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1 LINKING GENE WITH FUNCTION: ANALYSIS AND INVESTIGATION OF NOVEL PLAYERS IN BACTERIAL ZINC HOMEOSTASIS By CRYSTEN ELIZABETH BLABY HAAS A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIA L FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2011
2 2011 Crysten Elizabeth Blaby Haas
3 To my family
4 ACKNOWLEDGMENTS I would like to thank Dr. Valrie de Crcy Lagard for giving me the opportunity and support to work on this project, which has sparked my interest in microbial metal metabolism. I would also like to thank the members of my doctoral committee both past and present, Dr. Keelnatham T. Shanmugam, Dr. James F. Preston, Dr. Graciela L. Lorca, Dr. Robert J. Cousins and Dr. Thomas J. Lyons, for their invaluable advice, guidance and time. I would like to thank the faculty and staff of the Microbiology and Cell Science Department, specifically John Rice, Chris Gardner and Fernando P agliai. I would like to thank present and past graduate students from MicroCell, particularly Dr. Franz St. John, who was my original research mentor and taught me almost everything I know. I would like to thank Dr. Phi Min Do for assistance with hydrogenase and glyoxa lase assays. I would like to thank Dr. ShouMei Chang and Dr. Charles Guo. I would like to thank Drs. Richard Gourse, Herbert Schweizer Shouguang Jin and Chris Rensing for strains and/or plasmids. I would like to thank Dr. Zhonglin Mou for us e of his electroporator and UV crosslinker. I would like to thank Dr. Eric Triplett for using his restriction enzymes from time to time. I would like to thank Dr. Nemat Keyhani for allowing me to borrow amino acids. I would like to thank the staff at the I CBR sequencing and mass spec core as well as Dr. George Kamenov for ICP MS analysis. I would like to thank Dr. Maupin for supervising me during my PhD rotation and her lab members, especially Dr. Katie Rawles and Dr. Matthew Humbard for advice. I am gratef ul for the advice and support of my lab members, Gabriella Philips, Patrick Thiaville, Dr. Marc Bailley, Kevin Gulig and Dr. Basma El Yacoubi. I would like to thank my many collaborators, with whom I have been most privileged to publish with, Dr. Dmitry Ro dionov, Dr. Sabeeha Merchant, Dr. Janette Kropat, Dr. Davin Malasarn, Dr.
5 Irina Artsimovitch, Ran Furman, Dr. Deborah Zamble and Jessica Flood. I am very grateful to Dr. Nigel Robinson and Dr. Kevin Waldron for allowing me to be a squatter in their lab and showing me how to fractionate E. coli for determination of metal speciation and analyzing samples by ICP MS.I would like to thank my family for constant support and sympathy. I would especially like to thank my part time lab partner/ part time husband, Dr Ian Blaby, whose continued support and guidance I could not have done without.
6 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES .......................................................................................................... 10 LIST OF ABBREVIATIONS ........................................................................................... 15 ABSTRACT ................................................................................................................... 17 CHAPTER 1 LITERATURE REVIEW .......................................................................................... 19 Introduction ............................................................................................................. 19 Transition Metals in Biology .................................................................................... 21 Identification of Metal Dependent Proteins ....................................................... 22 The Dynamic Metallome ................................................................................... 26 Allocation of Metals within the Cell ................................................................... 27 Functional potential of transition metals ..................................................... 28 Abundance and availability of transition metals ......................................... 31 Relationship between the Metal Ion and the Protein ........................................ 33 Correct Allocation of Metals within the Cell ............................................................. 36 The G3E Family ............................................................................................... 39 Zinc Homeostasis ................................................................................................... 44 Zinc Transport and Regulators ......................................................................... 47 Zinc efflux ................................................................................................... 47 Zinc uptake ................................................................................................ 49 Zur .................................................................................................................... 50 Bioinformatics and Gene Function Discovery ......................................................... 52 The Functional Annotation Dilemma ................................................................ 53 Comparative Genomics and the Gene Family Approach ................................. 55 Phylogenomics ........................................................................................... 55 Gene neighborhoods ................................................................................. 57 Co occurrence ........................................................................................... 58 Shared regulatory sites .............................................................................. 59 The SEED database and the subsystem based approach ........................ 61 Comparative Genomics and Metals ................................................................. 63 Project Rationale, Design and Objectives ............................................................... 67 2 MATERIALS AND METHODS ................................................................................ 76 Chemicals and Strains ............................................................................................ 76 Materials ........................................................................................................... 76 Strains, Plasmids and Oligonucleotides ........................................................... 77
7 General Growth Conditions ..................................................................................... 77 Media ................................................................................................................ 77 Growth Curves ................................................................................................. 78 Plate Assays ..................................................................................................... 78 Bioinformatic Techniques ........................................................................................ 78 Multiple Sequence Alignments ......................................................................... 78 Subsystems ...................................................................................................... 79 Sequence Analysis ........................................................................................... 79 Phylogenetic Tree Reconstruction .................................................................... 79 DNA Techniques ..................................................................................................... 79 DNA Amplification ............................................................................................ 79 Standard Molecular Cloning ............................................................................. 80 DNA Electrophoresis ........................................................................................ 80 Plasmid Isolation and Transformation .............................................................. 80 Site Directed Mutagensis ................................................................................. 82 P1 Transduction ............................................................................................... 82 Generation of P. aeruginosa Mutants ............................................................... 82 RNA Techniqu es ..................................................................................................... 83 RNA Isolation ................................................................................................... 83 cDNA Synthesis and qRT PCR ........................................................................ 83 Protein Tec hniques ................................................................................................. 84 Protein Overexpression in E. coli ..................................................................... 84 Protein Quantification ....................................................................................... 84 Protein Separation and Chromatography ......................................................... 84 Immunoblotting ................................................................................................. 85 Electrophoretic Gel Shift Assays (EMSA) ......................................................... 86 Preparation of DNA substrate .................................................................... 86 Gel shift assays ......................................................................................... 86 Pyocyanin Assay .............................................................................................. 87 Detection of Hydrogen Production .................................................................... 88 Element Analysis .................................................................................................... 8 8 Sample Preparation .......................................................................................... 88 Anion Exchange Chromatography .................................................................... 88 Size Exclusion Chromatography ...................................................................... 89 ICP MS ............................................................................................................. 89 3 BIOINFORMATIC ANALYSIS OF THE COG0523 FAMILY .................................... 90 Background ............................................................................................................. 90 Results .................................................................................................................... 92 Sequence Attributes ......................................................................................... 92 Comparison with other G3E family members ............................................. 93 Correlation between His stretches and metallochaperone activity ............. 94 Phylogenomic Analysis ..................................................................................... 95 Gene clustering .......................................................................................... 95 Phylogenetic reconstruction ....................................................................... 96 Zur regulated COG0523 proteins subgroups 1, 5 and 13 ....................... 99
8 The nitrile hydratase activator subgroup subgroup 2 .............................. 99 The CobW subgroup subgroup 12 ........................................................ 100 COG0523 proteins in Archaea ................................................................. 100 COG0523 proteins in Eukarya ................................................................. 101 Discussion ............................................................................................................ 102 Conclusions .......................................................................................................... 106 4 INVESTIGATION INTO THE FUNCTION OF THE UNCHARACTERIZED GENE YEIR ..................................................................................................................... 116 Background ........................................................................................................... 116 Results .................................................................................................................. 118 EDTA Sensitivity ............................................................................................. 118 Rescue of EDTA Growth Defect by Zinc ........................................................ 121 Cadmium Sensitivity ....................................................................................... 122 Effect of Amino Acid Substitutions on the Activity of YeiR, in Vivo ................. 123 ICP MS Analysis ............................................................................................ 124 Hydrogenase activity ................................................................................ 126 Glyoxalase I activity ................................................................................. 126 Discussion and Conclusions ................................................................................. 127 5 PARALOGS OF ZINC DEPENDENT PROTEINS ................................................ 155 Background ........................................................................................................... 155 Results .................................................................................................................. 159 Putatively Zur Regulated Paralogs with Conserved Zinc Binding Residues ... 159 PyrC ......................................................................................................... 160 QueD ....................................................................................................... 162 Zur Regulated Paralogs without the Canonical Zinc Binding Residues ......... 163 Cam ......................................................................................................... 163 HemB ....................................................................................................... 164 DksA ............................................................................................................... 164 Complementation of the dksA deletion of E. coli by the dksA2 of P. aeruginosa ............................................................................................ 165 Complementation of a P. aeruginosa dksA mutant by dksA2 .................. 166 dksA2 is regulated by zinc through Zur .................................................... 167 Deletion of dksA2 results in a growth defect in the presence of metal chelators ............................................................................................... 169 Discussion and Conclusions ................................................................................. 170 Backup Proteins ............................................................................................ 170 DksA ............................................................................................................... 171 6 SUMMARY AND OVERALL CONCLUSIONS ...................................................... 189 APPENDIX A SUBSYSTEMS ..................................................................................................... 193
9 B DETAILED DESCRIPTION OF COG0523 GENE CLUSTERS ............................. 200 C COG0523 DISTANCE TREE ................................................................................ 217 D PROTEIN IDENTIFIERS AND GENE ABBREVIAITONS ..................................... 218 E ANALYSIS OF PUTATIVELY ZUR REGULATED PARALOGS ........................... 223 AmiA ..................................................................................................................... 223 HisI ........................................................................................................................ 223 CysRS and ThrRS ................................................................................................ 224 FolE ...................................................................................................................... 224 F STRAINS, PLASMIDS AND OLIGONUCLEOTIDES ............................................ 232 LIST OF REFERENCES ............................................................................................. 238 BIOGRAPHICAL SKETCH .......................................................................................... 281
10 LIST OF TABLES Table page 3 1 Co occurrence profil e of ureE and UreG His stretch. ....................................... 109 B 1 Subgroup 2. ...................................................................................................... 200 B 2 Genomes that cont ain the subgroup 3 gene cluster. ........................................ 201 B 3 Genomes that contain the subgroup 4 gene cluster. ........................................ 202 B 4 Genomes that contain the subg roup 5 gene cluster. ........................................ 203 B 5 Genomes that contain the subgroup 6 gene cluster. ........................................ 205 B 7 Genomes containing subgroup 8 gene cluster. ................................................ 207 B 8 Genomes containing subgroup 9 gene cluster. ................................................ 208 B 9 Genomes containing subgroup 10 gene cluster. .............................................. 210 B 10 Genomes containing subgroup 11 gene cluster. .............................................. 211 B 11 Genomes containing subgroup 12. ................................................................... 212 B 12 Genomes containing subgroup 13 gene cluster. .............................................. 213 B 13 Genomes containing subgroup 14 gene cluster. .............................................. 214 B 14 Genomes containing subgroup 15 gene cluster. .............................................. 216 D 1 Proteins used in COG0523 amino acid conservation analysis. ........................ 218 D 2 Gene abbreviations for Figure 32. ................................................................... 219 D 3 Proteins used in COG0523 phylogenetic tree reconstruction ........................... 220 F 1 Strains used in Chapter 3. ................................................................................ 232 F 2 Strains used in Chapter 4. ................................................................................ 233 F 3 Plasmids used in Chapter 3. ............................................................................. 234 F 4 Plasmids used in Chapter 4. ............................................................................. 234 F 5 Oligonucleotides used in Chapter 3. ................................................................. 235 F 6 Oligonucleotides used in Chapter 4. ................................................................. 236
11 LIST OF FIGURES Figure page 1 1 Typical coordinatio n geometry involving metal ions ........................................... 70 1 2 Organization of the hyp and ure gene clusters ................................................... 71 1 3 The G3E family of GTPases ............................................................................... 72 1 4 General schematic of phylogenomic analysis ..................................................... 73 1 5 Schematic of common comparative genomic approac hes to prediction gene function ............................................................................................................... 74 1 6 Scree nshot of a subsy stem from SEED ............................................................. 75 3 1 COG0523 amino acid conservation plot ........................................................... 108 3 2 Phylogenomic analysis of COG0523 ................................................................ 110 3 3 Genome context of predict ed nitrile hydratase activators ................................. 111 3 4 Genome context of subgroup 12 members ...................................................... 112 3 5 Genome context of subgroup 13 members ...................................................... 113 3 6 Phylogeny of eukaryotic COG0523 members .................................................. 114 3 7 Genome context of subgroup 5 members ........................................................ 115 4 1 Phylogenetic tree reconstruct ion of chosen COG0523 subgroups .................. 134 4 2 Growth curves of E. coli MG1655 (WT) and yeiR strains grown in LP medium without or with 1.3 mM EDTA ............................................................. 135 4 3 Growth curves of E. coli MG1655 (WT) and yeiR strains grown in LP medium with a range of EDTA concent rations ................................................. 136 4 4 Manual growth curves ..................................................................................... 137 4 5 Growth curves of the znuABC ::cam and znuABC ::cam yeiR mutants grown in LP medium without or with 20 M EDTA ........................................... 138 4 6 Growth curves of the znuABC ::cam and znuABC ::cam yeiR mutants grown in LP medium with a range of EDTA concentrations ............................. 139 4 7 Optical density (OD; measured at 600 nm) of cultures .................................... 140 4 8 Rescue of the yeiR strain EDTA sensitive growth defect by zinc.. ................. 141
12 4 9 Result of adding EDTA and metal to medium ................................................... 142 4 10 Effect of cadmium on growth ............................................................................ 143 4 11 Partial rescue of the cadmium sensitive growth defect of the yeiR strain with zinc or manganese. .......................................................................................... 144 4 12 Suppression o f cadmium toxicity with zinc ....................................................... 145 4 13 Addition of cobalt, copper, nic kel or iron plus cadmium on the growth of the yeiR strain in LP medium ............................................................................... 146 4 14 Effect of cadmium on growth of znuABC ::cam strains .................................... 147 4 15 Protein sequenc e alignment of COG0523 proteins ......................................... 148 4 16 Effect of C63MCC66 mutations on the ability of the corresponding gene to complement the deletion of yeiR ...................................................................... 150 4 17 Effect of H207XHXH211 mutations on the ability of the corresponding gene in trans to complement the deletion of yeiR ......................................................... 151 4 18 Native tw o dimensional separation analy zed by ICP MS for five elements ..... 152 4 19 Native two dimensional separation analyzed by ICP MS for zinc and nickel.. .. 153 4 20 Assay of hydrog enase and glyoxalase I activity ............................................... 154 5 1 Representative gene clusters composed o f Zur regulated COG0523 members .......................................................................................................... 175 5 2 Phylogenetic and sequenc e analysis of the PyrC paralogs .............................. 176 5 3 Phylogenetic and sequence analysis of the QueD paralogs ............................. 177 5 4 Proteins with homology to the DksA protein of E. coli are found with and w ithout the Cys4 Znfinger motif ...................................................................... 178 5 5 Cys4 Zn finger domain of E. coli DksA and h omologs from P. aerginosa ........ 179 5 6 Rescue of E. coli dksA ::tet phenotype ............................................................ 180 5 7 Complementation of P. aeruginosa dksA with dksA2 in trans ...................... 181 5 8 Suppression of P. aeruginosa dksA growth defect. ........................................ 182 5 9 Complementation of the dksA2 ::GmR mutant with d ksA2 in trans ................ 183 5 10 Pyocyanin defect of P. aeruginosa dksA is rescued by expression of dksA2 184
13 5 11 Transcript abundanc e of PA dksA and dksA2 and protein abundance of PA DksA and DksA2 .............................................................................................. 185 5 12 Effect of zur deletion of the transcript abundance of dksA2 and protein abundance of DksA2.. ...................................................................................... 186 5 13 Complex formation between the upstream DNA region of dksA2 and purified His6Zur ............................................................................................................ 187 5 14 Growth defect of P. aeruginosa dksA2 in the presence of EDTA or TPEN. ... 188 A 1 Comparative genomic analysis of ureG containing gene clusters. ................... 195 A 2 Gene clus tering of hypB, ureG and meaB with their target metalloen zyme or other accessory factors .................................................................................... 196 A 3 Gene clusters involving COG0523 genes in bacterial genomes. ...................... 197 A 4 Gene clusters involving COG0523 genes in archaeal genomes. ...................... 198 A 5 Eukaryotic genomes that contain COG0523 genes. ......................................... 199 B 1 Genome context of subgroup 3 members ........................................................ 201 B 2 Genom e context of subgroup 4 members ........................................................ 202 B 4 Genom e context of subgroup 6 members ........................................................ 204 B 5 Genom e context of subgroup 7 members ........................................................ 205 B 6 Genom e context of subgroup 8 members ........................................................ 206 B 7 Genome context of subgroup 9 members ........................................................ 208 B 8 Genome context of subgroup 10 members ...................................................... 209 B 9 Genome context of subgroup 11 me mbers ...................................................... 211 B 10 Genome context of subgroup 14 members ...................................................... 214 B 11 Genome context of subgroup 15 members ...................................................... 215 C 1 Phylogenetic reconstruction of selected COG0523 proteins. ........................... 217 E 1 Phylogenetic and sequence analysis of the AmiA paralogs ............................. 225 E 2 Sequence and phylogenetic analysis of HisI paralogs ...................................... 226 E 3 Sequence and phylogenetic a nalysis of CysRS paralogs ................................. 227
14 E 4 Sequence and phylogenetic analysis of ThrRS paralogs ................................. 228 E 5 Amino acid sequence comparison between the FolE from H. sapiens and cyanobacterial genomes .................................................................................. 229 E 6 Amino acid sequence alignment between the class carbonic anhydrase s .... 230 E 7 Protein s equence alignment HemB proteins .................................................... 231
15 LIST OF ABBREVIATION S % percent (I ) oxidation state of 1+ (II) oxidation sta te of 2+ (III) oxidation state of 3+ mAmp mili Amplitude BLAST Basic Local Alignment Search Tool C Degrees Celsius Co Cobalt CO2 Carbon dioxide COG Cluster of Orthologous Groups Cu Copper Da Dalton (atomic mass unit) DTT Dithiothreitol DMSO Dimethyl sulf oxide EDTA Ethylenediaminetetraacetic acid Fe Iron FLP Flippase FRT Flippase Recognition Target g gram GTP Guanosine 5 triphosphate HEPES 4 (2 hydroxyethyl) 1 piperazineethanesulfonic acid Hg Mercury hrs hours ICP MS Inductively Coupled PlasmaMass Spectr ometry (Spectrometeter)
16 IPTG Isopropyl D 1 thiogalactopyranoside kDa kilo Dalton L Liter M Molar min minute mg milligram Mn Manganese Mo Molybdenum N Normal NaOH Sodium hydroxide Ni Nickel NTP Nucleoside triphosphate PAGE Polyacrylamide gel electrophoresis Pb Lead RNAP RNA polymerase SDS S odium dodecyl sulfate TPEN N N N,N Tetrakis(2 pyridylmethyl) ethylenediamine UV Ultraviolet V Volt v/v volume per volume WT Wild type w/v weight per volume Zn Zinc
17 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 LINKING GENE WITH FUNCTION: ANALYSIS AND INVESTIGATION OF NOVEL PLAYERS IN BACTERIAL ZINC HOMEOSTASIS By Crysten Elizabet h Blaby Haas May 2011 Chair: Valrie de Crcy Lagard Major: Microbiology and Cell Science When deprived of the essential trace nutrient zinc, bacteria are known to adapt by increasing the intracellular concentration of zinc through transport or by lower ing the zinc quota of the cell through the use of zinc independent back up proteins. These mechanisms were discovered by functional and computational analyses of Zur regulons. A recent computational analysis of Zur regulons from newly sequenced genomes sug gested the existence of genes in addition to those presently known that may be involved in the adaptive response to zinc depletion. Of these novel genes the role of COG0523 genes and paralogs of zinc dependent proteins are investigated and discussed. COG05 23 proteins are, like the nickel chaperones of the UreG and HypB families, part of the G3E family of GTPases, strongly suggesting a link to metallocenter biosynthesis. Even though the first COG0523 encoding gene, cobW was identified almost 20 years ago, l ittle is known concerning the function of this ubiquitous family. Therefore, a phylogenomic study of the COG0523 family was performed, leading to the separation of the family into fifteen subgroups. To further probe the function of the COG0523 family, yeiR from Escherichia coli was chosen to test the apparent link
18 between some COG0523 genes and zinc homeostasis. T his previously uncharacterized gene was found to be involved in survival during EDTA or cadmium challenge and was linked to optimal growth during zinc depletion In addition to the canonical DksA protein, the Pseudomonas aeruginosa genome encodes a closely related paralog DksA2 that lacks the Znfinger motif and whose gene was predicted to be regulated by Zur. A study on the role of dksA2 and verifi cation of its regulation by zinc and Zur was performed. d ksA2 was found to be able to functionally substitute for the canonical dksA in vivo Expression was repressed by the presence of exogenous zinc, deletion of Zur resulted in constitutive expression, and Zur bound specifically to the upstream region of dksA2 T his data suggests that DksA2 plays a role in zinc homeostasis and serves as a back up copy of the canonical zinc dependent DksA in zinc poor environments.
19 CHAPTER 1 LITERATURE REVIEW Introduction It is estimated that twenty elements are required for life and that these elements were likely required by primitive life (Williams, 1997) Traditionally, biology students are taught the importance of the organic elements, carbon, hydrogen, nitrogen, oxygen, phosphorous and sulfur, with little mention of the inorganic elements, especially transition metals that are also of great importance. With the exception of iron, these metals are often found in trace amounts, causing their identification and characterization in cells difficult. For instance, the requirement of nickel by a protein was not recognized until 1975 (Dixon et al. 1975) and it wasnt unti l 2010 that researchers found that at least onethird of metal bound proteins in the cell are uncharacterized or mischaracterized (Cvetkovic et al. 2010) Because of the breadth and importance of metals in biology and implications on health, the study of these protein cofactors has called upon multiple disciplines ranging from physical to biological sciences. Inorganic c hemists, biochemists, biologists and bioinformaticians have all added their particular expertise and personal perspective on the use and evolution of these elements in biology. Organic chemists seek understanding through the creation of synthetic analogs o f biomolecule metal sites. Biochemists strive to understand reaction mechanisms. Biologists aspire to understand homeostasis and how the geological history of earth has shaped life. In the last decade, the benefit of bioinformatics to the study of metals i n biology has also become apparent. By drawing upon accumulated experimental and genomic data, the field of bioinformatics has generated new avenues of research.
20 Trace elements and their bioavailability across geological time have undoubtedly had a large impact on the evolution of life. Sometimes complicated and intricate machinies have had to evolve to carefully control their concentration and location within the cell. Many of these metals are essential but at the same time high concentrations can be toxi c; maintenance of their concentration within a defined window is essential. The details concerning these homeostatic systems are only now being addressed and many questions remain to be answered. In addition, mechanisms are being discovered that are causing researchers to reevaluate some of the assumed interactions bet ween metals and life processes. In the last decade, researchers discovered that like the more toxic metals iron and copper, the intracellular concentration of zinc in bacteria is highly regulated and a free pool of zinc does not exist. This conclusion indicates that once imported zinc is immediately bound to proteins or small molecules. Therefore, an open question with regard to zinc metabolism is how are newly synthesized proteins able to ac quire zinc? This question has spurred an investigation into how zinc is trafficked within the cell and if a hierarchy of metal acquisition exists under conditions where zinc is limiting. The discovery of metal trafficking chaperones at the end of the 20th century has spurred a renewed interest in metallocenter biosynthesis. Are all metals trafficked within the cell by metal specific chaperones? Do all metal dependent enzymes have an affiliated chaperone to aid in metal acquisition? Simple questions such as to the intracellular concentration of metals and the abundance of metal dependent proteins in the cel l are just now being addressed.
21 The biology of essential and nonessential trace mineral elements with special attention on zinc is the topic of this review. The current understanding on why the activity of some proteins is absolutely dependent on the presence of a metal ion and how proteins acquire that specific metal to the exclusion of others will be covered. Lastly, the contribution of bioinformatics to the understanding of gene function and how that relates specifically to metal metabolism will be discussed. The ability of bioinformatics to look at all genomes simultaneously has had and will continue to have an impact on uncovering the answers to open questions concerning metal metabolism in prokaryotes. In particular, a combination of bioinformatics with more traditional molecular biology approaches has opened the door to a revolution in the understanding of metals in biology. Transition Metals in Biolog y The period four transition metals cobalt, copper, iron, manganese, nickel and zinc play important roles in chemical reactions that are requisite for known life. A recent and popular estimate suggests that at least onethird of all proteins are metalloproteins and as such require a metal cofactor for either maintenance of structure, catalysis or regulation (Tottey et al. 2007) This and similar estimates are based mainly on surveys of three dimensional structures that take i nto account the presence of the nontransition metals, calcium and magnesium (Andreini et al. 2008b) A recent bioinformatic analysis suggests that zinc, non heme iron and copper proteins constitute roughly 10% of bacteri al and eukaryotic proteomes and 13% of archaeal proteomes (Andreini et al. 2006, Andreini et al. 2007, Andreini et al. 2008a) All six Enzyme Commission classes contain proteins that are strictly dependent on the presence of a transition metal cofactor (Andreini et al. 2008b)
22 The prevalence of each metal in catalysis differs among the enzyme classes and can also vary from one organism to the next. Currently, iron and zinc are the most prevalent transition metal cofactors in nature (Andreini et al. 2008b) Only a handful of nickel dependent enzymes are known (Dixon et al. 1975, Drake et al. 1980, Ellef son et al. 1982, Moura et al. 1984, Youn et al. 1996, Clugston et al. 1998) Specifically, higher organisms such as plants encode only one known nickel dependent enzyme, urease (Gerendas et al. 1999) ; a nickel dependent protein is yet to be discovered in vertebrates (Zhang et al. 2009) Roughly twenty manganese dependent enzymes and several corrin, noncorrin and porphyrinbound cobalt d ependent enzymes are also known (da Silva and Williams, 2001) A comprehensive understanding on the extent to which metal s are used in biology will certainly increase as techniques are developed to directly survey the proteome and thereby lead to the discovery of novel metalloproteins. Identification of Metal Dependent Proteins The seminal studies on the metalloproteomes of Synechocystis PCC 6803 and Pyrococcus furiosis highlight the feasibility and richness of such analyses (Tottey et al. 2008, Cvetkovic et al. 2010) Under nondenaturing conditions, the proteome of a cell can be fractionated by liquid chromatography and subsequently analyzed for metals by inductively coupled plasma mass spectrometry (ICP MS). By coupling this technique to high throughput tandem mass spectrometry (HT MS/MS), 158 potentially novel metalloproteins were identified in P. furiosis (Cvetkovic et al. 2010) Additionally, metals were found that were previously not known t o be incorporated by this organism, or the metal bound to specific proteins was different from the metal predicted based on sequence similarity.
23 These ICP MS techniques have the benefit of identifying the native metal cofactor, which is often not obvious. Two hurdles currently exist in identifying metalloproteins: cambialism and reliability on sequence homology to characterized metalloproteins to predict metal dependence. Several enzymes are cambialistic (Martin et al. 1986) which means that in vitro they display comparable activity with more than one metal, leading to ambiguity as to the native in vivo cofactor (Neu, 1967, Rajagopalan et al. 1997, D'souza and Holz, 1999, Proudfoot et al. 2004, Zheng et al. 2005) This ambiguity is compounded as in some cases, cambialism is a true mechanism to ensure enzyme activity under metal deficient growth conditions (Yee and Morel, 1996) In other cases, an enzyme purified under nonnative conditions will co purify with the wrong metal and/or in vitro ex periments will show that multiple metals can activate the enzyme. A prime example is the identification of the native cofactor of the class carbonic anhydrases. The prototype of this class is from the anaerobic prokaryote Methanosarcina thermophila. The X ray structure of this enzyme, purified aerobically in Escherichia coli revealed the presence of a zinc ion (Kisker et al. 1996) and dependence on zinc was also verified in vitro (Alber et al. 1999) These results were expected as carbonic anhydrases from the other known classes are classic zincdependent enzymes (Christianson and Fierke, 1996) However, when the enzyme was recons tituted with iron, activity exceeded that of the zinc form (Tripp et al. 2004) and when purified natively from M. thermophila it contained iron, not zinc (Macauley et al. 2009) Therefore, the class of carbonic anhydrase s is most certainly composed of iron dependent enzymes. As the vast majority of metalloenzymes are over expressed
24 and purified under non native conditions, usually in E. coli, identification of the wrong metal is a real conc ern (Jacob et al. 1998) The second hurdle to cofactor identification is that sequence similarity is not necessarily reliable for assigning a speci fic metal to a metalloprotein, although attempts are frequently made (Zhang and Gladyshev, 2009, Zhang and Gladyshev, 2010) The ArsR/SmtB family of metal proteins is a key example of the unreliability of sequence homology. This family is composed of metal sensing transcription factors that affect the transcription of target genes based on the concentration of a specific metal in the cell (reviewed in (Busenlehner et al. 2003) ). ArsR/SmtB homologs form eight distinct groups based on overall sequence similarity, however, membership in a group does not correlate with the specific metal sensed (Campbell et al. 2007) For instance, the cadmium sensing regulators from Firmicutes have higher overall similarity to the arsenic sensing regulators of Firmicutes than to cadmium sensing regulators from other organisms. The only way to correctly predict which metal is bound is by the detection of specific sensory motifs (Campbell et a l. 2007) Motif searching is not a standard protocol in the annotation of genomes. Therefore, it is easy to see how misannotations in databases arise. However in some cases, even motifs are not sufficient in predicting the in vivo cofactor. Two differen t enzymes can have the same metal binding motif but the native metal cofactor is different, as is the case for MncA and CucA in Synechocystis PCC 6803. The metal binding ligands are exactly the same in each protein but manganese is the in vivo cofactor of MncA and copper is the in vivo cofactor of CucA (Tottey et al. 2008)
25 To a certain extent, assignment of metal cofa ctors by sequence similarity and motifs can be strengthened by other comparative genomic techniques such as cooccurrence with the necessary metal transporters or by the presence of regulatory sites upstream of the corresponding gene (Zhang et al. 2009, Rodionov e t al. 2006b) If a protein is predicted to bind cobalamin based on sequence similarity but both known cobalamin transporters and biosynthetic pathways are missing from that organism, then most likely the protein is not dependent on cobalamin. Targeted ex perimental verification of this discrepancy can led to either identification of a novel cofactor or novel transporters. A better understanding of how metal allocation is dictated should translate into improved predictive tools. Based on the fundamental is sues in the identification of metals in biology, metalloproteomic approaches such as those discussed above will inevitably advance the communitys understanding of metal speciation (i.e. identity and abundance of metal complexes) by providing vital clues as to the identity of metalloproteins and their native cofactors. Unfortunately, like most highthroughput techniques, metalloproteomic approaches give only a snapshot of the cells constituents. The abundance and identity of a cells metalloproteins are dy namic and in constant flux. Microorganisms are continually faced with varying environmental conditions and the cells response to each situation can be drastically different, resulting in induction and/or repression of different gene sets. These gene sets may be composed of different types of metal dependent proteins. Additionally, introduction to a novel environment can result in the need to adapt to a different bioavailbility of metal ions.
