061 using CLC-MS2 ................................174

7-1. List and description of strains used in this study................................ ...............181

7-2. Correlation values for aged spores and spores stored under different conditions...188

7-3. Correlation values for mutated B. subtilis strains....................................................206
















LIST OF FIGURES


Figure page

1-1. Transmission electron microscopy image showing typical spore architecture. ........24

1-2. Sporulation and germ nation cycle.......................................... ....... ............... 26

2-1. Comparison of TFA versus formic acid. ......................................... ...............40

2-2. Form ic acid extraction effect .................................. ............... ............... 41

2-3. Comparison of different matrix compounds and 17% formic acid modifier. ...........42

2-4. Signal-to-noise versus solvent for calibration mix. ................................................44

2-5. Signal-to-noise versus solvent for the B. subtilis 168 spore suspension .................45

2-6. Signal-to-noise versus formic acid concentrations from 10 to 60% for
B su b tilis 16 8 .................................................................... .. 4 7

2-7. Spectra showing enhancement of biomarker signal for B. subtilis 168 when
increasing form ic acid concentration.. ........................................ ............... 48

2-8: 1-D Gel showing the effects of increasing formic acid concentration on extraction of
proteins from B. subtilis 168 spores...................................................................... 49

2-9. Signal-to-noise versus formic acid concentrations from 10-60% for FO-36b
sp o re s ......................................... .. .. ............................................. .5 1

2-10. Spectra showing enhancement ofbiomarker signal for FO-36b spores when
increasing form ic acid concentration.. ........................................ ............... 52

2-11. Signal-to-noise versus formic acid concentrations: organic modifier effects.........53

2-12. Treatment of spores with OGP detergent. .................................... .................55

2-13. Treatment of spores with Rapigest detergent. ................... .................58

2-14. Limit of detection for B. subtilis 168 spores. .................................. .................59

3-1. MALDI-TOFMS protein profiles of 14 Bacillus spore species...............................71









3-2. Correlation results of the 20 individual B. atrophaeus ATCC 9372 spectrum. ........77

3-3. Correlation results of the 20 individual B. subtilis 168 spectrum. .........................78

3-4. Visualization of the spectra in-line with the dendrogram for 14 Bacillus species....79

3-5. MALDI-TOFMS protein profiles of the 14 Bacillus vegetative cells.......................81

3-6. Visualization of the spectra in-line with the dendrogram for the vegetative cells. ...84

3-7. MALDI-TOFMS protein profiles of B. uh/I//l/I. i% 34F2 vegetative cells on
different growth media. .................................................. ......... 87

3-8. MALDI-TOFMS protein profiles of B. subtilis 168 vegetative cells on different
growth media. ................. ... ......... ....... ......... 88

3-9. MALDI-TOFMS protein profiles of B. thuringiensis ATCC 10792 vegetative
cells on different grow th m edia................................... .................. 89

3-10. MALDI-TOFMS protein profiles of B. pumilus 7061 vegetative cells on
different growth media. .................................................. ......... 90

4-1. MALDI-TOFMS protein profiles of the B. pumilus type strain group spores......105

4-2. MALDI-TOFMS protein profiles from selected spores in the FO-36b cluster. ....106

4-3. MALDI-TOFMS protein profiles comparing B. pumilus ATCC 706 T, FO-36b
and the tw o outlier strains. ............................................. ............... 107

4-4. Dendrogram and visualization of the B. pumilus spore strains. ...............................108

4-5. MALDI-TOFMS protein profiles of the B. pumilus type strain group vegetative
cells............................................................. ...............11

4-6. MALDI-TOFMS protein profiles of the FO group vegetative cells. ......................112

5-1. Average spectra from the BACT spores using 30% formic acid as a solvent. ......126

5-2. Clustering and visualization of the BACT spores obtained using 30% formic
acid as a solvent....................................... ............................ ......... 134

5-3. Average spectra from the BACT spores using 5% TFA as a solvent....................135

5-4. Clustering and visualization of the BACT spores protein profiles obtained using
TFA as a solvent ............... ................................. ....... ........................... 140

5-5. Average spectra from the BACT vegetative cells using 30% formic acid as a
solvent. ....................................................... 142


cells using 30% formic acid as a
solv ent. ............................................................................ 142









5-6. Clustering and visualization of the BACT vegetative cells using formic acid as a
solv ent. ............................................................................ 14 8

6-1. Peptide profiles obtained for Bacillus species.................................... ...............1. 64

6-2. 1-D gel electrophoresis for 6 Bacillus strains ...................................... .................. 165

6-3. Comparison of the protein profile of the cotT protein using a cotT mutant............ 169

7-1. MALDI-TOFMS protein profiles of aged FO36b spores.....................................189

7-2. MALDI-TOFMS protein profiles of B. subtilis 168 spores under different
storage conditions.................. .............. .. ..... ..............191

7-3. MALDI-TOFMS protein profiles of 1 month old FO36b spores under different
storage conditions .......... .. ..... ................... ...... ...... ......... .... 192

7-4. MALDI-TOFMS protein profiles of UV treated B. subtilis 168 spores.................. 194

7-5. MALDI-TOFMS protein profiles of H202 vapor treated B. subtilis 168 spores.....196

7-6. MALDI-TOFMS protein profiles of H202 vapor treated B. pumilus 7061 spores.. 197

7-7. MALDI-TOFMS protein profiles of H202 vapor treated FO36b spores...............198

7-8. MALDI-TOFMS protein profiles of H202 liquid treated B. subtilis 168 spores.....199

7-9. MALDI-TOFMS protein profiles of H202 liquid treated B. pumilus 7061 spores..200

7-10. MALDI-TOFMS protein profiles ofH202 liquid treated FO36b spores...............201

7-11. MALDI-TOFMS protein profiles of autoclaved B. subtilis 168 spores...............203

7-12. MALDI-TOFMS protein profiles of autoclaved B. pumilus 7061 spores.............204

7-13. MALDI-TOFMS protein profiles of autoclaved FO36b spores...........................205

7-14. MALDI-TOFMS protein profiles of B. subtilis sporulation mutants...................207

7-15. MALDI-TOFMS protein profiles of the cells of the B. subtilis spore coat
m utants at T6 .........................................................................208

7-16. MALDI-TOFMS protein profiles of the spores of the B. subtilis spore coat
m utants at T24 ........................................................................210















Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

MALDI-TOFMS BASED PROTEIN PROFILING AS A DIAGNOSTIC TOOL FOR
THE ANALYSIS OF Bacillus SPORES AND CELLS

By

Danielle Nicole Dickinson

August 2004

Chair: James D. Winefordner
Major Department: Chemistry

This research focuses on the development of Matrix-Assisted Laser

Desorption/Ionization Time-of -Flight Mass Spectrometry (MALDI-TOFMS)-based

protein profiling as a rapid diagnostic tool to detect and discriminate microbial species.

MALDI-TOFMS is well suited for this task because of its rapid analysis time (<1

minute), low sample requirement, sensitivity, reproducibility, and resolving power.

Analysis of whole bacterial cells and spores with this technique has given rise to unique

"protein fingerprints" that can be used for identification at the species and strain level.

Identification can be accomplished by using statistical algorithms to find the best match

in a database containing fingerprints from previously analyzed bacterial species. The

diversity found within bacterial species and the effects of environmental conditions on

protein profiles from identical strains have proven to be a challenge for the statistical

analysis of the spectra. To this end, we have sought an understanding of the variability in

the protein profiles among strains of the same species and have evaluated the factors


xviii









affecting the expression and extraction of the proteins used as biomarkers. Systematic

evaluation of these factors is crucial for bringing this technology into fruition as a viable

diagnostic tool for microbial analysis.

We have demonstrated the versatility and efficacy of MALDI-TOFMS protein

profiling for bacterial identification by examining over 50 different spore strains of

Bacillus, the most diverse study of the genus reported to date. A one-step sample

treatment and MALDI-TOFMS preparation was designed to obtain spectra rapidly with a

wide range of protein biomarkers, including several higher molecular weight (10-25 kDa)

protein species not reported in other MALDI spore preparations. Linear correlation

analysis, hierarchal cluster analysis, and spectral visualization were used to identify and

catalog all Bacillus spores evaluated. To validate the use of MALDI-TOFMS protein

profiling for species and strain differentiation, result of the protein profiling were

compared with 16S rDNA sequences and DNA:DNA hybridization for their bacterial

systematics and molecular phylogenetic affiliations. The effect of strain variation and

environmental conditions (such as age, storage conditions, and exposure to radiation and

sterilization) were examined to facilitate identification of invariant and omnipresent

biomarkers in the spectra. The biomarkers needed for species delineation were targeted

for further proteomic identification.














CHAPTER 1
INTRODUCTION

This research focuses on the development of matrix-assisted laser

desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) protein

profiling as a rapid diagnostic tool for identification of bacteria and bacterial spores.

Analysis of whole bacterial cells and spores with this technique gives rise to unique

"protein fingerprints" that can be used for the identification at the species and strain level.

Identification can be accomplished by using statistical algorithms to find the best match

in a database containing fingerprints from previously analyzed bacterial species. The

algorithms have been tested with both a large diversity of bacterial species and strains

and by the effect of environmental conditions on the resulting spectra of identical strains.

To this end, we have sought an understanding of the variability in the protein profiles

among strains of the same species; evaluated the factors affecting the expression and

extraction of the proteins used as biomarkers; and identified omnipresent genus-, species-

and strain-specific protein biomarkers. The systematic evaluation of these factors is

crucial for bringing this technology into fruition as a viable diagnostic tool for microbial

analysis.

Our interest in investigating this technology is two-fold. The primary interest

stems from the fact the Bacillus spores are the major source of contamination found in

spacecraft assembly facility (SAF) clean rooms. The planetary protection requirements

of space missions destined to contact the surface of other planets require technologies for

validating decontamination processes and archiving the bioburden of flight hardware and









facilities. These technologies must be sensitive, accurate, rapid, and cost-effective, and

must be able to provide an "organic signature" of the organism that could allow scientists

to distinguish it as "forward contamination" in the search for extraterrestrial life. The

MALDI-TOFMS methodology developed here provides one possible answer to these

challenges, and could record in the form of a protein fingerprint, the microbial diversity

associated with space missions. Our more general interest is in rapid, sensitive, and

selective microbial detection and identification at the species and strain level, which is a

necessity for the differentiation of viable pathogenic and nonpathogenic microbial

species. The development of technologies that accomplish this level of distinction would

have a significant impact in the areas of occupational and health care, homeland defense,

and environmental monitoring.

The Genus Bacillus

The genus Bacillus is one of the largest and most ubiquitous genera of bacteria

containing 65 valid species, with new species continually being described.1 The type

species of Bacillus, Vibrio subtilis was first described by Ehrenberg in 1835 and was

renamed Bacillus subtilis in 1872 by Cohn. The genus has become the graveyard for all

aerobic or facultatively anaerobic, spore-forming, rod-shaped bacteria. Taxonomic

characterization and systematics of Bacillus have been an area of great debate for over a

century. The genus has been classified into six RNA groups based on 16S rDNA

sequence similarity, spore morphology, spore position in the mother cell, and the

presence or absence of mother cell swelling during sporulation.2 The genus has gained

notoriety with taxonomists for its extreme phenotypic diversity and heterogeneity. As a

result, this is one of the most animated areas in systematic bacteriology studies.









Most Bacillus species are regularly encountered and cultivated from soil samples,

their primary habitat, from which they can contaminate anything. Bacillus species are

particularly important in the medical, veterinary, military, and industrial fields. They are

probably most noted for their negative effects, which include food spoilage, clean room

contamination, biodeterioration, and causing various infections and foodborne illnesses in

humans and many animals. The most infamous member is B. anthracis, the bioterrorism

agent that causes anthrax. Although notorious for the negative effect they can have on

human health in particular, Bacillus species possess redeeming qualities. They are rich

sources of extracellular enzymes (such as proteases and amylases); of peptide antibiotics

such as bacitracin; and of insecticides such as the widely used toxins from the species

such as B. iti/n ingie'n\i\ and B. popilliae.2

The most distinguishing characteristic of the genus is the ability to produce a

resistant endospore. The spore is formed within the mother cell in response to nutrient

deprivation and can be oval, spherical, or cylindrical. Spores are highly resistant to

agents such as heat and radiation, and cannot be easily destroyed even by harsh chemical

treatment, disinfectants, or desiccation.1'3 The increased resistance of spores, although

not completely understood, has been partly explained by the impermeability of the spore

coat, dehydration of the core, and the protective proteins that bind to the DNA. In the

metabolically inert spore form, these bacteria can remain dormant for hundreds of

thousands of years. Within the spore the essential macromolecules (and a variety of other

substances) are stored until conditions become favorable for survival; at which point they

are triggered to return to an active vegetative state. The resiliency they exhibit enables









the genus to be ubiquitous in the environment, a common source of contamination,

sterilization resistant, and an ideal bioterrorism agent.13

Spore Architecture and Composition

A closer look at the spore shows significant differences in the composition and

location of many biomolecules when compared to a vegetative cell. The cell wall of a

gram-positive vegetative cell is characterized by a rigid layer of peptidoglycan. This

layer is relatively easy to penetrate, either through the use of enzymes such as lysozyme

(which breaks the 1,4-glycosidic bonds in the peptidoglycan), or by extreme changes in

osmotic pressure or pH. Vegetative cells are also susceptible to desiccation, heat,

radiation, and sterilization.

The spore, in comparison, is more complex with several outer layers that are

believed to contribute to its increased resistance. Spore species may contain an outermost

layer called the exosporium (Figure 1-1A). All species contain a spore coat, typically

comprising an inner and outer layer (Figure 1-1A, B). The exosporium and spore coat

are mainly comprised of proteins and glycoproteins. The cortex, a peptidoglycan layer

similar to that found in a vegetative cell, is the next layer of the spore. Within the cortex

is the dehydrated spore core. The core contains the same parts as the vegetative cell

(including the cell wall, cytoplasmic membrane, ribosomes, and DNA). A high

concentration of a calcium-dipicolinic acid complex is present in the core of all spores.

Bound to the DNA (and unique to spores) are proteins known as small acid soluble

proteins (SASPs), which protect the DNA against damage from radiation, desiccation,

and dry heat.4





















Cor
Iw~r


,sc


0 .r'


Figure 1-1. Transmission electron microscopy image showing typical spore architecture.
A) B. odyssey PTA-4993 which contains an exosporium (EX). B) B. subtilis
168 which does not contain an exosporium. The core, cortex, and spore coat
(SC) are shown for both spore species.


1~-- .









Sporulation and Germination

Sporulation occurs in a series of stages (0, II, and III-VII) that can be monitored by

phase contrast microscopy. A pictorial representation of the sporulation and germination

stages is shown in Figure 1-2. The end of exponential growth is considered time 0 for

sporulation, and occurs when the cells reach stage II and the cell divides into two

asymmetric compartments, each with its own chromosome. The larger division is termed

the mother cell or sporangium; the smaller compartment is the forespore. In stage III and

IV, the forespore becomes engulfed by the mother cell, the peptidoglycan cortex layer is

deposited on the outside of the developing spore, and the SASPs are synthesized within

the forespore. During stage V and VI, the spore coat proteins are deposited and the spore

reaches maturity with a full arsenal of resistances. Finally, the mother cell lyses,

releasing the mature spore during stage VII. This results in the appearance of phase-

bright refractile bodies which are observed when using phase contrast microscopy. The

entire process of spore formation takes 6-8 hours.57

When nutrients are returned to the medium, the spore undergoes a process called

activation, whose mechanism is not well understood. Germination begins within minutes

and can be characterized by a rehydration of the spore core, release of cations and

dipicolinic acid, degradation of the SASPs by the germination protease protein (GPR),

and the loss of refractility and resistance. Later in germination, the cortex undergoes

hydrolysis followed by metabolism and protein synthesis. This is followed by outgrowth,

when emergence and elongation occur, during which normal cell division resumes and

the coat remnants are discarded. The time for completion of this process is under 1.5

hours.5-7























ACTIVATION
GERMINANTS LGRMINATION OUTGROWTII SYMMETRICA
------- DIVISION
SWELLING MERCENCE EL.ONC.ATION

FREi SPORE VEGETATVE
PHASE BRIGHT ELL

NUTRIENT
LYSIS OF CELL DEPRIVATION
SPORULATION

ASYMMWTRKCAL

STAGE I
MATURATION COATFORMATION CORTEX FORMATION ENGULFMENT
STAGE VI STAGE V STAGE IV STAGE HI


Figure 1-2. Sporulation and germination cycle.









Microbial Identification and Classification

"The biologist is attuned to the vagarities of living things and does not expect an
experiment to be exactly repeatable ... is surprised by the expected and astounded
by the fulfillment of a forecast of prediction. The bacteriologist must never forget
that genera and species are artificial concepts and that the bacteria show no interest
in their classification"-Sam Cowan, 1978

When developing technology for the identification of microbial species,

consideration should be given to the biological system itself, the processes it can

undergo, and the chemicals and biomolecules available for analysis. One of the most

challenging aspects of any biological system (in analytical terms) is its almost constant

potential for change and adaptation. Analytical chemists strive for reproducibility,

specificity, selectivity, and detection limits. Traditional analytical approaches are not

attuned to dealing with "biological flux" or the vast expanse of diversity that can exist.

To be successful, we must do what is less traditional, and accept that biological samples

have "a mind of their own." The definition of a successful biological analysis may or

may not concur with traditional analytical measures of success.

Traditional techniques for the characterization and identification of microorganisms

have relied on lengthy biochemical, nutritional, and physiological testing. Often these

tests are inconvenient to prepare and perform, difficult to standardize and interpret, and

can be challenging to reproduce.8-10 Modern techniques for microbial classification and

identification have focused on the development of chemotaxonomic and molecular-based

methods. These techniques can be classified broadly as genotypic or phenotypic.

Examples of genotypic techniques include PCR-based analysis, DNA hybridization,

genetic fingerprinting, direct sequencing, and nucleic acid probing. Fatty acid methyl

ester analysis, pyrolysis mass spectrometry, whole-cell protein profiling via gel

electrophoresis or mass spectrometry, antibody-based methods, and various miniaturized









test kits for determining biochemical and nutritional requirements are examples of

phenotypic techniques.8-10

Genotypic methods are faster and are usually more reliable than traditional

biochemical methods, though they have drawbacks, including the stability of

consumables, availability of specific probe sequences, and the associated cost and time

required for gene sequencing. Commercially available identification kits and other newly

developed technologies, mentioned above for phenotypic analysis, have the advantage of

speed and convenience when compared to most traditional methodologies, but still

require an incubation period and may have difficulties associated with reproducibility.

Protein expression, metabolic profiles, and fatty acid profiles can fluctuate dramatically

based on environmental and nutritional variables during different stages of growth.8-10

Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry
(MALDI-TOFMS)

MALDI-TOFMS has become an essential tool for analyzing a wide array of

biomolecules, particularly proteins. The explosion in genomic and proteomic research in

the past two decades has placed high demands on instrumentation and techniques for

analysis. MALDI-TOFMS has become a primary player in both of these arenas due to its

high throughput, sensitivity (femtomole range for most proteins), and handling of

complex biological samples.

In MALDI-TOFMS, a solid organic matrix compound is dissolved in an

appropriate solvent and combined with a protein sample solution. A small volume

(typically 0.5-3.0 [iL) is spotted on a stainless-steel target plate and allowed to dry. The

target is placed (via a probe) into the vacuum chamber of a time-of-flight mass

spectrometer. The sample is irradiated with a pulsed laser, resulting in the desorption and









ionization of the analyte molecules. The laser is most often a nitrogen laser which

produces photons in the ultraviolet range (337 nm), although infrared lasers are also used.

The matrix acts as the vehicle to desorb and ionize the sample molecules with little or no

fragmentation. The matrix molecules absorb most of the energy from the photons, and

vaporize to form an expanding plume that carries the sample molecules into the gas

phase. Ions are accelerated by an electrostatic potential (V) to a certain velocity (v) and a

total kinetic energy (E). The ions traverse a field-free drift region where they are

separated based on differences in their velocity. A channel electron multiplier detects the

ions. The time-of-flight of the ions is recorded and converted to a mass-to-charge ratio,

using the TOF relationship:

2Vt2
m /z = 2V--
L2
where t = time, L = length of flight tube, z = charge, V = accelerating voltage, and m =

mass of the ion.11 To increase the resolving power of the time-of-flight mass

spectrometer, a reflectron can be added to focus the kinetic energy of the ions. The

reflectron is most effective at relatively low masses, and is more frequently used for

peptide analysis below 4 kDa.

MALDI-TOFMS for Bacterial Fingerprinting

MALDI-TOFMS has demonstrated great promise for interrogating microbial

species and for identifying proteins using comparative and clinical proteomic

approaches.11-14 Microbial analysis with MALDI-TOFMS dates back to the late 1980s.15

Many groups have demonstrated the versatility of this technique, from analysis of cell

lysates to whole-cells to the analysis of PCR products.16 MALDI-TOFMS is well-suited

for this task due to its rapid analysis time (<1 min/sample), low sample requirements,









sensitivity, and resolving power. Analysis of whole bacterial cells and spores with this

technique has given rise to unique protein fingerprints that can be used for identification

at the species and (at times) strain level.16-33 All of the studies rely on the growth and/or

sporulation of cells in the laboratory; none are sampled directly from the environment.

Vegetative cells generally produce a relatively large number of biomarker proteins that

can be used for subsequent pattern recognition or correlation analysis. However, the

proteins expressed in vegetative cells are dynamic, and can vary dramatically based on

cultural conditions. In contrast, extraction of proteins from spores has been more

challenging, providing only a limited number of biomarker peaks when compared to their

vegetative counterparts.

The spore associated biomarker peaks detected using MALDI-TOFMS with a UV

laser are reported in the range of 3-10 kDa. Various sample pretreatments including the

use of infrared (IR) laser irradiation,34-37 corona plasma discharge,19,26 sonication,26 and

the addition of 5% trifluoroacetic acid (TFA)34 or 1M HC1,38 have been used on spores to

increase the number and intensity of biomarkers observed in the spectra. These methods

have had some success; however, in most cases, these treatments require longer sample

preparation times and visualization of peaks above 10 kDa is still limited. Fenselau et

al.39 reported detection limits as low as 5,000 cells/spot; however, only a single protein

biomarker was reported. Most conventional MALDI-TOFMS bacterial research has

focused on species differentiation without the identification of protein biomarkers, and

therefore, the ability to extract strain-specific and pathogen-specific biomarkers has not

been thoroughly investigated. In the case of spores, recent studies have identified a

limited number of biomarker peaks as SASPs; however, these proteins alone do not allow









for differentiation at the species level. This is evident in the case of B. thuringiensis and

B. cereus.3,40

In addition to the direct MALDI-TOFMS analysis of whole spores, various groups

have recently been engaged in full-scale proteomic analysis of B. lllb/l I/. i.37,41 and B.

subtilis37'42 using one or two-dimensional gel electrophoresis in conjunction with

MALDI-TOFMS or liquid chromatography mass spectrometry. While these extensive

studies improve our understanding of the spore coat and allow for limited species

comparisons, they are very time consuming and have not been applied to other Bacillus

strains. These studies are also limited to species with sequenced genomes.

Published studies show that MALDI-TOFMS of whole bacterial spores is feasible

and of practical value, lending speed and higher accuracy to the analysis. MALDI-

TOFMS for microbial analysis provides a rapid, relatively simple analysis that is

amenable to all species, and is not reliant on previous knowledge of DNA sequences or

antibody interactions. MALDI-TOFMS protein profiling is well-suited for high

throughput and automation, requires minimal sample preparation, has superior

reproducibility, and has much higher resolution than gel-based techniques.

To prove MALDI-TOFMS fingerprinting as a useful technology for bacterial

identification, the technique must be able to rapidly differentiate and identify genus-,

species-, and strain-specific biomarkers over a wide variety of spores. More importantly,

it must be able to identify biomarkers that can differentiate pathogenic strains from

nonpathogenic strains. To this end, this research was performed on over 50 species,

including 21 type strains and 25 wild-type environmental isolates, and 17 B. cereus

serovars. To our knowledge, this is the largest collection of Bacillus spores ever









evaluated with MALDI-TOFMS protein profiling. This large collection of Bacillus

affords us several advantages. First, it allowed elucidation of the protein differences that

are present at both the species and strain level. Second, it allowed evaluation of the

reliability of the biomarkers over a wide range of isolates. Third, it allowed for the

determination of the level of distinction needed to differentiate pathogens from other

similar nonpathogens that are of the same or related species. This highly specific level of

discrimination is required to differentiate nonpathogenic strains (B. allm/1IL/ i\ Sterne)

from pathogenic strains (B. alin////// i% Ames). These biomarkers allowed rapid

identification of proteins as targets for molecular probes and other biosensors that are

field-portable, robust, small, and both sensitive and highly specific. This could decrease

the time and cost of identifying targets for sensor-based counterterrorism systems.

Research Overview

This body of research begins with a description of the optimization of the

conditions for the extraction of proteins from spores. Using the optimized extraction

conditions the research moved into the analysis phase where over 50 different spore

species were analyzed. Chapter 3 addresses the successful differentiation of 11 different

Bacillus species, the most diverse study of the species to date. This chapter also

describes in detail the statistical processing of the spectra using linear correlation and

hierarchal cluster analysis. The effect of strain variation within a species is addressed in

Chapters 4 and 5 and the criteria for including a strain within a species using linear

correlation were established. Chapter 4 deals specifically with using MALDI-TOFMS

protein profiling in a polyphasic taxonomy approach for the identification and

classification ofB. pumilus isolates. MALDI-TOFMS protein profiling proved to be

more accurate than metabolic profiling and was complementary to gyrB sequencing and









DNA hybridization for the identification of these isolates, which included the possible

identification of a new species of Bacillus. Chapter 5 tackles the differentiation of the B.

auhI/lnt i,-B. cereus-B. thuringiensis (BACT) group spores and cells. This is the first

investigation of a wide variety of BACT group bacteria (20 strains) with MALDI-

TOFMS protein profiling where the results are compared directly with genetic analysis

for their bacterial systematics and molecular phylogenetic affiliations.

The next portion of the research focused on the identification of the protein

biomarkers that were found to be species specific in the studies outlined in Chapters 3-5.

MALDI protein extracts from several Bacillus species were analyzed by tandem mass

spectrometry techniques to obtain peptide mass tag data in Chapter 6. The first report of

the identification of coat proteins from a MALDI extract is included for the B. subtilis

168 strain in the study. For organisms that did not have sequenced genomes most of the

proteins identified are SASP associated due to the high sequence conservation among

these proteins, although some surface associated proteins are identified in several B.

pumilus species. The final chapter, Chapter 7, addressed the effect of environmental

exposures on Bacillus spores and demonstrated that species specific biomarker peaks

were maintained over most of the conditions analyzed. The additional information

provided by the appearance and disappearance of other peaks in the spectra was shown to

be useful for source tracking, forensic investigations, and epidemiological studies.














CHAPTER 2
OPTIMIZATION OF MATRIX AND SOLVENT CONDITIONS FOR THE
EXTRACTION OF PROTEINS FROM SPORES

Matrix and solvent selection is a critical factor in the success of MALDI-TOFMS.

Selection of matrix compounds is empirical and must be evaluated for each application.

Solvent systems for MALDI must balance the organic and aqueous phase to maintain

solubility of both the matrix and sample, and must optimize crystal formation. An acidic

modifier must also be present to maintain a pH less than 4 to promote crystallization of

the matrix in the free acid form. The number, quality, and intensity of peaks in a MALDI

spectrum can also be affected by the matrix compound, the solvent, and the acidic

modifier chosen for the analysis. Both the enhancement and suppression of peaks have

been observed in MALDI by changing various components.

The selection of the solvent system in the case of spores is complicated by the

presence of a wide range of hydrophobic and hydrophilic proteins in the exosporium, coat

layers, and core of bacterial spores, as well as by the rigidity and chemical resistance of

the spores. Two main families of proteins are present in spores at relatively high

concentrations: the SASPs and the spore coat proteins.

SASPs have recently been evaluated as biomarkers for the identification of spores.

Targeting the SASPs requires that the spores be disrupted, allowing for the release of

SASPs from the spore core. This is accomplished by using high concentrations of strong

acids, such as trifluoroacetic acid (TFA) and hydrochloric acid, to lyse open the spore.

Post release, the SASPs are digested with trypsin and are identified using post-source









decay or ion-trap technologies. Although this approach has allowed for identification of

SASPs that are species-specific, it is limited to the species that have sequenced genomes,

and it fails to differentiate closely related species such as B. cereus and B. thuringiensis

effectively.32'38'40 This failure is likely due to the high level of sequence homology

among the SASP proteins. The spore coat proteins have not been identified in any direct

whole-cell analysis experiments. They possess a high level of sequence divergence,

which should allow for higher levels of discrimination. To effectively extract and

analyze the spore coat proteins, it is necessary to target mainly hydrophobic proteins. On

average, 75% of the known proteins located in the spore coats are hydrophobic.43 In

addition, it would be ideal to use a gentle extraction scheme that would not lyse the spore

open during treatment, releasing SASP proteins that would dominate the spectra.