26 The Dynamic Metallome The metabolic state of the cell and metal availability contribute to a dynamic view of the metallome (element composition of the cell). The specific growth conditions of the cell can have a large impact on the abundance of metalloproteins and consequently the abundance of metals in the cell; the needs of the cell will determine the presence and abundance of certain metal dependent proteins. In particular, the absence of oxygen appears to have a major impact on the metallome of E. coli leading to increases in copper and nickel accumulation (Outten et al. 2001b, Rowe et al. 2005) Anaerobic growth of E. coli leads to production of [NiFe] hydrogenase (Ballantine and Boxer, 1985) and induction of nickel import (Rowe et al. 2005) Previous work has also shown that anaerobic E. coli cells accumulate 20fold higher copper than aerobically grown cells (Outten et al. 2001b) Perhaps, this phenomenon is due to reduction of copper to Cu(I) under anaerobic conditions, which can more easily diffuse through the membrane (Rensing and Grass, 2003) The availability of a specific metal in the environment can also lead to a change in the metall ome beyond a decrease or increase of that metal. The activity of multiple metalloproteins (many of which are essential proteins) is strictly dependent on the presence of a metal and in most cases a specific metal. Mechanisms have evolved that allow the cel l to switch between metal cofactors (by switching metalloprotein use) to carry out a specific reaction depending on the availability of that metal in the environment. The genomes of some organisms encode at least two proteins that can catalyze the same rea ction but employ different metals (Merchant et al. 2006, Panina et al. 2003) During ironlimitation, manganese dependent superoxide dismutase (MnSOD) can take the place of irondependent superoxide dismutase (FeSOD)
27 (Niederhoffer et al. 199 0) During copper limitation, iron dependent cytochrome c6 can replace copper dependent plastocyanin (Merchant and Bogorad, 1986b) Backup enzymes have also been described for reactions that are dependent on cobalt (Rodionov et al. 2003) nickel (Kim et al. 2000) molybdenum (Jacobitz and Bishop, 1992) and zinc (Gabriel and Helmann, 2009, Sankaran et al. 2009) Therefore, limitation of on e metal can lead to a drastic difference in the profile of metals in the cell. Comparative metallomics is a recently coined term that refers to an emerging field focused on the qualitative and quantitative measurement of a cells metallome under different growth conditions (Szpunar, 2004) This approach can also be applied to assaying the difference between a mutant and the isogenic parent. Currently, due t o technical limitations these studies have focused on measuring total metal content. Currently, the scientific breakthroughs are in simply discovering the identity of metalloproteins and the native cofactor under standard laboratory conditions. As the fiel d progresses, comparative metallomics will likely become a feasible and routine approach in the same way the use of DNA microarrays and comparative transcriptomics have become routine for many research groups. Allocation of Metals within the Cell The exist ence of metallloprotein back up copies underscores the redundancy of metal catalyzed chemistry; two metals can catalyze the same reaction. Except for the characterized cases on cambialism, metalloproteins, however, are generally specific to one metal or the other. Even when a protein is genuinely cambialistic, not all metal ions are sufficient for activity and a spectrum of activity is observed from one metal to another. The carbonic anhydrase from M. thermophila has the highest activity with iron, followed by cobalt then zinc; the presence of copper, manganese, nickel and cadmium
28 result in less than 10% activity (Tripp et al. 2004) Superoxide dismutase has two well characterized isoforms, MnSOD and FeSOD; manganese substituted FeSOD (Yamakura, 1978, Yamakura and Suzuki, 1980) and ironsubstituted MnSOD (Ose and Fridovich, 1979, Yamakura et al. 1995) retain little or no enzyme activity. Why proteins have evolved to use a particular metal cofactor appears to be governed by three criteria: 1) functional potential, 2) abundance, and 3) availability. The most important is functional potential as certain metals will only catalyze certain reactions. As catalytic redundancy among various metals does exist, speciation of metals throughout life appears to have been prejudiced by the abundance and availability of one metal over an analogous metal in the environment. Abundance and availability are not synonymous. A metal ion may be highly abundant in an environment but not available to an organism. A difference in oxidation state can render a metal ion water soluble or insoluble and therefore available or not as a protein cofactor. Functional potential of transition metals Generally, metal ions that can easily change oxidation states are important in electron transfer and redox reactions (cobalt, copper, iron, manganese and nickel), while zinc is commonly found serving as a Lewis acid or structural cofactor. Zinc with a full d orbital does not readily accept or donate electrons and as such only one oxidation state is found in nature. Indeed according to the International Union of Pure and Applied Chemistry definition, zinc is not considered a transition metal (McNaught and Wilkinson, 1997) The uniqueness of zinc among the d block elements is epitomized by the century old debate of where zinc belongs in the periodic table (Jensen, 2003) As a catalytic cofactor, zinc is generally only found in enzymes that catalyze non redox reactions such as hydrolases. Zinc commonly activates water or substrates
29 leading to an increase in acidity, nucleophilicity or nucleophilicity and electrophilicity (Vallee and Auld, 1990, Andreini et al. 2008b) In zinc dependent carbonic anhydrase, zinc facilitates the formation of a zinc bound hydroxide ion which is able to attack carbon dioxide ultimately converting it to bicarbonate (Lindskog and Coleman, 1973) In the majority of cases, the functional group is a zinc bound hydroxide but zinc has also been found to activate thiols for nucleophilic attack (Myers et al. 1993, Hightower and Fierke, 1999, Peariso et al. 1998) In both cobalamin dependent and independent methionine synthase, a m ethyl group from methyltetrahydrofolate is transferred to homocysteine to form methionine. The zinc in both enzymes binds to the sulfur group of homocysteine increasing the nucleophilicty of the thiolate group, which then abstracts a methyl group from the methyl donor resulting in methionine (Peariso et al. 1998, Koutmos et al. 2008) Copper and nickel are comparable Lewis acids to zinc but zinc predominates as the Lewis acid of choice for most proteins (Andreini et al. 2008b) The preference for zinc over copper or nickel could be due to the propensity of the later metal ions to change oxidation states and cause the generation of free radicals (Gutteridge and Wilkins, 1983, Torreilles and Gurin, 1990) Most likely due to a relative nontoxic nature, zinc was found to be one of the most abundant metals in enzymes annotated as such in public databases (second only to magnesium) (Andreini et al. 2008b) The absence of redox chemistry could also explain the predominance of zinc in structural sites, which enable otherwise thermodynamically unfavorable protein folds such as the zinc finger (Berg and Shi, 1996, Reddi and Gibney, 2007)
30 Cobalt, copper, iron, manganese and nickel have partially filled d electron orbitals. This characteristic permits energetically favorable oxidation or reduction of substrates; they are also occasionally found serving as Lewis acids. Iron and copper are commonly used in biological systems that require the transfer of electrons. A wire of three FeS clusters present in [NiFe] hydrogenase is responsible for the transfer of electrons between an electron donor (or acceptor) and the active site of the protein (Volbeda et al. 1995) The active site where oxidation of H2 (or reduction of H+) occurs is deeply buried within the protein (Volbeda et al. 1995) Three FeS clusters are proposed to enable sequential transfer of electrons between the active site and the protein surface (Volbeda et al. 1995) At the proteins surface electrons are transferred to a redox partner (Yagi, 1970, Fritz et al. 2001) While cobalt, copper, iron, manganese and nickel can all participate in redox reactions, these metals do differ in redox potential and vary in the types of group tra nsfer reactions usually catalyzed. The redox potential of the Cu(II)/ Cu(I) pairs in enzymes is between 0.25 and 0.75 V, while Fe(III)/ Fe(II) is 0.5 to 0.6 V (Crichton and Pierre, 2001) Man ganese and iron are preferred in the transfer of oxygen atoms, while cobalt and nickel are more suited to transfer methyl groups (da Silva and Williams, 2001) The choice of metal ion is also determined by other chemical characteristics such as lability. Cobalt is rarely found in biology outside of a corrin ring (referred to as cobalamin or B12). Oxidation of Co(II) to Co(III) can be deleterious to protein activity; Co(III) is kinetically inert and therefore does not readily bind or release groups (e.g. substrate) (Werner, 1913) The corrin ring of cobalamin, however, is able to perturb the
31 chemical properties of Co(III) and ligand exchange is relatively fast (Marques and Knapton, 1997) Incorporation of cobalt (outside of a corrin ring) into an active site is rarely observed in nature, especially when other metals can catalyze the same reaction without the risk of protein inactiv ation. An interesting exception in the cobalt type of nitrile hydratase that has a noncorrin Co(III) in the active site (Brennan et al. 1996) As wit h the corrin ring, perhaps the polypeptide chain of nitrile hydratase is able to advantageously perturb the chemical properties of Co(III) (Shearer et al. 2001) Abundance and availability of transition metals Copper is also commonly found as a cofactor i n electrontransfer proteins, however, iron and not copper is the cofactor used in the characterized hydrogenases. In general, iron is one of the most prevalent metal cofactors. This observation is due to the second and third metal preference criteria: abundance and availability. The abundance and availability of metal ions is thought to have had a large impact on metal speciation throughout the domains of life (Williams, 1997) Iron is the most common redox active metal cofactor found in proteins (Andreini et al. 2008b) because it was proposed that early life evolved under anaerobic conditions (Oparin, 1938) Water soluble Fe(II) was plentiful but the majority of copper was found in the water insoluble Cu(I) form (Crichton and Pierre, 2001) Therefore, life evolved with iron and not copper. As atmospheric dioxygen content increased, Fe(II) was gradually oxidized to the water insoluble Fe(III) form and Cu(I) was oxidized to the water soluble Cu(II) form. Therefore, copper containing proteins are thought to have evolved only after the emergence of dioxygen (E gami 1975) These two metals can catalyze the same reactions but, although iron is currently less bioavailable, copper cannot simply replace iron in proteins. Due to the unfortunate
32 predominance and dependence on iron as a protein cofactor, life had to compensate. A popular str ategy for microorganisms is the use of siderophores, which successfully compete with hydroxyl ion for Fe(III) (Neilands, 1995) Under some circu mstances, copper proteins eventually evolved and replaced irondependent analogs, such as found for diatoms (Peers and Price, 2006, Strzepek and Harrison, 2004) The availability for copper is higher relative to ir on in open oceanic waters (Bruland, 1980) The low zinc concentration in these waters has also led to unusual metal dependencies such as the use of cobalt or cadmium instead of zinc in carbonic anhydrase (Yee and Morel, 1996, Xu et al. 2008) and calcium instead of zinc in alkaline phosphatase (Kathuria and Martiny, 2011) Nickel and cobalt dependent enzymes are relatively rare. The modern day existence of these enzymes is thought to be a remnant from the Archaean era, which was dominated by methanogens and preceded the catastrophic oxidation event roughly 2.4 Gyr (gigayear; 109 years) ago (Bekker et al. 2004, da Silva and Williams, 2001) At the end o f the Archaean era, nickel abundance diminished presumably due to reduced volcanic activity, and this event is proposed to have precipitated a decline of methanogens and the rise of atmospheric oxygen (Konhauser et al. 2009) Cobalt is mainly found bound in the form of B12, biosynthesis of which is thought to have evolved 2.7 3.5 Gyr ago (Scott, 1993) In several systems, dependence on these metals has become redundant by the more recent evolution of analogous enzymes with different metal cofactors. For instance, B12dependent enzymes appear to have been lost by all land plants, most unicellular eukaryotes and insects (Zhang et al. 2009) For
33 methionine synthesis, these organisms encode a cobabalinindependent methionine synthase (Ravanel et al. 1998, Matthews et al. 2003, Gophna et al. 2005) In general, selection of a particular metal cofactor has been based on the principle of economical utilization of resourc es as described by da Silva and Williams (da Silva and Williams, 2001) This principle describes that a metal, which can perform the necessary function, is chosen based on cost, in terms of energy, required for uptake from the environment. The distribution of metals today is the result of billions of years of evolution under various and changing selective conditions that re flect the changing geochemistry of Earth. Relationship between the Metal Ion and the Protein Metalloproteins have evolved to specifically bind and harness the chemical reactivity of a particular metal ion. Several theories govern the selectivity and speci ficity of amino acid ligands for a metal ion. The hard and soft acids and bases principle from Parr and Pearson describes how soft Lewis bases and acids will form complexes, while hard Lewis bases will pair with hard acids (Parr and Pearson, 1983) For metal ligand interactions, metal ions are Lewis acids with hard (Fe(III) and Co(III)), intermediate (Fe(II), Co(II), Ni(II), Cu(II) and Zn(II)) or soft (Cu(I)) characteristics. Accordingly, the side groups of several amino acids can act as Lewis bases and are commonly found bound to met al ions: the imidazole of histidine, the thiolate of cysteine, the carboxylate of aspartic acid and glutamic acid, the phenoxide of tyrosine, and the thioether of methionine. The intermediate Lewis acid imidazole of histidine is the most common metal bindi ng residue followed by the soft base side group of cysteine (Rulsek and Vondrsek, 1998)
34 Metal ions can be divided into two classes; 1) the imidazole class includes manganese, cobalt and iron, and 2) the sulfur class includes nickel, zinc and copper (Zheng et al. 2008) Both groups are fou nd to interact mainly with oxygen, nitrogen and sulfur side groups of amino acids with a preference for the imidazole group of histidine (Zheng et al. 2008) The sulfur class in addition to preferring imidazole, also shows a preference for thiol side groups, and the imidazole class also shows preference for the side groups of aspartic and glutamic acid (Zheng et al. 2008) In addition to an observed preference for a type of ligand, metal i ons also prefer to bind to a particular number of ligands (determined by the coordination number, CN) and for those ligands to bind to the metal with a specific orientation (referred to as coordination geometry) (Figure 11). Surveys of metalloprotein X ra y structures have led to insights into these partialities (Harding, 1999, Harding, 2004, Dudev et al. 2006, Zheng et al. 2008) Co(II) and Ni(II) are commonly found in an octahedral arrangement (CN=6); Zn(II) ion s are found in tetrahedral arrangements (CN=4) while Cu(II) ions are commonly found in square planar arrangements (CN=4) (Rulsek and Vondrsek, 1998) The protein does not simply provide a scaffold to which a metal can bind. The chemical properties of a metal ion can be influenced and finetuned by the bound protein. The polypeptide provides a more or less rigid structure where the metal binding residues are fixed in space and the coordination geometry can be distorted relative to what is preferred by the metal. The classic example of distorted coordination geometry is plast ocyanin from plants (Katoh and Takamiya, 1961, Katoh et al. 1961) These proteins are often referred to as blue copper proteins because when the copper ion is
35 oxidized, it is an intense blue color (Katoh, 1960) Plastocyanin is an electrontransfer protein involved in phot osynthesis; to function the copper ion switches between oxidation states (Katoh and Takamiya, 1961, Fork and Urbach, 1965) Researchers suspected early on that the intense blue color was the result of an unusual copper site since the properties of copper observed in these proteins were not known in inorganic chemistry (Siiman et al. 1974) A high resolution crystal structure of plactocyanin from poplar was solved and revealed that the copper was bound in a very distorted geometry (Guss and Freeman, 1983) The coordination geometry was neither tetrahedral (the preferred geometry of Cu(I)) nor squarepl anar (the preferred geometry of Cu(II)) but intermediate between the two (Guss and Freeman, 1983) This suggests that the copper geometry in plastocyanin is in an entatic state: the copper site resembles the transition state (Vallee and Williams, 1968) Instead of decreasing the activation energy, the energy of the metal ion is increased (Vallee and Williams, 1968) The overall effect is lowering of the energy barrier. Because of the intermediate geometry imposed by the protein, reorganization energy of Cu(II) to Cu(I) to Cu(II) is minimal. Other features of the protein can affect reactivity of the metal ion. It is essential that the iron in cytochrome b transfers electrons but it is critical that iron does not transfer electrons during transport of oxygen by hemoglobin (Misra and Fridovich, 1972) Oxidation and reduction of iron in cytochrome b enables electron transfer. However, oxidation of Fe(II) to Fe(III) inactivates hemoglobin, as Fe(III) has almost no affinity for dioxygen (Conant, 1923) The iron in both proteins is bound to protoporphyrin IX so it is not the porphyrin ring that imparts this duality of function (Gribble and
36 Schwartz, 1965) Instead the protein is responsible for the functional constraints that cause iron to transfer electrons in one case but not in the other. The globin chains of hemoglobin are thought to stabilize the hemeoxygen complex thereby discouraging formation of Fe(III) (Percy et al. 2005) Indeed, mutation of key residues in the heme pocket were found to stabilize Fe(III) (Gerald and Efron, 1961, H ayashi et al. 1980, Priest et al. 1989, Brennan and Matthews, 1997, Hojas Bernal et al. 1999) In the light of these examples, it is clear that these proteins have specifically evolved to optimize the functional potential of iron. Due to the relationship that has evolved between the protein and the metal ion, the activity of metalloproteins is, consequently, strictly dependent on the presence of a metal and in most cases a specific metal. Metallation by the wrong metal can have detrimental effects such as an inactive or mis folded protein (Coleman, 1967, Cooper et al. 1997, Predki and Sarkar, 1994) Correct Allocation of Metals within the Cell It was initially assumed that pools of uncomplexed metal ions were available within the cell, such that a nascent poly peptide would acquire its cofactor solely through the metal affinity of the chelating ligands. However, more recently it has become clear that this picture of metal metabolism is oversimplified. Metal binding ligands in proteins are not sufficiently select ive to ensure that the proper cofactor is loaded and free metals do not appear to exist within the cell but are chelated by proteins and small molecular ligands (Outten and O'Halloran, 2001, Waldron and Robinson, 2009) The protein ligands that bind the metal and the binding pocket of a folded protein can favor the correct metal over an incorrect one. As discussed in the previous section, metals prefer to bind to certain chemical groups and prefer those groups to bind with a particular
37 geometry (Rulsek and Vondrsek, 1998, Harding, 1999) However, the influence of the protein in excluding incorrect metals is insufficient in a biological setting. The Irving Williams series dictates that the affinity between a ligand and a metal follows an order of preference with Mg(II) and Ca(II) forming the weakest bonds and Cu(II) and Zn(II) forming the strongest bonds (Irving and Williams, 1948) If metal protein speciation was dependent solely on the protein then all metal proteins regardless of the metal ligands would contain copper (Tottey et al. 2007) However, proteins successfully acquire the correct metal from the cellular milieu. The mechanisms responsible are just now being elucidated (O'Halloran and Culotta, 2000, Finney and O'Halloran, 2003, Tottey et al. 2005, Leach and Zamble, 2007, Tottey et al. 2007, Zhou et al. 2008, Tottey et al. 2008, Waldron and Robinson, 2009, Robinson a nd Winge, 2010) The availability of the metal ion is an important aspect and the cell actively regulates the intracellular concentration of metals through the use of multiple metal responsive transcription factors, transporters, and storage proteins (Brocklehurst et al. 1999, Outten et al. 2000, Robinson et al. 2001, Liu et al. 2004, Iwig et al. 2008, Leitch et al. 2007, Lee and Helmann, 2007) The folding location of a protein, cytoplasm versus periplasm, c an also help ensure that a protein binds the correct metal. Two proteins from Synechocystis PCC 6803 with identical metal binding residues were found to contain manganese or copper depending on the fact that one protein was allowed to fold in the cytoplasm (where manganese is available) and the other was not allowed to fold until in the periplasm (where copper is available) (Tottey et al. 2008) As expected from the Irving Williams series, when the Mnprotein folds in vitro in the presence of equimolar copper and manganese, it specifically acquires
38 copper (Tottey et al. 2008) Therefore, availability of metal ions in the cell is an important aspect in regards to metalloprotein maturation. As copper is the preferred partner based on af finity for protein ligands, several organisms encode special trafficking proteins that essentially make copper unavailable in the cell. Copper is also delivered to specifically to copper dependent enzymes by these specialized proteins, which are referred t o as metallochaperones. Since the discovery of the first copper metallochaperone, Atx1 (Pufahl et al. 1997) numerous accessory factors involved in ensuring target proteins are loaded with the correct metal have also been characterized. These accessory factors can be divided into two main types: metallochaperones and insertases. In general, metallochaperones are responsible for storage and delivery of a metal cofactor to a target metalloprotein (Rae et al. 1999, Shi et al. 2008) These proteins are particularly important in the trafficking of toxic metals and as such are frequently found trafficking copper (Glerum et al. 1996, Pufahl et al. 1997, Culotta et al. 1997) but different metallochaperones have been disc overed that specifically traffic and deliver iron (Bou Abdallah et al. 2004, Shi et al. 2008) cobalt (in the form of B12) (Padovani et al. 2008) manganese (Luk et al. 2003) or nickel (Musiani et al. 2004, Zhang et al. 2005) to target apoenzymes. In contrast to these other metals, a cytoplasmic zinc chaperone that targets a single zinc dependent protein has not been identified. While metallochaperones are responsible for storage and delivery, insertases facilitate incorporation of the metal ion in an energy dependent manner into the target protein's catalytic site (Jeon et al. 2001) In studied systems, the metal is specifically
39 inserted into the folded protein. The copper chaperone CCS ( copper chaperone for S OD1) appears to insert copper into the fully folded superoxide dismutase homodimer (Schmidt et al. 2000) A key characteristic for some of these insertases is the coupling of NTP hydrolysis with metal insertion (Loke and Lindahl, 2003, Ba et al. 2009) For several metalloproteins, such as [NiFe] hydrogenase (Volbeda et al. 1995) the metal site is buried within the protein. This organization creates a kinetic trap and the metal ion is not replaced by more competitive metal ions (Dudev and Lim, 2008) Commonly, maturation of these proteins requires the coupling of NTP hydrolysis with metal insertion, as will be discussed in the next section. This observation could be evidence of the structural rearrangements that must occur for metal insertion. The G3E Family Studies involving the maturation of Ni urease and [NiFe] hydrogenase have provided an extensive picture of how metal dependent catalytic centers are ass embled. These two nickel containing proteins require a suite of accessory proteins to properly insert nickel into the catalytic site (only one exception has been found to date; Bacillus subtilis encodes a functional urease in the absence of the canonical accessory proteins (Kim et al. 2005) ). In both cases, a GTPase (UreG for urease or HypB for hydrogenase) is proposed to be involved in the incorporation of the nickel ion. Deletion of hypB abolishes hydrogenase activity, which can be partially rest ored with the addition of exogenous nickel (Waugh and Boxer, 1986, Jacobi et al. 1992) Deletion of ureG abolishes urease activity and purified urease from cells lacking UreG is nearly devoid of nickel (Lee et al. 1992) The exact mechanism of how these proteins assist in maturation is still unclear. Perhaps they enable structural changes that allow cofactor insertion (acting as insertases) or regulate association between the other accessory
40 factors also required for maturation (Soriano and Hausinger, 1999, Leach and Zamble, 2007) The identification of these GTPases and the proposal for their involvement as maturation factors were aided by gene clustering. The genes encoding HypB and UreG are commonly found in gene clusters that contain genes encoding the target metalloenzyme and/or accessory factors also involved in maturation. Synthesis of the [NiFe] hydrogenase active site requir es the involvement of at least six proteins (Jacobi et al. 1992) I n characterized organisms, these genes form gene clusters with each other and the structural genes of hydrogenase (Vignais et al. 2001) The E. co li genome encodes four [NiFe] hydrogenases (Andrews et al. 1997) HypB is required for the activity of each (Lutz et al. 1991) but the corresponding gene is found in an operon divergentl y transcribed from an operon containing most of the structural genes for the formate hydrogenlyase complex (hydrogenase 3) (Figure 1 2A). Maturation of the urease active site requires at least four accessory proteins (Lee et al. 1992) The corresponding genes commonly form gene clusters with one another and the three structural genes for urease (Carter et al. 2009) In Klebsiella aerogenes ureG is found at the end of a seven gene urease cluster (Figure 12B). Clustering on the chromosome between accessory factors and the target metalloenzyme is a common occurrence for systems in addition to [NiFe] hydrogenase and urease. Gene clusters including chaperones and target metalloezymes are found for nitrogenase (Jacobson et al. 1989, Hong et al. 1996) nitrile hydratase (Hashimoto et al. 1994, Wu et al. 1997) trimethylamine oxide reductase (Ilbert et al. 2003) tyrosinase (Lopez Serrano et al. 2004) nitrate reductase (Blasco et al. 1998) acetyl -
41 CoA synthase (Loke and Lindahl, 2003) and carbon monoxide dehydrogenas e (Kerby et al. 1992) As novel metalloenzymes are discovered and metallocenter biosynthesis is further characterized, this list will most certainly increase. HypB and UreG are closely related and form two subfamilies of the G3E family of phosphatebinding loop (P loop) GTPases (G3E family) as defined by Leipe and colleagues (Figure 1 3) (Leipe et al. 2002) The G3E family is separated from the rest of the SIMIBI class of GTPases (for si gnal recognition G TPases, Mi nD superfamily, and Bi oD superfamily) by a glutamate residue in the Walker B motif and an intact G4 motif (Leipe et al. 2002) The P loop NTPase fold (also referred to as the mononucleotidebinding fold) is one of the most common folds and comprises roughly 15% of all gene products in some organisms (Koonin et al. 2000) This fold is characterized by an N terminal Walker A motif with the consensus sequence GXXXXGK[TS], which functions in the positioning of the triphosphate group of the nucleotide (la Cour et al. 1985, Saraste et al. 1990) The Walker B motif, typically represented by DXXG, coordinates a water bridge magnesium ion, which binds to the nucleotide (Pai et al. 1990) In HypB, the glutamine (present instead of aspartic acid) in the Walker B motif is, in contrast, a direct ligand to magnesium (Gasper et al. 2006) The G4 motif (NKXD) provides specificity to GTP (Hwang and Miller, 1987) GTPases are often referred to as molecular switches since binding and hydrolysis of GTP cause conformational changes effectively turning on or off interactions with other macromolecules (Vetter and Wittinghofer, 2001) As can be predicted by the commonality of t he P loop fold, a myriad of functions are carried out by GTPases. GTPases have been found to be involved in translation (Hauryliuk, 2006, Rodnina et al.
42 2000) signal transduction (Narumiya, 1996) cell motility (Wittmann and Waterman Storer, 2001) intracellular trafficking (Segev, 2010) cell cycle regulation (Meier et al. 2000) and membrane transport (Molendijk et al. 2004) Like other characterized GTPases, HypB and UreG have low intrinsic GTPase activity (Fu et al. 1995, Zambelli et al. 2005) Hydrolysis of GTP by these proteins was found to be essential for nickel insertion into their target (Maier et al. 1995, Soriano and Hausinger, 1999, Moncrief and Hausinger, 1997) Mutation of the P l oop domain of UreG abolishes formation of the urease maturation complex and subsequently urease activity (Moncrief and Hausinger, 1997) Upon interaction with a GTPase activating protein (GAP) or molecular target such as RNA, GTPase activity is stimulated (Meier et al. 2000, SalomoneStagni et al. 2007) Based on structure modeling and predicted similarity to other GAPs, the urease maturation factor UreF was proposed to perform the role of a GAP for UreG (Soriano et al. 2000, SalomoneStagni et al. 2007) The recent X ray structure, however, displayed little resemblance to the predicted structure model and as a consequence little if any similarity to characterized GAPs is actually observed (Lam et al. 2010) Therefore UreF may not function as a GAP (Lam et al. 2010) A GAP for HypB has not been predicted. Functionally, HypB and UreG belong to an expanding group of bact erial P loop NTPases proposed to be involved in synthesis of enzyme metal sites. The GTPases CooC and AcsF are proposed to insert nickel into carbon monoxide dehydrogenase (Jeon et al. 2001) and acetyl CoA synthas e (Loke and Lindahl, 2003) respectively. Several proteins involved in FeS cluster assembly are NTPases. HydF has GTPase activity and is proposed to be a scaffold protein involved in synthesi s and transfer of the
43 [2Fe 2S] center into [FeFe] hydrogenase (Shepard et al. 2010) ApbC was found to hydrolyze ATP and is responsible for insertion of a [4Fe4S] cluster into isopropylmalate isomerase (Boyd et al. 2008) The P loop GTPase MobB is proposed to be involved in Mo cofactor synthesis or transfer (Eaves et al. 1997) Having a molecular switch participate in maturation o f metalloenzymes could serve to ensure that the correct metal ion or metal cofactor is being inserted. In addition to HypB and UreG, t he G3E family is subdivided into two other subfamilies: MeaB which is required for the activation of methylmalonyl CoA m utase (an adenosylcobalamindependent enzyme) (Padovani and Banerjee, 2006) and COG0523, a large and diverse subfam ily of proteins with poorly defined function (Figure 1 3) In general, characterized G3E family proteins have been found to function as either metal insertases or as a dual function metallochaperone/insertase. MeaB appears to fulfill the role of an adenos ylcobalamin insertase, facilitating the insertion of B12 into methylmalonyl CoA mutase (MCM) (Figure 1 3B) (Padovani et al. 2006) Adenosyltransferase serves as the chaperone that delivers B12 to the MeaB MCM complex (Padovani et al. 2008) MeaB has been described as a gatekeeper and is able to distinguish active from inactive cofactor and elicit insertion or release of the cofactor as necessary (Korotko va and Lidstrom, 2004, Padovani and Banerjee, 2006, Padovani and Banerjee, 2009, Takahashi iguez et al. 2010) MeaB has low GTPase activity, which is stimulated roughly 100fold by interaction with its target (Padovani et al. 2006) A large structural rearrangement occurs upon interaction between MeaB and its target (Padovani et al. 2006) suggesting that MeaB may be responsible for the structural changes that must occur for cofactor incorporation.
44 Unlike MeaB, HypB is thought to carry out both the insertase and metallochaperone roles in a subset of organisms. The metallochaperone role is proposed based on a histidine stretch located at the N terminus of some HypB proteins which presumably serves to store nickel ions for subsequent transfer to hydrogenase (Olson et al. 1997) In Bradyrhizobium japonicum this histidine stretch was found to bind 18nickel ions per dimer (Fu et al. 1995) In E. coli, this His stretch is missing fro m HypB, and SlyD is presumed to be the metallochaperone component that delivers nickel to the assembly complex (Zhang et al. 2005, Leach et al. 2007) In contrast to the HypB proteins, all characterized UreG prot eins lack His stretches (except some plant orthhologs (Witte et al. 2001) ). Accordingly, UreG is proposed to serve solely as an insertase providing the GTPase activity required for urease maturation and a separate protein, UreE, is proposed to serve as the metallochaperone component delivering nickel to the maturation complex (Remaut et al. 2001, Benoit and Maier, 2003, Musiani et al. 2004) Little is known regarding the fourth G3E subfamily, COG0523. Currently, spurious and inconsistent reports have linked members of this subfamily to cobalamin biosynthesis (Crouzet et al. 1991) nitrile hydratase activation (Hashimoto et al. 1994) and zinc homeostasis (Gaballa and Helmann, 1998) Zinc Homeostasis Like all essential transition metals, a dichotomy exists that is defined by the essential but potentially toxic nature of zinc. As multiple essential proteins are reliant on zinc for activity, such as RNAP (Scrutton et al. 1971) and tRNA synthetases (Mayaux et al. 1982, Xu et al. 1994, Sood et al. 1999, Sankaranarayanan et al. 2000 Zhang et al. 2003b, Bilokapic et al. 2006, Sokabe et al. 2009) the presence of zinc to the cell is
45 essential. Because of implications in human health, an environment of particular interest is the vertebrate host, where access to zinc by a pathogen is thought to be limited. In 1973, Kochan introduced the concept of nutritional immunity as a defense strategy against invading pathogens (Kochan, 1973) The host organism actively deprives metals from the invader inducing both hypoferr emia and hypozincemia (deficiency of iron and zinc, respectively, in the blood) as part of the acute inflammatory response (Weinberg, 1975, Liuzzi et al. 2005, Motley et al. 2004, Kehl Fie and Skaar, 2010) Therefore, the mechanisms that enable a pathogen to overcome this host induced Znstarvation are considered essential to a pathogen's ability to cause infection (Panina et al. 2003, Kim et al. 2004, Pasquali et al. 20 08) Excess zinc, however, can be toxic. In contrast to vertebrates, plants may utilize this aspect of zinc as a defense strategy (Poschenrieder et al. 2006) Whereas for some pathogens highaffinity zinc uptake is essential for virulence, in Agrobacterium tumefaciens that machinery was downregulated in response to plant signals (Yuan et al. 2008) and repression of that machinery was required for full virulence of the plant pathogens, Xanthom onas campestris and Xanthomonas oryzae (Tang et al. 2005, Huang et al. 2008, Yang et al. 2007) The exact mechanism by which zinc becomes cytotoxic is not known, but most likely toxicity arises from the misincor poration of zinc into proteins, thereby displacing the native cofactor leading to reduced activity or inactivation. This mechanism could explain inhibition of the respiratory electron transport chain in bacteria by zinc (Kasahara and Anraku, 1972, Kasahara and Anraku, 1974, Kleiner, 1978, Singh and Bragg, 1974, Beard et al. 1995) Zinc toxicity may also be mediated through binding to nascent polypeptides disrupting proper folding or
4 6 binding to folded proteins gener ating protein aggregates through zinc mediated proteinprotein interactions (Maret and Li, 2009) Because zinc depletion and zinc excess can be detrimental to growth and survival, the intracellular concentration of zinc is tightly controlled through the use of zinc sensing transcriptional regulators (Westin and Schaffner, 1988, Patzer and Hantke, 1998, Brocklehurst et al. 1999, Zhao and Eide, 1997) import and export mac hineries (Palmiter and Findley, 1995, Zhao and Eide, 1996, Rensing et al. 1997, Grotz et al. 1998, Patzer and Hantke, 1998, McMahon and Cousins, 1998) compartmentalization (MacDiarmid et al. 2000, Devirgiliis et al. 2004) and storage proteins (Richards and Cousins, 1975, Blindauer et al. 2002) Using both narrow and broadspecificity import systems, E coli can actively accumul ate zinc to a level of 200,000 atoms/cell (Outten and O'Halloran, 2001) a 1,000fold excess over the typical zinc concent ration in the medium. However, biochemical measurements indicate that there is essentially no free zinc in an E. coli cell (Outten and O'Halloran, 2001) sugges ting that, once imported, zinc becomes sequestered by proteins and small molecules It has been proposed therefore that the only way for a newly synthesized protein to obtain zinc is via ligand exchange with zinc loaded macromolecules (Heinz et al. 2005) Whether specific proteins, such as a zinc specific chaperone, are involved in mediating this process is currently not known. Zinc binding proteins account for 5% of the average proteome (Andreini et al. 2006) and ribosomes most likely constitute the largest zinc reservoir. A rapidly growing E. coli cell conta ins as many as 50,000 ribosomes (Bremer and Dennis, 2008) each with possibly 34 bound zinc ions (Katayama et al. 2002, Gabriel and Helmann, 2009)
47 thereby tying up most of the zinc present Other abundant proteins must sequester the remaining zinc pool; RNAP contains two bound zinc ions (Giedroc and Coleman, 1986) and is present at ~2000 copies/cell (Lewis et al. 2000) Zinc Transport and Regulators With the exception of a few nontransport mechanisms that will be discussed, bacteria appear to rely heavily on infl ux and efflux to maintain zinc homeostasis. Multiple families of transporters are currently known to specifically transport zinc in prokaryotes. These transporters can be divided into two main groups: low affinity and high affinity. Low affinity transporters tend to have a broader spectrum as to which divalent metal cations they will transport, while the highaffinity transporters are specifically regulated in response to the intracellular concentration of zinc and are highly specific in the transport of zi nc. For highaffinity transport, specificity is critical to avoid poisoning the cell with a metal previously in sufficient supply. How zinc is transported across the inner membrane of gram negative bacteria is fairly well characterized, but how zinc is transported across the outer membrane is only known in a couple of organisms. Zinc efflux When the intracellular zinc level becomes high, zinc specific efflux pumps are employed to reestablishment of the intracellular zinc concentration. These transporters i nclude low affinity CDF ( cation d iffusion f acilitator) proteins, RND ( r esistance, n odulation, division ) efflux transporters, CorA family transporters and highaffinity P type ATPases/CPx ATPases. In E. coli, a high concentration of zinc activates expressi on of z ntA and energy dependent efflux of zinc is induced (Rensing et al. 1997) Znt A is specifically a
48 Zn(II)/Pb(II)/Cd(II) translocating P type ATPase (Liu et al. 20 06) and expression of zntA is specifically induced by Zn(II), Pb(II) or Cd(II) (Binet and Poole, 2000) The transcriptional regulator respons ible for expression is ZntR, a member of the MerR family of regulators (Brockleh urst et al. 1999) Like other MerR regulators, apoZntR (metal free) binds to specific promoter DNA repressing expression (Outten et al. 1999) When bound to zinc, ZntR distorts the promoter, repositioning the 10 and 35 sequences, leading to a more favorable interacti on with RNAP and expression of zntA in induced (Ansari et al. 1995, Outten et al. 1999) ZntR homologs have also been characterized in Bordetella pertussis (Kidd and Brown, 2003) In the gram positive bacterium Staphylococcus aureus and several cyanobacteria, zinc efflux is regulated by a member of the ArsR family of regulators (Endo and Silver, 1995, Thelwell et al. 1998, Liu et al. 2004) A rsR family proteins bind to target DNA in the absence of metal; in the presence of metal, a conformational change causes the protein to dissociate and transcription can occur (Eicken et al. 2003, Busenlehner et al. 2003) In Salmonella enterica, the efflux transporter ZntB is related to the CorA family of magnesium transporters (Worlock and Smith, 2002) CorA family proteins were originally characterized in the transport of magnesium cat alyzing both import and export. ZntB has been shown to specifically export zinc (Worlock and Smith, 2002) In Cupriavidus metallidurans and P. aeruginosa CMG103, a member of the RND multidrug efflux transport family, CzcABC, has been shown to be involved in zinc efflux as well as cobalt and cadmium (Mergeay et al. 1985, Hassan et al. 1999) This
49 transport system is a cation/proton antiporter and is the only machinery known to span both membranes (Nies, 1995) CDF proteins have been shown to be involved in resistance t o zinc in C. metallidurans (Nies, 1992) B. subtilis (Guffanti et al. 2002) S. aureus (Xiong and Jayaswal, 1998) and E. coli (Grass et al. 2001, Grass et al. 2005b) These proteins also transport zinc with an antiporter mechanism; efflux of zinc is catalyzed in exchange for potass ium or hydrogen cations (Guffanti et al. 2002) Structural studies of the CDF protein YiiP from E. coli suggest that these efflux proteins are autoregulated by cytoplasmic zinc and thereby serve as first responders to higher than normal zinc concentrations (Lu and Fu, 2007, Lu et al. 2009) Efflux by ZntA (discussed above), in contrast, is reliant on zinc sensing by ZntR and subsequent gene expression, translation and insertion into the membrane. Zinc uptake Several transport families have been identified and characterized among bacterial organisms that are responsible for uptake of zinc. Low affinity ZIP ( Z RT/ I RT like p roteins) fam ily transporters and highaffinity ABC ( A TP b inding cassette) transporters appear mainly responsible for zinc uptake. However, zinc can enter the cell through the use of multiple broad spectrum metal ion importers and/or porins (Blencowe and Morby, 2003) As in eukaryotes, ZI P family zinc transporters have been implicated in bacterial zinc uptake. The first characterized bacterial ZIP transporter was ZupT in E coli (Grass et al. 2002) ZupT appears to be expressed constitutively at a low level and is also capable of transporting other divalent cations (Grass et al. 2005a) Other characterized secondary zinc transporters include the PIT ( i norganic p hosphate t ransport ) system in
50 E. coli (Beard et al. 2000) and the citrate metal cotransporter CitM in B subtilis (Krom et al. 2000) When transport by these systems is inadequate, a highaffinity zinc transporter ZnuABC is specifically induced (Patzer and Hantke, 1998, Gaballa and Helmann, 1998) These systems are generally composed of a membranespanning permease (ZnuB), an ATP hydrolyzing component (ZnuC) that energizes transport and a periplasmic chaperone (ZnuA) that delivers zinc to the permease (Claverys, 2001) In addition to these principal components, some organisms express an auxiliary component ZinT that was recently shown to facilitate recruitment of zinc in the periplasm (Graham et al. 2009, Petrarca et al. 2010) Zinc specificity is proposed to be due to ZnuA conformational changes specifically induced by zinc (Yatsunyk et al. 2008) Other metal ions do not stabilize ZnuA to the extent zinc binding does (Yatsunyk et al. 2008) Zur Expression of the genes encoding the components of ZnuABC is dependent on the zinc sensing regulator Zur which was concurrently discovered in E. coli and B. subtilis (Patzer and Hantke, 1998, Gaballa and Helmann, 1998) Zur was shortly thereafter described for Listeria monocytogenes (Dalet e t al. 1999) and S. aureus (Lindsay and Foster, 2001) Zur is a member of the Fur family of metal sensing regulators. The founding member Fur regulates gene expression in response to iron (Hantke, 1981) Other members of this family include Mur (manganese sensing) and Nur (nickel sensing) (Lee and Helmann, 2007) Zur orthologs are present throughout Bacteria (Lee and Helmann, 2007) with the exception of Lactococcus lactis and Streptococcus spp. which appear to use a MarR family regulator AdcR to repress genes
51 involved in the response to zinc deficiency (Llull and Poquet, 2004, Reyes Caballero et al. 2010) Through a metal induced repression mechanism, zinc occupancy in a dosedependent manner directly controls affinity between Zur and DNA (Outten et al. 2001a) In the presence of zinc Zur binds to operator sequences upstream of target genes, preventing binding of RNAP and thus transcription initiation (Outten et al. 2001a) Conversely, upon zinc depletion, repression by Zur is lifted and expression of target genes is increased (Gaballa and Helmann, 1998) Zur proteins are found as dimers in solution (Gaballa a nd Helmann, 1998, Patzer and Hantke, 2000, Lucarelli et al. 2007, Shin et al. 2007, Feng et al. 2008) and are therefore proposed to bind as homodimers to palindromic DNA sequences (Patzer and Hantke, 2000, Maciag et al. 2007) Zinc chelators abolish Zur DNA interactions and zinc enhances those interactions (Gaballa and Helmann, 1998, Maciag et al. 2007, Huang et al. 2008, Li et al. 2009) For the E. coli and Mycobact erium tuberculosis Zur proteins, two distinct metal binding sites are present per monomer (Outten et al. 2001a, Lucarelli et al. 2007) With only one zinc ion per monomer the protein does not bind DNA. This zinc site is proposed to be a structural site (Outten et al. 2001a) and is conserved in both Zur and Fur homologs (Patzer and Hantke, 2000 ) Compared to the structural site, where the zinc is not readily exchangeable, the second zinc site is comparatively readily exchangeable and proposed to be the regulatory site (Outten et al. 2001a, Lucarelli et al. 2007) In the crystal structure of the M. tuberculosis Zur, the structural zinc site is composed of two CXXC motifs. One motif is located in the N terminus DNA binding domain and the other in the C terminus dimerization domain (Lucarelli et al. 2007) The
52 proposed regulatory site is located at the hinge region between the two domains (Lucarelli et al. 2007) Additionally, a third z inc ion was found in the crystal structure, however, the biological role of this zinc or whether it is an artifact of crystallization is not known (Lucarelli et al. 2007) Bioinformatics and Gene Function Discovery Over 1,000 genomes have now been published and another 6,000 are currently underway (Liolios et al. 2010) The current release of the Reference Sequence (RefSeq) collection (as of November 10, 2010) hosted by the National Center for Biotechnology Information (NCBI) includes a set of 11,652,892 nonredundant protein sequences from 11,354 organisms (Pruitt et al. 2007) From these sequences, a large volume of information about metabolic potential, differential responses to stimuli, niche adaptation and evolutionary history is available. However, in order to access that wealth of information, sense must be made of the countless strings of As, Ts, Gs and Cs. It is the field of bioinformatics and offshoots thereof that gives meaning and discerns information from the seemingly random order of an organisms chromosome. As a most basic definition, bioinformatics is the field of interpreting sequence information but also involves interpretation of any large data s et of biological information such as gene expression, 3D protein structures, or literature (Luscombe et al. 2001) When the first genome of a free living organism was published in 1995 (Fleischmann et al. 1995) the field of bioinformatics had already existed in one form or the other for almost thirty years. One could imagine that the field had its foundation in the first use of molecular sequences for evolutionary studies (Zuck erkandl and Pauling, 1965) the first collection of protein sequences (Dayhoff, 1968) or the first use of dynamic programming for sequence comparison (Needleman and Wunsch, 1970) The
53 central tenet to bioinformatics is that a greater understanding of biologic al systems can be ascertained by comparison. Since those pioneering works, the field of bioinformatics has expanded to include larger and larger datasets including computational studies of data from genome wide experiments on transcript or protein abundanc e (Luscombe et al. 2001) Advancement in the bioinformatics field is best exemplified by current progress with genomescale metabolic reconstructions (Reed et al. 20 06b, Reed et al. 2006a, Feist and Palsson, 2008, Suthers et al. 2009) Metabolic network reconstruction is the in silico modeling of an organisms metabolism that is converted to a mathematical format. Instead of studying the individual components of th e cell, which has been the main focus of biology during the last half of the 20th century, metabolic reconstructions focus on integration and viewing the cell as a system (Palsson, 2006) A genome level model begins with a parts list which is provided by the genome sequence (Edwards and Palsson, 2000) The increasing wealth of genomewide highthroughput data sets plus published reports provide information about functional, physical and temporal interactions between those components (Covert et al. 2004) C entral to these models is the genotypephenotype relationship (Edwards et al 2001) The model can be used to predict experimental outcomes such as the deletion of gene A will lead to phenotype1 and the outcomes of these experiments are used to improve the model in an iterative manner (Palsson, 2006) Without the tools, datasets and concepts provided by the field of bioinformatics, systems bi ology would not be conceivable. The Functional Annotation D ilemma For the majority of genomes, annotations continue to be determined by s equence similarity to characterized or partially characterized genes in other organisms, mainly
54 model organisms such as E. coli and Saccharomyces cerevisiae (Salzberg, 2007) The term annotation as used here is defined as the functional description of a gene or gene product. With the avalanche of genome sequence data and automated transfer of annotations between those genomes, the definition of function has become increasingly vague. Traditionally, g ene function discovery and/or verification have largely been ach ieved one gene at a time by bench scientists. As of 2008 59.3 % of the genes found in the E coli genome are affiliated with some type of experimental data (Keseler et al. 2009) E. coli however, is the exception rather than the rule, becaus e experimentally characterizing the tens of millions of genes currently sequenced is an unrealistic goal. As a consequence, the vast majority of annotations are sequence derived predictions. A few of these annotations are based on a combination of bioinfor matic evidence as will be discussed in the next section, but, in most cases, annotations are based solely on sequence similarity to a gene, most likely also annotated in the same way I t is often difficult to find the experimentally validated progenitor g ene and how the annotation was originally acquired (Poptsova and Gogarten, 2010) Unfortunately, current sequence based approa ches cannot predict a function for onethird of sequenced genes; moreover, for some gene families at least 60% of the gene predictions are wrong (Schnoes et al. 2009) The unreliability of gene annotations will inevitably become more apparent as newly sequenced genomes emerge containing genes of an ever increasing phylogenetic distance from those experimentally characterized. Attem pts are being made to address the need for reliable and accurate gene annotations, such as developing Gold Standard datasets of experimentally verified
55 annotations by the COMputational Bridge to Experiments (Galperin and Koonin, 2010) ; nevertheless this functional annotation dilemma is one of the lar gest challenges faced in the post genomic era and threatens to undermine efforts to extract knowledge from genome sequencing efforts. Comparative Genomics and the Gene Family Approach The unreliability of assigning gene function based on sequence similarit y soon became apparent after the first wave of genome sequences (Eisen et al. 1997, Galperin and Koonin, 1998, Brenner, 1999, Bork, 2000, Attwood, 2000, Devos and Valencia, 2001) As a solution, nonhomology based methods have been developed and employed to link genes with function. In combination with homology based methods, novel discoveries in all fi elds of biology have been made. Increasingly sophisticated bioinformatics techniques are available to aid in the d iscovery of gene function, which is no longer limited to studying one gene in isolation but as a member of an ever evolving genomic community. Entire gene families from diverse organisms can be studied simultaneously. The assumption is that a gene family i s an evolutionary unit that represents maintenance and divergence of function. The function of uncharacterized members can be inferred by comparison to characterized members through the use of phylogenomics and by cross species comparison through the use o f comparative genomics (Eisen, 1998b, Galperin and Koonin, 2000, Overbeek et al. 2005) as descr ibed in the following sections. Phylogenomics Phylogenomics is the approach put forth by Eisen in the late 1990s as a strategy to improve functional predictions (Figure 14) (Eisen et al. 1997, Eisen, 1998a) Instead of predicting the function of a gene based only on sequence similarity to a characterized
56 gene, the evolutionar y history of those genes is also taken into account ( Eisen, 1998b) To infer function from this type of study, the assumption must be made that gene functions change as a consequence of evolution and, by reconstructing the evolutionary history of a gene family, function for an uncharacterized gene can be in ferred based on its relatedness to characterized family members (Eisen, 1998b) The first step is to build a phylogenetic tree of the gene family of interest; members with any functional information are specifically included. Next, that functional information is overlaid on the tree. The last step is interpretation of the functionally annotated tree. The history of functional changes is used to predict functio ns for uncharacterized members. This approach was first applied to the MutS family of mismatch repair proteins (Eisen et al. 1997, Eisen, 1998a) MutS is the protein responsible for recognizing and binding to the site of a mismatch or a loop in doublestranded DNA (Su and Modrich, 1986, Levinson and Gutman, 1987) Some M utS proteins do not function in DNA repair but are involved in meiotic crossover and chromosome segregation (Ross Macdonald and Roeder, 1994, Hollingsworth et al. 1995) It became apparent that sequence similarity was not able to properly distinguish between these functions; as a consequence, mutS family genes were being erroneously annotated in published genomes (Eisen et al. 1997) By building a phylogenetic tree wit h available MutS protein sequences and overlaying that tree with functional information from previously published studies, the function of uncharacterized MutS homologs was predicted with more confidence than by sequence similarity alone. If the uncharacterized protein belonged to a subfamily involved in mismatch repair, then that protein was more likely to be involved in mismatch repair than in chromosome segregation (Eisen, 1998a) As
57 more genes sequences have become available, this analysis has been refined, and new MutS subfamilies with novel functions have been proposed (Lin et al. 2007, Sachadyn, 2010) In addition to phylogenomic analysis, which is concerned principally with the evolutionary history of gene families, other types of comparative genomic information can be used to infer gene function. The function of an uncharacterized gene can be deduced from the function of genes surrounding it on the chromosome (Overbeek et al. 1999a) co occurrence patterns with genes of known function (Pellegrini et al. 1999) and shared regulatory sites with genes of known function (Figure 15) (Gelfand et al. 2000) Gene neighborhoods Thirty six years before the first bacterial genome was sequenced, Demerec and Har tman, in 1959, noted that loci controlling related functions tend to cluster physically on the chromosome and that only the force of selective adaptation could account for this phenomena (Demerec and Hartman, 1959) The advantage of gene neighborhoods is presumably co transcription of genes that interact either physically and/or are in the same metabolic or response pathway (Dandekar et al. 1998, Price et al. 2005) Since transcription and translation occur simultaneously in E. coli, having two genes in the same transcript reduces the delay in complex formation (Shapiro and Losick, 1997, Pal and Hurst, 2004) Other theories for the co localization of functionally related genes in genomes have emerged such as the selfish operon paradigm. In this theory, gene clusters predominate because maintenance of horizontally transferred genes is more lik ely to occur if all the genes necessary for a particular function are co transferred (Lawrence and Roth, 1996) Regardless of the reason for functionally related genes to
58 be clustered in genomes, thi s observation has provided a useful tool in the prediction of gene function (Overbeek et al. 1999a, Overbeek et al. 1999b) Overbeek et al. were the first to develop an algorithm to find and score gene neighbors (Overbeek et al. 1999a) They first detected pair s of close bidirectional best hits in sequenced genomes. A PCBBH is basically two genes that are neighbors in one genome with the homologs of those two genes that are also neighbors in another genome. The presence of gene neighbors in closely related genomes is not necessarily significant. Genes could be neighbors due to chance and not enough evolutionary time may have passed in closely related genomes to rearrange those genes. A score can be given to gene neighbors, which takes into account the number of genomes and the phylogenetic distance between those geno mes where the gene pair s occur. Gene clustering is also found in eukaryotes (Blumenthal, 1998, Lee and Sonnhammer, 2003) but the use of this method has had much more success in prokaryotes. In prokaryotes, functionally coupled genes often share the same operon or are transcribed divergently from the same promoter (Beck and Warren, 1988) However, functionally coupled genes can be neighbors without being co transcri bed (Yanai et al. 2002) Co occurrence Phylogenetic co occurence profiles infer functional coupling by as suming that during evolution functionally related proteins are maintained or eliminated in a correlated manner (Pellegrini et al. 1999, Osterman and Overbeek, 2003) Also, analysis of co occurrence can identify non orthologous gene displacement; distribution of non orthologous genes that functionally replace one another will be negatively correlated (Morett et al. 2003, Makarova and Koonin, 2003) Co occurrence profiles ar e
59 useful in identifying missing genes in pathways whether a gene is locally missing (the gene for a pathway step is found in some genomes but missing from others) or globally missing (the gene encoding a particular pathway step has not been identified in any genome) (Osterman and Overbeek, 2003) Shared regulatory sites The genes encoding proteins that belong to the same pathway or proteins that respond to the same environmental stimulus are usually part of the same regulon. In most cases, membership in a regulon is dictated by the binding of a specific regulatory protein upstream of a gene (Epstein and Beckwith, 1968) More recently, mechanisms of gene regulation has expanded to include mRNA binding proteins (Babitzke and Yanofsky, 1993, Liu and Romeo, 1997) regulatory RNA (Liu et al. 1997, Nahvi et al. 2002, Wagner et al. 2002) and RNAP binding proteins (Stepanova et al. 2009) Co regulation between a gene of known function and a gene of unknown function can by inference lead to the prediction of a general function for the uncharacterized gene. Multiple comparative genomi c tools are now available for the robust identification of co regulated genes based on genome sequence. These tools rely on the computational identification of transcription factor binding sites or riboswitches upstream of genes (Rodionov, 2007) Since these sites are rarely identical, two main methods are available for the representation of binding sites or riboswtiches. A consensus sequence is a representative sequence that matches all known sites but through the use of an extended language that properly describes degeneracy (Stormo, 2000) For instance, the presence of a C or T at a single position would be represented as a Y (for py rimidine) (Cornishbowden, 1985) Building upon the idea of consensus sequences, sequence logos are a way to display sequence motifs by giving
60 the relative frequencies of each nucleotide at each position (Schneider and Stephens, 1990) A more informative representation of a degenerate motif is the PWM ( p ositional w eight m atrices). PWMs take into account the observation that some positions are a site are more important than others (Stormo et al. 1982) Most methods for searching for potential regulatory sites and therefore regulation of novel genes use PWM (Rodionov, 2007) The training set composed of regulatory regions can be from several sources such as exper imentally determined sites or DNA microarray experiments. Comparative genomic approaches can also be used to determine novel regulatory sites with no a priori knowledge of the regulatory protein or the corresponding binding sites. For these in silico analy ses, the upstream regions of potentially co regulated genes, such as genes from the same metabolic pathway or involved in responding to the same stress, are used (McGuire et al. 2000) There are two main comparative approaches to identification of novel regulatory elements. The consistency check approach assum es that sets of co regulated genes are conserved in genomes that encode orthologous transcription factors (Mironov et al. 1999, Tan et al. 2001) Confidence in the site predictions is strengthened if it is found upstream of the same gene in several genomes. The phylogenetic footprinting approach makes the same assumption as the consistency check but it also assumes that regulatory sites diverge slower than nonregulatory sites (Blanchette and Tompa, 2002) This approach searches the upstream regions of orthologous genes for conserved regions. An important consideration in use of this approach is the selection of genomes; if the genom es are too closely related the alignment of upstream regions will be informative,
61 whereas sites are not sufficiently conserved in genomes too distantly related (Rodionov, 2007) These techniques have led to the identification and validation of novel regulons including fatty acid biosynthesis (McCue et al. 2001, Zhang et al. 2002) ribonucleotide reductases (Qin et al. 2003, Torrents et al. 2007) N a cetylglucosamine utilization (Yang et al. 2006a) and NAD metabolism (Rodionov et al. 2008) The SEED database and the subsystem based approach In 2005, the Fellowship for Interpretation of Genomes (FIG) released the SEED database, an annotation platform that puts genome annotation into the hands of experts (Overbeek et al. 2005) The SEED is built around the idea of subsystems which are basically spreadsheets of gene sets from sequenced genomes. The user builds a subsystem around a particular metabolic pathway such as NAD biosynthesis (Gerdes et al. 2006) or a process such as metal homeostasis (Rodionov et al. 2006b) by adding functional roles that are known or predicted to be involved in that pathway or process. For a NAD biosynthesis subsystem some example functional roles would be ADP ribose pyrophosphatase and nicotinamide phosp horibosyltransferase. For manganese homeostasis, the functional roles would be manganesesensing regulators and manganese transporters. Once the functional roles are defined the subsystem is populated with genes that belong to those functional roles. Each row in the subsystem represents a genome and each column represents a functional role (Figure 16). The genes are found within the cells of the spreadsheet. Once the subsystem is built, the user can then refine it by detecting mis annotations, over annotat ions or unannotated genes. Missing genes become immediately evident. The subsystem enables visual inspection of the presence of
62 proposed gene functions in genomes. If an organism is missing every gene in a given pathway but one, that one gene may be mis annotated. If all genes for a given pathway are present but one, that one gene may be mis annotated or locally missing. The SEED platform provides comparative genomic tools to finding these missing genes. For instance, using the subsystem approach, novel enz ymes required for the oxidation of D and Llactate to pyruvate were discovered. Shewanella spp. are able to use lactate as a sole carbon and energy source (Venkateswaran et al. 1999) however, homology searches failed to detect orthologs of known lactate oxidizing enzymes (Serres and Riley, 2006) To solve this discrepancy, Pinchuk et al. built a Lactate utilization subsystem that contained all known functional roles involved in the utilization of lactate (Pinchuk et al. 2009) Genes conserved and missing in Shewanella spp. and other organisms were determined. Using the tools available through SEED, a chrom osomal cluster of uncharacterized genes was predicted to encode the missing D and Llactate dehydrogenases (Pinchuk et al. 2009) The comparative genomic evidence leading to this prediction is provided. First, t hese uncharacterized genes clustered with one of the characterized genes in the pathway. This cluster was found to be missing from the one Shewanella sp. that lacked the ability to grow on lactate. Phylogenetic cooccurrence analysis revealed a negative co rrelation between one of these uncharacterized genes and the gene encoding the canonical D lactate dehydrogenase. The three other uncharacterized genes always formed a putative operon. There was also a negative correlation between these genes and the gene encoding the canonical Llactate dehydrogenase in some organisms. The prediction that one of the uncharacterized genes encoded a novel D lactate
63 dehydrogenase was tested and confirmed as was the prediction that the other three uncharacterized genes encoded a novel Llactate dehydrogenase (Pinchuk et al. 2009) Comparative Genomics and Metals Simulating metal depleted environments in the lab oratory has proven difficult because c ommon metal chelators exhibit broad sp ecificity that precludes targeted depletion of one specific metal from the culture medium. T o observe growth defects linked to the deletion of genes involved in zinc homeostasis i n most cases, the absence of the high affinity zinc transporter is required (Petrarca et al. 2010, Gabriel and Helmann, 2009) By growing E. coli under continuous culture conditions in a specially designed metal free chemostat, sufficient zinc depletion was achieved to reveal g rowth defec ts in the wild type znuABC background (Graham et al. 2009) However, this approach is labor intensive and not amenabl e to a broad s tudy of zinc homeostasis mechanisms across the bacterial kingdom. Fortunately, identification of putative Zur binding sites has proven a productive way to identify novel proteins involved in the adaptation to zinc limited environments By us ing experimentally determined Zur binding motifs and phylogenetic footprinting, PWMs were built and used to search available bacterial genomes (Panina et al. 2003) The ZnuABC transporter imports zinc in an ATP dependent manner and is thought to be the main target for Zur regulation (Patzer and Hantke, 2000) However, this analysis revealed that the Zur regulon in several bacteria is not limited to zinc transporters and other mechanism s that allow adaptation to zinc depleted environments were found. As ribosomes most likely constitute the largest reservoir of zinc within the bacterial cell, it is no surprise that a system has evolved to utilize this stockpile when needed. A
64 comparative genomic analysis originally performed by Makarova, et al. led to the identification of four ribosomal protein paralog pairs: one copy contained a Cys4 zinc ribbon motif (and are thus called C+) and the other copy lacked two or more of those residues (and are thus called C-) (Makarova et al. 2001) At the time, it was not understood why some organisms retained both copies. The Zur regulon analysis by Panina, et al. provided an explanation. In genomes where both C+ and Ccopies were found, the Ccopy was downstream of a Zur binding site (Panina et al. 2003) leading to the hypothesis that when zinc levels dropped, the Cribosomal paralog would replace the C+ copy in ribosomes liberating zinc for use by other zinc requiring proteins (Panina et al. 2003) This mechanism was subsequently experimentally confirmed in B. subtilis and Streptomyces coelicolor (Nanamiya et al. 2004, Natori et al. 2007, Shin et al. 2007, Gabriel and H elmann, 2009) Several other mechanisms were discovered by this comparative genomic analysis. ZinT, whose gene was fused to znuA in some genomes, was proposed to encode an additional component of the zinc ABC transporter (Pani na et al. 2003) This prediction was recently confirmed (Petrarca et al. 2010) The presence of uncharacterized genes belonging to COG1469 and COG0523 were also found in the Zur regulons of several bacteria. COG1469 was later shown to encode a GTP cyclohydrolase I, an example of nonorthologous gene displacement. In sequenced genomes, a negative correlation was found between the presence of the canonical GTP cyclohydrolase I and COG1469, which was subsequently shown to also have GTP cyclohydrolase I activity (El Yacoubi et al. 2006) Regulation of COG1469 by zinc was later rationalized. Some genomes
65 contain both a gene for the canonical GTP cylohydrolase I and COG1469. It is in those genomes where COG 1469 is predicted to be regulated by Zur. A model where COG1469 (a zinc independent enzyme) replaces the canonical GTP cylohydrolase I (a zinc dependent enzyme) was put forth and validated (Sankaran et al. 2009) The function of the COG0523 genes or what their role in zinc homeostasis may be is still unknown. Comparative genomic approaches have also been used to analyze the regulation of genes by iron, heavy metals, manganese, nickel and cobalt. A comparative genom ic analysis of Fur regulons led to the identification of novel iron acquisition mechanisms in proteobacteria, including novel siderophores and transporters (Panina et al. 2001) In Eubacteria, heavy metal resistance is commonly regulated by transcription factors from the MerR family of regulators. Individual members are responsible for mercury, copper, cadmium, lead or zinc resistance. Using a comparative genomic approach that included phylogenetic analyses and identification of regulatory sites, the functions of uncharacterized MerR proteins could be determined and novel resistance genes were discovered (Permi na et al. 2006) Analysis of reconstructed manganese responsive MntR and Mur regulons in proteobacteria revealed novel manganese transporters (Rodionov et al. 2006a) Analysis of nickel responsive NikR binding sites and B12responsive riboswtiches led to the identification of novel ABC type transporters (Rodionov et al. 2006b) These in silico studies reveal the advantages of using comparative genomics to indentify metal homeostatic mechanisms. A plethora of predictions in a large breadth of organisms are made with relative ease than can be used for targeted expe rimental validation.