Spores are more resilient and difficult to destroy than vegetative cells, making it

difficult to design an efficient protein extraction scheme. Most of the published MALDI-

TOFMS spore spectra have used a mixture of acetonitrile/water with various

concentrations of TFA.25-27'32'38 Components used to analyze vegetative cells are far

more varied, with past studies using a-cyano-4-hydroxycinnamic acid (HCCA), ferulic

acid, and sinapinic acid with a variety of solvents including ethanol, isopropanol, and

acetonitrile.16'20'27'29'31,33,44,45 Voorhees et al. 46 and Chait et al.47 recommended using a

mixture of 17% formic acid, 30% acetonitrile, and ferulic acid to enhance the high mass

signal in whole-cell analysis. This mixture has also been shown to be more tolerant of

salts and surfactants, an important factor when considering possible contamination from

using crude cell samples. Procedures for analyzing hydrophobic proteins also regularly

employ the use of a detergent additive to increase the solubility of the proteins.4851









Detergents typically used include low levels of sodium dodecyl sulfate (SDS), Triton X-

100, and octylglucoside. However, various studies show that adding detergents can have

negative impacts on the MALDI signal.52

The goal of this research was to develop a simple, one-step extraction protocol that

provides for the maximum availability of biomarkers for analysis. To this end, we

systematically evaluated the extraction of proteins from spores by MALDI-compatible

solvents. Several common MALDI matrices, acidic modifiers, and organic solvents for

analysis spores were evaluated. Detergent additives were also examined as a method of

increasing the number of biomarkers extracted from the spore coat. Spectra generated

were evaluated based on the following criteria: signal-to-noise ratio, number of

discernable peaks, molecular weight range, suppression effects, reproducibility, and

homogeneity of crystal formation. The limits of detection of the optimized extraction

system were also investigated.

Materials and Methods

Chemicals and Reagents

The evaluated MALDI matrices, purchased from Sigma Chemical Co. (St. Louis,

MO), included sinapinic acid (SA), ferulic acid (FA), dihydroxybenzonic acid (DHB),

and a-cyano-4-hydroxycinnamic acid (HCCA). All matrices were used as received

except HCCA. The HCCA was further purified by preparing a saturated solution of

HCCA in warm ethanol, to which 3 parts water was added. The solution was allowed to

stand at 40C overnight. The HCCA precipitate was then filtered and the matrix was

allowed to dry in a desiccators.

Organic solvents used included acetonitrile (ACN), methanol, ethanol, and

isopropanol. All solvents were HPLC grade from Fisher Scientific Co. (Fairlawn, NJ).









Trifluoroacetic acid (TFA) was from Sigma-Aldrich Chemical (St. Louis, MO).

Aldehyde-free formic acid was obtained from Fisher Scientific Co. (Fairlawn, NJ). The

two detergents evaluated included N-octylglucoside (OGP) from Sigma-Aldrich

Chemical Co. and the acid labile Rapidgest from Waters (Milford, MA). Cytochrome C,

myoglobin, bovine serum albumin (BSA), and insulin were used in calibration mixtures

and were purchased from Sigma-Aldrich Chemical Co.

The spore suspensions used for analysis were provided by the Biotechnology and

Planetary Protection Group at the Jet Propulsion Laboratory. Three strains were used in

the extraction protocol development: B. subtilis 168, B. pumilus 7061, and the wild-type

FO-36b, which has been putatively identified as B. pumilus. All spore suspensions were

between 1 x 108 and 1 x 109 spores/mL. The spores were stored in sterile water at 40C

before use.

Sample Preparation and Mass Spectrometry

Saturated solutions of the MALDI matrices (typically 10-20 mg/mL) were prepared

in the selected solvent system for analysis. Unless otherwise indicated, standard dried-

droplet sample preparation was used to prepare the MALDI spots for analysis. The

optimum ratio for mixing was found to be 10 parts matrix to 1 part sample, where the

initial concentration of spores was 1 x 10 to 1 x 109 spores/mL. The spore suspension

was premixed 1:10 with the matrix solution and 1 [iL of the resultant solution was spotted

on the MALDI plate. Samples were allowed to air dry, and no further treatments were

applied to the spot post deposition.

MALDI analysis was performed on a Bruker Reflex II TOFMS (Bruker Daltonics,

Billerica, MA) retrofitted with delayed extraction. The instrument uses a pulsed nitrogen

laser (337 nm) for ionization. Ions were collected in the linear mode and were detected










with a HIMASSTM detector (Bruker Daltonics, Billerica, MA). An acceleration voltage

of 20 kV was used in conjunction with a 50 ns delay time. For deflecting matrix and

other low molecular weight ion signals, a deflector was set at 2,000 Da. All spectra were

obtained by the accumulation of 50 laser shots in positive mode. A three point external

calibration was performed daily using either a mixture of insulin, myoglobin, and BSA;

or insulin and the doubly and singly charged ions of cytochrome C.

Results and Discussion

Initial Studies

Initial studies focused on the use of sinapinic acid as a matrix compound. Sinapinic

acid was typically used in combination with 0.1% TFA and 30% ACN for the analysis of

proteins. When this combination was applied to the B. subtilis 168 spores in this study,

very few biomarkers were observed (Figure 2-1A). Changing the acidic modifier to 17%

formic acid had a profound effect on the spectrum, increasing the observable number of

biomarker peaks from 6-8 barely discernable peaks to approximately 15 well-resolved

peaks (Figure 2-1B).

Because the addition of formic acid increased the organic content of the solvent

system, a 50% ACN/ 0.1% TFA solvent was also evaluated (Figure 2-2A) and

demonstrated little improvement over the previous TFA solvent system (Figure 2-1A).

The spectrum in Figure 2-2B represents an analysis where a 0.1%TFA/50% ACN solvent

was first deposited and allowed to dry. A mixture of the spore sample with 10 parts 17%

formic acid/30% ACN was deposited on top of the matrix layer. This gave a similar

spectrum to the premixed dried droplet approach used above (Figure 2-1B), indicating

that the effect of the formic acid is likely an enhancement in protein solubility more than

an effect of the mechanics of the MALDI deposition.









Using the 17% formic acid/30% acetonitrile solvent system as a "base solvent,"

several matrix compounds other than sinapinic acid were evaluated. All matrix

compounds were dissolved in the base solvent. DHB, unlike the other 2 matrices, was

water soluble, and was also tested in 17% formic acid/83% water. Representative spectra

from each matrix are shown in Figure 2-3. Ferulic acid (not shown) gave an identical

spectrum to the sinapinic acid, and the effects of these 2 matrices will be discussed

separately. When compared with DHB and HCCA, sinapinic and ferulic acid matrices

gave higher signal-to-noise ratios and the largest range of biomarkers. The higher

molecular weight proteins were not evident in the DHB samples (Figure 2-3B and C).

However, the 17% formic acid/83% water sample (Figure 2-3C) highlighted additional

biomarker peaks found in the 5-10 kDa range.

Acidic Modifier

To further characterize the discrepancy between the two matrix solutions a study

was performed to evaluate the effects of the acidic modifier on the resultant MALDI

spectra. The following solvent systems were prepared:

* 30% ACN, 70% 0.1%TFA (pH=1.90)
* 30% ACN, 53% H20, 17% formic acid (pH=1.56)
* 30% ACN, 55% H20, 15% formic acid (pH=1.58)
* 30% ACN, 60% H20, 10% formic acid (pH=1.67)
* 30% ACN, 65% H20, 5% formic acid (pH=1.82)

Sinapinic acid and ferulic acid were dissolved in each of the solvent systems. A

calibration mixture (CM-IMB) was prepared containing insulin, myoglobin, and bovine

serum albumin at concentrations of 15, 100, and 100 pmole/iL, respectively. A 1 iL

aliquot of the calibration mixture was mixed with 24 [iL matrix solution. The calibration

mixture was used to ascertain suppression effects that do not result from differences in







40














A) Sinapinic Acid in 0-1% TFA/ 30% ACN











I 4S i


a.i.



3000



2000 -



1000



0



a.i.





10000





5000


15000


B) Sinapinic Acid in 17% Formic Acid/ 30% ACN


Il? ?3


1O09.2O1


10000


14212 31
c.c t
*^^-


15000


Figure 2-1. Comparison of TFA versus formic acid. A) B. subtilis 168 spores in 0.1%
TFA/30% acetonitrile. B) B. subtilis 168 spores in 17% formic acid/30%
i acetonitrile.


10000


5000


20000


5000


20000















a. i.
A) Matrix and Sample Spot Sinapinic Acid in 0.1% TFA/50%0 ACN
1500



1000


6945,21
500 i, g ? 6



0 1 1
5000 10000 15000 20000

B) Matrix Spot Sinapinic Acid in 0.1% TFA/50% ACN
a.i. Sample in 17% Formic/30% ACN


6000
7751.3]


4000

3J888.70 ;
2000 116.53 110,7 15557.39
I T *lJ I / 9 74 11356.' 1162 5.

0 j F I
cnnn I Annrcnn nAft
Figure 2-2. Formic acid extraction effect. A) B. subtilis 168 spores in 0.1% TFA/50%
ACN dried droplet preparation. B) 0.1% TFA/50% ACN matrix layer applied
first followed by deposition ofB. subtilis 168 spores in 17% formic acid/30%
acetonitrile.





















T II l% 11 lI I T
III U A r l


A) Sinapinic Acid in 17% Formic Acid/30% ACN


fT llll-l
-1- T


5000 10000 15000 20000 25000

B) DHB in 17% Formic Acid/30% ACN




I II I
5000 10000 15000 20000 25000


SiC) DHB in 17% Formic Acid/83% H20


A TI l j


5000 10000 15000 20000 25000

D) HCCA in 17% Formic Acid/30% ACN

ll .11

TT


5000


10000


15000


20000


25000


Figure 2-3. Comparison of different matrix compounds and 17% formic acid modifier.
A) Sinapinic acid in 17% formic acid/30% ACN B) DHB in 17% formic
acid/30% ACN C) DHB in 17% formic/83% water D) HCCA in 17% formic
acid/30% ACN









extraction efficiency. Each sample (CM- IMB and B. subtilis 168) was spotted in

triplicate on the MALDI plate. The signal-to-noise ratio was determined for peaks of

interest in each spectrum. In the CM-IMB spectrum, the three peaks of interest were at

masses 5,734, 16,952, and 66,432 Da. In the spore spectrum, the peaks of interest were

the biomarker peaks at 3,950, 6,648, and 7,760 Da. Data analysis was performed by

averaging 3 spectra per spot and obtaining the standard deviation within the spot. The

signal-to-noise values from each of the samples were averaged and the standard error was

calculated. The resulting data can be seen in Figure 2-4 for the calibration mix and

Figure 2-5 for the spore samples. The plots are of the signal-to-noise versus solvent

composition for each peak of interest in the spectra.

Sinapinic acid gave higher signal-to-noise ratios overall except in the case of high

molecular weight proteins like BSA. The solvent system 30% ACN, 70% 0.1%TFA

produced superior results for the calibration mix in both matrices; however, neither

produced significant signals from the spore sample. In contrast, both matrices produced

superior signals for the spore biomarkers when dissolved in the 30% ACN, 53% H20,

17% formic acid solvent system. For both matrices, the biomarker signal detected

decreased as the percent formic acid was decreased in the solvent mixture. In the formic

acid series, there was a decrease in signal for all the proteins in the calibration mix as the

percent formic acid increased. These results were in opposition to the spore samples, as

signal increased with increasing formic acid. These trends suggested the formic acid aids

in the extraction of proteins from the spore coat.




















A) S vs SdountirCarMauln Iax M Smawlc Add IbhM

500- m BSA

450 m Myogtobin

40M O Insulin

3500

3000 -


200 -
2000






50

01%TFA 5% Furic 10% Funic 15% Fnnic 17% Funic
Solwent
B) I wvs Soleatlor cafrom IbK i FemLCAcTd AbiM

D 1 w BSA

450D0 M Myogl bin

D u- o insulin

3500 -

3100 -





1500 -

000 -

500 -


D.1%1FA 5% Funic 11% Funic 15% Funic 17% Funic


Figure 2-4. Signal-to-noise versus solvent for calibration mix. A) Sinapinic acid matrix.
B) Ferulic acid matrix. The solvents, from left to right in each graph are 0.1%
TFA, 5% formic acid, 10% formic acid, 15% formic acid, and 17% formic
acid in 30 % acetonitrile. The error bars represent the standard error of 9
measurements.





















2000-

1800-

1600-

1400-

1200-

1000-

800-

600-

400-

200-

0


* 3875



D 7760


0 1%TFA


2000



1600

1400

1200

10o


600

400

200

0


A) SlgtUnhlsew SolWutferf Sb s 168 IWn ShMq Ac IlAlk





















5% Fomc 10% Fumei 15% Fmumc 17'


qH SM s S teolutar iB Surii 168 hu Fen lcAcdd Ih


I Fanic


B 3950

* 6648

D 7760


0.1%TFA 5% Fornic 10%Fonnic 15% Fnnic 17% Fmuic
Sohert
Figure 2-5. Signal-to-noise versus solvent for the B. subtilis 168 spore suspension with
varying acidic modifier concentrations. A) Sinapinic acid matrix. B) Ferulic
acid matrix. The solvents, from left to right in each graph are 0.1% TFA, 5%
formic acid, 10% formic acid, 15% formic acid, and 17% formic acid in 30 %
acetonitrile. The error bars represent the standard error of 9 measurements.


mm









Because increasing the formic acid concentration seemed to increase the extraction

efficiency of the protein biomarkers from the spores, higher concentrations of formic acid

were investigated. The percentage of acetonitrile was kept at 30% while the percent

formic acid was increased from 10 to 60%. The results are shown in Figure 2-6 for both

sinapinic and ferulic acid matrices. Sample spectra from the sinapinic acid samples for

each concentration are shown in Figure 2-7. Higher concentrations of formic acid (30 to

40%) enhanced extraction, giving rise to higher molecular weight biomarkers (> 15 kDa)

not seen at lower concentrations. This observation was supported by a 1-D gel

electrophoresis studies (Figure 2-8) where bands emerged at higher molecular weights

with increasing formic acid concentrations. However, MALDI spectral quality declined

as formic acid concentrations above 30-40% were used. This decline was attributed to

inhomogenieties in crystal formation; as the solvent became more hydrophobic, crystal

homogeneity suffered due to spreading of the spot.