66 The relative disadvantage of using traditional approaches to discover novel metal related mechanisms is epitomized by efforts to study the response of E. coli to zinc depletion. Studies on the effect of zinc depletion on E. coli start ed at the end of the 20th century. These were made possible by the identification and characterization of highaffinity zinc transport and the corresponding zinc sensing regulator (Patzer and Hantke, 1998, Patzer and Hantke, 2000) Five years later, Panina and colleagues built a putative Zur regulon in E. coli and over twenty other bacterial genomes. The first attempt to study the in vivo response of gene regulation to zinc depletion employed assistance from the met al chelator TPEN. Over 100 genes were found to be differentially expressed in the presence and absence of TPEN (Sigdel et al. 2006) compared to the five predicted by Panina. TPEN, however, is not specific to zinc and other divalent metal cations can be chelated. As a consequence, genes involved in iron and copper metabolism were detected in addition to any genes specifically responding to zinc depletion. This experiment highlights the difficultly accompanying highthroughput studies of regulation. They often reveal both direct and indirect responses which cannot be easily teased apart. To overcome the inherent problems with using metal chelators, Graham, et al. devised a method to specifically deplete cells of zinc through the use of continuous culture. Ten years after the discovery of Znu ABC and Zur, they were finally able to achieve specific depletion of zinc to see growth defects due to known homeostatic mechanisms. After specific zinc depletion was achieved (85fold reduction over normal minimal medium), a microarray analysis of cells g rown in zinc replete and zinc deplete
67 conditions was performed. In stark contrast to the TPEN experiment, only nine genes were identified to be differentially expressed (Graham et al. 2009) In comparison to the in silico Panina study six years earlier, three genes were in common: zinT znuA and a Cparalog. The Graham studied failed to detect induction of the permeas e and ATPase component of the highaffinity transporter, which were members of the Panina Zur regulon. Six genes in the Graham study were not found in the Panina study. None of these genes have previously been shown to be directly regulated by Zur and coul d be indirect effects of zinc depletion. Project Rationale, Design and Objectives Discovery of novel proteins and an understanding of these mechanisms can be accomplished by the combination of comparative genomic predictions and targeted experimental studies. The main objective of this project was to gain insight into novel mechanisms that allow bacteria to grow in environments poor in available zinc. The first goal of this project was to analyze the COG0523 protein family, which is composed of uncharacter ized proteins and poorly characterized proteins with putative links to metal related processes. As mentioned on page 43 COG0523 is a subfamily of the G3E family of GTPases, characterized members of which are involved in the maturation of metal dependent enzymes. The hypothesis was formed that COG0523 proteins may also be chaperones for yet unknown enzymes. Since the characterized members of GE3 cluster physically on the chromosome with their targets, COG0523 genes may cluster with their target. A comparati ve genomic approach, specifically a combination of phylogenomics and gene clustering, was chosen to examine this family in all domains of life. Gene clustering of COG0523 genes in prokaryotic chromosomes was determined in the
68 SEED database. From this analy sis, representative homologs were chosen to reconstruct the phylogeny of this family. To infer the gene function of uncharacterized members, COG0523 proteins found in the literature were included. Known and novel roles were examined by overlaying the phylogenetic tree with gene clustering data, functional information from the literature, and regulatory site predictions. Prior to the start of this project, an update to the Panina Zur regulon analysis was performed and has been made publically available through the RegPrecise database (Novichkov et al. 2010) This database includes regulon predictions for more recently sequenced genomes from proteobacteria, firmicutes and cyanobacteria. COG0523 homologs were frequently found in these putative regulons. A second group of COG0523 homologs were previously identified downstream of B12dependent riboswitches (Rodionov et al. 2003) From the phyl ogenomic analysis, general and specific predictions were made. One of these specific predictions was chosen and experimentally tested in E. coli genetically. The second goal of this project was to investigate the existence of paralogs for zinc dependent enzymes found in the putative Zur reglons. For targeted experimental verification, the DksA paralog was chosen. P. aeruginosa was used to test the hypothesis that a DksA paralog missing an essential motif can functionally replace the characterized DksA protein and expression of the paralog is regulated by zinc. P. aeruginosa is an ideal organism to study how bacteria have evolved to thrive in growth conditions where access to zinc is relatively restricted. Such an environment is encountered in the human host. Therefore, an understanding of how pathogens like P.
69 aeruginosa can persist under zinc depleted conditions can give valuable insight into infection.
70 Figure 11. Typical coordination geometry involving metal ions. M etal ions are represented by red spheres. Metal binding ligands and bonds to the metal are represented by blue spheres and blue sticks, respectively. CN, coordination number.
71 A B Figure 12. Organization of the hyp and ure gene clusters. A) G ene cluster from E. coli containing hypB B) Gene cluster from K. aerogenes containing ureG.
72 Urease [ NiFe ] Hydrogenase Methylmalonyl CoA mutase HQ2300A sce2717 Daci_1179 Fjoh_4832 cce_2903 WS0791 MeaB HypB UreG meaB B12dom. meaB mcm hypE hypD hypC hypB hypF hypB hypA ureG ureF ureE ureC ureB ureJ ureA ureD ureD ureG ureF ureE ureC ureB ureAFJ DA CY WS SC HWhypA COG0523 A B Figure 13. The G3E family of GTPases. A) A neighbor joining tree of the G3E family divided into the four subfamilies, COG0523, UreG, HypB and MeaB. Representative gene clusters for u reG h ypB and meaB are given. With the exception of COG0523, the leaves are protein names from the given organisms: FJ, Flavobacterium johnsonia; DA, Delftia acidovorans ; CY, Cyanothece sp. ATCC 51142; WS, Wo linella succinogenes ; SC, Sorangium cellulosum ; HW, Haloquadratum walsbyi Gene abbreviations: ureA urease gamma subunit (EC 18.104.22.168); ureB u rease beta subunit (EC 22.214.171.124); ureC urease alpha subunit (EC 126.96.36.199); ureD urease accessory protein; ureE u rease accessory protein; ureF urease accessory protein; ureG urease accessory protein; ureJ HupE UreJ family metal transporter; hypA [NiFe] hydrogenase nickel incorporation protein; hypB [NiFe] hydrogenase nickel incorporationassociated protein; hypC [NiFe] hydrogenase metallocenter assembly protein; hypD [NiFe] hydrogenase metallocenter assembly protein; hypE [NiFe] hydrogenase metallocenter assembly protein; hypF [NiFe] hydrogenase metallocenter assembly protein; meaB methylmalonyl CoA mutase auxillary protein; mcm, methylmalonyl CoA mutase; B12 dom. B12binding domain with homology to B12binding domain of methylmalonyl CoA mutase B) Cartoons of the metal centers from the target metalloenzymes of UreG (urease), HypB ([NiFe] hydrogenase) and MeaB (methylmalonyl CoA mutase).
73 Figure 14. General schematic of phylogenomic analysis. In step 1, a phylogenetic tree composed of members from a protein family is constructed. In step 2, functional information from the literature is overlaid on t he tree. A red line signifies that a protein has the characterized function A. A blue line signifies that a protein has the characterized function B. In step 3, function is inferred to uncharacterized members of the protein family.
74 Figu re 1 5. Schematic of common comparative genomic approaches to prediction gene function. The function of an unknown gene can be inferred by clustering or co occurrence with genes of known function. In phylogenetic co occurrence, the occurrence of genes in the same genomes is analyzed. Correlations in the phylogenetic distribution of genes relative to one another can be informative.
75 Functional roles Organisms Each number represents a gene with the specified functional role Genes with the same color signifies that those genes are neighbors Empty cells signify that a gene with the specified functional role is not found Figure 16. Screenshot of a subsystem from SEED ( http://theseed.uchicago.edu/FIG/ ). Terms discussed in the text are shown and descriptions for several elements are given. The term Neighbors is used to two or more genes that occur in a run as calculated in (Overbeek et al. 1999a)
76 CHAPTER 2 MATERIALS AND METHOD S Chemicals and Strains Materials Restriction endonucleases, T4 DNA ligase, prestained Protein Marker broad range (7 175 kDa), DNA ladders, Taq DNA polymerase, Phusion high fidelity polymerase and Phototope Star Detection Kit were from New England BioLabs (Beverly, MA). Desalted and biotinlabeled oligonucleotides were from Integrated DNA Technologies (Coralville, IA). Organic and inorganic analytical grade chemicals were from SigmaAldrich (S t. Louis, MO) and Fisher Scientific (Atlanta, GA). M etal salts (ZnSO4, CoCl2, CuCl2, MnCl2, FeCl3 and NiCl2) wer e purchased from Alfa Aesar (Ward Hill, MA) and were puratronic grade. Quantitative real time polymerase chain reaction (qRT PCR) reagents and m aterials, gel filtration standard, 40% arylamide/bis acrylamide solutions, Quick Start Bradford Protein Assay kit were purchased from Bio Rad (Hercules, CA). TRI zol LS reagent and One Shot Top 10 chemically competent E. coli were purchased from Life Tec hnologies (Carlsbad, CA). RNase Zap and T URBO DNase were from Ambion (Austin, TX). 2X Laemmli sample buffer, polyvinyl difluoride membranes (0.45 m pore size), Tris buffered saline with 0.3% nonfat milk, alkaline phosphatase conjugate antibody developed in goat were from Sigma Aldrich. Ni Sepharose High Performance resin was from GE healthcare ( Waukesha, WI ) QIAprep plasmid purification kit, QIAquick PCR and Gel extraction kits and RNeasy mini kits were purchased from QIAGEN (Valencia, CA). For gel shift assay, p ositively charged nylon membran e s were purchased from Roche (Indianapolis, IN )
77 Strains, Plasmids and Oligonucleotides Strains, plasmids and oligonucleotides used in each study are listed in Appendix F. E. coli K 12 MG1655 and P. aeruginosa P AO1 were used as WT strains. E. coli Top10 (Life Technologies) was used for routine cloning and E. coli BL21 DE3 was used for overexpression of recombinant protein. General Growth Conditions Media E. coli K 12 MG1655, P. aeruginosa PAO1 and derivatives were routinely grown at 37C in LB Lennox medium (LB) or in minimal medium containing 1X M9 salts (Sambrook and Russell, 2001) 0.1 mM CaCl2, 2 mM MgSO4, 3 mg L FeSO4 7H20 and 0.2% (w/v ) glycerol as the carbon source Incubation of liquid cultures was routinely performed in a Multitron INFORS shaker/incubator at 200 rpm. For E. coli EDTA and cadmium sensitivity assays, cells were grown in a low phosphate (LP) minimal medium (Mergeay et al. 1985) supplemented with 0.3% casamino acids and 0.2% glycerol. The iron citrate in this medium was replaced with 3 mg L FeSO4 7H20 When required for induction of PBAD, arabinose was added at a concentration of 0.0002% 0.2% (w/v) as specified. Liquid browth was solidified with 15 g of agar/liter. For plasmid maintenance in E. coli, the medium was supplemented with 100 g ml ampicillin (Amp) 10 g ml tetracycline (Tet), or 15 g ml gentamicin (Gm).For marker selection, 50 g ml kanamycin (Kan) or 30 g ml chloramphenicol (Cam) was used for the appropriate antibiotic resistance gene. For P. aeruginosa, 30 g m l Gm was used for marker selection and 200 g ml Amp was used for plasmid maintenance
78 Growth Curves Overnight cultures of strains inoculated with a single colony were grown in 5 mL LB, washed once with the appropriate minimal medium, and then normaliz ed to an optical density at 600 nm of 1.0 for E. coli and optical density at 660 nm of 1.0 for P. aeruginosa Optical density was measured with a 1 ml disposable cuvette in a BioSpec mini spectrometer. Normalized cultures were then diluted 1/500 into fresh minimal medium. Growth curves were generated with a Bioscreen C (Gr owth Curves USA, Piscataway, NJ ) (37 C, intensive shaking, 600 nm wavelength) in triplicate unless otherwise specificed. All growth experiments were repeated independently at least three times. Plate Assays Overnight cultures grown in 5 mL LB were washed with the appropriate minimal medium and normalized to an optical density of 1.0 at 600 nm for E. coli and optical density of 1.0 at 660 nm for P. aeruginosa Cells were washed once with an equal volume of the appropriate minimal medium, normalized to the same optical density, then serially diluted and 10 L of each dilution were plated onto appropriate solid media. N ormalization of cell number was confirmed by plating the various strains on minimal medium without selection. Growth was imaged at 24 hours after plating for E. col i and 36 or 67 hours for P. aeruginosa. All experiments were repeated independently at least three times. Bioinformatic Techniques Multiple Sequence Alignments Protein sequences were downloaded from the SEED (Overbe ek et al. 2005, 2009) or Genbank (Benson et al. 2009) databases. Sequences were aligned using the
79 ClustalW2 or MUSCLE algorithm with default parameters (Thompson et al. 2002, Edgar, 2004) Alignments were edited using Jalview and viewed using ESPript 2.2 (Waterhouse et al. 2009, Gouet et al. 1999) Subsystems Subsystems were built in the SEED database (Overbeek et al. 2005) Subsystems in their original format are available on the public SEED server at www.theseed.org Sequence Analysis Identification of protein motifs was performed with Fuzzpro from the EMBOSS software package (Ri ce et al. 2000) Sequence identity was determined with the NeedlemanWunsch Global Sequence Alignment Tool available at NCBI (Needleman and Wunsch, 1970) Phylogenetic Tree Reconstruction Phylogenetic analyses were carried out by employing the Phylip 3.67 program package (Felsenstein, 1997) Distance based matrices were generated between all pairs of sequences using the Jones Taylor Thornton matrix as employed in Protdist (Phylip). Phylogenetic trees were generated from these matrices using the neighbor joining m ethod as implemented in Neighbor (Phylip). Reliability of branches was determined with the bootstrap method of 1000 replicates using Bootseq (Phylip). Tree visualization was performed with Treedyn (Chevenet et al. 2006) DNA Techniques DNA Amplification DNA wa s amplified by polymerase chain reaction (PCR) using Phusion high fidelity polymerase (for subsequent cloning) or Taq DNA polymerase (for verification)
80 PCRamplified DNA was column purified with either QIAquick gel or QIAquick PCR purification kits acc ording to manufacturer s directions (Qiagen). Standard Molecular Cloning PCR products and destination vectors were digested with the appropriate restriction enzyme(s) and 1X restriction buffer as per the manufacturer s recommendations (New England Biolabs ). Ligation reactions were performed with T4 DNA ligase and 1X T4 ligase buffer at room temperature for 10 minutes or 4C overnight. To ensure fidelity of the PCR reaction, c loned PCR amplified products were sequenced using an Applied Biosystems Model 3130 Genetic analyzer (DNA Sequencing Facilities, Interdisciplinary Center for Biotechnology Research, University of Florida). DNA Electrophoresis The size of PCR products and linearized plasmids relative to a NEB 1 kB DNA ladder or NEB 100 bp DNA ladder were anal yzed by horizontal agarose gel electrophoresis using 0.8% 2% (w/v) agarose gels containing in 1X TAE buffer (40 mM Tris acetate, 2 mM EDTA, pH 8.5). Samples (5 l) were mixed with 1 l loading buffer (0.25% (w/v) bromophenol blue, 40% (w/v) sucrose) and loaded onto the gel. Following sufficient separation time (typically 45 min at 100V), the gel was visualized under UV light using a Kodak Gel Logic 2200 Imaging System with Kodak molecular imaging software (Carestream, New Haven, CT). Plasmid Isolation an d Transformation When high purity plasmid DNA was required, plasmid DNA was isolated with a QIAprep mini kit according to manufacturer s directions (Qiagen). For checking plasmid constructs by restriction enzyme digestion, 2 ml of an overnight culture of cells
81 harboring the plasmid grown in LB were centrifuged at 14,000 rpm in a benchtop microcentrifuge (Eppendorf 5417C) for 5 min. The cell pellet was resuspended in 50 l lysis buffer (0.2 N NaOH, 0.5% (w/v) SDS, 20% (w/v) sucrose) and vortexed. The mixture was then boiled for 5 min and allowed to cool to room temperature. 1.5 l 4 M KCl was added and the solution was vortexed. Cell debris was removed by centrifuging 3 min at 14,000 rpm (Eppendorf 5417C centrifuge). 5 l of the supernatant was removed used in a 10 l restriction enzyme digestion with appropriate restriction enzymes according to the manufacturer s guidelines (NEB). E. coli Top 10 chemically competent cells were transformed as per manufacturer s directions (Life Technologies). E. coli MG1655 derivatives and BL21 (DE3) were made competent with CaCl2. 2 ml of LB in a 5 ml capped test tube was inoculated with 50 l of an overnight culuture grown in LB. The culture was allowed to incubate with shaking (200 rpm). At the end of 2 hrs, the culture was centrifuged at 4,000 rpm (Eppendorf 5417C centrifuge) and resuspended in 200 l 0.1 M CaCl2. 50 ng of plasmid DNA was added to the cells and allowed to incubate on ice. At the end of 20 min, the cells were heat shocked at 42C for 35 sec. The cells wer e inbated on ice for 2 min, 1 ml LB was added and the cells were allowed to recover at 37C with shaking for 1 hr. The cells were then plated on solid LB medium supplemented with the appropriate antibiotic. P. aerginosa strains were transformed by electroporation as previously described (Choi et al. 2006) with the following changes. Instead of using an overnight culture, 50 m l of LB were inoculated with 1 ml of an overnight culture and grown for 2 hours at 37C then washed in preparation for electroporation.
82 Site Directed Mutagensis Site directed mutants were created by the overlap extension or megaprimer PCR method as described in (Sambrook and Russell, 2001) Phusion polymerase was used for each PCR reaction. QIAquick gel extraction kit was used for purification of each PC R product. For expression in E. coli mutated genes were inserted into pBAD24 (Guzman et al. 1995) between the unique Nco I and Xba I restriction sites. Primers used in the site directed mutagenesis are listed Appendix F, Table F 5 and Table F 6. P1 Tran sduction Transfer of mutant alleles between E. coli strains w as performed by bacteriophage P1 transduction as described by Miller (Miller, 1972) When required, the resistance marker was excised from the chromosome using FLP recombinase (Chere panov and Wackernagel, 1995) Deletions were confirmed by locus specific PCR amplification using primers that anneal to DNA either flanking the gene or anneal internal to the gene. Generation of P. aeruginosa M utants The Gm resistance gene from pEX18Gm w as PCR amplified with primers containing FRT sites (Zhou and Sadowski, 1994) at the 5 end (Hoang et al. 1998) Upstream and downstream regions flanking the gene of interest were PCR amplified from PAO1 genomic DNA and gel extracted using the QIAquick gel extraction kit. Genera tion of the gene deletion construct was performed by PCR overlap extension as previously described (Choi and Schweizer, 2005) and inserted into the appropriate res triction enzyme sites of pEX18Tc (Hoang et al. 1998) For gene replacement, a sacB based strategy (Schweizer and Hoang, 1995) was employed. The appropriate parent strain was transformed with the pEX18Tc deriv ative by electroporation. After recovery in LB, shaking at 200 rpm for 2 hr, the cells were plated on LB solid medium
83 plus Gm and incubated overnight. Gm resistant colonies were screened for Tet sensitivity. If only single homologous recombination events occurred as indicated by resistance to Gm and Tet, those colonies were inoculated into 5 ml LB, grown overnight, and plated onto LB (minus NaCl) and 10% (w/v) sucrose to select for excision of the plasmid from the chromosome Deletions were confirmed by PCR using both primers external to the upstream and downstream flank regions and primers internal to the gene. When required, the Gm cassette was excised with FLP recombinase (Hoang et al. 1998) RNA Techniques RNA Isolation For wholecell RNA isolation, a 5 ml aliquot of culture was taken at the appropriate time from a growing culture in the appropriate medium, then centrifuged at room temperature and the cell pellet was resuspe nded in TRIzol LS reagent then frozen at 80C. Once all the samples were collected, the s amples were t hawed at room temperature and RNA was extracted with chloroform The aqueous phase was then further purified using the RNeasy mini kit according to manufacturer s directions (Qiagen). T race DNA was removed with TURBO DNase according to manufacturer s gui delines (Ambion). Total RNA concentration was determined using a NanoDrop ND1000 spectrophotometer at an absorbance of 260 nm cDNA Synthesis and qRT PCR cDNA was reverse transcribed from total RNA using an iScript cDNA synthesis kit. qRT PCR reactions were performed using iQ SYBR Green Supermix according t o the manufactures guidelines Routinely, o ne nanogram of total m RNA was reverse transcribed, and then 1 l of cDNA was added to a 20 l SYBR Green reaction mix
84 containing 2.5% DMSO. qPCR on the generated cDNA was conducted in an iCycler MyiQ 2 real time system (Bio Rad) in triplicate. Reactions containing 0.1 ng of total m RNA from each sample served as controls for DNA contamination. Primers used in the qPCR reactions are listed in Appendix F, T able F 6 Standard curves were generated with serial dilutions of plasmid DNA containing the target gene. The cycling conditions were as follows: 1 cycle at 95C for 3 min, 40 cycles of 9 5C for 10 sec and 58C for 30 sec. Product uniformity was determine using melt curves. Data was analyzed using iQ 5 optical system software (Bio Rad) and the quantity of transcript presenct was determined by comparison to the standard curve. Protein Techniques Protein Overexpression in E. coli Overexpression of the Zur protein from P. aeruginosa was achieved as previously described (Gabriel et al. 2008) Briefly, 6 liters of LB supplemented with a final co n centration of 50 M ZnSO4 and 100 mg ml1 Amp was inoculated with 10 mL per 1 L from an overnight culture grown in LB. Cells were grown to an optical density of 0.8 at 600 nm. IPTG (final concentration, 1 mM) was added and the cultures which were then inc ubated at 30C for 6 hrs. Protein Quantification Protein concentrations were determined using a Quick Start Bradford kit with bovine gammaglobulin as the standard as per the manufacturers directions for 1 ml assays (BioRad). This kit is based on the Bra dford method (Bradford, 1976). Protein Separation and Chromatography Cells were harvested by c entrifugation at 5,000 rpm ( SORVALL RC 5B Superspeed centrifuge) at 4 C for 20 min. The pellet was stored at 80C. The cell
85 pellet was resuspended in ice cold lysis buffer (20 mM sodium phosphate, 500 mM NaCl, 10 mM imidazole, pH 7.3 and 2 mM DTT) and cells were lysed using TEEN B Lysing matrix and a FastPrep 24 (MP Biomedicals, Aurora, OH). The lysate was cleared by centrifuging at 5,000 rpm at 4C for 20 min Lysate was then transferred to 2 ml microcentrifuge tubes and centrifuged at 13,500 rpm (Eppendorf 5425R benchtop centrifuge) at 4C for 20 min in preparation for downstream chromatography. Cell lysates (to determine overexpression of target gene) and c hromatography fractions were monitored for purity by staining with Coomassie blue after separation by 10 or 12% SDS PAGE according to (Sambrook and Russell, 2001) Size of the protein band was estimated based on comparison to a broad range protein marker (BioRad). Cleared lysat e was loaded at 0.5 ml min1 on a 25 mL Ni Sepharose High Performance column preequilibrated with 200 ml lysis buffer The column was then washed with 200 ml wash buffer (lysis buffer with 20 mM imidazole instead of 10 mM). Protein was eluted with a linear gradient of imi dazole from 20 mM to 500 mM; 655 ml fractions were collected. Immunoblotting Cell lysates were separated by gel electrophoresis using 15% SDS PAGE gels. Proteins was transferred to an ImmobilonP polyvinylidene fluoride (PVDF) membrane using a Mini Trans Blot cell and a Mini PROTEAN 3 vertical electrophoresis system (Bio rad) with 1X Tris glycine buffer (3.029 g L1 Tris Base, 14.41g L1 glycine) at 40 mAmps for 90 min. Transferred membranes were blocked with Tris buffered saline with 0.3% nonfat milk for 1 hr at room temperature. Primary antibody, polyclonal DksA or DksA2 generated in rabbit (Blaby Haas, et al 2010), was prepared by diluting 1:500 in blocking buffer. The membrane was incubated with antibody for 1 hr then washed 3
86 times with 1X wash buffer (1.21 g L1 Tris Base, 8.77 g L1 NaCl, 5 ml 10% Tween, pH 7.4 with HCl). For each wash, the membrane was incubated for 10 min. The secondary antibody ( anti rabbit IgG (whole molecule) alkaline phosphatase conjugate antibody developed in goat ) was p repared by diluting 1:5000 in blocking buffer. The membrane was incubated with the secondary antibody for 1 hr, then washed 3 times for 10 min each wash with wash buffer. CPDStar reagent was added and the membrane was exposed to a Kodak x ray film for 30 sec to 15 min. Western blot analysis was independently repeated twice. Specificity of primary antibodies was confirmed by blotting against whole cell extracts from P. aeruginosa PAO1, dksA and zur grown in LB. Electrophoretic Gel Shift Assays (EMSA) Preparation of DNA substrate The DNA fragment used in the EMSA experiment was generated by PCR. One oligonuclotide was prelabeled at the 5 end with biotin. The PCR fragment was purified using a QIAquick spin column. Additionally, unlabeled DNA fragments for competition assays were generated by annealing two complementary oligonucleotides combined at equimolar concentration in 1X T4 ligase buffer. The oligonucleotide mixture was incubated at 95C for 5 min in a heat block. The heat block was removed from the incubator and allowed to cool to room temperature. Gelshift assays Protein of varying concentration and 1.5 ng of biotinlabeled DNA was added to 20 l of binding buffer (20 mM Tris HCl (pH 8.0), 50 mM KCl, 1 mM DTT, 5% glycerol, 0.1 mg ml1 bovine serum albumin, 5 g ml1 sheared salmon sperm DNA). The mixture was incubated for 20 min at room temperature. Samples were loaded on a 6% acrylamide-
87 bisacry lamide nondenaturing gel in 40 mM Tris acetate buffer (without EDTA) Electrophoresis was performed at 120 V and 4C using prechilled 40 mM Tris acetate buffer (without EDTA) as the running buffer. DNA was then transferred to a positively charged nylon membrance using a Mini Trans Blot cell and a Mini PROTEAN 3 vertical electrophoresis system at 400 mA for 40 min in 0.5x TBE. Transferred DNA was cross linked with a Fisher Scientific FB UVXL 1000 UV Crosslinker by using the optimal cross link setting. B io tin labeled DNA was detected using a Phototope Star Detection Kit following manufacturers directions. Membranes were exposed to a Kodak x ray film for 1015 min. Density of DNA bands was measured using Kodak molecular imaging software (Carestream, New Haven, CT). Pyocyanin Assay Overnight cultures of strains grown in LB were normalized to an optical density of 1.0 at 660 nm and then diluted 100fold into fresh LB. The cultures were incubated at 37C. At different time intervals, a 5 ml aliquot of culture was transferred to a 15 ml centrifuge tube and centrifuged at 4,000 rpm ( SORVALL RC5B Superspeed centrifuge) for 10 min. The supernatant was transferred to a fresh 15 ml centrifuge tube. Pyocyanin was then extracted from the supernatant with 3 ml chloro form, which was then centrifuged at 4,000 rpm for 5 min. The chloroform phase (will be a blueishgreen color) was removed and 1 ml 0.2 M HCl was added. The sample was vortexed and then centrifuged at 4,000 rpm for 5 min. The HCl phase (a pinkish color) was removed into a 1 ml plastic cuvette. Absorbance of the HCl pyocyanin phase was measured at 520 nm on a BioSpec mini spectrometer. A sample of uninculated medium that was also processed as per above and was accordingly used as the blank. The concentration of
88 pyocyanin was calculated by multiplying the absorbance at 520 nm by 17.072 ( Kurachi, 1958) Detection of Hydrogen Production Overnight cultures of strains grown in LB were diluted 100fold into 1 ml of LB supplemented with 0.3% glucose i n a 12 x 75 mm heavy wall tube, which was then sealed with a rubber stopper The tubes were degassed and filled with N2 and incubated. Hydrogen production was determined after injecting a 100 l sample with a Hamilton gas tight syringe into a gas chromatograph. Element Analysis Preparation of cell fractions and element analysis was performed per the prorocol provided by (Robinson, N. et al 2008). This protocol is detailed below. Sample Preparation Overnight cultures grown in LB were diluted 1000fold into 500 ml LB. The cultures were grown to an optical density of 0.7 at 600 nm. The cells were centrifuged and washed twice with 20 mM HEPES (pH 8.8) and resuspended in 5 ml of the same buffer. A p estle and mortar was e quilibrated in liquid nitrogen. Once equilibrated, the cell suspension was added to the liquid nitrogen is a drop wise manner and then the cells were ground thoroughly to a fine powder. The cell powder was placed in an anaerobic chamber and allowed to thaw for 10 min. The cell paste was placed in an airtight centrifuge tube and centrifuged at 160,000 X g, 30 min, 4C The supernatant was transferred in the anaerobic chamber to a fresh 15 ml centrifuge tube. Anion Exchange Chromatography In the anaerobic chamber, the cleared lysate (corresponding to 30 mg of protein) was loaded onto a 1 ml HiTrap Q HP anion exchange column (GE Healthcare) and
89 washed with 10 ml HEPES (pH 8.8). Protein was eluted by step gradient using 1 ml aliquots of the same buffer with 100 mM, 200 mM, 300 mM, 400 mM, 500 mM and 1 M NaCl. Size Exclusion Chromatography Each fraction from the anaion exchange separation was then further separated by HPLC size exclusion chromotagraphy. 200 ul aliquots from each fraction of eluant was loaded onto a TSK SW3000 column (Tosoh Biosciences) preequilibrated with 10 mM Tris HCl (pH 7.5), 1 M NaCl and 10 mM EDTA at 1.0 ml min1. 30 0.5 ml fractions were collected. ICP MS Three hundred microliter aliquots of each fraction from the size exclusion separat ion were diluted into 2.7 ml 2.5% (v/v) Suprapur HNO3 (Merck) and analyzed by I CP MS on a Thermo Electron Corporation X series inductively coupled mass spectrometer (Kevin Waldron, University of Newcastle, Newcastle, England).
90 CHAPTER 3 BIOINFORMATIC ANA LYSIS OF THE COG0523 FAMILY Background Although the other subfamilies of the G3E family of P loop GTPases are relatively well characterized, only sparse reports are found on COG0523 proteins. The first member of the COG0523 family to be identified was foun d in Pseudomonas denitrificans and named CobW (Crouzet et al. 1991) Disruption of cobW which is found in a gene cluster with cobalamin synthesis genes, leads to a defect in the production of cobalamin (Crouzet et al. 1991) Cobalamins are organometallic compounds that are composed of a Co(III) bound in an octahedral configuration to a corrin ring (Hodgkin et al. 1955) The proposed role for CobW is in presentation of cobalt to the cobaltchetelase component of the pathway, which is responsible for inserting cobalt into the corrin ring (Heldt et al. 2005) However, 20 years after its discovery, there is as of yet no experimental evidence for this function. Since cobalamin biosynthesis protein was the first role assigned to a member of COG0523, this annotation has been propagated by sequence similarity (e.g. BLAST) to nearly all COG0523 genes in current databases. Other partially ch aracterized members of COG0523 include the nitrile hydratase activators, which are required for iron type nitrile hydratase (NHase) activity (Nojiri et al. 1999) NHases are important enzymes in the industrial production of acrylamide and employ either an octahedral nonhe me iron (III) or non corrin cobalt (III) in the hydration of nitriles to amides (Yamada and Kobayashi, 1996) The active site residues of both NHase metal types are highly conserved and the same coordination geometry was determined for both Co(III) and Fe(III) (Endo et al. 2001) The two types of NHases,
91 however, explicitly incorporate the correct metal (Nojiri et al. 2000) This specificity is thought to be due to an activator protein, which is required for full activity (Nojiri et al. 2000, Nishiyama et al. 1991, Zhou et al. 2008, Nojiri et al. 1999, Hashimoto et al. 1994) In the case of irontype NHase, the corresponding activator protein is a COG0523 protein and is referred to as Nha3. As with CobW, ev en if the involvement of Nha3 in irontype NHase activation is documented, its exact role is not known. It has been postulated that it has an insertase role involved in incorporation of iron into the active site of the hydratase (Lu et al. 2003) When the iron d ependent NHase from Rhodococcus sp. N 771 was expressed in E. coli without Nha3 in cobalt supplemented media, it incorporated cobalt instead of iron (Nojiri et al. 2000) Therefore, Nha3 may not only be involved in incorporating iron, but also in ensuring that competing metal ions are excluded. In addition, the coexpression of Nha3 with NHase was found to be unnecessary with the coexpression of the GroESL chaperones (Stevens et al. 2003) which suggests that Nha3 is involved in ensuring proper folding of NHase. The most recently studied COG0523 protein is Y ciC from B subtilis Several observations led to the assumption that yciC coded for a component of a low affinity zinc transporter (Gaballa and Helmann, 1998) The gene, yciC is repressed by Zur, a zinc responsive transcription factor, and deletion of yciC in combination with a deletion in the highaffinity zinc transporter results in an EDTA sensitive growth defect (Gaballa and Helmann, 1998, Gaballa et al. 2002) As with CobW and Nha3, the mechanism responsible for this phenotype remains elusi ve.