Using formic acid as a modifier resulted in spectra with higher signal-to-noise

ratios and a significantly greater number of biomarker peaks. The visualization of these

higher molecular weight proteins has not typically been seen in other MALDI-TOFMS

analyses of whole spores.25'26'34'35'38 When comparing the two matrices, sinapinic acid

clearly was advantageous due to enhanced signal-to-noise ratios. However, the ferulic

acid matrix produced spots which were more reproducible. Since the long term goals of

this project deal with the statistical treatment of spectra, reproducibility was a critical

factor in the success of this methodology. Therefore, signal-to-noise was sacrificed in

exchange for better reproducibility and the ferulic acid matrix was used in all subsequent

studies.
























S/N vrsus Formic Add Concentration: Matrix Comparison


I
'~ 3U10 -
a


*Ferulic

* Siuaiciii


0 I-


10%Foiuc


20%Fosmh


3fl%FouiC


40%Foic


6r/.FUIoiC


% 10tc

Figure 2-6. Signal-to-noise versus formic acid concentrations from 10 to 60% for the m/z
7,760 peak from B. subtilis 168. Ferulic acid is shown in blue and sinapinic
acid is in red. The error bars represent the standard error across 9
measuremests.


















B suhli is
^-__k-^_____




^----- -^-^J -Jv ^^__ _


60 % Formi c


40% Formic


30% Formic


20% Formic




1 % Formic

4000 6000 8000 10000 12000 14000 16000 18000 m/z


Figure 2-7. Enhancement in biomarker signal for B. subtilis 168 by increasing formic
acid concentration. From top to bottom, B. subtilis in 60%, 40%, 30%, 20%,
10% formic acid. The scale is from m/z 2,000-20,000. Note the emergence of
higher molecular weight proteins as formic acid concentration increased.


a. i



30000



25000



20000 -



15000


10000 -



5000 -



0 -



30000


25000


20000


15000


10000


5000


0 -






49








Nbs Aceuonlie Mehand

75 I
50 .,r-


259

20

15 0 _. C









S0 3 0, C C3 0 0 3 0 C C
EE E Ei E E E E E E E
aw LL LL- LL. LL- L ap LL- LL- Ll_ Ll_ LL_
o o o o o o o
0 r 4 (W i) D 0 r 4 ) t VI WD
Figure 2-8: 1-D Gel showing the effects of increasing formic acid concentration on
extraction of B. subtilis 168 spores compared to SDS solublized extract. This
is shown for 2 organic solvents, 30% acetonitrile and 30% methanol.









The higher formic acid concentrations also had a significant impact on the

biomarkers that were extracted, possibly due to differences in the hydrophobicities of the

proteins. This was highlighted when analyzing the FO-36b spore sample. As formic acid

concentration increased, the biomarker peak at 7,620 peak was favored over the 7,250

peak (Figure 2-9 and 2-10). This peak was one of the few peaks that differed between

spores of FO-36b and B. pumilus 7061 and was critical for differentiation of these two

strains.

Organic Modifier

The effect of the organic solvent was also investigated. The acetonitrile

preparation was compared with methanol, ethanol, and isopropanol. A range of formic

acid concentrations was studied with each of the different solvents. Similar results were

obtained for all three of the spore lines evaluated. A graph of the results for B. subtilis

168 is shown in Figure 2-11 for methanol and isopropanol with acetonitrile for

comparison. Results with ethanol were nearly identical to those with isopropanol and are

not shown in the graph. Overall, the effect of the organic modifier on the spectra was

minimal. Similar trends were noted for the formic acid concentrations as seen with ACN

before. The signal increased for samples with up to -30% formic acid, and then

decreased again due to poor MALDI spot formation at higher formic acid concentrations.

Methanol shows an advantage in signal-to-noise ratio but, as indicated by the error bars,

didn't give results as reproducible as when acetonitrile was used. Isopropanol and

ethanol were very similar to acetonitrile in signal-to-noise, although the MALDI spots

were less reproducible and tended to spread over the plate. Therefore, acetonitrile was

generally used as the organic solvent in our studies.








51













Signal to-oise viess Foxmic Comantration FI36b

2000- 15428

1800 7255
O 7618
1600 O 9606

1400 -



1000 -
14OO









400 -

200


10%Fonmk 20%FFonnk 3 Fd 40 Foi 60%Fonde
% Fomm
Figure 2-9. Signal-to-noise versus formic acid concentrations from 10-60% for 4
biomarker peaks from FO-36b spores. Feru the ord was used as a matrix and
30% acetonitrile is the organic solvent. The error bars represent the standard
error of 9 measurements.















35000


30000


25000


20000





10000


5OOO-
5000


20% Formic Acid


30% Formic Acid


YJL


40% Formic Acid


60% Formic Acid


5nnn innnn innn 2nnnn 2nnn innnn snnn in
Figure 2-10. Enhancement in biomarker signal for FO-36b spores by increasing formic
acid concentration. From top to bottom, FO-36b in 20%, 30%, 40%, and 60%
formic acid. Each spectrum is displayed from m/z 2,500-40,000. At 20%
formic acid the 7,250 Da peak is the base peak in the spectra. As the formic
acid concentration increased to 30% and higher, the 7,620 Da peak became
the base peak in the spectra.


C-I-r-~-~-~--W -~'-- Lr-~--LL-~- -~-LI---. i~- ---L--.-L-y~__


Y- -------5-~ --1 ---. -------r-- -----~------- -- ---
-I L ---- I-


- --11--11- -_1_~1.-_-


j L








53











SigmaI-to-moise Trv s Forni Cocatration: OiMauc Modifer Efects
6000- AC
U ACN

MeOH
5000-
O IPA

4000





2000-


1000-



10YFomic 2M0Fonmc 30%Faomk 40%Fomic 60Faomic
% Fonic
Figure 2-11. Signal-to-noise versus formic acid concentrations: organic modifier effects.
Comparison of acetonitrile (ACN), methanol (MeOH), and isopropanol (IPA)
as the organic modifier in the MALDI solvent using B. subtilis 168 as the
sample.









Detergent Additives

Detergent additives were also examined as a mechanism for increasing the number

of biomarkers extracted from the spores. Two MALDI compatible detergents were

examined, N-octylglucoside (OGP) and the acid labile Rapigest. Sodium dodecyl sulfate

(SDS) was not evaluated as a detergent additive because MALDI compatible

concentrations of SDS are less than 0.01%. During the purification of a spore

preparation, 0.05% SDS was used to clean the spores and did not disrupt the spore coat

proteins.7 Therefore, lower concentrations of SDS would have no effect on protein

solubilization. A 0.1% TFA/50% ACN solution was used as the matrix solution instead

of formic acid in order to ascertain whether it was the detergents which improved

solubilization,.

OGP was added directly to the matrix solution at concentrations ranging from

0.425-68 mM. Figure 2-12 shows sample spectra from B. subtilis 168 spores treated with

0.1%TFA/50% ACN matrix preparation alone in A, and with increasing OGP

concentrations of 13.6 mM OGP added in B, and 68mM OGP added in C. Spores treated

with a 30% formic acid/30% acetonitrile solvent are shown for comparison in D. OGP

enhanced the extraction of proteins from the spores as indicated by the higher signal-to-

noise in the spectra with OGP added. However, even with the highest level of OGP, this

enhancement was still lower than the formic acid treatment (D). The OGP also did not

allow for the detection of the higher molecular weight peaks in the spectra.

Rapigest was also evaluated at a concentration of 0.1% and was used per the

manufacturer's instructions. This involved boiling the spore sample in the detergent and

then adding 50 mM hydrochloric acid to degrade the Rapigest. As a control, a spore

sample in water was also boiled and added to the formic acid matrix. The Rapigest



















ai, A) B. subtilis 168 spores in 0-1% TIFAI5% ACN


2000 *




B) B. subidi 168 spores in 0- 1% TFA/50% ACN with 13 6 mM OGP







a -i C)B. subtilis 168 spores in 0-1% TFA/50% ACN with 68 mM OGP


5000




SD)B. sRbtils, 168 spores in 300 formic acid/ 30% ACN

loooo T 2



Figure 2-12. Treatment of spores with OGP detergent. A) B. subtilis 168 spores in 0.1%
TFA/50% ACN. B)B. subtilis 168 spores in 0.1% TFA/50% ACN with 13.6
mM OGP. C) B. subtilis 168 spores in 0.1% TFA/50% ACN with 68 mM
OGP. D)B. subtilis 168 spores in 30% formic acid/30% acetonitrile. The
OGP improved extraction from the spores; however the formic acid treatment
was still superior.












treatment significantly altered the visible biomarkers spectra (Figure 2-13, top). The

dominating biomarker became the 9,130 peak, which had not been previously observed.

This spectrum is similar to that obtained when concentrated TFA or HCI treatments were

used to lyse spores for SASP extraction, and these peaks correspond to the molecular

weights of the major SASPs in B. subtilis 168. Since Rapigest required degradation with

high acid concentrations prior to analysis, the SASPs would be expected to dominate the

spectra. In the formic acid matrix, the boiled spores gave rise to an even higher

molecular weight protein at -43 kDa that had not been previously discernable, indicating

that a boiling step might aid in the solubilization of additional proteins.

Characteristics of Optimized Solvent Extraction System

The best combination of solvents evaluated for the analysis of spore was a 30%

formic acid/30% ACN solvent system with ferulic acid as the matrix. This solvent

system represented a compromise between signal-to-noise, reproducibility, and the

availability of a wide range of low and high molecular weight biomarkers for analysis.

Higher formic acid concentrations allowed for the extraction of higher molecular weight

proteins; however, inconsistencies in the MALDI spot formation were detrimental to

analysis. At a concentration of 30% formic acid, the MALDI spot formation was

homogeneous and consistently gave a good crystal layer for the analysis. This treatment

was rapid and did not require any additional sample preparation or spot treatment. It was

also relatively inexpensive in comparison to the use of detergents such as Rapigest and

OGP.

Unlike other sample preparation procedures, such as treatments for SASP

extractions, in which the spores were not viable post-treatment, the B. subtilis 168 and

FO-36b spores in our studies remained viable for up to 1 hour in 30% formic/30%









acetonitrile. After 1 hour in the solvent there was a 2 decade reduction in growth. In

contrast, spores from B. pumilus 7061 were affected by the formic acid treatment and

there was a 2 decade reduction in growth after only 10 minutes of treatment. The

difference in viability between the three spore strains might be explained by differences

in the permeability of the spore coats by the MALDI solvent. This could also be a result

of storage conditions and storage times.

Limit of Detection Study for MALDI Spore Preparations

Although a limit of detection for bacterial cells has been reported in the literature

(5,000 cells/spot), no comprehensive study has been compiled. To assess a more realistic

limit of detection for whole-cell analysis of spores by MALDI, an experiment was

designed to determine the minimum number of spores necessary to obtain useful spectra.

Obtaining a useful spectrum depends on a number of factors including the signal-to-noise

ratio and the number ofbiomarker peaks discernable in the spectrum. Dilutions of the

spore suspension were made in water and the resulting solutions were mixed with the

ferulic acid matrix described above. Figure 2-14 is an overlay of the spectra collected for

the spore sample at each of the dilutions in the series. The results from the spore samples

show a drastic decrease in spectral information very early in the dilution series. Nearly

all spectral information is lost when there are fewer than 50,000 cells on the spot. The

peak at approximately 7,760, the most abundant biomarker for the spores, remains barely

discernable at 5,000 cells/spot; and no other peaks are seen in the spectrum. The ability

to identify the spores at lower concentrations will be dependent on the statistical

approaches used.

















a.i.

1500


1000


500


0



d.i.


A) B. subtilis 168 spores (boiled) with Rapidgest in 0.1% TFA/50% ACN


5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 m/z


1 B) B. subtilis 168 spores (boiled) in 30% formic acid/ 30% ACN


Li


5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 m/z
Figure 2-13. Treatment of spores with Rapigest detergent. A) B. subtilis 168 spores in
boiled with Rapigest and analyzed in 0.1% TFA/50% ACN matrix solvent. B)
B. subtilis 168 spores boiled in water and analyzed in 30% formic/ 30% ACN.
The Rapigest treatment resulted in the release of SASP proteins from the
spores. With the additional boiling step, a 43 kDa protein was also extracted
with the formic acid treatment.


- 0 OYM -- P 1%- %. M E-% .0 kA, ^ '. m M .^.^^ OM I ^* *^
























7000

6000

5000 100,000 cells/spot
4 4000J 50,000 cells/spot
w A_ 10,000 cells/spot
3000 0 5,000 cells/spot
2000 1,000 cells/spot

1000 -500 cells/spot
S100 cells/spot

0 5000 10000 15000 20000 25000
m/z
Figure 2-14. Limit of detection for B. subtilis 168 spores. The dilution series runs from
100,000 cells/spot to 100 cells/spot. At 5,000 cells/ spot the 7,760 Da
biomarker is barely discernable in the spectra.


rely discernable in the spectra.














CHAPTER 3
SPECIES DIFFERENTIATION OF A DIVERSE SUITE OF BACILLUS SPORES AND
CELLS WITH MASS SPECTROMETRY BASED PROTEIN PROFILING

Introduction

In order to overcome the problems involved with phenotypic characterization, 16S

ribosomal RNA (16S rDNA) analysis has been used for decades to more accurately

define the phylogenetic affiliation of the given test microorganism.53 However, being

highly conserved, the 16S rDNA molecule at times cannot differentiate closely related

microbial species.54'55 Therefore, alternative biomarkers56 or a suite of protein profiling

methods would be useful to effectively differentiate closely related microbial species.

In this chapter, the versatility of Matrix-Assisted Laser Desorption/Ionization

Time-of-flight Mass Spectrometry (MALDI-TOFMS) protein profiling for the species

differentiation of a diverse suite of Bacillus cells and spores is demonstrated. MALDI-

TOFMS protein profiles of fourteen different strains of Bacillus, encompassing eleven

different species, were evaluated. Bacillus species selected for MALDI-TOFMS analysis

represented the spore-forming bacterial diversity of typical class 100K clean-room

spacecraft assembly facilities.

A majority of the MALDI-TOFMS research directed at Bacillus has focused on

only a few spore species. These include B. acui ha, i% and its closely related species B.

1/hni ingien'\i, B. cereus,55 B. atrophaeus (formally called B. globigii)57, an anthrax

surrogate, and B. subtilis, whose genome has been completely sequenced and has been

thoroughly examined by molecular biological methods.25'26'38'58 Very little research










attention has been given to other Bacillus species, which naturally occur in the

environment. The nonpathogenic Bacillus spores, which are ubiquitous in the

environment, are the most likely source of interference for any detection technique and

have the highest potential to produce false positives.

To demonstrate the versatility of MALDI-TOFMS protein profiling for the

identification of a variety of spores and cells, a subset of Bacillus species isolated from

various NASA spacecraft assembly facilities (class 10 to 100K clean rooms) was used in

this study. The optimized one-step sample treatment and MALDI-TOFMS preparation

was used to obtain spectra rapidly with a wide range of protein biomarkers, including

several higher molecular weight (10-25kDa) protein species for the spores. A library of

MALDI-TOFMS spectra was created from the 16 different spores and vegetative cells of

the Bacillus species, the most diverse study of the genus reported to date. Linear

correlation analysis was used to identify all Bacillus species evaluated. The results

obtained from MALDI-TOFMS protein profiling of these Bacillus species were

compared with 16S rDNA sequences for their bacterial systematics and molecular

phylogenetic affiliations.

Materials and Methods

Bacterial Strains

Bacillus strains used in this study and their source are listed in Table 3-1. Fourteen

strains consisting of 11 Bacillus species were studied. The type strains ofB. atrophaeus,

B. licheniformis, B. megaterium, B. mojavensis, B. 1/thn iiigie'n\i, B. pumilus, and B.

subtilis were procured from the American Type Culture Collection (ATCC, Manassas,

Virginia). B. subtilis 168 was received from Wayne Nicholson, Univ. of Arizona and the

B. (auhi ,I/ i\ 34F2 vaccine strain was from M. Satomi, National Institute of Fisheries,










Japan. B. odyssey, B. licheniformis KL-196, B. niacini 51-8C, B. megaterium FO-38,

and B. psycrodurans were isolated from several NASA spacecraft and assembly facilities

surfaces. Bacterial isolation procedures from spacecraft and assembly facilities surfaces

were described elsewhere59'60. Identity of the test organisms was determined based on

16S rDNA sequencing for the environmental isolates; for the ATCC strains, those

sequences available in the GenBank database were used61. The 16S rDNA sequences of

the environmental isolates have been deposited in the GenBank nucleotide sequence

database.

Table 3-1. List of Bacillus species used in this study
Name Strain Number Source Remarks
B. anthracis 34F2 Inst. of Fisheries, Japan Vaccine strain
B. atrophaeus 9372 ATCC Surrogate to B. anthracis
B. licheniformis 14580 ATCC Most predominate species in clean room facilities
B. licheniformis KL-196 JPL-SAF Class 100K clean room floor, JPL
B. megaterium 14581 ATCC
B. megaterium FO-38 JPL-SAF Clean room air particulate
B. mojavensis 51516 ATCC
B. niacini 51-8C KSC, SAEF-II Mars Odyssey assembly facility floor
B. odyssey 34hsl KSC, SAEF-II Mars Odyssey spacecraft surface
B. psycrodurans VSE1-06 KSC, PHSF Mars Exploration Rover assembly facility air particles

Second most predominate species in clean room
B. pumilus 7061 ATCC
facilities
B. subtilis 168 University of Arizona Genome fully sequenced
B. subtilis 6051 ATCC Type species of Bacillus genus
B. s 1 2 A C Insecticide producing bacteria and phylogenetically
B. thuringiensis 10792 ATCC
unseparable from B. anthracis
Abbreviations: ATCC, American type culture collection; SAF, Spacecraft assembly facility; SAEF-II, Spacecraft assembly
and encapsulation facility-II; PHSF, Payload handling and spacecraft assembly facility; JPL, Jet Propulsion Laboratory; KSC,
Kennedy Space Center

Sporulation of Bacillus isolates

A nutrient broth sporulation medium (NSM) was used to produce spores.7'62 A

single purified colony of the strain to be sporulated was inoculated into the NSM liquid

medium. After 1 to 3 days of incubation at 32C under shaking conditions, cultures were









examined using phase-contrast microscopy to determine the level of sporulation.

Microcosms that attained >99% of spores were further purified to remove vegetative cells

or cell debris as previously reported.7 The purified spores were suspended in sterile

deionized water and stored at 40C in glass tubes until analyzed. Before the analysis, spore

suspensions were adjusted to give an optical density of 0.6 at 600 nm, which resulted in

suspensions that were between 108 to 109 spores/mL.

Preparation of Vegetative Cells

A stock culture of each Bacillus species was streaked for isolation on tryptic soy

agar (TSA) plates. B. ii/am/li i\ 34F2, B. subtilis 168, B. pumilus 7061, and B.

ihuin iigie'%\i\ were also streaked on nutrient agar (NA) plates and Luria-Bertani (LB)

plates for a study of the effect of different growth media on the spectra. The plates were

incubated at 320C for 16 hours except in the case of the media study where the plates

were incubated for 24 hours. Single purified colonies were removed from the plate with

a sterile loop and were placed in 100 [iL of a phosphate buffered saline (PBS) solution.

Most colonies were approximately 2 mm in diameter. If larger colonies were present

only a 2 mm portion was removed for washing and analysis. The cells were vortexed in

PBS for 15 minutes and then were pelleted by centrifugation for 10 minutes at 9600 x g.

The supernatant was removed and the cell pellet was used for subsequent analysis.

Sample Preparation for Mass Spectrometry

A saturated matrix solution was prepared by dissolving 20 mg of ferulic acid into a

1 mL solution of 30% acetonitrile, 30% formic acid. As described in Chapter 2, this

solvent system was selected due to the higher signal-to-noise, consistent crystallization,

and better ability to differentiate across the various bacterial species. This effect was due

to a combination of an increased number of biomarker peaks and the higher molecular










weight range of these peaks in the spectra.63'64 A 2.5 [iL aliquot of the spore suspension

(0.6 OD660) was added to 22.5 [L of the matrix solution. This mixture was vortexed

briefly and then 1 [L of the sample containing both spores and matrix compound was

removed and spotted on a SCOUT26 MALDI plate (Bruker Daltonics; Billerica, Ma).

For the preparation of vegetative cells, 25 [iL of the matrix solution was mixed directly

with the cell pellet. This solution was sonicated for 3 minutes and then vortexed for 3

minutes. A 1 [L aliquot of the vegetative sample was then placed on the MALDI plate

for analysis. Spots were allowed to air dry. No further treatments were applied to the

spots once dried. Spots were prepared in duplicate for each sample mixture. Sample

preparation required only a few minutes per sample.

Mass Spectrometry Analysis

MALDI-TOFMS analysis was performed on a Bruker Daltonics Reflex II Mass

Spectrometer (Bruker Daltonics, Billerica, Ma) retrofitted with delayed extraction. The

instrument was operated in the linear mode. A nitrogen laser (337 nm) pulsed at a

frequency of 5 Hz irradiated the sample. Spectra were obtained in positive ion mode with

a delay time of 50 ns. The acceleration voltage was 20 kV. An ion deflector was used to

deflect low mass ions that would saturate the detector. The deflector was set at 2,500 Da.

The laser intensity was adjusted to just above the threshold for ion formation for each

sample. The instrument was calibrated daily using external calibration with a mixture of

bovine insulin and equine cytochrome C. All spectra represent the accumulation of 50

laser shots. Ten spectra were collected from each spot on the MALDI plate. A total of

20 spectra were collected per sample.










Spectral Processing and Statistical Methodology

Prior to statistical analysis, each spectrum was baseline-corrected and smoothed

using a ten point Savitzky-Golay smoothing algorithm. Normalized spectra were

converted into ASCII files for statistical processing. Because linear correlation is

invariant with respect to a linear transformation of spectra, the relative, not absolute,

intensities were important for correlation analysis. Statistical analysis of the data was

performed using linear correlation software developed in house using Visual Basic

6.0.65-67 Spectra from the mass spectrometer were imported into the software as ASCII

files and libraries were created using the average of the 20 spectra collected per sample

(10 spectra per spot). Correlation analysis was performed on a point-to-point basis based

on the following equation for the Pearson correlation coefficient, r:

Z (X -x)(y y)
r= -



where x is the mean of x, 's and y is the mean of y, 's. The x, 's and y, 's are the

intensities at the i-th pixel of the detector which in this case corresponds to the m/z

(i=l....N; for the m/z range 2,500-60,000 N is approximately 16,000 points). The x, 's,

belong to an analyzed spectrum, and the y, 's belong to one of the library spectra. The

spectrum consisting of x, 's is correlated against each spectrum in the library (different

sets of y, 's) and the closest match with the highest correlation coefficient indicated a

similarity of this spectrum with the corresponding library spectrum. Conversely, the

difference between this and other correlation coefficients signified spectral

dissimilarities. To quantify the level of significance of these differences, a Student's t-









test was applied. Student t values were calculated differently depending on whether the

two distributions had the same or different variances. To check this, an F-test was

applied (F denoting the ratio of the variances) as the basis oft-values. The probabilities

that two distributions of correlation coefficients had different means were calculated.

A reference library of spores and vegetative cells, consisting of the average

spectrum created from the 20 spectra collected for each sample, was produced for all of

the fourteen species evaluated in this study. The individual spectrum and the average

spectrum obtained for each of the 14 strains were then compared to the MALDI-TOFMS

spectra stored in the library to elucidate the bacterial speciation. To evaluate the

reproducibility of the technique, a separate set of MALDI-TOFMS spectra were collected

and averaged for all of the different species of spores in this study. The averages of these

separate analyses were compared with the library spectra. To address batch-to-batch

variability, B. subtilis 168 spore cultures prepared at different times over the course of

two years were analyzed and compared to the library spectra. In the case of vegetative

cells, colonies from 3 different agar plates were analyzed to ascertain the effect of

different growth media and incubation times on the spectra.

In conjunction with the correlation analysis, hierarchal cluster analysis (HCA) was

used to help visualize and categorize the different species. The HCA analysis was

performed using the commercially available statistical software SPSS (Chicago, IL).

Dendrograms were produced based on the Pearson correlation value between the spectra

using the nearest neighbor method (single linkage). To help visualize the peak patterns

for the spectra, Surfer 8.0 from Golden software (Golden, CO) was used to create an

image map with 10 Da resolution from the average spectra for each species. The image










map provided a 3D representation of the spectra where the color of the band was

indicative of peak intensity.

Results and Discussion

Incidence of Spore-Forming Microbes from Spacecraft Associated Environments

Among several hundred aerobic spore-forming bacteria isolated from several

spacecraft and associated facility surfaces, >90% of the isolates were found to be

phylogenetically affiliated with the members of the genus Bacillus. 59-61 B. licheniformis

(25%) and B. pumilus (16%) were the most prevalent Bacillus species isolated. Since B.

licheniformis was the most prevalent Bacillus species in the environment and B. subtilis

is the type species of the Bacillus genus, multiple strains of these species were included

in this study. An additional wild-type strain of B. megaterium was included as well. To

avoid confusion about the identity of the bacterial species, wherever possible, authentic

type strains were procured from the culture collection and used. All tested Bacillus

species fall into the RNA group I except B. psychrodurans and B. odyssey, which are in

RNA group II.68,69 Group I includes aerobic Bacillus species that produce acid from a

variety of sugars including glucose and whose spores are ellipsoidal and do not swell the

mother cell. Group II Bacillus species are also aerobic; however, they do not produce

acids from sugars and even though they also produce ellipsoidal spores, they swell the

mother cell. As the Bacillus species of other rDNA groups were not isolated from class

100K clean-room facilities,59-61'70 the characterization of the species by MALDI-TOFMS

was restricted to the sixteen members of these two rDNA groups.

Molecular Phylogeny of Spore-Forming Microbes

The sequence similarities based on 16S rDNA sequences of the various Bacillus

species tested are shown in Table 3-2. These sequences were either obtained from the







68


GenBank database or were sequenced in previous studies.59-61'70 The similarities in 16S

rDNA nucleotide sequence between the tested Bacillus species, recognized by GenBank

"BLAST" searches, were between 91 and 99%. A sequence variation of -9% was found

between rDNA groups 1 and 2 Bacillus species. A very high sequence variation within a

well-described genus is not uncommon. Further analyses indicated that B. atrophaeus

shares a close phylogenetic relationship with several Bacillus species such as B.

mojavensis, B. pumilus and B. subtilis (>97.5%). Similarly, B. licheniformis wild-type

Table 3-2. 16S rDNA sequence similarities for the various Bacillus species studied





Bacteria x .4 2. 9 10





B atrophaeus X60607 100
B"licheniformis AF387515 96.9 100
B"licheniformis X68416 a 'a 100
B megaterium X60629 94.4 92.7 94.1 100
B mojavensis AB021191 a 96.7 M 94.1 100
B odyssey AF526913 92.0 90.1 91.5 93.4 91.8 100
Bpsychrodurans VSE1 06 91.8 90.5 91.5 92.9 91.5 95.4 100
Bpumilus AB020208 94.9 96.3 94.3 96.9 91.8 92.4 100
B subtilis 168 rrnA 96.9 M 94.1 Mi 91.6 91.4 97.2 100
Bsubtilis X60646 96.7 94.1 91.6 91.2 96.9 100
B thuringiensis X55062 95.2 92.9 94.2 94.7 94.3 92.8 92.0 94.3 94.2 94.3 100

strain KL-196 and B. mojavensis, as well as two B. subtilis strains tested in this study

showed >98% 16S rDNA sequence similarities. Such high 16S rDNA sequence

similarities was also noticed (>99%) in the case of the two B. subtilis strains sequenced

and B. mojavensis. This clearly showed that 16S rDNA sequence analysis was not useful

in differentiating these closely-related species of the genus Bacillus. The species


the genus Bacillus. The species









identities of all these strains were confirmed by DNA-DNA hybridization (M. Satomi,

personal communication). The two strains of B. licheniformis and B. subtilis showed

>70% DNA-DNA hybridization dissociation values and exhibited >98.5% 16S rDNA

sequence similarities. When all these species were grouped together, the maximum-

likelihood based phylogenetic tree showed two major clusters (M. LaDuc, K.

Venkateswaran, personal communication). One cluster consists of B. megaterium, B.

odyssey, B. psychrodurans, and B. thuringiensis, where the spores of these species

contained an additional structure called exosporium around the spore outer coat. The

second cluster formed by the other species tested did not contain an exosporium.