92 As a result of these studies, genes encoding a COG0523 protein have been arbitrarily assigned either a function in cobalamin biosynthesis, in the activation of NHase, or as a low affinity zinc transporter without the means to automatically distinguish between these different functions. Nevertheless, each of these functions is related in a general sense to intracellular metal handling. The diversity of the metals putatively associated with COG0523, cobalt, iron, or zinc, suggests that there might be diff erent subgroups identifiable within the COG0523 family. This chapter presents the efforts to better understand the COG0523 family through comparative genomic techniques. COG0523 proteins occur in all kingdoms of life, and most sequenced genomes encode one or more homologs. An analysis is presented with the purpose to distinguish between the putative functional subcategories that are evident in the literature and enable predictions for the characterization of uncharacterized COG0523 genes. Particularly, the members of COG0523 found in eukaryotic and archaeal genomes are completely uncharacterized. Analysis and functional assignment of prokaryotic genes has been demonstrated to be a powerful technique to annotate eukaryotic genes (de Crcy Lagard and Hanson, 2007) indicating the importance of investigating the family with bioinformatic tools. Furthermore, to enrich these analyses, the results are placed in context with the current understanding on the other (nonCOG0523) members of the G3E family of P loop GTPases. Results Sequence Attributes The amino acid sequences of 887 COG0523 proteins from all kingdoms of life were compared. COG0523 gene sequences in the SEED database were identified by
93 homology to known COG0523 members and the presence of the conserved CXCC motif and P loop GTPase domain as found in the corresponding protein sequences. This definition led to the reannotation of genes that did not meet these criteria. cobW gene sequences were identified based on homology to cobW from P. denitrificans (Crouzet et al. 1991) and occurrence within cobalamin biosynthesis operons and/or downstream of a putative B12responsive riboswitches (Rodionov et al. 2003) a re gulatory RNA element modulating gene expression in response to changing B12 concentrations (Nahvi et al. 2002) Comparison with other G3E family members The region of highest similarity between COG0523 and the other members of the G3E family (G3E) was the GTPase domain, defined by the canonical Walker A, Walker B, and G4 motifs (Figure 31) (Leipe et al. 2002) Located within the GTPase domain, all members of COG0523 had a conserved, putative, metal binding CXCC motif (Figure 3 1). In addition to the GTPase domain, MeaB and most COG0523 proteins contained an additional C terminal domain that was not found in UreG or HypB. On average, COG0523 was 99 and 147 amino acids larger than HypB and UreG, respectively, and only 26 residues larger than MeaB. While the N terminal GTPase domain was well conserved among COG0523 members, this extra C terminal domai n was highly variable (Figure 3 1). Some HypB proteins are known to contain histidinerich regions (His stretches) (Fu et al. 1995) Therefore, the presence of these motifs in COG0523 proteins was examined. Located in the C terminal domain, approximately 40% of the sequences analyzed contained a histidinerich region (Figure 31); 365 COG0523 proteins contain
94 the minimal HXHXHXH motif, where X represents 0 4 residues. Some proteins contain a His stretch with up to 29 histidines, such as Ava_3717 from Anabaena v ariabilis : HSHDHHDHDHDHDHSTCEHDHHDHEHDHSACSHDHHDHDHSACGHDHHDHEHHH HHSDH. Correlation between His stretches and metallochaperone activity In [NiFe] hydrogense metallocenter biosynthesis, HypB is proposed to serve as a metallochaperone, delivering nickel to the maturation complex, which is facilitated by the presence of the His stretch (Fu et al. 1995, Olson et al. 1997) The HypB protein from E. coli does not have a His stretch, and, accordingly, a separate protein is proposed to serve as the metallochaperone component (Zhang et al. 2005) Therefore, the presence of a His stretch could be indicative of metallochaperone activity. Unlike HypB, most UreG proteins do not contain His stretches and a separate protein UreE is proposed to serve as the metallochaperone (Remaut et al. 2001, Benoit and Maier, 2003, Musiani e t al. 2004) However, an analysis of UreG proteins in the SEED database revealed that several UreG proteins do contain His stretches. This observation provided a chance to test the hypothesis that the presence of His stretches in G3E family proteins is evidence of metallochaperone activity. A comparative genomic analysis involving ureG was performed (Appendix A, Figure A 1). As with COG0523, a distribution of UreG proteins with and without a His stretch was found (Table 31). Furthermore, in genomes wher e UreG had a His stretch, the gene encoding UreE was missing (Table 31). The absence of ureE did not correlate with the presence of slyD the metallochaperone component of hydrogenase maturation (Zhang et al. 2005) as would be expected if SlyD performed the metallochaperone role
95 in those organisms (Table 31). B. japonicum USDA 110 and Frankia sp. Ccl3 were two exceptions to this trend as they lacked both ureE and a His stretch extension in UreG. Phylogenomic Analysis Literature reports suggest that COG0523 can be divided into subgroups based on putative function even though the exact mechanism behind those functions is unknown. These known functional subgroups include cobalamin biosynthesis, NHase activation, and zinc homeostasis. As of yet, efforts have not been made to determine the extent to which COG0523 can be divided among these subgroups and whether other roles are possible. Gene clustering The non COG0523 members of G3E ( hypB ure G and meaB ) were commonly found next to either genes encoding their target metalloenzyme or other accessory factors that are also involved in metallocenter biosynthesis (Appendix A, Figure A 2). Therefore, a comparative genomic analysis was performed to investigate the gene neighborhoods containing COG0523 genes (Appendix A, Figures A 3 and A 4). Previously, an analysis of cobalamin biosynthesis pathways in bacteria revealed that cobW was consistently found next to other cobalamin biosynthesis genes (Rodionov et al. 2003) and the NHase activator was found downstream from structural genes for NHase (Nojiri et al. 1999, Hashimoto et al. 1994) As summarized in Figur e 32 and detailed in Appendix B CO G0523 genes were found in fourteen significant gene clusters. Significance was determined by the SEED database score and corresponds to the number of genomes a gene cluster was found and the phylogenetic distance between those genomes (Overbeek et al. 1999a) It should be noted that there may be functionally significant gene clusters whose scores were not above the threshold set by
96 this algorithm. The interaction between NHase and COG0523 has been experimentally shown but the NHase/COG0523 gene cluster was not detected in this computational analysis. In comparison to the other G3E members, COG0523 was more widespread and more promis cuous in regards to gene neighborhoods. 32.8% of prokaryotic genomes within the SEED database contained ureG and 96% of those genes were in a putative operon with the other known urease accessory factors. 29.5% of prokaryotic genomes contained hypB and 95% of those genes were in a putative operon with characterized hydrogenase accessory factors. meaB was found in 26% of genomes and 63% of those genes were in a cluster with either the gene that encodes MCM or a gene that encodes the adenosylcobalamin binding domain of MCM. In contrast, 54.6% of prokaryotic genomes contained at least one COG0523 gene and these genes were found in at least 14 significant gene neighborhoods (Figure 32; Appendix B). Most genomes contain only one homolog of hypB ureG or meaB (A ppendix A, Figure A 2) Conversely, 62.4% of prokaryotic genomes that contained a COG0623 gene had at least two. Up to 11 COG0523 genes could be found in a single genome, as seen in Cyanothece sp. ATCC 51142. Phylogenetic reconstruction To analyze the pr esence of multiple COG0523 subgroups, gene neighborhood analyses performed with the SEED database, literature reports, and gene regulation predictions provided by (Rodionov et al. 2003) the RegRecise collection (Novichkov et al. 2010) and the SEED database (Overbeek et al. 2005) were mapped onto a phylogenetic tree reconstruction of represent ative COG0523 proteins. The COG0523
97 distance tree was built with 177 full length COG0523 sequences. Protein names can be found in Appendix D, Table D 3. These sequences were chosen based on three criteria. First, from each of the 14 COG0523 gene clusters f ound in the gene clustering analysis above, sequences were chosen for inclusion in the tree based on their PCBBH score (PCBBH is the acronym for p air of close b idirectional h its and the PCBBH score is a measure of the phylogenetic distance between the pair, which correlates with significance). Because of how the score is calculated, certain COG0523 genes will have higher scores than other COG0523 genes (proportional to the predicted significance of the clustering). For example, if a COG0523 gene in a Firm icute genome (A) was recently acquired from the genome of a proteobacterium (B), then those two COG0523 genes (A and B) will have a higher PCBBH score than two COG0523 genes from proteobacteria (B and C). This is because 1) genes A and B have higher sequence similarity than B and C, and 2) the genomes to which A and B belong are phylogentically more distant than the genomes to which genes B and C belong. For each of the 14 gene clusters observed, the COG0523 genes with the highest PCBBH score were chosen. Second, all COG0523 proteins whose genes were identified as being downstream of predicted Zur binding sites (Novichkov et al. 2010) were included. Third, the CO G0523 proteins from six eukaryotes were also used, including 10 COG0523 homologs from the alga Chlamydomonas reinhardtii C. reinhardtii is a model organism for the study of trace metal homeostasis (Merchant and Bogorad, 1986a, Allen et al. 2007, Merchant et al. 2006) and the response of these COG0523 genes to zinc, copper, iron and manganese deficiency was available. Therefore, these data
98 represented an opportunity to test whether this phylogenomic analysis was i n agreement with the results of that analysis. RV0106 from M. tuberculosis CDC1551 was used as an outgroup in the phylogenetic reconstruction. This protein, while having similarity to COG0523, does not contain the canonical CXCC motif (CXSC). In addition, it is missing the canonical Walker A motif of the GTPase domain, suggesting that this COG0523like protein does not have GTPase activity. The phylogenomic analysis resulted in the identification of fifteen subgroups (summarized in Figure 32, detailed in Appendix B and Appendix C). To be designated as a subgroup, a group of proteins had to be monophyletic (forms a clade; composed of an ancestor and all of its descendents (Ashlock, 1971) ) and the corresponding genes should belong to similar genomic neighborhoods and/or share conserved regulatory sites: coenzyme B12responsive riboswitches or Zur binding sites. Two exceptions were made. Subgroups 1 and 5 appeared to be paraphyletic. The clade composed of subgroup 1 also contained subgroup 2 and the clade that contained subgroup 5 also contained subgroup 4 (Appendix C). Subgroup 1 and 2 were separated because subgroup 1 proteins were encoded by genes linked to zinc homeostasis through gene clustering or the presence of putative Zur binding sites, and subgroup 2 proteins appeared to be NHase activators based on literature reports and gene clustering. Subgroup 5 and 4 were separated due to respective gene clusters. Five subgroups (1, 2, 5, 12 and 13) are analyzed in more detail below. The remaining 10 subgroups are detailed in Appendix B.
99 Zur regulated COG0523 proteins subgroups 1, 5 and 13 Sixtyeight COG0523 genes were found to be downstream of a potential Zur binding site mainly in Firmicutes and and proteobacteria. Two COG0523 genes were found downstream of a putative Zur site in C yanobacteria, Prochlorococcus marinus, Nostoc sp. PCC 7120 and several Cyanothece spp. While most proteins encoded by Zur regulated COG0523 members were found in subgroup 1 (75%), several paralogs were found in other subgroups. For instance, in Pseudomonas entomophila, Pseudomonas fluorescens and Pseudomonas putida there were two COG0523 homologs per genome predicted to be downstream of a Zur binding site. From the phylogenetic analysis one paralog was assigned to subgroup 1, while the other was assigned to subgroup 11 (Appendix C). Zur regulated COG0523 paralogs were also found in subgroup 5, 8, 10 and 14 (Appendix B and Appendix C). The nitrile hydratase acti vator subgroup subgroup 2 Based on this analysis, less than 0.7% of the COG0523 family was represented by the NHase activators (Subgroup 2, Figure 32). A complete list of identified irontype NHase activators from both Genbank and SEED databases is given in Appendix B. In the literature, these proteins are referred to as Nha3, P44K, or P47K, depending on the organism in which the protein was identified (Appendix B). Here, this subgroup of COG0523 is referred to as Nha3. Nha3 was found clustered exclusively with the genes encoding the two subunits of the irontype NHase (Figure 33), which can be distinguished from the cobalt type NHase by the strictly conserved metal binding motifs CSLCSCT for Fe(III) and CTLCSCY for Co(III) (Banerjee et al. 2002) In addition, this COG0523 subgroup appeared to be clos ely related with the COG0523 proteins expected to be involved in zinc homeostasis (Figure 32, Appendix C).
100 The CobW subgroup subgroup 12 Although "cobalamin biosynthesis protein" is the most highly propagated annotation for COG0523 members, this compar ative genomic and phylogenetic analysis suggested that true CobW proteins (Subgroup 12, Figure 32) represent only 12.5% of the COG0523 family. In three proteobacteria genomes from the Rhodospirillaceae family, cobW genes belonged to the cobalamin biosynthesis gene clusters that were not preceded by putative B12regulated riboswitches cobW orthologs in Cyanobacteria were neither clustered with B12 biosynthesis genes nor putatively regulated by a B12 riboswitch. However, these orthologs were included in s ubgroup 12 since they were highly similar to other CobW proteins and the corresponding genes co occurred with the cobalamin biosynthesis genes of the aerobic pathway. cobW was often found adjacent to the cobalt chelatase component, cobN (Figure 3 4) and al l CobW proteins analyzed contained a His stretch, which on average was composed of 7 histidines (the least being 4 histidines and the most being 15). COG0523 proteins in Archaea Although COG0523 was previously assumed to be missing from Archaea (Leipe et al. 2002) the availability of recently sequenced genomes revealed that out of 44 archaeal genomes in the SEED database, eig ht genomes contained at least one COG0523 homolog. Eight homologs were found in Methanosarcina acetivorans C2A containing (Appendix A, Figure A 4). Most Archaeal members belonged to subgroup 13, members of which co localized with genes for corrinoiddependent methyltransferase (Figure 35). In Methanosarcina barkeri, M. acetivorans, Methanosarcina mazei and Methanococcus maripaludis COG0523 genes clustered with genes involved in methanol:CoM methylation: mtaA,
101 mtaB (both are zinc dependent (Sauer and Thauer, 1997) ), mtaC (corrinoid protein (Sauer et al. 1997) ) and ramM (iron sulfur protein (Ferguson et al. 2009) ) (Figure 3 5). Clustering between COG0523 and methanogenesis genes was not limited to Archaea but also found in Clostridium botulinum (Figure 35), which was the reason for the high functional coupling score between COG0523 genes and methanol:CoM methylation. Another clostridium, Desulfitobacterium hafniense DCB 2, encoded a COG0523 gene that clustered with a MeTr homolog (methyltetrahydrofolate:corrinoid/ ironsulfur protein methyltransferase) (Figure 35). In support of the functional coupling between COG0523 genes and ramM, MM1072 ( M. mazei COG0523 gene ) was induced to the same extent as its neighbor ing ramM homolog, MM1071 during growth in high salt conditions (2.38and 2.21fold, respectively) (Pflger et al. 2007) COG0523 proteins in Eukarya COG0523 genes were found to be widespread in eukaryotic genomes. Most eukaryotic organisms contained one to four homologs (Appendix A, Figure A 5). Gene clustering is not very informative in eukaryotes but most eukaryotic COG0523 homologs including Homo sapiens belonged to subfamily 5 (Figure 36). The prokaryotic members of subfamily 5 were found to cluster on the genome with genes that encode WD40repeat proteins (Figure 37). WD40 repeat proteins form a propeller structure thought to mediate proteinprotein interactions (Smith et al. 1999) Subfamily 5 COG0523 genes also were found to cluster the genes encoding the components of the highaffinity zinc transporter and creatinase encoding genes (Figure 37). Several prokaryotic members of subfamily 5 were pr edicted to be downstream of a Zur binding site (Appendix C).
102 Discussion Characterized members of the G3E family are proposed to perform two roles in metallocenter assembly: 1) facilitating incorporation of the cofactor in an energy dependent manner into t he target protein's catalytic site (the insertase role), and 2) storage and delivery of a metal cofactor to a target metalloprotein (the metallochaperone role). G3E family proteins have been found to function as either metal insertases or as a dual function metallochaperone/insertase. Little is known regarding the function of COG0523; however, the other G3E subfamilies are relatively well characterized. As a way to infer the function of COG0523 proteins, a comparison with those subfamilies was performed. T he assumption was made that general features such as metallochaperone and/or insertase activity is maintained among COG0523. As a way to distinguish these two roles, an analysis of His stretches was performed, since for HypB the His stretch seems to correl ate with metallochaperone function. To strengthen the argument that a His stretch in a G3E protein eliminates the need to an additional metallochaperone, a comparative genomic analysis of UreG was performed. Although, the presence of His rich regions was previously thought to be absent from bacterial orthologs of UreG and only present in plant orthologs (Witte et al. 2001) one of the comparative genomic analyses presented here revealed that several bacterial orthologs do contain His rich regions. As expected, if the His stretch signifies metallochaperone activity, a His stretch in UreG was found in genomes that lacked the gene for the characterized metallochaperone component UreE (Table 31). This observation sugg ests that the His stretch can compensate for the lack of metallochaperone in urease maturation. B. japonicum USDA 110 and Frankia sp. Ccl3
103 were found to be two exceptions to this trend. In these cases, the nickel metallochaperone involved in urease maturat ion could be HypB, which was present in both of these organisms (Appendix A, Figure A 2). Indeed, in Helicobacter pylori, HypB is required for activity of both [NiFe] hydrogenase and urease (Olson et al. 2001) and a physical interaction between UreG and HypB has been verified (Stingl et al. 2008) These two observations suggest that Hyp B may be responsible for delivery of nickel to UreG. Although the traditional urease metallochaperone UreE is encoded in the H. pylori genome, it is missing the His stretch found in other UreE proteins. The addition of a His stretch to the H. pylori UreE w as found to eliminate the need for HypB in the maturation of urease (Benoit and Maier, 2003) These results further support the conclusion that the His stretch functions in metallochpaerone activity. Another putative metal binding motif, CXCC, was found in all COG0523 proteins analyzed. This motif is commonly found in metallothioneins, which are involved in metal homeostasis (Gutirrez et al. 2009) The CXCC motif was found to be essential for the activity of the NHase activator, a member of COG0523 proposed to be involved in the inco rporation of iron into irontype NHase (Lu et al. 2003) In the crystal structure of YjiA, a COG0523 protein from E. coli this motif was found in a threestranded meander, which was directly attached to the switch I region of the protein (Khil et al. 2004) .Characteristically, GTPases are composed of two regions, switch I and switch II, that contain residues which bind to the phosphate of GTP (Vetter and Wittinghofer, 2001) Upon GTP hydrolysis, the phosphate is cleaved releasing the switch region residues that then relax into the GDP bound form of the protein (Milburn et al. 1990)
104 Therefore, depending on whether GTP or GDP is bound, the protein can have two structural conformations (Milburn et al. 1990) Since the CXCC motif is attached to the switch I region, binding of GTP may affect its relative position in the tertiary structure of the protein (Khil et al. 2004) COG0523 proteins on average appeared to have an extra C terminal domain that was not found in either HypB or UreG proteins. The size of COG0523 proteins was on average more similar to the size of MeaB proteins. Size could be an indication of the number of other accessory proteins required for activation of the target metalloprotein. The smallest G3E protein, UreG, is the GTPase component of a complex composed of UreD and UreF, where the three proteins act together in the activation of urease (Soriano and Hausinger, 1999) In contrast, activation of MCM appears to only require delivery of the cofactor by adenosyltransferase and the activity of MeaB (Padovani et al. 2008) The amino ac id sequence of the extra C terminal domain found in COG0523 proteins was highly variable (Figure 31). Indeed, COG0523 proteins fall under the category of "segmentally variable genes (SVGs)," as defined by Zheng et al. (Zheng et al ., 2004) SVGs are genes that code for proteins that have highly variable regions inte rspersed with well conserved regions. The authors observed that SVGs encode proteins that are involved in adaptation to environmental stresses and proposed that highly variable domains are an indication of proteinprotein interaction specificity or specifi city of small molecule binding. Of the subgroups defined here, several of them (5 out of 15) were associated with zinc either through putative regulation by Zur or through colocalization on the genome
105 with genes known to be involved in the response to zinc. A survey of the literature reveals that members of COG0523 are often implicated in the virulence of pathogens whose hosts are known to induce zinc limitation as a defense strategy.In M. tuberculosis a COG0523like gene, RV0106, (shown to be repressed by Zur (Maciag et al. 2007) ) was upregul ated during human macrophage infection (Cappelli et al. 2006) (although RV0106 shows homology to COG0523, it was found to be missing the canonical GTPase motifs, and the second cysteine of the CXCC motif was not conserved). In the closely related Mycobacterium avium subsp. paratuberculosis this gene was found on a pathogenicity island (Stratmann et al. 2004) and the corresponding protein was the second strongest antigen consistently reactive with cattle sera infected with M. avium or Mycobacterium bovis (Bannantine et al. 2008) COG0523 genes were also found in a pathogenicity island from Enterococcus faecalis (McBride et al ., 2009) Loss of the COG0523 gene in Brucella suis rendered this bacterium incapable of intramacrophagic replication (Khler et al. 2002) while loss of the COG0523 gene in Burkholderia pseudomallei resulted in the inability to infect Caenorhabditis elegans (Gan et al. 2002) An ortholog from Francisella tularensis was expressed exclusively in bacteria separated from infected murine spleen tissue (Twine et al. 2006) This gene was downregulated in the Francisella novicida pmrA mutant (Mohapatra et al. 2007) PmrA is a transcription factor found to be essential for survival/growth inside human and murine macrophage cell lines (Mohapatra et al. 2007) In plants, an opposing defense st rategy may be employed, as repression of zinc uptake machinery is required for full virulence of the plant pathogens, X. campestris and
106 X oryzae (Tang et al. 2005, Huang et al. 2008, Yang et al. 2007) In contr ast to animal pathogens and further supporting a role for COG0523 in zinc homeostasis, two COG0523 gene homologs of A. tumefaciens as well as the genes encoding the highaffinity zinc transporter, ZnuABC, were downregulated in response to plant signals (Yuan et al. 2008) The phylogenomic analysis presented here further suggests that, in addition to the bacterial orthologs, the eukaryotic orthologs of COG0523 may be involved in zinc homeostasis. In support of this assertion, two COG0523 gene homologs from the alga C. reinhardtii were found to be induced under zinc deficient conditions compared to zinc replete conditions (Haas et al. 2009) The corresponding protein for one of these genes was assigned to subgroup 1 and the other was assigned to subgroup 5. As discussed, both of these subgroups are enriched with prokaryotic members whose genes either physically cluster on the genome with genes involved in zinc homeostasis or are putatively regulated by Zur. Conclusions These analyses provide a foundation for understanding the function of known and yet to be identified COG0523 proteins. The sequence analysis suggests that COG0523 proteins have characteristics similar to and distinct from the nonCOG0523 members of the G3E family. On the one hand, sequence motifs suggest that like characteri zed G3E family members COG0523 proteins are GTPases and most have metal binding motifs. The distribution of His stretch motifs suggests that COG0523 proteins could function as metallochaperones and/or insertases. Unlike the other members of G3E, COG0523 pr oteins can be separated into numerous subgroups that are supported by computational approaches and literature reports. The diversity of genomic co-
107 localization suggests that COG0523 is more diverse than the other subfamilies of G3E. Both the metal specific ity and the protein target(s) might vary from one subgroup to another. While known roles in cobalamin biosynthesis and response to zinc limitation predominate, this analysis implies members of COG0523 are not limited to those roles. Based on genome context (co localization and/or presence of a coenzyme B12 riboswitch) and protein similarity analyses, only 12.5% of sequenced COG0523 from the SEED database are true CobW proteins and assigned to the cobalamin biosynthesis pathway. Only ~30% of COG0523 members analyzed are linked to zinc homeostasis either through putative Zur sites (~8%) or co localization with genes involved in the response to zinc starvation (~20%). In addition the third known role, NHase activator, only applies to less than 1% of sequenced C OG0523 genes. Over half of COG0523 may perform a role in the activity of unknown proteins.
108 A B G xxG x GK GC x CC Walker A GTPase domainhhhE xx G Walker B NKx D Variable C -terminus domain +/ stretch +/ stretchHFLEDHHHHHHDD Bacillus licheniformis Bordetella pertussis HDHHDHDHGHGHDHDHDHDHE GECGAHCNHHHHHHHAHHDD Salmonella enterica HSHTHTS Prochlorococcus marinus HEHEHEHEHEHEHEHEHEHEH Figure 3 1 COG0523 amino acid conservation plot A) Plot of amino acid conservation. The conserved GTPase motifs are highlighted in red. The conserved GCXCC motif is highlighted in yellow. The most common positions of His stretches are shown. The taller the bar the higher the conservation of amino acid residues is at that position. For instance, the Walker A motif (G XXG X GK) and the cysteine motif (C XCC) are absolutely conserved. B) Typical histidine rich sequence s found in COG0523 homologs from specified genomes. Protein identifiers used in this analysis are available in Appendix D, Table D 1
109 Table 31. Co occurrence profile of ureE and UreG Hi sstretch. Presence (+) or absence ( ) of ureE, a His stretch in UreG, and the presence of slyD in representative genomes from the SEED database Organism ureE UreG histidine stretch slyD Anaeromyxobacter sp. Fw1095 HDHSLHSGHDHGLGPGSFHDRGAPH + Arabidopsis thaliana HDHHHHHHDHEHDH B. japonicum Cytophaga hutchinsonii HLDHFDSPGHFHHRELIH + Frankia sp. Ccl3 Gibberella zeae HSHDGQSHSHDGFNAQEHGHSH + Herpetosiphon aurantiacus HVHDDHHHHHHH (Cterminus) Magnaporthe grisea HSHSHDGSAPHSHSHDGSTFNAQEHGH SH + M. bovis HSHPHSH Mycobacterium marinum HSHDHTHDHH M. tuberculosis HSHPHSH Mycobacterium vanbaaleni HFLDGQPHGH Neurospora crassa HTHSHDHGDGGHHHHPHSHSHDFNSQ SGFNAQEH GHSH + Nocardia farcinica HDHAH Schizosaccharomyces pombe HKGGSDDSTHHHTHDYDHHNHDHHGH DHHSHDSSSNSSSEAARLQFIQEHGHSH Sorangium cellulosum HDPGEHGHGRHDHDHDHDHVHDHDHD HDHVHGGGHRHAHEHEHAHEHAHGHE HGHAHAHAHAHAHEHAHGHTHEHWAH + Streptomyces avermitili s HLDHAHTH S. coelicolor HLDHHH Verminephrobacter eiseniae HHLHH + Bacillus cereus + Corynebacterium glutamicum + Haloarcula marismortui + Rhizobium leguminosarum + Ureaplasma urealyticum + H. pylori + +
110 1 folE2 yciCAcinetobacter baylyi 2Acinetobacter baylyi (12)amdA nha3 nhaB nhaA Prochlorococcus marinus ( 6 )pcd ppa futB 0523 0432 taqCP 3mhubiD ubiX uraA 0523mhBurkholderia multivorans ( 5 ) atzB 4 wd40 0523 znuA znuB znuCBradyrhizobium japonicum ( 29 )5 6 0523 dacC amaBrucella suis ( 13 )7 gatA potD potA 0523 cih potD fabGRhizobium leguminosarum (5 )9yjiX 0523 cstA2Pseudomonas aeruginosa (19 )11DUF1826 0523 yciCPseudomonas putida (6)12cbiP pduO cobU cobW cobN cobG cbiC cbiL cbiHGranulibacter bethesdensis ( 51 )13ramA mtbA mtaA mtaC 0523Methanococcus maripaludis ( 7 )15 0523 feoB trxBStaphylococcus aureus ( 4 )10 0523 lpxT spr rtn oppA oppB oppC oppDYersinia pseudotuberculosis ( 39 )8zur 0523 znuA znuB znuC dksA hslV hslUBordetella avium ( 27 ) 14 0523 4989Staphylococcus saprophyticus ( 8 ) putative Zur binding site putative B12riboswitch members linked to zinc homeostasis members linked to activation of Fe NHase members linked to B12biosynthesis folE2 yciC zurPseudoalteromonas atlanticaDUF1826 1Pseudomonas fluorescens DUF1826 yciC dksA2 0523-11 1 yciCBacillus subtilis (51) 1 Figu re 3 2. Phylogenomic analysis of COG0523. Collapsed COG0523 distance tree; each subgroup (3,4 and 615) was collapsed to its common node. Since subgroup 5 and 1are paraphyletic, branches were collapsed to multiple nodes. Representative gene neighborhoods for each subfamily are shown and corresponding genome. Numbers in parentheses refer to the number of species where the gene cluster occurs. For subfamily 1, this number refers to the number of species that contain a putative Zur regulated yciC Abbreviations: 0523', COG0523 homologs ; yciC ', subfamily 1; cobW ', subfamily 12; nha3', subfamily 2. For subfamily 1, 052311' refers to a subfamily 11 COG0523 homolog that is found in the same gene cluster as yciC All other gene abbreviations can be found in A ppendix D, Table D 2. The full COG0523 tree is available in Appendix C.
111 Roseobacter sp. MED193 Sinorhizobium meliloti 1021nhlA nhlB nhlE amdA nhaA nhaB COG0523Rhodococcus jostii RHA1 Burkholderia ambifaria AMMD Burkholderia ambifaria MC40 6 Pseudomonas putida F1 Acinetobacter baylii ADP1 Burkholderia cenocepacia AU 1054 Burkholderia cenocepacia MCO 3 A B Figure 33. Genome context of predicted nitrile hydratase activators. A) Gene clusters of predicted Fe type nitrile hydratase subunits and corr esponding activator proteins. A COG0523 family gene, encoding the activ ator, is found upstream of the and subunits of the Fetype NHase genes NhaA contains the Fe (III) binding motif, CSLCSCT. B ) Gene cluster of representative, predicted Co type nitrile hydratase activator subunits. nhlE which shares no sequence homology with COG0523, is found upstream of the Cotype nitrile hydratase subunit genes NhlA contains the Co(III) binding motif, CTLCSCY.
112 Methylobacterium sp. 4 46 cobW cbtA cbtB cobN B12riboswitch cobG cbiC cbiL cbiH Rhizobium leguminosarumcobW cobU cobN / cobG p duO Granulibacter bethesdensis cobW cobN cobG cbiC cbiL cbiH Delftia acidovoranscobW cobN btuB btuF btuC btuD Pseudomonas mendocina cobW cobN cobU pduO Figure 34. Genome context of subgroup 12 members. A bbreviations: cobW subfamily 12 COG0523 paralog; cbtB c obalt transporter subunit; cbtA cobalt transporter subunit; cobN cobaltochelatase subunit; cobG precorrin 3B synthase; cbiC cob alt precorrin 8x methylmutase; cbiL c obalt prec orrin 2 C20 methyltransferase ; cbiL c obalt preco rrin 3b C17methyltransferase; cbiH, cobalt precorrin 6x reductase; cobU a denosylcobinamidephosphate guanylyltransferas e; pduO c ob(I)alamin adenosyltransferase; btuB o uter membrane vitamin B12 receptor; btuF v itamin B12 ABC transporter, B12binding component; btuC b itamin B12 ABC transporter, permease component; btuD v itamin B12 ABC transporter, ATPase component. Grey arrows represent genes annotated as hypothetical.
113 COG0523 MeTr CBP COG0523 ramA mtaC cmuC cmuCClostridiaDesulfitobacterium hafniense Desulfitobacterium hafniense COG0523 ramA mtbC mtbA mtbA mtbAClostridium botulinum Syntrophomonas wolfei COG0523 ramA mtaC mtaA mtbA mtaA COG0523 ramA mtaA metH mtbA mtbA COG0523 mtaC / uroD COG0523 ramA mtaA COG0523 mtaA ramA COG0523 ramA mtaA mtaC mtaB EuryarchaeotaMethanosarcina acetivorans Methanosarcina barkeri Methanosarcina mazei Methanococcus maripaludis Figure 35. Genome context of subgroup 13 members. Subgroup 13 g enes colocalize with genes encoding methyltransferases, corrinoidbinding proteins, and a protein responsible for corrinoid recycling. Abbreviations: cmuC corrinoid methyltransferase like; metH methyltetrahydrofolate:corrinoid/ironsulfur protein methyl transferase; CBP, B12 binding domain of corrinoid proteins; mtaC/mtbC corrinoidbinding protein; ramA iron sulfur protein that mediates the ATP dependent reductive activation of Co(II) corrinoid to the Co(I) state; mtbA m ethylcobalamin:coenzyme M methyl transferase, methylaminiespecific; mtaA m ethylcobalamin:coenzyme M methyltransferase, methanol specific; mtaB m ethanol:corrinoid methyltransferase.
114 Chlamydomonas reinhardtii ( 117458 ) Chlamydomonas reinhardtii ( 106748 ) Saccharomyces cerevisiae (YNR029c) Taeniopygia guttata Rattus norvegicus Homo sapiens (CBWD1) Homo sapiens (CBWD2) Oceanobacillus iheyensis Sinorhizobium meliloti Nitrobacter sp. Nb 311A Bradyrhizobium japonicum Caulobacter crescentus Chlamydomonas reinhardtii ( 195946 ) Chlamydomonas reinhardtii ( 122261 ) Enterococcus faecalis Chlamydomonas reinhardtii ( 101629 ) Arabidopsis thaliana (At1g26520) Arabidopsis thaliana ( A t1g80480) Arabidopsis thaliana (At1g15730) Nitrobacter hamburgensis Rhodopseudomonas palustris Bartonella henselae Rhizobium leguminosarum Serratia marcescens Mesorhizobium sp. BNC1 Brucella suis Synechococcus sp. WH 8102 Nostoc sp. PCC 7120 3 7 8 9 10 11 12 13 14 15 1 and 2 4 6 Figure 36 Phylogeny of eukaryotic COG0523 members Lightly shaded tree represents the collapsed CO G0523 distance tree. Branches are labeled with corresponding subgroup number. Subgroup 5 tree: branches representing eukaryotic homologs are colored green. A blue diamond next to an organisms name indicates a putative Zur binding site is found upstream of the corresponding gene. For the C. reinhardtii ortholog, the blue diamond indicates confirmed induction of corresponding gene to zinc deficiency as reported in (Haas et al. 2009)
115 Nostoc sp. PCC 7120 COG0523 WD40 Gloeobacter violaceus PCC 7421 COG0523 HoxN WD40 COG0523 ZnuB ZnuC ZnuA WD40Synechococcus sp. WH 8102Cyanobacteria -ProteobacteriaBradyrhizobium japonicum USDA 110 COG0523 ZnuC ZnuB ZnuA WD40 SapBNitrobacter hamburgensis X14 COG0523 ZnuC ZnuB ZnuA WD40Brucella suis 1330 COG0523 COG1402 WD40 Mesorhizobium sp. BNC1 COG0523 COG1402 WD40 Caulobacter crescentus CB15 COG0523 WD40 Putative Zur binding site Figure 37 Genome context of subgroup 5 members. Subgroup 5 genes colocalize on the genome with genes encoding metal transporters, H oxN/HupN/NixA family cobalt transporter ( hoxN ) and highaffinity zinc transporter ( znuABC ), WD40 repeat containing proteins ( WD40 ), uncharacterized membrane family proteins ( sapB ), and creatine amidohydrolase like proteins ( COG1402).
116 CHAPTER 4 INVESTIGATI ON INTO THE FUNCTION OF THE UNCHARACTERIZ ED GENE YEIR Background E. coli is the prototypical model organism and is used both to gain insight into gene function and cellular processes and simply as another molecular biology tool. Due to the length of time this organism has been studied and ease of genome manipulation, the genome of E. coli is by far the best annotated of all sequenced genomes. Yet approximately only 59% of the gene annotations in E. coli are supported by experimental data and only the functi on for half of these are actually experimentally validated (Keseler et al. 2009, 2010) That leaves 71% of the genes in E. coli with annotations based solely on sequence similarity to genes in other organisms, whi ch may or may not themselves be experimentally validated. The pitfalls associated with annotating based on sequence similarity alone are well documented and have been thoroughly reviewed (Schnoes et al. 2009, Devos and Valencia, 2001, Brenner, 1999) To overcome the inherent error in annotations by sequence similarity, several bioinformatic techniques have been developed for producing or refining gene annotations (Poptsova a nd Gogarten, 2010, Overbeek et al. 2005) Sometimes referred to as guilt by association, these techniques have lead to a plethora of gene function discoveries (for some recent examples, see (Yang et al. 2006a, El Yacoubi et al. 2006, Rodionov et al. 2007, Rodionov et al. 2009, Phillips et al. 2010) The COG0523 family phylogenomic analysis described in Chapter 3 was used as a basis to predict functions for the two COG0523 proteins in E. coli: YjiA and YeiR In the EcoCyc database ( www.ecocyc.org ), yjiA is annotated as a P loop guanosine triphosphatase and yeiR is annotated as a predicted enzyme (Keseler et al. 2009)
117 From the phylogenomic analysis presented in Chapter 3, YjiA was assigned to su bgroup 9. Subgroup 9 proteins are encoded by genes that cluster physically on the genome with two genes, encoding a paralog of a carbonstarvation protein, CstA, and a small uncharacterized protein, YjiX. The function of these two proteins is currently unk nown. In the case of YjiA, guilt by association methods do not provide an obvious functional prediction, as the genes that yjiA associates with are also of unknown function. YeiR was assigned to subgroup 10 of COG0523, which has an enrichment of proteins whose genes are downstream from putative DNA binding sites for Zur. Zur is a well characterized transcription factor that represses gene expression in the presence of zinc (Gaballa and Helmann, 1998, Patzer and Hant ke, 1998) As zinc concentrations within the cell drop, Zur repression is lifted and genes involved in adapting to zinc deplete conditions are expressed such as highaffinity zinc transporters and back up enzymes ( Patzer and Hantke, 1998, Sankaran et al. 2009, Gabriel and Helmann, 2009) Work from the Helmann lab has shown that deletion of the Zur regulated COG0523 gene yciC in combination with a ycdH deletion in B. subtilis leads to a cell growth defect in the pr esence of the metal chelator, EDTA, and more recently zinc deficient medium (Gaballa and Helmann, 1998, Gabriel and Helmann, 2009) The gene ycdH encodes a homolog to the highaffinity zinc transporter that has bee n characterized in several bacteria (Patzer and Hantke, 1998, Yatsunyk et al. 2008, Lewis et al. 1999, Davis et al. 2009) Phylogenetically, YeiR is a member of a distinct COG0523 clade separate from the YciC cl ade (Figure 41). Although this observation resulted in assignment of YeiR to subgroup 10 and YciC to subgroup 1, YeiR is closely
118 related to other putatively zinc regulated COG0523 proteins (Figure 41). Therefore, YeiR could also be involved in survival w hen the cell is faced with a zinc depleted environment. Application of this same logic, suggests that YjiA is not predicted to be involved in zinc homeostasis. Based on the phylogenomic study presented in Chapter 3 and literature reports suggesting a role for a subset of COG0523 proteins in the response to zinc depletion, a study on the involvement of YeiR in metal related process particularly growth during zinc depletion and cadmium toxicity was performed. Since the other G3E family proteins, HypB, UreG and MeaB, are chaperones involved in maturation of a target metalloenzyme, YeiR may also be a metal chaperone. A mutagenesis study on conserved, putative metal binding motifs found in YeiR and a preliminary experiment with the purpose of finding a target for YeiR are also presented. Results EDTA S ensitivity The effect of a deletion of yeiR on optimal growth during zinc depletion was tested. To obtain E. coli MG1655 yeiR, the yeiR ::kan allele from E. coli BW25113 yeiR::kan (JW2161) was transduced by P1 phage into E. coli MG1655 by the method of (Miller, 1972) Kanamycin resistant recipient colonies were selected an d verified by locus specific PCR. The yeiR ::kan strain was then transformed with pCP20, which encodes FLP recombinase (native to S. c erevis i ae) and catalyzes the sitespecific recombination reaction between the two FRT sites flanking the resistance casset te, thus removing the resistance marker from the chromosome (Cherepanov and Wackernagel, 1995) Loss of
119 the resistance gene was confirmed by plating on appropriate antibiotics and by locus specific PCR. The parent (WT) and mutant strains were grown in a low phosphate minimal medium commonly used for the characterization of metal related physiology and was previously used to study low affinity zinc transporters in E. coli (Grass et al. 2002) In order to creat e zinc depletion, EDTA was added to the medium at various concentrations. EDTA is a hexadentate ligand and one molecule of EDTA has the potential to bind one metal ion in a ring structure (Wheelwright, 1953) Once bound, the EDTA metal complex is soluble (Plumb et al. 1950) and eq uilibrium between bound and unbound metal in the medium is formed. Due to the difficulty in specifically limiting growth conditions for zinc, EDTA is a popular choice for investigating physiology in the response to zinc deficiency (Gaballa and Helmann, 1998, Grass et al. 2002, Patzer and Hantke, 1998, Zhao and Eide, 1996) The E. coli cell in particular has been shown to be well equipped for acquiring zinc from the environment. Measurements of extracellular and int racellular zinc concentrations have revealed that the cell was able to concentrate intracellular zinc to a level ~2,000fold higher than the growth medium (Outten and O'Halloran, 2001) This trait makes depleting growth conditions of zinc difficult without the aid of a metal chelator such as EDTA. Growth of the WT and yeiR strains was compared in the presence of EDTA at a concentration from 0 2 mM. Growth was monitored in Bioscreen C machine (Growth Curves USA) that measures the optical density of up to 200 cultures in plate format practically simultaneously (200 l culture were well) This system was used previously to study the effect of B. subtilis and Proteus mirabilis gene deletions on growth in the
120 presence of zinc depletion (Sankaran et al. 2009, Gabriel and Helmann, 20 09, Nielubowicz et al. 2010) In the absence of EDTA, both the WT and yeiR strains had the same growth rate and reached the same final density ( Figure 42A). The WT strain did not exhibit a noticeable growth defect until EDTA was present at 1.2 mM (Figure 43A). Growth was progressively more perturbed with higher concentrat ions of EDTA until growth was abolished in the presence of 2 mM EDTA. In contrast, the yeiR mutant exhibited an observable sensitivity to EDTA at and above 1.1mM EDTA (Figure 43B). In the presence of concentrations at and above 1.3 mM EDTA, growth was inhibited and the cells did not recover (Figure 43B). The yeiR deletion could be complemented by uninduced expression of yeiR from the PBAD of pBAD24 (Figure 42B). The EDTA sensitive growth defect of the yeiR mutant was not dependent on growth in the Bios creen C machine and was reproducible with manual growth curves (Figure 44). Typically, deletion of the genes encoding the highaffinity zinc transporter ZnuABC, increase s growth defects caused by zinc depletion (Grass et al. 2002, Gabriel and Helmann, 2009) Therefore, to further evaluate whether the observed growth phenotype in the presence of EDTA could be due specifically to chelation of zinc, the znuABC ::cam allele from E. coli GR352 (Grass et al. 2002) was transferred to MG1655 and the yeiR strain by P1 transduction. Chloramphenicol resistant recipient colonies were selected and verified by locus specific PCR. The znuABC ::cam and znuABC ::cam yeiR mutants were grown in LP medium with or without EDTA. As with the WT and yeiR strains the znuABC ::cam and znuABC ::cam yeiR mutants had the same growth curves in the absence of EDTA
121 (Figure 4 5A). The znuABC ::cam mutant did not display a noticeable sensitivity to EDTA until a concentration of 30 M whereas the additional deletion of ye iR shifted the sensitivity of the strain to 10 M EDTA (Figure 4 6). At 75 M EDTA, the znuABC ::cam mutant was found to be as sensitive to EDTA as the yeiR znuABC ::cam mutant (Figure 4 7A). The difference in final density between the two strains at 20 M EDTA was comparable to the difference in final density between the WT and yeiR strains at 1.2 mM EDTA (Figure 4 7B). The yeiR deletion could be complemented by uninduced expression of yeiR from the PBAD of pBAD24 (Figure 45B). Rescue of EDTA Growth Def ect by Zinc As EDTA is a non specific metal chelator, it was not known which metal ions depletion was causing the observed phenotype. Therefore, various metal salts were added one at a time to the growth medium supplemented with 1.4 mM EDTA to determine w hich metal could suppress the growth defect observed with the yeiR mutant. The EDTA dependent growth defect of the yeiR mutant was suppressed only by the addition of 25 M Zn(II), whereas the same concentration of Ni(II), Cu(II), Co(II), Mn(II) or Fe(III) did not rescue cell growth (Figure 4 8 ) The metal rescue profile was different for the znuABC ::cam yeiR mutant. With the highaffinity zinc transporter present, a molar ratio of 56:1 (EDTA:Zn) was sufficient to see suppression of the phenotype due to deletion of yeiR (Figure 4 9A). However, with the genes encoding the high affinity zinc transporter deleted, a molar ratio of 2:1 (EDTA:Zn) was required to see suppression of the phenotype (Figure 49B). In addition, 10 M cobalt appeared to suppress the growth defect of the znuABC ::cam yeiR
122 mutant in the presence of 20 M EDTA to the same extent as 10 M zinc (Figure 4 9B). Nickel at 10 M was able to restore growth to 65% of the strains growth in LP medium without EDTA (Figure 49B). Cadmium S ensitivity It has been proposed that intracellular zinc depletion c an be mimicked by the presence of Cd(II), as Cd(II) is thought to displace zinc in protein metal sites since cadmium has a highaffinity for those sites (Graham et al. 2009, Zhang et al. 2003a) Therefore, to fur ther probe the zinc suppressible EDTA dependent growth defect, growth of WT pBAD24, yeiR pBAD24 and yeiR pCH011 (pBAD24 yeiR) strains were compared in the presence of Cd(II) at a concentration from 20 50 M (Figure 4 10). The yeiR mutant was found to exhibit a clear difference in growth as compared to the WT strain in the presence of 30 M cadmium (Figure 4 10B). The growth curve of the yeiR strain in the presence of 30 M cadmium was similar to the growth curve of the WT strain in 50 M cadmium (Figure 4 10E). The yeiR deletion could be complemented by uninduced expression of yeiR f rom the PBAD of pBAD24 (Figure 4 10). The effect of a combination of CdII) and Zn(II), Co(II), Cu(II), Mn(II), Ni(II) or Fe(III) on the growth of the yeiR and WT strains was also tested. The presence of zinc was able to partially suppress the cadmium sen sitive growth defect of the yeiR mutant (Figure 4 11A) and manganese was able to suppress to a lesser extent (Figure 411B). The presence of zinc did not significantly suppress the cadmium toxicity observed with the WT strain (Figure 412A). In contrast, growth of the yeiR mutant in the presence of 40 M zinc plus 40 M cadmium was comparable to growth in 30 M cadmium (Figure 4 13B). The presence of cobalt, nickel or iron did not lead to suppression or further
123 exacerbation of the cadmium growth defect (F igure 413A), while the addition of copper further exacerbated growth of the WT and yeiR strains (Figure 413B). As was observed with EDTA, the cadmium sensitive phenotype was exacerbated if the znuABC genes were deleted. The znuABC ::cam and znuABC ::cam yeiR mutants were grown in LP medium in the presence of 2.5 20 M Cd(II) (Figure 4 14). The difference in growth between the WT and yeiR strains in the presence of 20 M cadmium was similar to the difference in growth between the znuABC ::cam and znuABC ::cam yeiR mutant strains in the presence of 2.5 M cadmium (Figure 4 14E). As with the EDTA growth experiments, the difference in growth between these strains diminished with higher concentrations of cadmium; the znuABC ::cam mutant was as sensitiv e to the presence of 20 M cadmium as the znuABC ::cam yeiR mutant (Figure 414D). The yeiR deletion could be complemented by uninduced expression of yeiR from the PBAD of pBAD24 (Figure 4 14). Effect of Amino Acid Substitutions on the Activity of YeiR, i n Vivo The robust EDTA sensitivity phenotype allowed probing of the importance of the conserved motifs found in COG0523 proteins. Like all COG0523 protein sequences, YeiR contains a CXCC motif where X is a non polar amino acid in the N terminal GTPase domain (Figure 4 15). For YeiR, this motif is at positions 63 65 in the protein sequence and X is a methionine. Each of the three cysteines and the methionine in this motif was mutated to alanine using the PCR overlap strategy (Sambrook and Russell, 2001) The mutated genes were inserted between the Nco I and Xba I sites of pBAD24 a nd the resulting plasmids were transformed into the yeiR mutant. The resulting strains were grown in LP medium with or without 1.4 mM EDTA (Figure 416). All strains
124 had identical growth curves when grown in LP without EDTA (Figure 416A). However, when grown in LP medium with EDTA, m utation of any one of the three cysteines or methionine to alanine abolished the ability of the corresponding gene in trans to complement the yeiR deletion (Figure 4 16B). In addition to the cysteine rich motif, a short His stretch was found in the C terminus of YeiR (Figure 4 15). This region of the COG0523 protein sequences commonly contains His stretches (Chapter 3). To test if these histidines play a substantial role in the activity of YeiR, each residue was mutated to alanine as described above. The mutated genes were inse rted between the Nco I and Xba I sites of pBAD24 a nd the resulting plasmids were transformed into the yeiR mutant. The resulting strains were grown in LP medium with or without 1.4 mM EDTA (Figure 417). Mutation of either H209 or H211 to A had no observabl e effect on the ability of the corresponding gene in trans to complement the yeiR deletion (Figure 4 17B). Mutation of H207 to A led to presumably a less active YeiR, because the yeiR pCH140 (encodes YeiR H207A) mutant had a decreased growth rate in the p resence of 1.4 mM EDTA compared to the yeiR pCH011 (encodes WT YeiR) mutant (Figure 417B). Deletion of all three histidines to alanine severely perturbed the ability of the corresponding gene to complement the yeiR deletion (Figure 417B). ICP MS Analysi s Based on the prediction that COG0523 family proteins are chaperones involved in metallocenter biosynthesis (Chapter 3), a search for a potential target for YeiR was performed. If YeiR is involved in metal insertion, then deletion of yeiR could affect the abundance of the metal bound form of the target. Analysis of wholecell metal content
125 by ICP MS did not yield a difference between the WT and mutant strains (data not shown). Therefore a protein fractionationcoupled ICP MS technique was employed to analy ze single metalloproteins (Tottey et al. 2008) Detection of metal bound proteins from the cytoplasmic fraction of t he WT and yeiR strains was performed using twodimensional protein purification and detection of metal by ICP MS Purification was performed under native conditions to ensure metalloproteins did not lose their native metal cofactor. Anaerobic conditions were used ( except for sizeexclusion chromatography) as the presence of oxygen can also alter metal protein speciation. The cytoplasmic extract was loaded onto an anion exchange column and protein was eluted in steps of 100 mM, 200 mM, 300 mM, 400 mM, 500 mM and 1 M NaCl. Each fraction was then further fractionated by sizeexclusion chromatography and 35 fractions were collected which were then analyzed by ICP MS to determine the presence of copper, manganese, cobalt, nickel and zinc. The metal profiles for copper, m anganese and coablt were not significantly different between the two strains (Figure 418). However, the nickel pool extracted from the yeiR strain was noticeably reduced (Figure 4 18). Also a putative Ni/Znbound protein was present in the extract from the mutant but not from the parent (Figure 419). However, these peaks could represent two separate proteins (one nickel bound and one zinc bound) that elute in the same fractions. The nickel peaks that are not found in the yeiR strain extract were most l ikely bound to small molecular weight species as they eluted off the sizeexclusion column in the later fractions and the peaks were relatively sharp. The nickel phenotype was reproduced by the Robinson lab (University of Newcastle), therefore, this obser vation was investigated further. To date, only two
126 proteins in E. coli are known to require nickel for activity: [NiFe] hydrogenase and glyoxalase I. Therefore, based on the previous results, the activity of these two proteins was determined for the WT and mutant strains. Hydrogenase a ctivity Perturbation of hydrogenase activity seemed an unlikely result of the nickel defect observed in the ICP MS analysis of the yeiR mutant. The E. coli strain MC4100 commonly used to assay hydrogenase activity (Wu and MandrandBerthelot, 1986, Penfold et al. 2003, Jacobi et al. 1992) carries a 6,678bp deletion (compared to E. coli MG1655) that encompasses a deletion of the yeiR gene (Peters et al. 2003) Activity of hydrogenase from MC4100 was the same as from E. coli W3110, which has an intact yeiR gene (Pinske and Sawers, 2010) To confirm that deletion of yeiR does not affect hydrogenase activity as suggested indirectly from previous reports, dihydrogen evolution was measured with a gas chromatograph from 1 ml cultures grown overnight in stoppered culture tube s under a nitrogen atmosphere. Whereas deletion of the known hydrogenase maturation factor, hypF noticeably affected dihydrogen production, deletion of yeiR had no effect compared to the parent strain (Figure 420A). Glyoxalase I activity The glyoxalase system composed of two enzymes, glyoxalase I and glyoxalase II is responsible for t he detoxification of cytotoxic keto aldehydes, such as methylglyoxal (R acker 1951) While glyoxalase I from other sources has been found to use zinc as the catalytic cofactor (Aronsson et al. 1978) glyoxalase I from E. coli has been shown to use nickel (Clugston et al. 1998) It has not been determined whether additional factors are involved in ensuring that glyoxalase I from E. coli attains the nickel cofactor
127 Glyoxalase I activity was assayed by testing the sensitivity of the WT and yeiR strains to exogenous methylglyoxal. Deletion of the gene encoding glyoxalase I ( gloA ) results in the inability of the strain to grow in the presence of 0.5 mM methylglyoxal (K im et al. 2007) however, deletion of yeiR had no observable affect on the ability of cells to grow in the presence of exogenous methylglyoxal (Figure 420B ). Discussion and Conclusions The growing experimental information collected in the past few year s for some subfamilies of the G3E P loop GTPase proteins (HypB, UreG and MeaB) indicate that they act as metal insertases and/or metallochaperones. However, a large number of proteins in the COG0523 subfamily are predominately uncharacterized (Chapter 3). This study on the biological role of the E. coli COG0523 gene, yeiR, helps to shed some light on this poorly defined family and strengthens the hypothesis that a fundamental characteristic of these genes is involvement in metal related processes. The resu lts presented here suggest that the previously uncharacterized COG0523 gene yeiR is involved in a zinc related process. Presence of yeiR either in cis (on the chromosome) or in trans (cloned into pBAD24) was found to be required for the optimal growth of E coli MG1655 in the presence of high concentrations of EDTA or Cd(II). These phenotypes are thought to be due specifically to zinc depletion as both growth defects were exacerbated by the deletion of the genes encoding the highaffinity zinc transporter, znuABC or rescued by the addition of zinc. To maintain zinc homeostasis, several bacteria express a highaffinity zinc uptake system to transport zinc across the membrane in an energy dependent manner (Patzer and Hantke, 1998) Although, several other transporters have been shown to participate
128 in the uptake of zin c under growth conditions of zinc sufficiency (Grass et al. 2002, Beard et al. 2000) the high affinity zinc transport system is expressed specifically to transport zinc into the cell under growth conditions of z inc deficiency. This transporter is from the ABC family and is composed of three proteins: ZnuC serves as the ATPase component, while ZnuA, the periplasmic zinc metallochaperone, delivers zinc to ZnuB, the membrane permease (Patzer and Hantke, 1998) Although ZnuA is able to bind various metal ions, the structural changes induced specifically by zinc are thought to be responsible for the high specificity of this transporter (Yatsunyk et al. 2008) As suggested previously (Berducci et al. 2004) the results presented here imply that znuABC is able to compete with EDTA for binding to zinc in the medium. As such, approximately 60fold less EDTA is needed to see the yeiR strains growth defect when znuABC is also deleted from the chromosome. The different metal suppression profiles collected for the yeiR and znuABC ::cam yeiR mutants could also be a direct result of the competition between the transporter and EDTA. With znuABC present on the chromosome, only 25 M zinc was able to suppress the presence of 1.4 mM EDTA (Figure 4 9A). However, with znuABC deleted, 10 M zinc was needed to suppress the presence of 20 M EDTA (Figure 4 9B). In addition to zinc, cobalt and to a lesser extent nickel were also able to suppress the EDTA dependent growth defect exhibited by the znuABC ::cam yeiR mutant (Figure 4 9B). At this ratio of EDTA:metal (2:1), it is likely that cobalt and nickel are displacing zinc from EDTA making i t available to the cell as has been suggested previously (Patze r and Hantke, 1998) The stability constants between EDTA and Co(II) and EDTA and Zn(II) are roughly the same (log K equals 18.1 and 18.3, respectively)
129 (Stumm and Morgan, 1996) The stability cons tant between EDTA and Ni(II) is roughly two order of magnitude higher (log K equal to 20.4) (Stumm and Morgan, 1996) A remote possibility is that cobalt and nickel are transported into the cell and can compensate for the lack of zinc. In vitro the activity of several zinc dependent enzymes is slightly less, the same or in some cases higher with a metal cofactor other than zinc (for recent examples see (Cam pos Bermudez et al. 2007, Cmara et al. 2008, Hall et al. 2007) ). Under zinc limitation and supplementation with cobalt, the zinc in carbonic anhydrase of the marine diatom, Thalassiosira weissflogii, is substituted with cobalt in vivo and remains acti ve (Yee and Morel, 1996) However, expression of the highaffinity Co(II) transporter from Salmonella typhimurium LT2 did not lead to suppression of the EDTA defect in the presence or absence of exogenous cobalt (data not shown). The first characterization of ZnuABC from E. coli w as performed in the strain MC4100 (Patzer and Hantke, 1998) w hich contains a deletion in yeiR (Peters et al. 2003) The authors found that growth of the znuA ::MudX and znuB ::MudX mutants on solid medium was inhibited in the presence of 400 M EDTA. A repeat of those experiments (with the MG1655derived strains carrying deletions in the zinc transporter genes with or without deletion of yeiR ) revealed that a 10fold increase in EDTA concentration was required to inhibit the growth of the znuABC:: ca m strain w ith yeiR present (data not shown). Therefore during the original phenotype elucidation of znuA and znuB the authors may have observed the effect of the yeiR deletion in concert with the deletion of the transporter. To further support a role for yeiR in metal related processes, the yeiR strain displayed increased sensitivity to the toxic metal Cd(II). One of the effects of cadmium
130 on the cell has been suggested to be intracellular zinc limitation (Graham et al. 2009, Zhang et al. 2003a) P rotein metal sites where the metal ion is bound to cysteine residues should be sensitive to cadmium competition, because cadmium binds to sulfur groups with a higher affinity (Helbig et al. 2008) Accordingly, the znuABC ::cam mutant, which is unable to transport zinc in a highaffinity capacity (Patzer and Hantke, 1998) is more sensitive to cadmium than the isogenic parent and the znuABC ::cam yeiR mutant is more sensitive still. Also in support of the hypothesis that cadmium induces zinc limitation, attempts to suppress the cadmium phenotype of the yeiR strain led to partial rescue of growth by zinc. The presence of equimolar zinc increased the tolerance of the mutant strain to cadmium (Figure 411A). Perhaps, to a certain extent, increasing the zinc concentration in the medium ensures loading of zinc dependent proteins with zinc rather than cadmium. Another explanation is that zi nc inhibits cadmium uptake. Zinc has been previously shown to inhibit uptake of cadmium by E. coli (Laddaga and Silver, 1985) Interestingly, manganese was also able to partially suppress th e growth defect (to a lesser extent than zinc) (Figure 411B). Manganese has not been shown to inhibit cadmium uptake by E. coli (Laddaga and Silver, 1985) An explanation for the ability of manganese to suppress the observed growth defect could be the stimulation of a manganese dependent SOD by the presence of manganese. It has been proposed that one of the reasons for cadmium toxicity is superoxide generation (Stohs and Bagchi, 1995) Dele tion of both iron dependent and manganesedependent SOD was shown to increase the sensitivity of E. coli to cadmium (Geslin et al. 2001) Therefore, increased activity due to cofactor ability could enhance the activity of manganese SOD and thus
131 increase resistance of E. coli to cadmium. However, neither zinc nor manganese suppressed the cadmium specific growth defect of the WT strain. Ens uring proper metal allocation in the active sites of metalloenzymes is critical for the survival of any organism. Studies involving the maturation of [NiFe] hydrogenase and of urease have provided the most thorough picture of metallocenter assembly (Kuchar and Hausinger, 2004, Leach and Zamble, 2007) The mechanism and function of each accessory factor required for maturation of these enzymes is still not fully understood, but in both cases a G3E P loop GTPase is involved in the incorporation of the Ni(II) ion into the enzymes active site. By analogy, members of COG0523, which have motifs that classify them as G3E P loop GTPases, could have similar roles in the activation of target enzymes. More specifically, YeiR m ay be acting as a chaperone involved in the activity of a target metalloeznyme whose activity is essential under zinc deficient growth conditions. To further support a role in a metal related process, the putative metal binding site C63MCC66 was found to be essential for the ability of the corresponding gene in trans to complement the yeiR deletion (Figure 416B). The short histidine stretch was also found to be putatively involved in activity (Figure 417B). However, single mutations of the histidine moti f were not as detrimental as single deletions in the cysteine motif. Indeed mutation of either H209 or H211 had no observable effect on the ability of the corresponding gene to rescue growth, and H207 only affected the growth rate and not the yield. Mutati on of all three histidines appears to be required to sufficiently inactivate the gene product of yeiR Deletion of the His stretch found in the G3E protein HypB from B. japonicum was found to cause a partial defect in hydrogenase activity, which
132 could be r estored by providing high concentration of nickel to the growth medium ( Olson et al. 1997) The characterized and partially characterized P loop GTPases of the G3E family are commonly found in the same operon as their target enzyme. Coexpression of the chaperone and the target is important; without the chaperone, the target metalloenzyme is inactive. However, deletion of any of the genes surrounding yeiR did not result in an observable growth defect in the presence of EDTA (data not shown), suggesting that these genes do not encode the missing target protein. As an alternat ive conclusion, YeiR may have a general chaperone role and therefore does not target a single enzyme. If yeiR encodes a metal chaperone, it was hypothesized that the intracellular pool could be disrupted by deletion of yeiR. Indeed, deletion of yeiR appea red to affect several peaks from the ICP MS analysis of the cytoplasmic fraction after native twodimensional separation as compared to extract from the WT strain. Most noticeably, nickel bound to putative small molecular weight species appeared to have di sappeared in the mutant strain. The results of the ICP MS analysis suggest a potential role of yeiR in nickel metabolism. However, no other link with nickel was made during the course of this study. This study provides critical insights into the potential role COG0523 genes and more specifically the previously uncharacterized gene yeiR in metal related processes. The B. subtilis COG0523 gene yciC was previously shown to display an EDTA dependent growth defect in a znuA background (Gaballa and Helmann, 1998, Gaballa et al. 2002) which was later confirmed to be due specifically to zinc depletion (Gabriel
133 a nd Helmann, 2009) Similar to yciC, yeiR is linked to growth in zinc deficient conditions. Unlike yciC deletion of the high affinity zinc transporter is not necessary to observe a growth defect in the presence of extracellular metal depletion. Also unlik e yciC which is regulated by zinc through Zur (Gabriel et al. 2008) y eiR has never been directly id entified by any of the studies performed on the response of E. coli to zinc depletion (Sigdel et al. 2006, Graham et al. 2009) Zur regulatory sites are not predicted to exist upstream of yeiR (Novichkov et al. 2010) The results presented here on yeiR may suggest an uncharacterized zinc homeostatic process in E. coli during zinc deplete conditions.
134 Hahella chejuensisYeiRVibrio fischeri Vibrio fischeri Reinekea sp. MED297 Vibrio alginolyticus Agrobacterium tumefaciens Pseudomonas denitrificans Erwinia carotovoraYjiAAzotobacter vinelandii Pseudomonas aeruginosa Pseudomonas fluorescens Acinetobacter baylii Rhodococcus sp. N 771 Acinetobacter baylii Bacillus subtilis Zur binding site NHase Carbon starvation protein paralog yjiX cobU cobN B12riboswitch Zur binding site CobW YciC NHase activator Figure 41. Phylogenetic tree reconstruction of chosen COG0523 subgroups. Distance tree of the three COG0523 subgroups for which experimental work is available (CobW (subgroup 12), YciC (subgroup 1), and NHase activ ator (subgroup 2)) and the two uncharacterized COG0523 proteins in E. coli YeiR (subgroup 10) and YjiA (subgroup 9). The background for each subgroup is shaded. Proteins encoded by a gene putatively regulated by Zur (Novichkov et al. 2010) are indicated by a dotted line. Representative genome context for each subgroup is given.
135 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 0 EDTAWT pBAD24 yeiR pBAD24 yeiR pCH011 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 1.3 mM EDTAWT pBAD24 yeiR pBAD24 yeiR pCH011 OD (600nm) Time (hr) OD (600nm) Time (hr) A B Figure 4 2. Growth curves of E. coli MG1655 (WT) and yeiR strains grown in LP medium without or with 1.3 mM EDTA A) Growth curves of the WT pBAD24, yeiR pBAD24, and yeiR pCH011 (PBAD yeiR ) strains in LP medium. B) Growth curves of the WT pBAD24, yeiR pBAD24, and yeiR pCH011 (PBAD yeiR) strains in LP me dium plus 1.3 mM EDTA. Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of three replicates.