MALDI-TOFMS Spore Profiles

A representative spectrum from each Bacillus species analyzed in this study is

shown in Figure 3-1 A-N. The mass spectra are presented with m/z values from 3,000-

25,000. The m/z region from 9,500-25,000 is amplified (see inset of each spectrum) to

aid in visualization of the less abundant peaks present at higher m/z. The observation of

proteins at higher m/z is seldom reported in other MALDI-TOFMS analyses of whole

spores.25'26'34'35'38 We hypothesize that the appearance of large proteins at high m/z is due

to optimization of the solvent system used in this study.

From the spectra, we were unable to identify an obvious Bacillus-ubiquitous

biomarker with the sample preparation protocol adapted in this study. A peak at 14,500

m/z was present in most of the spore spectra obtained except for that of the B.

licheniformis ATCC 14580 type strain, its wild-type strain KL-196, and B. (a/liCan.l i%

34F2. The absence of a genus specific biomarker might be due to the extraction protocol

used in this study, post translational modifications of proteins that may differ between the

strains, or the need for more sophisticated spectral comparisons of the different species.










All of the spores have a group of peaks in the m/z region from 6,500-8,000. B.

licheniformis ATCC 14580, B. licheniformis KL-196, B. psychrodurans, B. odysseynsis

and B. megaterium ATCC 14581, and B. megaterium FO-38 all have an additional group

of peaks between m/z 5,000-6,500 that was not observed in the other spectra. It was

challenging to obtain good spectra from the B. odyssey samples as shown by the lower

signal-to-noise in the spectra. This could have been a result of glycoproteins present in

the exosporium layers. Glycoproteins can be challenging to analyze due to difficulty in

the ionization of the sugar moieties and the inherent heterogeneity of glycosolations. An

expected result was the level of similarity between the strains of the same species. B.

licheniformis ATCC 14580 type strain (Figure 3-1C) and its wild-type strain KL-196

(Figure 3-1B), B. subtilis 168 (Figure 3-11) and ATCC 6051 (Figure 3-1J), and B.

megaterium ATCC 14581 (Figure 3-1D) and B. megaterium FO-38 (Figure 3-1M) have

very comparable MALDI-TOFMS profiles upon visual inspection. The spectra for the B.

licheniformis pair were very similar except for a difference in intensity of the m/z 7,260

peak and the presence of different higher molecular mass species in B. licheniformis

14580. The B. subtilis pair has the same pattern in that there was a difference in peak

intensity for the peak at m/z 6,936 and variation in the masses observed above m/z

10,000. Similar patterns were also observed in the B. megaterium pair. This observation

supports the theory that it is important to examine a wide variety of Bacillus spores

before assigning definitive genus, species, and strain specific protein biomarkers.

Linear correlation analysis provided a means of statistical comparison of the

spectra. Correlation values close to 1 indicate that the fingerprint patterns of two

organisms are very similar. Table 3-3 shows the linear correlation values for the



















A) B. arophaeus 9372



II I I I
r<- __ __ _________________


B) B- lichenirmris KL-196


I


S C) B_ lihenifbimn-s 14580

S I, "
Js L s.. s '
^ _jJ*_J ^ ," "' 1 J J-I____________ 1_____


D) B. megatenun 14581


I mI -I I
So -*1F0
p~v Hpii


E) B. moavensis 51516


SI II

4000 6000 9000 10000 12000 14000 16000 1000 20000 22000 mi/
Figure 3-1. MALDI-TOFMS protein profiles of the 14 Bacillus spore species analyzed in
this study. The mass range depicted is from m/z 3,000-25,000. The higher
molecular mass region from m/z 9,500-25,000 is amplified 4x (see inset of
each spectrum) in order to visualize the higher molecular weight peaks that
are present but are at much lower abundance in the samples. A) B. atrophaeus
ATCC 9372. B) B. licheniformis KL-196. C) B. licheniformis ATCC 14580.
D) B. megaterium ATCC 14581. E) B. mojavensis ATCC 51516. F) B.
odyssey ATCC PTA-4993. G) B. psycrodurans VSE1-06. H) B. pumulis
ATCC 7061. I) B. subtilis 168. J) B. subtilis ATCC 6051. K) B.
i/nul igi'enii\ ATCC 10792. L)B. an///////i/i 34F2. M)B. megaterium FO-38.
N) B. niacini 51-8C.


- a


-------------- -------- ----- --


c
P 8
s ; o ,
4 8 r:
~"~?: ~







72










F) B. odyssey PTA-4399





















J) B. sublis 6051









4000 6000 8000 10000 12000 14000 16000 18000 20000 22000 m/z
Figure 3-1. Continued.psyc ansSE-06
| A H) B. piinilus 7061




s n I) B. subflis 168




SJ) B. subtilis 6051

S" ( l |D ," --


SK} B, thurngtensis 10792



4 6]? 6000 8000 10000 12000 14000 16000 18000 20000 22000 m /Z
Figure 3-1. Continued.




























L) B. anthracis 34F2


M) B- megaterrn FO-38


N)B. niacini51-8C










T s s


4000 6000 6000 10000 12000 14000 16000

Figure 3-1. Continued.


S100 20000 2000
19000 20000 22000


I I


0)0


m/t


C_ ___ II


__ _II___I_ I___ __ I


o n
r E


I
P


m
m
I
O
6











MALDI-TOFMS spectra of the various Bacillus spore species evaluated when compared


to the library spectra. Each of the 20 individual spectra from each species was searched


against the user generated average library spectra. All individual spectra were


successfully identified as their corresponding species and strain. These results were


verified by applying a Student's t-test to the data. Using the t-test, we confirmed that we


could differentiate all the species studied at the 95% confidence level. Figure 3-2 shows


the correlation results of the 20 individual B. atrophaeus spectra when searched against


Table 3-3. Correlation values based on MALDI-TOFMS protein profiling of the spores
of the Bacillus species in this study
Q -



Bacterial spores





B. anthracis 34F2 1
B. atrophaeus ATCC 9372 0.05 1
B. licheniformis ATCC 14580 0.01 0.09 1
B. licheniformis KL-196 0.01 0.03 M 1
B. megaterium ATCC 14581 -0.01 0.14 0.30 0.09 1
B. megaterium FO-38 0.00 0.16 0.14 0.00 0.74 1
B. mojavensis ATCC 51516 0.01 0.20 0.23 0.07 0.37 0.45 1
B. niacini 51-8C 0.02 0.05 0.13 0.12 0.06 0.03 0.02 1
B. odyssey 34hsl 0.01 0.35 0.15 0.05 0.26 0.28 0.21 0.17 1
B. psychrodurans VSE1-06 0.00 0.04 0.45 0.42 0.35 0.19 0.05 0.06 0.16 1
B. pumulis ATCC 7061 0.00 0.14 0.27 0.04 0.45 0.48 0.44 0.02 0.34 0.07 1
B. subtilis 168 -0.01 0.09 0.04 0.01 0.11 0.41 0.07 -0.01 0.05 -0.01 0.02 1
B. subtilis ATCC 6051 0.01 0.23 0.05 0.01 0.11 0.36 0.07 0.03 0.29 0.01 0.05 M 1
B. thuringiensis ATCC 10792 0.11 0.52 0.06 0.03 0.07 0.05 0.05 0.03 0.33 0.08 0.09 0.02 0.13 1


the library spectra. The y axis represents the linear correlation values obtained and the x-


axis represents the 1st-5th ranks (hits) from the library. At each rank, the standard


deviation of the measurement across the 20 spectra is represented by the error bars. The


graph demonstrates that for rank 1 (B. atrophaeus), we have very high correlation values


(0.960.02). For the next best hit, B. thuringiensis, the correlation values are much lower


(0.510.02). Since none of the correlation values approach the B. atrophaeus hit, we can


confirm the differentiation of B. atrophaeus from all of the other strains in the library.


e correlation values are much lower


(0.51+0.02). Since none of the correlation values approach the B. atrophaeus hit, we can


confirm the differentiation of B. atrophaeus from all of the other strains in the library.









The linear correlation method applied here also allows for differentiation of the species

whose MALDI-TOFMS profiles are almost indistinguishable upon visual inspection,

including the type strain and wild-type strains of B. subtilis, B. megaterium, and B.

licheniformis. Figure 3-3 shows the correlation results of B. subtilis 168 versus the

library spectra as described above. The 2nd rank (or hit) is much closer than in the case of

B. atrophaeus, the values for the first rank are 0.980.02 and the second rank are

0.860.02. The second rank represents B. subtilis 6051, the other B. subtilis strain in this

study. With statistical treatment of the data, the 2 strains were still able to be

differentiated at the 95% confidence interval. The close correlation values of 0.880.02

for the B. licheniformis pair and 0.860.02 for the B. subtilis pair illustrate that close

correlation values indicate a relationships between the organisms. However, with

statistical treatment of the data, differentiation at the strain level in these two examples

can still be obtained.

To ascertain the robustness of the technique, separate spectra collected and

averaged from the same spore culture were examined. All 16 species were correctly

identified by comparison to the library spectra (r=0.85-0.98). This result was consistent

whether the individual spectra themselves or averages of the individual spectra were used

to search the library. In addition to the new preparations from the same culture, four

batches of spores of B. subtilis 168, prepared at different times over the course of 2 years,

were also compared against the library spectra. All of the B. subtilis 168 spores were

correctly identified as the B. subtilis 168 from the library, regardless of the batch or

storage time (r=0.92-0.98).









Aligning the correlation results from the MALDI-TOFMS profiles (Table 3-3) with

the 16S rDNA sequence analysis (Table 3-2) shows that the MALDI-TOFMS profiles

were complementary to 16S rDNA analysis. Using MALDI-TOFMS spore profiles of

these organisms, we were able to differentiate all of the species studied confidently,

whereas there are several species including B. subtilis 168, B. licheniformis, B.

mojavensis, and B. atrophaeus that 16S was unable to differentiate at the species level.

MALDI-TOFMS analysis on these species would allow for differentiation at the species

level. Comparing the MALDI protein profiles with the phenotypic groupings was

challenging due to the large diversity in the number and range of the peaks across the

spectra for all of the species studied. In general, spores with an exosporium resulted in

spectra that had more peaks over a broader range than the non-exosporium organisms.

On average, the phenotypic group IV organisms had more peaks than the group II

organisms, with the exception of B. megaterium and its wild-type FO-38. Cluster

analysis was applied to the data to allow the relationships based on protein profiles

between the different species to be visualized. The results of the single linkage cluster

analysis using the SPSS software package are shown in Figure 3-4 combined with an

image map of the spectra for visualization.

MALDI-TOFMS Vegetative Profiles

The bulk of this work was focused on the analysis of spores; however, the same

technology was applicable for the analysis of vegetative cells. For routine analysis and

identification (not direct environmental sampling), samples would likely be cultured prior

to analysis. One of the advantages, other than speed, of the MALDI technique developed
















1


'U



04
]

> I06-
o


*ca
,VIA


02-


u


RaLi ibW1s6j

R j


a.... I ----^ ^ --- i


Figure 3-2. Correlation results of the 20 individual B. atrophaeus ATCC 9372 spectrum
when searched against the library. The y axis represents the linear correlation
values obtained and the x-axis represents the 1St-5th ranks (hits) from the
library. At each rank, the standard deviation of the measurement across the 20
spectra is represented by the error bars.














1I



0-8


0_6




o
U

O2


IR aBdilis 1B6

R aslrilis 6Q


aI
:alnrphammg


r-


Rank
Figure 3-3. Correlation results of the 20 individual B. subtilis 168 spectrum when
searched against the library. The y axis represents the linear correlation
values obtained and the x-axis represents the 1st-5th ranks (hits) from the
library. At each rank, the standard deviation of the measurement across the 20
spectra is represented by the error bars.


RwMydpimxnT























13 zubnklil6
B subtdk 1-68
B subuinr .H-642
B.rakbills6051
B. sublis NB-200

B. udyssc4
B. mc.Ratermm
FO-38
R pumdks 7061




.. .
KL19

B. psycrmn








Figure 3-4. Visualization of the spectra in-line with the dendrogram for the spores in this
study. The dendrogram is based on a single linkage scheme. Peak intensity is
indicated by brighter colors in the image map. The dendrogram is highlighted
trato show that the closest clusters are between strains of the same species.









here was the amenability to the presence of numerous cultures on a single plate, which

could be removed individually with a sample loop for analysis. This could eliminate the

need for several incubation steps while trying to isolate a single organism.

To determine the scope of the current methodology the vegetative cells of the

different species were also examined. The same extraction protocol with no

modifications was used on the vegetative cells and should be effective since spores

should present the more difficult challenge for protein extraction. The vegetative cell

spectra for each of the species analyzed are shown in Figure 3-5 from m/z 2,500-60,000.

The region from m/z 20,000-60,000 is amplified by 4x to highlight the upper molecular

weight region of the spectra. Profiles of the vegetative cells have protein biomarker

peaks that extend to a much higher range than their corresponding spore spectra. The

vegetative profiles also have a greater number of peaks than the spores. The spectra

obtained in this study have similar numbers of peaks as vegetative cell spectra in other

studies where formic acid and ferulic acid were used in the matrix. No protein peaks

were observed to overlap between the vegetative and spore spectra from the same strain,

particularly due to the presence of peaks above 30 kDa in most the vegetative cell

spectra.

Correlation analysis of the vegetative cells gave us very similar results to those of

the spores. Complete differentiation of the different strains examined was possible and

the highest correlation values were found between the B. subtilis and B. licheniformis pair

(Table 3-4). Repeat analysis of different colonies from the plates gave correlation values

of 0.71-0.85 with their corresponding library spectra. Since the vegetative cell spectra










A) B. atrophaeus 9372


I -IT
L T 1


B) B. licheniformis KL-196

,, a *O h.

T 7 -7


C) B. licheniformis 14580
n


S i ,-,- 0 I .,-

T TT
+ ~Y 1I LC ( CI + "
711 iT~ + 8,


I 1


D) B. megaterinum 14581



= @- N r
<^ ^ t ^ ^*^-" f-t:2
c^~~~ ~~ T~ ^ ^^^ ^^ ^


E) B. mojavensis 51516




T T 7


F) B. odyssey PTA-4399


I T TT
*4J'hi. 5&.tLt


7C
I,,I 'I


5 oo60 6 10 SOOO 2000 Sooo 6o6o 3fOOO 42000 4500o 160O. S.o.o .n.i
Figure 3-5. MALDI-TOFMS protein profiles of the 14 Bacillus vegetative species
analyzed in this study. The mass range depicted is from m/z 2,500-60,000.
The higher molecular mass region from m/z 20,000-60,000 is amplified 4x
(see inset of each spectrum) in order to visualize the higher molecular weight
peaks that are present in the samples. A) B. atrophaeus ATCC 9372. B) B.
licheniformis KL-196. C) B. licheniformis ATCC 14580. D) B. megaterium
ATCC 14581. E) B. mojavensis ATCC 51516. F) B. odyssey ATCC PTA-
4993. G) B. psycrodurans VSE1-06. H) B. pumilus ATCC 7061. I) B.
subtilis168. J) B. subtilis ATCC 6051. K) B. thuringiensis ATCC 10792. L)
B. (Iath/lI i%\ 34F2. M) B. niacini 51-8C.