136 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) WT0 EDTA 1.2 mM 1.4 mM 1.6 mM 1.8 mM 2 mM OD (600nm) Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) yeiR0 EDTA 1.1 mM 1.2 mM 1.3 mM 2 mM OD (600nm) Time (hr) A B Figure 43. Growth curves of E. coli MG1655 (WT) and yeiR strains grown in LP medium wi th a range of EDTA concentrations A) Growth curves of the WT strain grown in the presence of 0, 1.2 mM, 1.4 mM, 1.6 mM, 1.8 mM or 2 mM EDTA. B) The yeiR strain grown in the presence of 0, 1.1 mM, 1.2 mM ( or 1.3 mM 2 mM EDTA as shown (in steps of 0.1 m M). Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of three replicates
137 0 0.5 1 1.5 2 2.5 3 3.5 0 10 20 30 40 50 OD 600nm Time (hr) 0 EDTAWT pBAD24 yeiR pBAD24 yeiR pCH011 0 0.5 1 1.5 2 2.5 3 3.5 0 10 20 30 40 50 OD 600nm Time (hr) 1.3 mM EDTAWT pBAD24 yeiR pBAD24 yeiR pCH011 OD (600nm) OD (600nm) Time (hr) Time (hr) A B Figure 44. Manual growth curves. Manual growth curves of E. coli MG1655 (WT) pBAD24 yeiR pBAD24, and yeiR pCH011 (PBAD yeiR ) strains in LP medium (A) or LP medium plus 1.3 mM EDTA (B). 200 mL cultures were grown in 500 mL Erlenmeyer flasks at 200 rpm. The optical density was measured at 600 nm with a BioSpec mini (Shimadzu Technologies) spectrometer. Error ba rs represent the standard deviation of three replicates.
138 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 0 EDTA 20 M EDTA znuABC ::cam pBAD24 znuABC ::cam yeiR pCH011 znuABC ::cam yeiR pBAD24 znuABC ::cam pBAD24 znuABC ::cam yeiR pCH011 znuABC ::cam yeiR pBAD24 OD (600nm) OD (600nm) Time (hr) Time (hr) A B Figure 45. Growth curves of the znuABC ::cam and znuABC ::cam yeiR mut ants grown in LP medium without or with 20 M EDTA. A) Growth curves of the znuABC ::cam pBAD24, znuABC ::cam yeiR pBAD24, and znuABC ::cam yeiR pCH011 (PBAD yeiR) mutants in LP medium. B) Growth curves of the znuA BC ::cam pBAD24, znuABC ::cam yeiR pBAD24, and znuABC ::cam yeiR pCH011 mutants in LP medium plus 20 M EDTA. Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of three replicates.
139 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 0 EDTA 10 M 2 0 M 30 M 40 M 5 0 M 75 M 100 M 0 EDTA 10 M 20 M 100 M znuABC ::cam yeiR znuABC ::cam OD (600nm) OD (600nm) Time (hr) Time (hr) A B Figure 46. Growth curves of the znuABC ::cam and znuABC ::cam yeiR mutants grown in LP medium with a range of EDTA concentrations A) Growth curves of the znuABC ::cam mutant grown in the presence of 0, 10 M, 20 M, 30 M, 40 M, 50 M, 75 M or 100 M EDTA. B) The znuABC ::cam yeiR mutant grown in the presence of 0, 10 M, 20 M, 30 M, 40 M, 50 M, 75 M or 100 M EDTA. Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of three replicates.
140 0 0.2 0.4 0.6 0.8 1 1.2 OD 600nm 0 0.2 0.4 0.6 0.8 1 1.2 0 10 15 20 25 30 35 40 50 75 100 OD 600nm [EDTA] znuABC ::cam znuABC ::cam yeiR = 0.32 = 0.35 yeiR : + + WT znuABC ::cam 20 M EDTA 1.2 mM EDTA OD (600nm) OD (600nm) [EDTA] A B Figure 47. Optical density (OD; measured at 600 nm ) of cultures. A) OD of the znuABC ::cam and znuABC ::cam yeiR mutants in stationary phase (45 hrs after inoculation) that were grown in LP medium in the absence or presence of EDTA at the indic ated concentrations ( M). B) Comparison of final OD of the WT and yeiR strains grown in LP medium plus 1.2 mM EDTA with the znuABC ::cam and znuABC ::cam yeiR mutants grown in LP medium plus 20 M EDTA. OD values were generated with a Bioscreen C. The di fference in OD between parent and mutant is given. Error bars represent the standard deviation of three replicates.
141 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) Time (hr) OD (600nm) Figure 48. Rescue of the yeiR strain EDTA sensitive growth defect by zinc Growth curves of the yeiR strain grown in LP medium in t he absence of EDTA (dark grey circle) or in the presence of 1.4 mM EDTA ( grey square) plus various metals at 25 M: zinc ( triangle ), cobalt ( X ), copper ( star ), iron (rectangle ), manganese ( open circle) or nickel (+ ). Growth curves were generated with a Bio screen C Error bars represent the standard deviation of 3 replicates.
142 0 0.2 0.4 0.6 0.8 1 1.2 600 0 0.2 0.4 0.6 0.8 1 1.2 600 znuABC ::cam yeiR yeiRGrowth relative to growth in LP medium Growth relative to growth in LP medium0 metal 0 metalLP LP Zn Co Ni Mn Fe Cu Zn Co Ni Mn Fe Cu 25 M 50 M 75 M 2.5 M 10 M 1.4 mM EDTA 20 M EDTA A B Figure 49. Result of adding EDTA and metal to medium. A) Growth of the yeiR strain in LP medium in the absence of EDTA (LP) or presence of 1.4 mM EDTA +/ the indicated metals at either 2.5 M or 10 M metal. The values shown are a ratio of the final OD of the yeiR mutant in the indicated medium relative to the final OD of the yeiR mutant in LP medium without metal or EDTA. B) Growth of the znuABC ::cam yeiR mutant in LP medium in the absence of EDTA (LP) or presence of 20 M EDTA +/ the indicated metals at either 2.5 M or 10 M metal. The values shown are a ratio of the final OD of the znuABC ::cam yeiR mutant in the indicated medium relative to the final OD of the znuABC ::cam yeiR mutant in LP medium without metal or EDTA.
143 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 600 Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 OD 600nm Time (hr) 20 M Cd (II) 3 0 M Cd (II) 4 0 M Cd (II) 50 M Cd (II) yeiR pBAD24 yeiR pCH011 WT pBAD24 yeiR pBAD24 yeiR pCH011 WT pBAD24 yeiR pBAD24 yeiR pCH011 WT pBAD24 yeiR pBAD24 yeiR pCH011 WT pBAD24 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 OD 600nm Time (hr) WT pBAD24 50 M Cd yeiR pBAD24 30 M Cd OD (600nm) OD (600nm) Time (hr) Time (hr) Time (hr) Time (hr) Time (hr) OD (600nm) OD (600nm) OD (600nm) A B C D E Figure 410. Effect of cadmium on growth. Growth curves of E. coli MG1655 (WT) pBAD24 yeiR pBAD24, and yeiR pCH011 (PBAD yeiR ) strains in LP medium with Cd(II) at 20 M (A), 30 M (B), 40 M (C) or 50 M (D) E) Growth curves of WT pBAD24 in the presence of 50 M Cd and yeiR pBAD24 in the presence of 30 M Cd. Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of 3 replicates.
144 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 OD 600nm Time (hr) WT WT + Zn yeiR yeiR + Zn 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 OD 600nm Time (hr) WT WT + Mn yeiR yeiR + Mn 40 M Cd (II) +/ Zn 40 M Cd (II) +/ Mn OD (600nm) OD (600nm) Time (hr) Time (hr) A B Figure 411. Partial rescue of the cadmium sensitive growth defect of the yeiR strain with zinc or manganese. A) LP medium plus 40 M Cd(II) +/ 40 M Zn(II); WT or yeiR strains without Zn(II) and WT or yeiR strains with Zn(II). B) LP medium plus 40 M Cd +/ 40 M Zn; WT or yeiR strains without Mn(II) and WT or yeiR strains with Mn(II). Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of 3 replicates
145 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 60 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) WT yeiR30 M Cd 40 M Cd 40 M Cd +40 M Zn 30 M Cd 40 M Cd 40 M Cd + 40 M Zn OD (600nm) Time (hr) OD (600nm) Time (hr) A B Figure 412. Suppression of cadmium toxicity with zinc. Growth of the WT and yeiR strains in: LP medium plus 30 M Cd(II), LP medium plus 40 M Cd(II), LP medium plus 40 M Cd(II) and 40 M Zn(II). A) The presence of Zn at 40 M does not rescue growth of WT cells grown in LP medium plus 40 M Cd(II). B) The presence of equimolar Zn(II) does partially rescue growth of the mutant strain. Growth in LP medium plus 40 M Cd(II) and 40 M Zn(II) is equivalent to growth in LP medium with 30 M Cd(II). Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of 3 replicates.
146 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 25 50 75 100 125 OD 600nm Time (hr) Cd WT + Cd WT + Cd and +Cu yeiR + Cd yeiR + Cd and +Cu + Cd and +0 metal, Co, Ni, or Fe + Cd and +Cu40 M Cd (II) +/ 40 M Cu(II) yeiR OD (600nm) Time (hr) OD (600nm) Time (hr) A B Figure 413. Addition of cobalt, copper, nickel or iron plus cadmium on the growth of the yeiR strain i n LP medium A) Growth curves of the yeiR strain without or with 40 M Cd(II) plus 40 M Fe(III), Co(II), Ni(II) or Cu(II). B) Growth curves of the WT and yeiR strains in the presence of 40 M Cd(II) or the WT and yeiR strains in the presence of 40 M C d(II) plus 40 M Cu(II). Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of 3 replicates.
147 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) znuABC ::cam yeiR pBAD24 znuABC ::cam yeiR pCH011 znuABC ::cam pBAD24 znuABC ::cam yeiR pBAD24 znuABC ::cam yeiR pCH011 znuABC ::cam pBAD24 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) znuABC ::cam yeiR pBAD24 znuABC ::cam pBAD24 znuABC ::cam yeiR pBAD24 znuABC ::cam yeiR pCH011 znuABC ::cam pBAD24 10 M Cd (II) 2 0 M Cd (II) 2.5 M Cd (II) 5 M Cd (II) 0 0.2 0.4 0.6 0.8 1 1.2 0 5 10 15 20 25 30 35 OD 600nm Time (hr) WT pBAD24 20 M Cd (II) znuABC ::cam pBAD24 2.5 M Cd (II) znuABC ::cam yeiR pBAD24 2.5 M Cd (II) yeiR pBAD24 20 M Cd (II) OD (600nm) Time (hr) Time (hr) Time (hr) Time (hr) Time (hr) znuABC ::cam yeiR pCH011 OD (600nm) OD (600nm) OD (600nm) OD (600nm) A B C D E Figure 414. Effect of cadmium on growth of znuABC ::cam strai ns. Growth curves of E. coli MG1655 znuABC ::cam pBAD24 znuABC ::cam yeiR pBAD24, and znuABC ::cam yeiR pCH011 (PBAD yeiR) strains in LP medium with Cd(II) at 2.5 M (A),5 M (B), 10 M (C) or 20 M (D). E) Growth curves of the WT pBAD24 and yeiR pBAD2 4 strains in the presence of 20 M Cd(II) and the znuABC ::cam pBAD24 and znuABC ::cam yeiR pBAD24 mutants in the presence of 2.5 M Cd(II) Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of 3 replicates.
148 Figure 415. Protein sequence alignment of COG0523 proteins. These COG0523 proteins were used for the phylogenetic tree reconstruction in Figure 41. Secondary structure as determined from the crystal structure of the YjiA homolog is given at the top of the alignment (PDB: 1NIJ). The motifs analyzed in the mutagenesis study are shown in bold.
149 Figure 4 15. Continued.
150 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 0 EDTA 1.4 mM EDTA yeiR pCH011 yeiR pBAD24 yeiR pCH086 yeiR pCH137 yeiR pCH138 yeiR pCH141 yeiR pBAD24 yeiR pCH011 yeiR pCH086 yeiR pCH137 yeiR pCH138 yeiR pCH141 OD (600nm) Time (hr) OD (600nm) Time (hr) A B Figure 416. Effect of C63MCC66 mutations on the ability of the corresponding gene to complement the deletion of yeiR. Growth curves of the yeiR pBAD24, yeiR pCH011 (encodes WT YeiR), yeiR pCH086 (encodes YeiR C63A), yeiR pCH141 (encodes YeiR M64A), yeiR pCH137 (encodes YeiR C65A), and yeiR pCH138 (encodes YeiR C66A) mutants in LP medium without EDTA (A) o r with 1.4 mM EDTA (B). Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of 3 replicates.
151 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 600nm Time (hr) 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 50 OD 6 00nm Time (hr) yeiR pCH011 yeiR pBAD24 yeiR pCH011 yeiR pCH140 yeiR pCH145 yeiR pCH152 yeiR pCH150 yeiR pCH152 yeiR pCH145 yeiR pCH140 yeiR pCH150 yeiR pBAD24 1.4 mM EDTA 0 EDTA OD (600nm) Time (hr) OD (600nm) Time (hr) A B Figure 417. Effect of H207XHXH211 mutations on the ability of the corresponding gene in trans to complement the deletion of yeiR. Growth curves of the yeiR pBAD24, yeiR pCH011 (encodes WT YeiR), yeiR pCH140 (encodes YeiR H207A) ( ), yeiR pCH145 (encodes YeiR H209A), yeiR pCH152 (encodes YeiR H211A) and yeiR pCH150 (encodes YeiR H207A H209A H211A) mutants were grown in LP medium without EDTA (A) or with 1.4 mM EDTA (B). Growth curves were generated with a Bioscreen C. Error bars represent the standard deviation of 3 replicates.
152 Anion exchange [ NaCl] Size exclusion volume (ml)Cu Mn Zn Co NiWT yeiR 0 80 0 200 0 800 0 80 0 100 [Metal] nM Figure 418. Native two dimensional separation analyzed by ICP MS for five elements. Native two dimensional separation of a cytoplasmic extract from E. coli MG1655 (WT) and the yeiR mutant analyzed for copper, manganese, zinc, cobalt and nickel by ICP MS. Individual metal concentrations are represented as surfaces. The colors represent incremental increases in concentration (nM): copper, 10; manganese, 20; zinc, 100; cobalt, 10; nickel, 10. The bottom left graph shows the axis labels that are the same for each graph. The arrow on the right shows the scale to which each metal concentration is plotted.
153 Anion exchange [ NaCl] Size exclusion volume (ml)Zn WT yeiR Ni 0 100 [Metal] nM 0 600 yeiR WT Figure 419. Native two dimensional separation analyzed by ICP MS for zinc and nickel. Fractions 1625 for each NaCl separation are shown for zinc and nickel analysis. A protein peak (outlined in dark blue) that contains zinc and nicekl at a ratio of 8:1 is seen in the yeiR mutant but not in the WT strain extract.
154 WT yeiR gloA WT yeiR gloA + 0.5 mM MG: 10-310-410-510-610-7Culture dilution: 0 0.2 0.4 0.6 0.8 1 1.2 yeiR hypFH2quantity relative to WT A B Figure 420. Assay of hydrogenase and glyoxalase I activity. A) The concentration of H2 produced by overnight cultures of the WT, yeiR, and hypF strains was measured by gas chromatography. The concentration produced by the yeiR and hypF mutants relative to the WT strain is shown. B) Glyoxa lase I activity was assayed by measuring sensitivity of the WT, yeiR and gloA strains on M9 minimal medium (1.5% agar) to the presence of 0.5 mM mehtylglyoxal (MG). Overnight cultures of each strain grown in LB were normalized to an OD of 1.0, serially diluted and 10 l of the appropriate dilution were plated as shown.
155 CHAPTER 5 PARALOGS OF ZINC DEPENDENT PROTEINS Background Numerous enzymes have evolved to require a cofactor for activity. These nonprotein constituents such as metal ions can endow a protein with catalytic activity or enable otherwise thermodynamically unfavorable structural protein folds (Fisc her et al. 2010, Andreini et al. 2008b) Cofactors are essential for the activity of the user enzyme. If that enzyme is required for an essential process, then the host organism has an absolute requirement for the cofactor. In some cases, these cofactor s must be imported from the environment, and as such may or may not be readily available. To overcome dependence on a particular cofactor, several isofunctional forms of cofactor dependent enzymes have evolved (Galp erin et al. 1998a, Galperin et al. 1998b, Matthews et al. 2003, Graham et al. 2009, Sankaran et al. 2009, Macauley et al. 2009) For instance, four classes of superoxide dismutase, which catalyzes the conversion of superoxide radical to oxygen and hydrogen peroxide, have been discovered. Each class utilizes a different catalytic metal cofactor: copper, iron, manganese or nickel (Abreu and Cabelli, 2010) By encoding two or more of these SOD classes, an organism can ensure that SOD activity is present even if a particular essential metal cofactor is not available. Several Streptomyces spp. genomes encode both a nickel and ironcontaining SOD isozyme (Youn et al. 1996) Therefore, when one of those metal ions is unavailable, free radical detoxification can still occur with use of the other metal. A further optimization of flexible cofactor requirement is differential regulation of the distinct isofunctional genes by those cofactors (Rodionov, 2007) In the case of Streptomyces spp. w hen nickel is present in the growth medium, expression of
156 the gene encoding ironSOD is repressed and expression of the gene encoding nickel SOD is induced (Kim et al. 1998, Kim et al. 2000) In some cases, distinct isoforms have evolved that do not require any cofactor. Some organisms contain a methionine synthase that is dependent on the cofactor B12, while in ot her organisms this enzyme is independent of B12 (Gophna et al. 2005) Some organisms encode both isoforms (Gophna et al. 2005) In some of those cases, t he gene encoding the B12independent isozyme is regulated by a B12 ribo switch and is expressed when B12 is not available (Rodionov et al. 2003) A similar regulatory strategy has been described for zinc availability. Zinc independent proteins are negatively regulated by the transcription factor Zur and expressed under zinc limiting conditions to replace zinc dependent proteins. The best characterized examples of differential regulation of zinc dependent and independent isofunctional proteins are the C+ and C ribosomal protein paralogs (Makarova et al. 2001, Pani na et al. 2003) In contrast to the main copies that contain Cys4 Znribbon motifs (and are thus called C+), C ribosomal protein duplicates lack the key Cys residues, do not bind zinc and are repressed by Zur. When zinc is scarce, these C paralogs are expressed and substitute for the C+ proteins in ribosomes (Natori et al. 2007, Gabriel and Helmann, 2009) This mechanism is proposed to increase cell survival in zinc limiting growth conditions by supplying func tional copies of zinc free proteins for the newly made ribosomes. At the same time, a pool of zinc is liberated through dissociat ion from the existing ribosomes and subsequent degradation of the C+ proteins.
157 In addition to the ribosomal paralogs, the use of a back up GTP cyclohydrolase I (GCYH I A folE ) was also discovered as part of the Zur mediated response to zinc depletion (Sankaran et al. 2009 ) In this case, the main constitutively expressed GCYH I A which c atalyzes the first step in de novo folate biosynthesis, is an essential zinc dependent protein (Auerbach et al. 20 00) When Zur repression is relieved, a GCYH I B ( folE2 ) that does not require zinc as a cofactor is expressed (Sankaran et al. 2009) Only remote sequence similarity is found between FolE and FolE2. This back u p strategy appears to ensure that folate biosynthesis is functional even with decreased activity of the main GCYH I A due to zinc depletion. Genome context analysis revealed that a significant proportion of the Zur regulated COG0523 genes were located within chromosomal gene clusters that contain genes encoding uncharacterized paralogs of various zinc dependent proteins (Chapter 3 and Figure 51). It remains to be determined whether these paralogs whose genes are positioned downstream from putative Zur bin ding sites, functionally replace their zinc dependent counterparts when the activity of the latter is adversely affected by the absence of zinc Alternatively, these proteins may play other roles in the cell that are distinct from those of their paralogs. Of these paralogs, the comparative genomic analysis presented in Chapter 3 suggested functional coupling between COG0523 and the DksA paralog. This prediction was strengthened by the physically clustering of these two genes in the absence of putative co re gulation through Zur. DksA was initially identified in E. coli (EC) as a suppressor of the dnaK phenotype (Kang and Craig, 1990) Since then, DksA was shown to act synergistically with (p)ppGpp to control the bact erial response to stress and starvation (also known as the
158 stringent response) (Paul et al. 2004, Potrykus and Cashel, 2008) The crystal structure of EC DksA revealed that it belongs to a class of bacterial trans cription factors (which includes GreA, Gre B and GfhI) that bind within the RNA polymerase ( RNAP ) secondary channel near the active site located at the base of this channel (Perederina et al. 2004) The stringent response enables rapid and global change of gene expression following nutrient stress, which leads to a rapid increase in ppGpp levels (Magnusson et al. 2005, Srivatsan and Wang, 2008) DksA/ppGpp strongly inhibits transcription of rRNA genes while activating genes for amino acid biosynthesis and transport. Both effects utilize the main activity of DksA : destabilization of open promoter complexes through interaction with RNAP At the rrn promoters, open complexes are very unstable (Gaal et al. 1997) and further destabilization essentially abolishes transcription of rRNA genes (Rutherford et al. 2009) Conversely, RNAP forms very stable complexes at amino acid promoters such as hisG (Paul et al. 20 05) DksA and ppGpp destabilize these complexes and increase transcription in vitro (Paul et al. 2005) In vivo a part of the control could be through liberating RNAP from rrnB promoters that account for 70% of the total RNA synthesis in rapidly growing cells (Zhou and Jin, 1998) The end result of this dual control is the restored balance between ribosome production and available amino acid pools. Interesti ngly ppGpp and DksA may play independent, or even opposing, roles at some E. coli promoters (Magnusson et al. 2007, Aberg et al. 2008, Dalebroux et al. 2010) and during replication (Tehranchi et al. 2010 Trautinger et al. 2005) DksA proteins characterized t o date contain a canonical Cys4 Znfinger motif. Structural analysis of the EC DksA suggests that this motif plays a key role by
159 maintaining the fold of the globular domain and its orientation relative to the catalytic coiled coil (Perederina et al. 2004) The zinc ion is chelated by two cysteines from each domain and cannot be mobilized after extensive dialysis in the presence of chelators; mutation of this motif renders DksA nonfunctional (Paul et al. 2004, Perron et al. 2005) In this chapter, an initial phylogenetic and sequence analysis of zinc dependent p aralogs found in the putative Zur regulons of bacterial genomes (Novichkov et al. 2010) is presented wi th a focus on the putatively Zur regulated paralog DksA. The DksA paralog of P. aeruginosa was chosen for experimental validation of the hypothesis that these DksA paralogs are zinc independent functional paralogs of the main DksA proteins and are specific ally expressed during zinc depletion. P. aeruginosa was chosen to test this hypothesis due to the simple reason that the deletion of the dksA gene was previously shown to have a robust growth defect (Jude et al. 2003) and regulon predictions (Novichkov et al. 2010) suggested that the uncharacterized dksA paralog should be repressed by zinc through Zur. Although the DksA protein from E. coli is by far the best characterized, the E. coli genome does not encode the DksA paralog. This observation, however, was useful for an initial screen of the DksA paralogs activity before performing experiments directly in P. aeruginosa. Results Putatively Zur Regulated Paralogs with Conserved Zinc Binding Residues An analysis of putative Zur regulons in Cyanobacteria, and and proteobacteria (Novichkov et al. 2010) revealed ten families of genes annotated as zinc dependent enzymes. These zinc dependent enzymes include N acetylmuramoyl L alanine amidase (AmiA), phosphoribosyl AMP cyclohydrolase (HisI), dihydroorotase (PyrC), class
160 carbonic anhydrase (Cam), porphobilinogen synthase (HemB), cysteinyl tRNA synthetase (CysRS), threonyl tRNA synthetase (ThrRS), 6carboxy 5,6,7,8tetrahydropterin synthase (QueD), GTP cychlohydrolase Type IA (FolE) and the C4type zinc finger regul ator DksA. These putatively Zur regulated genes specifically occur in genomes that also encode a homologous gene and are most likely part of a zinc deficiency response mechanism similar to the Zur regulated ribosomal paralogs or FolE2. Unlike the Zur regul ated ribosomal paralogs, however, the zinc binding residues in the PyrC, QueD, AmiA, HisI, FolE, CysRS and ThrRS sequences appear to be conserved (Appendix D). The f olE paralog present in the putative Zur regulons of cyanobacterial genomes is distinct from the Zur regulated folE2 genes found in Fimicutes and Proteobacteria. While FolE and FolE2 share only remote sequence similarity, the characterized FolE proteins and the cyanobacterial FolE paralogs share significant sequence similarity (Appendix D). Resul ts from the bioinformatic analysis of the PyrC and QueD paralogs is given in more detail below, as the metal binding residues are noncanonical in the PyrC paralogs and the QueD paralogs have a variant catalytic motif. PyrC Dihydroorotase (DHOase) encode d by the pyrC gene catalyzes the third step in pyrimidine biosynthesis, a reversible cyclization of carbomyl aspartate to form dihydroorotate (Lieberman and Kornberg, 1953) Characterized DHOases are zinc dependent proteins (Sander et al. 1965, Taylor et al. 1976, Ogawa and Shimizu, 1995, Williams et al. 1995, Thoden et al. 2001) Two classes of DHOases have been described in the literature: type I and type II. The type II class is thought to have evolved
161 more recently since members are relatively similar compared to the type I class whose members are widely divergent from one another (Fields et al. 1999) Type I DHOases are found in multienzyme complexes (carbamyl phosphate synthetase dihydroorotase aspartate transcarbamylase ( CAD) is a multisubunit enzyme that catalyzes the first three steps in pyrimidine biosynthesis) (Simmer et al. 1990) or as uncomplexed enzymes ( Porter et al. 2004) Type II DHOases are monofunctional enzymes (Washabaugh and Collins, 1984) Alcanivorax borkumensis Burkholderia cepacia, C metallidurans Hahella chejuensis Vibrio alginolyticus Acinetobacter baylyi P aeruginosa, P. fluorescens and P. putida encode one type II DHOase and two type I DHOase proteins (Figure 52A). The type II DHOases found in these genomes are thought to serve as the main DHOase and are represented by the characterized DHOase from E. co li (Lee et al. 2005) One of the type I DHOases encoded in these genomes are homologous to the PyrC from Pseudomonas spp., which is a noncatalytic structural subunit of the aspartate transcarbamoylase enzyme (Schurr et al. 1995) The second type I DHOase encoded by these genomes is referred to here as PyrC2 and the corresponding gene is found downstream of putative Zur binding (Novichkov et al. 2010) The PyrC2 proteins are currently uncharacterized, except for the PyrC2 from P. aeruginosa, which was shown to have DHOase activity, but the authors could not explain the redundancy between encoding the type II DHOase and PyrC2 (Brichta et al. 2004) Phylogenetic analysi s of the PyrC2 proteins reveals that they share significant sequence similarity with the PyrC from Porphyromonas gingivalis for which a crystal structure is available (Figure 52A). Interestingly, the P. gingivalis PyrC was shown to
162 have a binuclear zinc s ite and these zinc binding residues are conserved in the PyrC2 proteins whose corresponding genes are found in Zur regulons (Figures 5 2B and C). The zinc binding residues found in the P. gingivalis PyrC crystal structure are mostly identical to the zinc b inding residues found in the E. coli PyrC crystal structure; including a metal bridging lysine that is carboxylated in both cases. However, there is a slight deviation in the metal binding residues of these two proteins: one of the histidines bound to the alphazinc ion in the E. coli ortholog is a glutamine in the P. gingivalis ortholog (Figure 52B). This difference suggests that a metal other than zinc would be bound under native conditions; the borderline Lewis acid zinc does not form as strong a bond w ith a hard Lewis base such as glutamine compared with a borderline Lewis base such as histidine (Gurd and Wilcox, 1956, Lesburg et al. 1997) Which begs the question: why would the cell express a DHOase under zinc deficient conditions that has a lower affinity for zinc? QueD Similar to the PyrC paralogs, a phylogenetic reconstruction of the QueD protein family reveals two main lineages, which are referred to here as QueD and QueD2 (Figure 5 3A). One of the QueD pr oteins in Azotobacter vinelandii B cepacia and C metallidurans is a QueD, and the other protein is a QueD2 (Figure 53A). The queD2 genes in these genomes are putatively regulated by Zur. Proteins from both lineages have been shown to be involved in queuosine biosynthesis (Reader et al. 2004, McCarty et al. 2009) A crystal structure representing a QueD2 protein is not available, but, based on sequence analysis, the zinc binding residues found in the P. aerugi nosa QueD crystal structure (PDB:2OBA) are conserved in the QueD2 protein sequences (Figure 5 3B).
163 However, the position of the putative active site cysteine is not conserved in the QueD2 proteins. Instead of three amino acids away from the zinc binding H GH motif as found in QueD, the cysteine is four amino acids away in the QueD2 proteins (Figure 53B). QueD and QueD2 are homologs of 6pyruvoyl tetrahydropterin synthase (PTPS), an enzyme involved in tetrahydrobiopterin biosynthesis (McCarty et al. 2009) For PTPS, the zinc ion is proposed to coordinate the substrate for proton abstraction by the cysteine residues thiolate moiety (Brgisser et al. 1995) Perhaps, the novel catalytic motif of QueD2 proteins is indicative of a nonzinc metal cofactor, which correctly positions the substrate for catalysis by the displaced cysteine. Indeed, in the crystal structure of human PTPS (PDB: 3I2B), a nickel ion in found bound to the corresponding metal ligands (Figure 53C). Zur Regulated P aralogs with out the Canonical Zinc Binding R esidues Cam Carbonic anhydrase catalyzes the reversible hydration of CO2 (Meldrum and Roughton, 1933) Until recently, all carbonic anhydrase classes were assumed to use zinc as the catalytic cofactor (Christianson and Fierke, 1996) However, plasticity of the metal site has become apparent (Yee and Morel, 1996, Lane and Morel, 2000, Lane et al. 2005) In particular, the class of carbonic anhydrases appears to use iron as the in vivo catalytic cofactor (Tripp et al. 2004, Macauley et al. 2009) The carbonic anhydrase genes present in the computationally reconstructed Zur regul ons of and proteobacteria (Novichkov et al. 2010) share significant sequence similarity with the p rototypical class carbonic anhydrase from M. thermophila (Appendix D, Figure D 6).
164 HemB HemB catalyzes the first common step in the biosynthesis of tetrapyrroles (Nandi and Shemin, 1968) Th e existence of zinc binding and nonzinc binding variants of HemB is documented in the literature (Jaffe, 2003) As expected, the HemB paralog putatively regulated by Zur in the genome of P. putida has highest sequence similarity to the non zinc HemB isoforms and accordingly the zinc binding residues are not conserved (Apendix D, Figure D 7). DksA DksA proteins are RNAP binding factors that affect the interaction between RNAP and target promoters causing changes in gene expression. Prot eins belonging to the DksA/TraR superfamily are present throughout the bacterial kingdom (MarchlerBauer et al. 2009) and the majority of these proteins are of unknown function. For instance, i n addition to the ch aracterized DksA protein ( PA4723), which has been shown to be involved in the stringent response, the P. aeruginosa genome (Stover et al. 2000) encodes f our other proteins from this superfamily (Figure 5 4A) Thre e of t hese DksA like proteins (PA4577, PA4870, and PA0612) contain the characteristic C XX C (X17) C XX C Zn finger motif but otherwise have low sequence homology to DksA ( 24%, 16%, and 14% identity respectively) The fifth DksA like protein (PA5536), which i s refer red to here as DksA2, has significant sequence homology to the classical DksA (34% identity) but contains a CXXT (X17) C XXA motif instead of the typical Cys4 Zn finger motif (Figure 5 5A). DksA2 proteins are found in several genomes belonging to pro teobacterial species and can be identified based on sequence similarity to the DksA protein of E. coli and the presence of a variant Cys4 Znfinger motif: CXX [S/T](X17) [C/S/T]XXA.