-- YUy -.~~r-ru-~ly~LLIIY IY~xYIIY-----~----LLI-LY.I.I --rrr~lLL .-*u--L~1Lu


"-"-' '"7 "Y.='. I-. *I_11


h/>
f--- ^


i ,2


















T. -


G) B. psychrodurans VSE1-06



'4 -- C
7 7


H) B. pumilus 7061


h*YZrYD~LHrrrrrYlr*ih
" n P"
J: ~
c
ri 5 7


tds.J_ _--I*-) B. subtilis 168
8- 0~l0
CP)
I CN CC
^; t~l 03^-c C
a, t, '4 4? r'

l lljiK IT^ i ^'
i ~ ~ rP l3 '""' T' t i i


F'n


S TS
0,

7CO '4* '4 4,
S ^ S 2 SC
T IcCI | : "h
'4 ~r -,aC
'4 a) 7


J) B. subfifis 6051


I'


K) B. thuringiensis 10792


77 7 T 7 7


L) B. anthracis 34F2



"O R s ,

I'
?f s


TI-



l~l!I I
ill .7


M)B. niacini5l-8C





-r => '*>
= 0' = = Ca
'4 | '- '4 ~ t


5000 10000 15000 20000 255000 50000 55000 m/2

Figure 3-5. Continued.


T L _
IT


Sr<
I 11 1







83


are more complex than the spore spectra, hierarchical cluster analysis (HCA) in


conjunction with visualization using image mapping was used to observe patterns in the


spectra (Figure 3-6). The HCA analysis divided the vegetative cells into two clusters,


one consisting of B. atrophaeus, B. mojavensis, the B. licheniformis pair, and B. subtilis


pair and the second cluster containing the other species. B. t/i/h illgie/lli had fewer peaks


in comparison with the other vegetative cells and, therefore, was not similar to either


cluster. The second cluster had more peaks overall than the first cluster and contained the


RNA group 2 organisms. All of the species in the first cluster contained a biomarker


peak at 9,890 Da which was not present in the second cluster. In addition, all the species


in the first cluster except the B. licheniformis pair had a biomarker peak at 3,405. There


were no obvious biomarker peaks observed in the second cluster.


Table 3-4. Correlation values based on MALDI-TOFMS protein profiling of the
vegetative cells of the Bacillus species in this study







Bacteria (vegetative)
S0 0 0









B. licheniformis KL-196 0.09 0.07 M 1
B. egateium ATCC 14581 0.37 0.27 0.25 0.15 1

B. nojavensis ATCC 51516 0.16 0.21 0.22 0.19 0.21 1
B. niacini 51-8C 0.40 0.32 0.20 0.13 0.61 0.24 1
B. odysseyi 34hs1 0.37 0.25 0.15 0.06 0.53 0.21 0.57 1
B. psychrodurans VSE1-06 0.37 0.26 0.20 0.10 0.49 0.23 0.49 0.63 1
B.pumnlis ATCC 7061 0.31 0.21 0.18 0.10 0.45 0.29 0.49 0.52 0.39 1
B. subtilis 168 0.18 0.53 0.29 0.24 0.28 0.67 0.25 0.32 0.30 0.34 1
B. subtilis ATCC 6051 0.22 0.32 0.43 0.35 0.30 0.58 0.20 0.29 0.33 0.30 M 1
B. thuingiensis ATCC 10792 0.27 0.01 -0.02 -0.02 0.03 -0.01 0.04 0.07 0.06 0.03 -0.01 0.00 1
Soo U U U


Bacteria (vegetative)



S I *



B. anthracis 34E2 1
B atrophaeus ATCC 9372 0.23 1
B. licheniformiis ATCC 14580 0.16 0.14 1
B. lichen iformis KL-196 0.09 0.07 1
B. megaterimm ATCC 14581 0.37 0.27 0.25 0.15 1
B. mojavensis ATCC 51516 0.16 0.21 0.22 0.19 0.21 1
Bniacini 51-8C 0.40 0.32 0.20 0.13 0.61 0.24 1
Bodysseyi 34hsl 0.37 0.25 0.15 0.06 0.53 0.21 0.57 1
B. psychrodnrans VSE1-06 0.37 0.26 0.20 0.10 0.49 0.23 0.49 0.63 1
B. pnmulis ATCC 7061 0.31 0.21 0.18 0.10 0.45 0.29 0.49 0.52 0.39 1
B. subtilis 168 0.18 0.53 0.29 0.24 0.28 0.67 0.25 0.32 0.30 0.34 1
B. subtilis ATCC 6051 0.22 0.32 0.43 0.35 0.30 0.58 0.20 0.29 0.33 0.30 1
B. thuringiensis ATCC 10792 0.27 0.01 -0.02 -0.02 0.03 -0.01 0.04 0.07 0.06 0.03 -0.01 0.00 1








84














0 5 10 15 2 25


KL-196
B. lihe3mformis
B subatoi 168
B srbti 6051

B mojavensi
B_ atrphaewr
SB.ys eyi
B psiyctrdcoi
B. megataium

B. niacim
B. pwmdiW 7061
B. anthrai? 34-F2
B. thuringiemi

2500 1000 20000 300Mo 40M0 50000


Figure 3-6. Visualization of the spectra in-line with the dendrogram for the vegetative
cells in this study. The dendrogram is based on a single linkage scheme.
Peak intensity is indicated by brighter colors in the image map.












Four strains (B. subtilis 168, B. am/inn i/ 34F2, B. pumilus ATCC 7061, and B.


ihnll iigielli ATCC 10792) were chosen to further study the variability of growth media


on the spectra from vegetative cells. These strains were cultured on 3 media, TSA, NA,


and LB, under identical incubation conditions. Upon observation, there was a significant


difference in the size of the colonies on the different plates. The largest colonies were on


the TSA plates, followed by NA and then LBA plates. Every effort was made to remove


similar size samples for each strain by only using a small portion from the edges of the


larger colonies. Table 3-5 shows the results of the correlation analysis of these samples


with each other. Figure 3-6, 3-7, 3-8, and 3-9 show the average spectra from each species


on each of the growth plates.


Table 3-5. Correlation values based on MALDI-TOFMS protein profiling of vegetative
cells of select Bacillus species incubated on three different growth media


Bacteria (vegetative)


Media


rt. r r t

u- u


00 0 00
r- r- -
(^ (^ (
; ; a .
S S S
a a a a
cd cd d c


E -2 -2

**f vi CQ ,


,- t-- t~
<= <> =
,(> (- ,-
o0 0 ne n; in
^o ^o a a a
^ ^^ ^ ^
^ ^ s s< s
99 .s s .
'*<3 '*<3 S S
cdcs cs % %


B. anthracis 34F2
B. anthracis 34F2
B. anthracis 34F2
B. pumilus 7061
B. pumilus 7061
B. pumilus 7061
B. subtilis 168
B. subtilis 168
B. subtilis 168
B. thuringiensis 10792
B. thuringiensis 10792
B. thuringiensis 10792


&-m
0.31 0.35 0.58
0.29 0.31 0.44 1
0.32 0.34 0.56
0.14 0.10 0.14 0.24 0.27 0.25
0.46 0.55 0.37 0.06 0.07 0.07 0.03
0.15 0.14 0.18 0.23 0.27 0.25 0.05
0.56 0.56 0.48 0.40 0.48 0.12 0.21 0.17
0.44 0.46 0.37 0.11 0.11 0.12 0.04 0.45 0.09 0.39
0.41 0.40 0.37 0.14 0.10 0.14 0.03 0.34 0.06 0.63 0.64


Abbreviations: LB, Luria-Bertani Agar; NA, Nutrient Agar; TSA, Tryptic Soy Agar


ryptic Soy Agar









In the case of B. uiiln/I i (Figure 3-6) and B. pumilus (Figure 3-9), the spectra from all 3

of the growth media maintained correlation values of above 0.70 when compared with

each other. In both cases, visual observation of the spectra revealed that the 3 samples

had several biomarker peaks in common but the NA sample (middle) had additional

biomarker peaks not seen in the TSA (top) or LB (bottom) samples. In B. subtilis 168

(Figure 3-7), the TSA and LB samples were similar to each other (r = 0.80); however, the

NA sample had few biomarkers in common with the other two samples and was

significantly different. The B. subtilis 168 sample grown on NA also demonstrated the

presence of higher molecular weight biomarkers not seen in the other samples. The B.

1thii iigie'll\i cells grown on the different media (Figure 3-8) were very dissimilar,

supported by very low correlation values and visual observation of the spectra. The most

significant difference in these samples is seen in the range above 30 kDa and below 7

kDa. Several biomarkers, including 2,891 Da, 10,010 Da, and 19,046 Da are common

across all B. thuringiensis samples in this study. Therefore, it is still possible to identify

species specific biomarkers present in several growth media. Notably, the B.

1thii iigiell\i\ cells grown on the LB plates had a correlation value of 0.70 with the B.

(auh,1hi i% cells grown on TSA even though they do not share the above mentioned

biomarkers. The B. cllI/bal, i% and B. ihiin iigienll\i samples have the 7,350 Da biomarker

in common. The differences in the protein profiles on the 3 media could be an effect of

the difference in growth phase of the organism or the differences in the proteins

expressed due to the nutrients available in the different media.

The cells in the media study were grown for 8 hours longer than the cells in which

the initial comparisons of the vegetative cells were done. The media samples (20 hour






87









B. anthracis 34F2
TSA, 20 hours



fl- 0V3



NA 20 hours
^I P a. S N ^ r












LBA, 20 hours




T
I I l l eo






5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 miz
Figure 3-7. MALDI-TOFMS protein profiles of B. (///m/ I/ i 34F2 vegetative cells from
different growth media: tryptic soy agar (top), nutrient agar (middle), and
Luria Bertani agar (bottom). The mass range is from m/z 2,500-60,000. The
higher molecular mass region from m/z 20,000-60,000 is amplified 4x (see
inset of each spectrum) to aid in the visualization of the higher molecular
weight peaks that are present.






88










B. subtilis 168 TSA, 20 hours








I I I I I I I
NA, 20 hours








LBA, 20 hours





5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 m/2

Figure 3-8. MALDI-TOFMS protein profiles ofB. subtilis 168 vegetative cells from
different growth media: tryptic soy agar (top), nutrient agar (middle), and
Luria Bertani agar (bottom). The mass range depicted is from m z 2,500-
60,000. The higher molecular mass region from m z 20,000-60,000 is
amplified 4x (see inset of each spectrum) to aid in the visualization of the
higher molecular weight peaks that are present.






89








B. thuringiensis 10792

TSA, 20 hours


















L J T i IT




5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 55000 rnz
Figure 3-9. MALDI-TOFMS protein profiles of B. thuringiensis ATCC 10792 vegetative
cells from different growth media: tryptic soy agar (top), nutrient agar
ot(middle), and Luria Bertani agar (bottom). The mass range depicted is from
mz 2,500-60,000. The higher molecular mass region from mz 20,000-60,000
is amplified 4x (see inset of each spectrum) to aid in the visualization of the
higher molecular weight peaks that are present.
Ill l T m lTcla wegt Tek th ar Trse



















B. pumilus 7061


TSA, 20 hours


) WI *tM rn t)
"- ) (00 C=
yl O r -f K C4
r*- C C*OO C


NA, 20 hours


-, LBA, 20 hours

T -- --W---i_-M*^ .r*^.*r. .^.^ ---- Lu .-- -


I .


5000 10000 15000 20000 25000 30000 35000 40000 45000 5o000 55000 m/2
Figure 3-10. MALDI-TOFMS protein profiles of B. pumilus 7061 vegetative cells from
different growth media: tryptic soy agar (top), nutrient agar (middle), and
Luria Bertani agar (bottom). The mass range depicted is from m/z 2,500-
60,000. The higher molecular mass region from m/z 20,000-60,000 is
amplified 4x (see inset of each spectrum) to aid in the visualization of the
higher molecular weight peaks that are present.


L1I UWY**Wlrr~u-r~ub---*rlOr~L. ~Y-~LJYL~Y~I L~lrY*4rYY









incubation) were compared with the vegetative cell library above (16 hour incubation) to

ascertain the difference that growth time can make on the spectra. In the case of B.

pumilus 7061 and B. au(///// i\ 34F2, all of the media samples were positively identified

with the B. pumilus 7061 and B. ial/it/1I/ i% 34F2, samples from the previous day. The

correlation values for the TSA, NA, and LB samples with the type strain sample on TSA

from the previous day were 0.85, 0.76, and 0.83 respectively for the B. pumilus 7061 and

0.68, 0.62, and 0.88 for the B. a//lli//I/ i% 34F2. In the case of B. thuringiensis, the TSA

and NA samples were correctly identified with correlation values of 0.88 and 0.58;

however, the LB sample again had the highest correlation with the B. a/l/1//i / i% sample

from the previous day (r = 0.57). Only B. subtilis 168 grown on LB was properly

identified, with a correlation value of 0.71. The NA sample was closest to B.

thuringiensis (r = 0.40) and the TSA sample was closest to B. atrophaeus (r = 0.68), both

grown on TSA from the previous study.

Although not all of the species type out properly, the robustness of the technique

was highlighted, as cells grown on different media and incubation times still gave

relatively high correlation values to a library strain of the same species under different

conditions. To determine if the absolute value of r was significant (i.e., does an r of 0.40

indicate a good match?), a more detailed study was needed to determine the range of

correlation values encountered when considering the strain variation across a species.

Conclusion

MALDI-TOFMS based protein profiling is a useful, rapid, and sensitive technology

to differentiate spores and vegetative cells from closely related microbial species.

Although a standardized sample preparation protocol is required, it is obvious that this






92


technology is promising for species differentiation of a wide variety of bacterial spores

and cells.














CHAPTER 4
MALDI-TOFMS COMPARED WITH OTHER POLYPHASIC TAXONOMY
APPROACHES FOR THE IDENTIFICATION AND CLASSIFICATION OF Bacillus
pumilus SPORES

Introduction

To verify the efficacy of matrix-assisted laser desorption/ionization time-of-flight

mass spectrometry (MALDI-TOFMS) protein profiling for identifying and differentiating

bacterial species, several strains of Bacilluspumilus were examined in a thorough

taxonomic study incorporating a polyphasic approach. MALDI-TOFMS protein profiling

is rapid, sensitive, and has higher resolution and better reproducibility than gel-based

protein or DNA fingerprinting, and has proven effective for bacterial identification.16'31'33

By carefully controlling extraction conditions combined with suitable software for data

analysis, MALDI-TOFMS has the potential to identify and classify previously

unidentified environmental isolates. The realization of this potential is dependent on the

availability of standardized MALDI-TOFMS profile libraries for comparison of unknown

isolates with reference strains. Verification of this microbial classification scheme has

not been thoroughly explored, and published studies on this technique have focused

solely on bacteria from culture collections and/or blind studies using strains already

represented within user generated libraries.20 71'72 These studies have included members

of Enterobacteriaceae, Bacillus, Staphylococcus, Streptococcus, and other medically

important species.

Similar MALDI-TOFMS studies have been reported on the species and strain

differentiation of Bacillus spores;25,26'29,32,73 however, protein profile variation in spores









of a single species by examining several strains isolated from various sources has not

been reported to our knowledge. Such research will support the application of MALDI-

TOFMS in field applications. In the current study, 16 isolates of putative B. pumilus from

different spacecraft assembly facilities, the Mars Odyssey spacecraft, and the

International Space Station, were characterized using the Biolog system, DNA

techniques, and MALDI-TOFMS protein profiling. B. pumilus is one of the predominant

spore-forming microbes in spacecraft and associated clean room environments.60

Moreover, resistance ofB. pumilus spores to various stressors is strain-specific74 and

might be influenced by the environmental factors resulting in the expression of different

proteinaceous compounds for protection.75'76 A one-step sample treatment and MALDI-

TOFMS preparation was used to obtain spectra for the creation of a library of spectra

from the different isolates of putative B. pumilus, providing the most diverse study of a

single bacterial spore species using protein profiling reported to date.

The results obtained from MALDI-TOFMS protein fingerprinting of these B.

pumilus isolates was compared with DNA-DNA hybridization for their bacterial

systematics and molecular phylogenetic affiliations. MALDI-TOFMS protein profiling

was more accurate than Biolog metabolic profiling, more discriminating than 16S rDNA

sequence analysis, and complemented the results ofgyrB sequence analysis and DNA-

DNA hybridization for the identification of the B. pumilus spores. This is the first report

whereby MALDI-TOFMS generated protein profiles from a set of microbes are

compared directly with DNA-DNA hybridization yielding a positive correlation. Unique,

cluster-specific biomarker peaks have been identified in the spores of the B. pumilus

examined in this study. MALDI-TOFMS protein profiling is a rapid and simple analysis










and is demonstrated as a useful taxonomic tool for differentiating spores of the genus

Bacillus. For practical purposes, it would be ideal (and necessary) to have a publicly

available, standardized MALDI profile database, to facilitate the use of the technique as a

diagnostic method to differentiate bacterial species.

Materials and Methods

Bacterial Strains

Table 4-1 contains a list of the wild-type bacterial strains used in this study. All

ATCC strains were procured from the American Type Culture Collection (Manassas,

VA), including the type strains of B. atrophaeus, B. subtilis, B. megaterium, B.

mojavensis, B. pumilus, and B. licheniformis. The B. odyssey type strain was from our

culture collection and B. subtilis 168 was obtained from Dr. Wayne Nicholson at the

University of Florida. The source, location, and date of isolation of the 16 wild-type

isolates of putative B. pumilus are indicated in Table 1 along with the other isolate

species used in this study. Bacterial isolation procedures from spacecraft assembly

facility surfaces are described elsewhere 59,61

Sporulation of Bacillus isolates

A standard protocol for the production of spores was used in this study 7. A single

purified colony of the strain to be sporulated was inoculated into nutrient broth

sporulation medium (NSM) and incubated at 320C with shaking for ca. 2-4 days, until the

cultures reached >99% spores as examined by phase-contrast microscopy. Spore cultures

were harvested by centrifugation and purified to remove remnant vegetative cells and

cellular debris, as previously reported 7. The purification protocol involved a lysozyme

treatment followed by salt and detergent washes to remove vegetative cellular debris.








96



Purified spores were adjusted to an optical density of 0.6 at 600 nm and were stored in


sterile deionized water at 40C in glass vials until analyzed.


Table 4-1. Strain designation, grouping, and source of Bacillus species in this study
16S rDNA Genbank
Species Strain Source' Year of Isolation Accession NumberComments
Accession Number_
B. pumilus type strain group
B. pumilus ATCC 7061 ATCC AB020208 Type strain
B. pumilus ATCC 27142 ATCC n/a Gamma radiation resistant strain
B. pumilus 0105342-2 ISS-hardware 2000 n/a International Space Station hardware
B. pumilus SAFN-029 JPL-SAF 2001 AY167883 Air-lock
B. pumilus SAFR-032 JPL-SAF 2001 AY167879 Air-lock
B. pumilus FO-036b group
B. pumilus FO-033 JPL-SAF 1999 AF234851 Clean room air particulate
B. pumilus FO-036b JPL-SAF 1999 AF234854 Clean room air particulate
B. pumilus SAFN-001 JPL-SAF 2001 AY167886 Entrance floor
B. pumilus SAFN-027 JPL-SAF 2001 AY167884 Ante-room
B. pumilus SAFN-036 JPL-SAF 2001 AY167881 Clean room floor
B. pumilus SAFN-037 JPL-SAF 2001 AY167880 Clean room floor
B. pumilus KL-052 JPL-SAF 2000 AY030327 Clean room cabinet top
B. pumilus 51-3C Mars Odyssey 2002 AF526907 Mars Odyssey spacecraft surface
B. pumilus 81-4C KSC-SAEF II 2002 AF526903 Mars Odyssey assembly facility floor
B. pumilus 82-2C KSC-SAEF II 2002 AF526902 Mars Odyssey assembly facility floor
B. pumilus 84-1C KSC-SAEF II 2002 AF526898 Mars Odyssey assembly facility floor
B. pumilus 84-3C KSC-SAEF II 2002 AF526896 Mars Odyssey assembly facility floor
B. pumilus 84-4C KSC-SAEF II 2002 AF526895 Mars Odyssey assembly facility floor
Wild-type strains of other Bacillus species
B. cereus FO-11 JPL-SAF 1999 AY461790 Clean room air particulate
B. hcheniformis KL-196 JPL-SAF 2000 AF387515 Clean room cabinet top
B. nacini 51-8C KSC-SAEF II 2002 AF526905 Mars Odyssey assembly facility floor
B. odyssey PTA-4399 Mars Odyssey 2002 AF526913 Mars Odyssey spacecraft surface
B. psychrodurans VSE-01 KSC-PHSF 2002 n/a Mars Exploration Rovers assembly facility air particles
aAbbreviations JPL, Jet Propulsion Laboratory, KSC, Kennedy Space Center, SAF, Spacecraft Assembly Facility, PHSF, Payload Hazardous Servicing Facility, SAEF, Spacecraft
Assembly and Encapsulation Facility, ATCC, Amencan Type Culture Collection
b Included sequences reported in vanous publications were used for comparison (LaDuc et al 2003b, Venkateswaran et at 2001)



Vegetative Cell Growth


To produce vegetative cells for analysis, cultures were first streaked out on tryptic


soy agar plates and incubated overnight at 320C. A single, isolated colony was then used


to inoculate a 5 mL tryptic soy broth culture. This culture was incubated at 320C with


shaking at 250 rpm for 8 hours. A milliliter of the culture was removed from the tube


and spun down for 10 minutes at 9,600 x g. The supernatant solution was removed and


the pellet was resuspended in phosphate buffered saline solution. The culture was again


centrifuged the supernatant removed, and the remaining cell pellet used for the MALDI


analysis.









Metabolic profiling

All isolates were subjected to Gram staining and the presence of spores was

confirmed using light microscopy. Metabolic profiling was performed on the various

isolates using the Biolog system (Biolog, Foster City, CA). This 96-well microplate

method tests for the oxidation of 95 different carbon sources. Protocols for the

preparation and analysis of Bacillus species were followed per the manufacturer's

directions. Microplates were read after 6 and 20 hours of incubation in the 96 well plates.

The Microstation hardware was used to read the plates and Microlog 3 software was used

to analyze the data.

16S rDNA and gyrB sequencing

Chromosomal DNA from each of the isolates was extracted by standard PCIAA

and ethanol precipitation protocols77, and was used as the template for PCR amplification

(ca. 10 ng). Universal primers (Eub 8f and Univ. 1492r) were used to amplify 16S rDNA

fragments, as per established protocols53. Procedures developed by Yamamoto and

Harayama56 were followed for gyrB amplification. Amplicons were gel-excised, purified

with Qiagen columns (Qiagen, Valencia, CA), and sequenced as described elsewhere59'61

The phylogenetic relationships of organisms covered in this study were determined by

comparison of individual 16S rDNA (www.ncbi.nlm.nih.gov) or gyrB (www.mbio.co.jp)

sequences to other existing sequences in the public databases. Evolutionary trees were

constructed with PAUP software, following maximum- parsimony parameters78

DNA-DNA hybridization

Bacterial strains were cultivated in tryptic soy broth (Difco, St. Louis, MO)

containing 1.5% glycine by shaking at 300C for 16 hours. Cells were harvested by

centrifugation, resuspended in TE buffer (pH 8.0), and lysed by the addition of 50 [g/mL









labiase (Seikagaku Corporation, Japan) and Img/ mL achromopeptidase (Wako Pure

Chemicals, Japan). Cell suspensions were incubated at 370C until they became viscous,

at which time chromosomal DNA was purified per standard methods DNA-DNA

homology was performed using the microplate hybridization method79 with photobiotin

labeling and colorimetric detection as described previously80. Cluster analysis based on

DNA hybridization was performed via the neighbor-joining method8l using PHYLIP

software82

MALDI-TOFMS protein profiling

Purified spores were diluted one to ten in a saturated solution of ferulic acid matrix

using a 30% formic acid, 40% water, and 30% acetonitrile mixture as the solvent73. The

mixture was vortexed briefly and 1 IL of the sample containing both spores and matrix

was deposited on the MALDI plate. For vegetative cell samples, 50 [iL of the matrix

solution was used to resuspend the cell pellet. The mixture was vortexed briefly and 1 iL

of the sample containing both vegetative cells and matrix was spotted. Spots were

allowed to air dry and no further treatment was applied to the spots post drying. The

sample preparation was done in duplicate from each spore and vegetative cell suspension.

MALDI-TOFMS protein profiling was performed on a Bruker Daltonics Reflex II Mass

Spectrometer (Bruker Daltonics, Billerica, MA) retrofitted with delayed extraction.

Positive ion mass spectra were collected in the linear mode using a delay time of 50 ns,

an acceleration voltage of 20kV, and a deflector set at 2,500 Da. All spectra represent the

accumulation of 50 laser shots. Ten spectra were collected across each spot for a total of

20 spectra per sample. Each spectrum was baseline corrected and smoothed using a ten-

point Savitzky-Golay smoothing algorithm prior to statistical analysis.









Statistical processing of MALDI-TOFMS profiles

Linear correlation analysis was performed on software developed in-house with

Visual Basic 6.0 as described previously 73. A library of isolate spore spectra was

complied by averaging the 20 spectra collected from each spore sample. The individual

and the average spectrum obtained from the strains in this study were compared to

MALDI-TOFMS profiles stored in this library and to a user generated library of eleven

Bacillus species. Higher correlation coefficients are indicative of spectral similarity. To

quantify the level of significance of these differences, a simple t-test was applied. A

similar procedure was used for the vegetative cells except they were compared only with

themselves, rather than with another library.

In addition to the linear correlation analysis, SPSS software (Chicago, IL) was used

for performing a hierarchal cluster analysis (HCA) on the average spectrum obtained

from each strain in this study. The HCA analysis was based on the Pearson correlation

and dendrograms were produced using a single linkage (nearest neighbor) scheme.

Spectral visualization is accomplished through the use of Surfer 8.0 mapping software

from Golden Software (Golden, CO). Using this mapping software, an image map with

10 Da resolution is produced from the average spectrum from each species. The intensity

of the peaks is represented by the color of the bands in the image.

Results

Metabolic fingerprinting of B. pumilus strains

Among the 95 carbon substrates tested, N-acetyl-D-glucosamine, inosine, and

thymidine were oxidized by all the B. pumilus strains but were not oxidized by B. subtilis

168. Alpha- and P-cyclodextrin and L-lactic acid were oxidized by B. subtilis 168 but

were not oxidized by any of the B. pumilus strains. All of the 16 wild-type B. pumilus









isolates, B. pumilus ATCC 27142, and B. subtilis 168 reduced maltose, methyl-D-

glucoside, palatinose, turanose, pyruvic acid methyl ester and cellibose whereas B.

pumilus ATCC 7061T did not.

The Biolog identification system was not able to discriminate the spore forming

aerobic bacteria in this study. The system correctly identified only 3 out of 18 strains

tested, ATCC 7061T, SAFN-036, and SAFN-037 as B. pumilus. Eight of the B. pumilus

strains (FO-36b, SAFN-001, SAFN-027, 51-3C, 82-2C, 84-1C, 84-3C, and 84-4C) were

incorrectly identified as B. subtilis (44%). Metabolic fingerprinting profiles of the

remaining 7 B. pumilus strains (ATCC 27142, FO-033, KL-052, SAFN-029, SAFR-032,

81-4C, and 015342-2) did not match with any of the species contained in the Biolog

metabolic fingerprinting database (39%).

16S rDNA and gyrB sequencing

The results of 16S rDNA sequencing and maximum-parsimony analysis rendered

no apparent phylogenetic clustering pattern among the isolates tested. All of the B.

pumilus examined, excluding 84-1C, 82-2C, 84-3C, and SAFR-032, had greater than

97.5% sequence similarity with each other. Strains 84-1C and SAFR-032 exhibited 16S

rDNA sequence similarities of >99% with B. pumilus ATCC 7061T and -96.5%

similarities with FO-36b group of isolates. Likewise, 82-2c and 84-3c isolates showed

16S rDNA similarities of -96.5% with both ATCC 7061T and the FO-36b group. Sensu

lato, the strains examined in this study were indistinguishable by 16S rDNA sequence

analysis.

The gyrB analysis of 12 strains sequenced exhibited two distinct clusters based on

maximum-parsimony analysis. The first cluster showed >96.5% sequence similarities

among 5 strains, B. pumilus ATCC 7061T, ATCC 27142, 0105342-2, SAFN-029, and