165 Some genomes such as P. aeruginosa contain both a dksA and a dksA2 gene. In these situations, dksA2 genes are found downstream of putative Zur binding sites ( Serratia marcescens Klebsiella pneumoniae H chejuensis Pseudomonas spp., and Methylobacillus flagellatus ) (Novichkov et al. 2010) (Figure 5 4). As such, dksA2 is often clustered physically on the chromosome with factors known to be involved in the response to zinc deple tion, such as znuABC (Figure 5 1 ). Complementation of the dksA deletion of E. coli by the dksA2 of P. aeruginosa The P. aeruginosa DksA protein (PA DksA; PA4723) has been the focus of several studies examining its roles in the quorum sensing circuitry, rR NA transcription and survival during antibiotic stress (Branny et al. 2001, Jude et al. 2003, Perron et al. 2005, Viducic et al. 2006) DksA2 (PA5536), on the other hand, is annotated as a conserved hypothetica l protein ( Pseudomonas genome database (Winsor et al. 2009) ). To test the prediction that DksA2 can functionally replace the canonical DksA, complementation experiments with E. coli were used initially. Unlike P. aeruginosa, t he E. coli genome does not contain a dksA2 gene E. coli dksA is unable to grow on minimal media lacking leucine, valine, glycine, phenylalanine or t hreonine (Brown et al. 2002) As shown in Figure 5 6A dksA2 expressed in trans from PBAD was able to complement the E. coli dksA gene deletion, suggesting that dksA2 may have a similar function to dksA C ompared to EC dksA or PA dksA where uninduced expression from PBAD was sufficient for complementation r escue by dksA2 required a higher concentration of the inducer arabinose (0.00 2 0.2%). As previously shown for EC dksA (Potrykus et al. 2006) overexpression of PA
166 dksA was toxic in the presence of 0.2% arabinose. Toxicity was not observed when expressing dksA2 with the arabinose concentrations used in this study The zinc ion found in the crystal structure of E. coli DksA appears to orient the CT helix relative to the coiledcoil domain (Figure 55B). The coiledcoil is proposed to insert into the secondary channel of RN AP and the CT helix is proposed to hug the outside of RNAP, positioning DksA (Perederina et al. 2004) In the Cys4 Zn finger motif of DksA2, two of the four cysteines are conserved (Figure 55A). Degeneracy of this motif could be an indication that only two of the four cysteines in the Znfinger motif of DksA are necessary to maintain function. To test if the variant Zn finger motif found in DksA2 is adequate for maintaining the function of DksA, t he conserved Cys114 and Cys135 in PA DksA were mutated to the corresponding residues found in DksA2 ( Thr and Ala, respectively ) B oth substitutions eliminated the ability of PA DksA to complement the E. coli dksA gene deletion (Figure 5 6B) Expression of these mutant PA dksA genes was not found to be more toxic than expression of the wildtype PA d ksA gene (Figure 56C). Toxicity was relieved to a certain extent by both mutat ions. This result is consistent with a key role of a complete Znfinger motif in the function of DksA. Complementation of a P. aeruginosa dksA mutant by dksA2 Phenotypic studies were then performed directly in P. aeruginosa PAO1. Like in E. coli, d eletion of the dksA gene in P. aeruginosa le a d s to a growth defect in M9 minimal media with glucose (0.2% w/v) as a sole carbon source (Jude et al. 2003) an effect which was reproduced in M9 minimal medium with glycerol as a sole carbon source (Figure 5 7 ). S imilarly to the situation observed in a heterologous E. coli host d ksA2 expressed from PBAD (of pBAD24) rescued the growth defect of the P. aeruginosa
167 dksA strain (Figure 5 7) strongly suggesting that d ksA2 can functionally replace PA dksA The growth defect of the dksA strain could be suppressed by the addition of 100 M EDTA or by combining the dksA deletion with the deletion of the gene encoding the Z ur homolog (PA5499 np20) ( Figure 58 ). In both cases, suppression was dependent on the presence of dksA2 in cis (on the chromosome) (Figure s 5 8A and B) or in trans (expressed from PBAD of pHERD20T ) (Figure 5 9 ). The addition of zinc, but not other transition metals tested, counteract ed the suppression effect of EDTA (Figure s 5 8A and D) By contrast, zinc did not affect growth of the dksA zur strain (Figure 58A ). During these experiments, the observation was made that pyocyanin was differentially produced in the various strains and that these trends mimicked the growth defects observed above (Figure 5 10A) Pyocyanin is a secreted virulence factor that is thought to play a role in the tissue damage of infected hosts (Caldwell et al. 2009) The synthesis of this metabolite is regulated by quorum sensing and PA DksA was initially characterized in a complementation screen of a quorum sensing mutant (Branny et al. 2001) During growth in LB at 37oC, the dksA strain produced less than 10% of the pyocyanin produced by the parent strain (Figure 510B ). Pyocyanin production was restored by expressing dksA2 in trans (Figure 5 10B) dksA2 is r egulated by zi nc t hrough Zur Suppression of the P. aeruginosa dksA growth defect by EDTA or deletion of zur together with the promoter region organization of the dksA2 gene ( Figure 54B ), suggest that dksA2 is regulated by Zur in P. aeruginosa, and that its expression may be induced under zinc limitation. Therefore, an analysis of the effect of EDTA and
168 extracellular zinc on dksA and dksA2 transcript levels by qRT PCR and on DksA and DksA2 protein levels by Western blot ting was performed As shown in Figure 511A the a bundance of dksA transcript was not significantly affected by either EDTA or zinc and was found to gradually decrease throughout the growth cycle as previously described (Perron et al. 2005) In contrast, as shown in Figure 511B, dksA2 was not significantly expressed in the WT s train until late logarithmic /early stationary phase when grown in M9 medium, the same growth condition that gave rise to the dksA strain growth defect described above. In the presence of EDTA, which was able to suppress the dksA strain phenotype, the level of dksA2 transcript was increased during early/mid logarithmic phase (Figure 511B) The dksA2 transcript was undetectable t hroughout the growth cycle when the cells were grown in the presence of 25 M ZnSO4 (Figure 5 11B) In the absence of Zur, zinc failed to repress dksA2 expression compared to the strain grown in M9 medium without supplementation (Figure 5 12A) The abundance of DksA and DksA2 (as discerned from the Western blot) paralleled changes in the transcript levels (Figure s 11C and 12C) As expected from the expression results above, His6Zur was found to bind specifically to the upstream region of dksA2 in the presence of zinc (Figure 513). In the absence of zinc, binding was observed but only in the presence of higher concentrations of purified His6Zur (Figure 5 13C), while in the presence of 100 M EDTA, binding was abolished (Figure 513C). Competition with the dksA2 upstream region DNA was achieved with specific competitor (annealed oligonucleotides (42 bp) containing the putative binding site) but not with nonspecific competitor (control oligo nucleotides (42 bp) which lack a consensus Zur binding site) (Figure 513D). Zur
169 (after cleavage of the tag) had the same affinity for the dksA2 upstream DNA (data not shown). Deletion of dksA2 results in a growth defect in the presence of metal chelators DksA2 may be a conditionspecific functional variant of PA DksA, and this analysis suggest ed that dksA2 is expressed during zinc depletion. Under zinc deficient growth conditions, a larger proportion of DksA proteins may be in the apoform (metal free) and therefore inactive. Under these conditions, growth would then be dependent on DksA2. To test this hypothesis, dksA2 was deleted in the WT background. Growth of the mutant was assayed in the medium that results in the dksA growth defect but with the addi tion of metal chelators. The absence of dksA2 resulted in an observable growth defect in the presence of EDTA or TPEN, two chelators frequently used to mimic zinc limitation ( Figure 514). To confirm that th is phenotype was due specifically to zinc deplet ion (as opposed to that of another metal) znuA was deleted in the dksA2 strain background; z nuA encodes a homolog of the periplasmic chaperone component of the highaffinity zinc transporter ZnuABC, and its deletion impairs zinc uptake (Patzer and Hantke, 1998) Growth of WT, dksA2 znuA ::GmR, and dksA2 znuA ::GmR strains on minimal medium were compared in the presence of various concentrations of EDTA and TPEN (Figure 514). D eletion of znuA exacerbated the growth defect due to the deletion of dksA2 in the presence of EDTA or TPEN The growth defect was rescued by expressing dksA2 in trans from PBAD of pHERD20T in the presence of 0.2% arabinose (Figure 5 14). As further confirmation that the EDTA sensitive phenotype of the dksA2 mutant was due to depletion of zinc, 25 M of various transition metals were added to the medium
170 containing 1.25 mM EDTA. Only the addition of zinc was able to fully suppress the growth defect caused by the presence of EDTA (Figure 514C). Discussion and Conclusions Backup Proteins Zinc depletion can have detrimental effects on bacterial cell viability and can impede an organisms ability to infect a vertebrate host. P. aeruginosa is a significant human opportunistic pathogen and a major cause of mortality among cystic fibrosis patients (Govan and Deretic, 1996) As part of the acute immune response, the host act ively sequesters zinc limiting its availability to the invading pathogen (Lusitani et al. 2003, Liuzzi et al. 2005, Corbin et al. 2008) For the invading pathogen, one common solution is to induce the expression of a high affinity zinc transporter and transport available zinc from the environment. Indeed, highaffinity zinc transporters have been shown to be required for virulence of several pathogens (Dahiya and Stevenson, 2010, Davis et al. 2009, Ammendola et al. 2007, Yang et al. 2006b, Kim et al. 2004, Campoy et al. 2002) Other strategies may include expression of zinc independent functional copies of key proteins, sometimes coupled to mobilization of proteinbo und zinc (Panina et al. 2003, Gabriel and Helmann, 2009, Akanuma et al. 2006, Sankaran et al. 2009) as predicted for the HemB, Cam and DksA paralogs. An additional strategy, suggested by the presence of the Py rC, QueD, AmiA, HisI, FolE, CysRS and ThrRS paralogs, may be the induction of zinc dependent proteins when the zinc concentration within the cell becomes limiting. The purpose of expressing these genes could be to ensure that at least a subpopulation of the corresponding protein pool is metallated from available zinc. Assuming the distribution of zinc in the
171 cell is in equilibrium, increasing the concentration of one particular zinc dependent protein may shift the equilibrium in favor of that protein acquir ing zinc. However, for these paralogs, the in vivo cofactor may be a metal other than zinc, even though this analysis found the zinc binding ligands to be conserved. As an example, natively purified CucA and MncA from Synechcystis PCC 6803, contain copper and manganese, respectively, even though they have identical metal binding ligands (Tottey et al. 2008) For PyrC, t he presence of a glutamine residue instead of histidine in the PyrC2 metal binding site also argues that in vivo the metal cofactor may not be zinc. The fact that the close ortholog from P. gingivalis co crystallized with a zinc ion may not be significant. When CucA and MncA were allowed to fold under in vitro conditions they specifically bound the wrong metal (Tottey e t al. 2008) Therefore, over expression in E. coli may have resulted in mis metallation of the P. gingivalis PyrC homolog with zinc. Multiple factors affect protein metallation independent from the metal binding ligands, such as protein location (Tottey et al. 2008) and chaperones (Nojiri et al. 2000, O'Halloran and Culotta, 2000) Interestingly, these Zur regulated operons, which are rich in protein paralogs, also contain members from the predicted metal chaperone family COG0523. Therefore, if one or more of these paralogs are dependent on a chaperone for proper metal acquis ition, a candidate does exist. DksA To further investigate the model that some of these paralogs exist to replace their zinc dependent counterparts during conditions of zinc deficiency, a more thorough investigation into the role of the DksA paralog was performed. The results from this study argue that P. aeruginosa utilize s the zinc independent DksA2 protein as a part of
172 the adapt ation to zinc limited environments specifically to compensate or replace the zinc dependent DksA The results supporting this model are as follows. DksA2 lacks a conserved Zn finger motif (Figure 55). Thus, DksA2 function should be independent of zinc, in contrast to DksA where it appears to be critical (Figure 5 6B). The growth assays revealed that DksA2 could (at least under the conditions tested) functionally replace DksA (Figure s 5 7 and 5 11) T ranscript analysis reveal ed that dksA2 was expressed during metal depletion and repressed in the presence of zinc (Figure 5 12) This response was mediated by Zur a previously unch aracterized protein in P. aeruginosa ; expression of dksA2 was not repressed by zinc in the absence of zur and Zur was found to bind specifically to the upstream region of the dksA2 gene (Figure s 5 13 and 514). The observation that at least two shifts wer e present in the EMSA experiment (Figure 5 24A) is a common result when working with Fur family regulators (Huang et al. 2008, Li et al. 2009, Kallifidas et al. 2010) and this result has been explained by the te ndency of these proteins to form higher order structures at the DNA binding site (Bagg and Neilands, 1987, Owen et al. 2007, Ahmad et al. 2009) For instance, the Fur protein tends to polymerize at many operator sites and binds cooperatively at some sites resulting in a helical arrangement that spreads beyond the recognition site (Lecam et al. 1994, Lavrrar et al. 2002) The most recent model for the interaction of Fur f amily regulators with DNA suggests that the operator site is recognized by two protein homodimers, each contact the DNA on opposite sides of the helix. Depending on the strength of the proteinprotein interaction, extended protein arrays form as the dimers
173 polymerize and bind with reduced stringency to adjacent DNA (Lee and Helmann, 2007) To further support the model, deletion of dksA2 was found to impair growth in the presence of the metal chelators, EDTA and TPEN. Under these growth conditions (minimal medium with glycerol as the carbon source and without amino acids) growth was dependent on the presence of dksA (Figure 5 18) Therefore, the dksA2 strain phenotype observed could be a result of an increase in the proportion of unmetallated verses metallated DksA proteins. Since zinc is likely required for the proper folding and function of DksA the newly synthesized DksA proteins would be inactive in a zinc depleted environment, leading to defects in gene expression control. Under these conditions, it could be advantageous to express a back up, zinc independent DksA variant Combined, t hese results suggest that DksA2 exerts its activity when cells encounter an environment poor in available zinc In agreement, dksA2 was previously found to be induced during growth in cystic fibrosis sputum (Palmer et al. 2005) Sputum from cystic fibrosis patients was shown to have high levels of calprotectin (Gray et al. 2008) a neutrophil protein that chelates zinc making it unavailable to pathogens (Clohessy and Golden, 1995) suggesting that the host environment is low in available zinc. DksA2 may be a previously unknown virulence factor involved in the adaptation and survival of P. aeruginosa during infection. These results are consistent with a model where DksA ( that requires zinc ) can be functionally replaced with its paralog DksA 2 (that does not require zinc ) when cellular zinc levels are low However, it is quite possible that DksA2 plays additional roles in
174 cellular physiology. For example, DksA2 may regulate promoters required for adaptation to various stresses, in essence acting as a specialized version of DksA. The growth defects due to the deletion of dksA2 observed in the presence of EDTA and TPEN could result from altered regulation at yet unknown promoters The discovery of the DksA paralog, DksA2, adds an extra level onto the already complex global regulation of gene expression by RNAP binding factors. Uniquely, DksA2 brings to light the potential for novel gene regulati on during zinc limitation, a condition that triggers an increase in DksA2 levels (Figure 512). It is also possible that DksA2 (or other DksA paralogs) may be upregulated in response to other environmental stresses. The DksA family of regulators may be the key players of an elaborate gene expression program designed to integrate diverse environmental cues and balance the cells growth under a large variety of conditions.
175 Figure 51. Representative gene clusters composed of Zur regulated COG0523 members Genes labeled yciC represent subfamily 1 COG0523 members. 052311 and 05238 refer to subfamilies 11 and 8, respectively. Other gene abbreviates: folE2, GTP cyclohydrolase IB; cysS2, paralog of cysteinyl tRNA synthetase; queD2, paralog of 6 ca rboxy 5,6,7, 8 tetrahydropterin synthase; cam class carbonic anhydrase; pyrC2 paralog of dihydroorotase; zur zinc responsive transcription factor; dksA2 paralog of C4type zinc finger regulator DksA; OMR putative outer membrane protein; thrS2 threonyl tRNA synthetase; hisI2 paralog of phosphoribosyl AMP cyclohydrolase; znuABC high affinity zinc transporter; amiA2 amidase; DUF1826, Pfam protein family of unknown function; OMR outer membrane protein.
176 A B C Figure 52. Phylogenetic and sequence a nalysis of the PyrC paralogs. A) Neighbor joining tree of PyrC protein sequences from Porphyromonas gingivalis A. borkumensis B. cepacia, C metallidurans H. chejuensis V. alginolyticus A. baylyi P aeruginosa, P. fluorescens and P putida. Proteins for which a crystal structure is available are highlighted in green. Red indicates that the corresponding gene is putatively regulated by Zur. Deduced metal binding motifs are given to the right. B) Binuclear zinc site from the crystal structure of P. gin givalis PyrC2. C) Partial protein sequence alignment of selected PyrC2 proteins. The metal binding residues are marked with a star. Secondary structural elements were derived from the crystal structure of P. gingivalis PyrC2 (PDB: 2GWN ).
177 A C B Figure 53. Phylogenetic and sequence analysis of the QueD paralogs. A) Neighbor joining tree of QueD and QueD2 protein sequences Red indicates that the corresponding gene is putatively regulated by Zur. A partial catalytic site motif is given to the right indicating position of the catalytic cysteine relative to two of the three metal binding histidines. B) P rotein sequence alignment of selected QueD2 proteins with the QueD of P. aeruginosa The metal binding residues are marked with a st ar. Catalytic triad residues are marked with a diamond. Secondary structural elements were derived from the crystal structure of P. aeruginosa QueD (PDB: 2OBA ). C) Nickel site from the crystal structure of human PTPS (PDB: 3I2B).
178 Pseudomonas aeruginosa ( PA0612) Escherichia coli ( TraR ) Pseudomonas aeruginosa (PA4870) Escherichia coli ( YbiL ) Pseudomonas aeruginosa (PA4577) DksA DksA2Nitrosomonas eutrophaDksA -likeAzotobacter vinelandiiPseudomonas aeruginosa (PA4723)Pseudomonas fluorescens Pseudomonas syringae Pseudomonas entomophilaPseudomonas aeruginosa (PA5536)Azotobacter vinelandii Klebsiella pneumoniaea Hahella chejuensis Methylobacillus flagellatus Bordetella pertussis Cupriavidus metallidurans Burkholderia cenocepacia Nitrosomonas eutropha Hahella chejuensis Legionella pneumoniaea Escherichia coli ( DksA ) CxxC -(x17)-CxxC Cxx [S/T]-(x17)-[C/S/T]xxA CxxC -(x17)-CxxC P. aeruginosa dksA2 COG0523 tAAtTGTTATAgTATAACgTTTt Putative Zur binding site A B Figur e 54. Proteins with homology to the DksA protein of E. coli are found with and without the Cys4 Znfinger motif. A) Neighbor joining tree of DksA homologs The DksA family contains three main subgroups: DksA, DksA2 and DksA like. The corresponding cystei ne motif for each subgroup is given. Dotted branches designate that the corresponding gene is putatively regulated by Zur. B) Operon organization of the dksA2 of P. aeruginosa. The putative Zur binding site (Haas et al. 2009) is given.
179 C C/T Coiled coil domain CT helix C C/A EC DksA A B Figure 55. Cys4 Znfinger domain of E. coli DksA and homologs from P. aerginosa. A) Partial sequence alignment of the DksA homologs from E. coli (EC) and P. aeruginosa (PA4723/DksA, PA5536/DksA2, PA4577, PA4870 and PA0612). The conserved and variant cysteine residues are marked. B) Cartoon of the E. coli DksA crystal st ructure (PDB: 1TJL). The Znfinger is highlighted with a red halo and the Znbinding cysteines are represented with balls and sticks.
180 PBAD PBAD EC dksA PBAD PA dksA PBAD dksA20 0.0002% 0.002% 0.02% 0.2%arabinose+ caa araPBAD PBAD PA dksA PBAD PA dksA ( Cys114 Thr ) PBAD PA dksA ( Cys135 Ala ) 0 0.0002% 0.002% 0.02%arabinose PBAD PBAD PA dksA PBAD PA dksA ( Cys135 Ala ) PBAD PA dksA ( Cys114 Thr ) PBAD EC dksA PBAD dksA2 0 0.0002% 0.002% 0.02% 0.2%arabinose A B C Figure 56. Rescue of E. coli dksA ::tet phenotype. Overnight cultures of E. coli dksA ::te t derivatives grown in LB were washed with M9 medium and normalized to an OD of 1.0. 10 l of a 103 dilution was plated on M9 medium without or with various concentrations of arabinose A) Complementation of the dksA deletion with dksA from E. coli or P. aeruginosa or dksA2 from P. aeruginosa expressed in trans from the PBAD of pBAD24. Strains were grown on M9 medium without casamino acids. B) Complementation of the dksA deletion with WT or mutated forms of dksA from P. aeruginosa expressed in trans from PBAD of pBAD24. Strains were grown on M9 medium with (first lane) or without casamino acids (lanes 25). C) Expression of the indicated genes in trans was tested for toxicity in the WT E. coli background. Strains were grown on M9 medium without casamino aci ds.
181 PBAD 0.2% 0arabinose PBAD dksA2 PBAD WT dksA 0.2% arabinose 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) WT pHERD20T PA4723 pHERD20T PA4723 pCH115 WT PBAD dksA PBAD dksA PBADdksA2 OD (600nm) Time (hr) A B Figure 57. Complementation of P. aeruginosa dksA with dksA2 in trans A) Overnight cultures of P. aeruginosa (WT) pHERD20T (PBAD ), P. aeruginosa dksA pHERD20T and P. aeruginosa dksA pCH115 (PBAD dksA2 ) grown in LB were washed with M9 medium then normalized to an OD of 1.0. 10 l of a 103 dilution was plated on M9 medium without or with 0.2% arabinose. B) Overnight cultures of WT pHERD20T, dksA pHERD20T and dksA pCH115 grown in LB were washed with M9 medium then normalized to an OD of 1.0. Each culture was then diluted 500fold into fresh M9 medium plus 0.2% arabinose. Growth curves were monitored with a Bioscreen C. Error bars represent the standard deviation of three cultures.
182 WT dksA dksA dksA2 ::GmR dksA zur dksA zur dksA2 ::GmR Zn Cu Co Ni + + + + + Mn + 100 M EDTA 25 M Metal 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) WT PA4723 PA4723 PA5536::GmR PA4723 PA54 PA4723 PA5499 PA5536::GmR WT dksA dksA dksA2 ::GmR dksA zur dksA zur dksA2 ::GmRM9 100 M EDTA 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) no metal Zn(II) Cu(II) Co(II) Ni(II) Mn(II) 100 M EDTA + 25 M Metal 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 OD 600nm Time (hr) WT PA4723 PA4723 PA5536::GmR PA4723 PA54 PA4723 PA5499 PA5536::GmR WT dksA dksA dksA2 ::GmR dksA zur dksA zur dksA2 ::GmRWT dksA zur dksA dksA2 ::GmR dksA dksA zur dksA2 ::GmR WT dksA zur dksA dksA dksA2 ::GmR dksA zur dksA2 ::GmR Zn 0 metal, Cu, Ni, Co or Mn OD (600nm) OD (600nm) OD (600nm) Time (hr) Time (hr) Time (hr) A B C D F igure 58. Suppression of P. aeruginosa dksA growth defect. A) Overnight cultures of P. aeruginosa derivatives grown in LB were washed with M9 medium then normalized to an OD of 1.0. 10 l of a 103 dilution was plated on M9 medium with the indicated supplementation. B D) Overnight cultures of P. aeruginosa derivatives grown in LB were washed with M9 medium then normalized to an OD of 1.0. Each culture was then diluted 500 fold into fresh M9 medium without supplementation (B) or with 100 M EDTA (C). D) The dksA strain was grown in the presence of 100 M EDTA 25 M zinc, copper, cobalt, nickel or manganese. Growth curves were monitored with a Bioscreen C. Error bars represent the standard deviation of three cultures.
183 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 0 0.2 0.4 0.6 0.8 1 1.2 0 20 40 60 80 100 + 100 M EDTA EDTA 0.2% 0 arabinose dksA PBAD dksA zur dksA2 ::GmRPBAD dksA2 dksA dksA2 ::GmRPBAD dksA dksA2 ::GmRPBAD dksA2 dksA D zur dksA2 ::GmRPBAD 100 M EDTA and 0.2% arabinose 0.2% arabinoseOD (600nm) OD (600nm)Time (hr) Time (hr) dksA dksA2 ::GmRPBAD dksA2 WT PBAD dksA dksA2 ::GmRPBAD dksA zur dksA2 ::GmRPBAD dksA2 dksA D zur dksA2 ::GmRPBAD A B C Figure 59. Complementation of the dksA2 : :GmR mutant with dksA2 in trans A) Overnight cultures of P. aeruginosa derivatives grown in LB were washed with M9 medium then normalized to an OD of 1.0. 10 l of a 103 dilution was plated on M9 medium with the indicated supplementation. B) and C) Over night cultures of P. aeruginosa derivatives grown in LB were washed with M9 medium then normalized to an OD of 1.0. Each culture was then diluted 500fold into fresh M9 medium plus 0.2% arabinose and the indicated supplementation. Growth curves were monitored with a Bioscreen C. Error bars represent the standard deviation of three cultures.
184 Pyocyanin : WT PBAD dksA PBAD dksA PBAD dksA2 WT dksA dksA dksA2 ::GmR dksA zur dksA zur dksA2 ::GmR dksA dksA2 ::GmRPBAD dksA dksA2 ::GmRPBAD dksA2 dksA zur dksA2 ::GmRPBAD dksA zur dksA2 ::GmRPBAD dksA2++ +++ + + ++ ++ 0 1 2 3 4 5 6 7.5 9.5 11.5 22.5 ug ml 1 pyocyanin Time (hr) PAO1 pHERD20T PA4723 pHERD20T PA4723 pCH115 0 0.5 1 1.5 2 2.5 0 5 10 15 20 25 OD 660nm Time (hr) PAO1 pHERD20T PA4723 pHERD20T PA4723 pCH115 WT PBAD dksA PBAD dksA PBAD dksA2 OD (600nm) Time (hr) g ml-1pyocyanin WT PBAD dksA PBAD dksA2 Time (hr) dksA PBAD A B C Figure 510. Pyocyanin defect of P. aeruginosa dksA is rescued by expression of dksA2 A) Pyocyanin production of various P. aeruginosa mutant strains harboring the indicated constructs in trans 5 ml cultures of LB were inoculated with a colony and grown overnight (~16 hrs) at 37C. B) Pyocyanin production of WT pHERD20T, dksA pHERD20T and dksA pCH115 at various time points during in LB at 37C. C) Corresponding growth curve of the strains assayed in (B).
185 EDTA Zn M9 EDTA Zn M9 19 hrs 21 hrs 23 hrs 25 hrs 27 hrs DksA DksA2 0 0.5 1 1.5 2 2.5 3 0 5 10 15 20 25 30 OD660nm Time (hr) M9 100 M EDTA 25 M ZnSO4 0E+00 1E+03 2E+03 3E+03 4E+03 5E+03 6E+03 7E+03 8E+03 19 21 23 25 27 copy number (dksA) Time (hr) M9 100 M EDTA 25 M Zn 0E+00 1E+03 2E+03 3E+03 4E+03 5E+03 6E+03 7E+03 8E+03 19 21 23 25 27 copy number (dksA2) Time (hr) M9 100 M EDTA 25 M Zn copy number ( dksA ) copy number ( dksA2 ) Time (hr) Time (hr) Time (hr) OD (600nm) A B C D Figure 511. Transcript abundance of PA dksA and dks A2 and protein abundance of PA DksA and DksA2 Average abundance of dksA (A) and dksA2 (B) transcript in total mRNA extracted from P. aeruginosa at 19, 21, 23, 25 and 27 hrs of growth in M9 medium without supplem entation (M9), plus 100 M EDTA or plus 25 M ZnSO4. Copy number refers to the number of dksA or dksA2 transcripts per 0.1 ng total m RNA. Error bars represent one standard deviation of three replicates. C) Immunoblot of DksA and DksA2 from total protein extracts from P. aeruginosa harvested at the same time points as for the transcript isolation in A and B. Blots were exposed to either anti DksA or anti DksA2 antibodies as indicated. D) Corresponding growth curves of P. aeruginosa cultured in M9 medium without (M9) or with 25 M ZnSO4.
186 0.0E+00 5.0E+02 1.0E+03 1.5E+03 2.0E+03 2.5E+03 3.0E+03 3.5E+03 21 23 25 27 copy number (dksA2) Time (hr) M9 25 M Zn M9 Zn 25 27 21 23 25 27 DksA DksA2 21 23 hrs 0 0.5 1 1.5 2 2.5 3 0 5 10 15 20 25 30 OD 660nm Time (hr) M9 25 M Zn copy number ( dksA2 ) Time (hr) Time (hr) OD (600nm) A B C Figure 512. Effect of zur deletion of the t ranscript abundance of dksA2 and protein abundance of DksA2 A) Average abundance of dksA2 transcript in total mRNA extracted from P. aeruginosa zur ::GmR at 21, 23, 25 and 27 hours of growth in M9 medium without (M9) or with 25 M ZnSO4. Copy number refers to the number of dksA2 transcripts per 0.1 ng total mRNA. Error bars represent one standard deviation of three replicates. B) Immunoblot of DksA and DksA2 from total protein extracts from P. aeruginosa zur ::GmR harvested at the same time points as for the transcript isolation in A. Blots were exposed to either anti DksA or anti DksA2 antibodies as indicated. C) Corresponding growth curve of P. aeruginosa zur ::GmR cultured i n M9 medium without (M9) or with 25 M ZnSO4.
187 + ZnHis6Zur + + + + + + + +1:0 1:25 1:50 1:100 1:25 1:50 1:100 1:200 Zur site control 0 0.2 0.4 0.6 0.8 1 1.2 1 10 100 Fraction of DNA bound nM His 6 Zur DNA (free) DNA Protein 1 DNA Protein 2 0 4 8 16 32 64 128 256 512 His6Zur (nM ) + Zn Zn0 12 24 36 48 60 72 120 2 40+ EDTAHis6Zur (nM ) A B C D Figure 513. Complex formation between the upstream DNA region of dksA2 and purified His6Zur. Complexes were separated by nondenaturing polyacrylamide gel electrophoresis and visualized with a Phototrope kit (NEB). A) Increasing concentrations of purified His6Zur were incubated in the presence of 100 M ZnSO4 and 1.5 ng of a 223 bp DNA fragment labeled with biotin at the 5 end. The fragment represents the DNA region including and surrounding the putative Zur binding site (shown in Figure 54B). The concentration of His6Zur shown corresponds to the monomeric unit. B) Graphical representation of the concentration of free (DNA (free)) and complexed DNA (DNA Protein 1 and DNA Protein 2) at each concentration of His6Zur from A. DNA Protein 1 refers to the smaller complex and DNA Protein 2 refers to the larger complex. C) The binding buffer contained 100 M ZnSO4, no added Zn or 100 M EDTA as indicated. D) +/ 240 nM of His6Zur as indicated plus 1.5 ng biotin labeled DNA with increasing amounts of either specific competitor (annealed oligonucleotides that contains the putative Zur binding site) or nonsp ecific competitor (oligonucleotides that do not contain a putative site).
188 WT PBAD dksA2 PBAD dksA2 PBAD dksA2 znuA ::GmRPBAD dksA2 znuA ::GmRPBAD dksA znuA ::GmRPBAD dksA2 M9 M9 10-4dilution 10-5dilution 48 hrs 67 hrs M9 10-5dilution [EDTA] [EDTA] [EDTA] WT PBAD dksA2 PBAD dksA2 PBAD dksA2 znuA ::GmRPBAD dksA2 znuA ::GmRPBAD dksA znuA ::GmRPBAD dksA2 M9 1 5 10-5dilution TPEN WT PBAD dksA2 PBAD dksA2 PBAD dksA2 znuA ::GmRPBAD dksA2 znuA ::GmRPBAD dksA znuA ::GmRPBAD dksA2 M9 48 hrs 67 hrs EDTA Zn Cu Co Ni Mn M9 EDTA Zn Cu Co Ni M9 EDTA Zn Cu Co Ni Mn Mn 10-4dilution 10-5dilution 10-5dilution A B C Figure 514. Growth defect of P. aeruginosa dksA2 in the presence of EDTA or TPEN. Overnight cultures of P. aeruginosa derivatives grown in LB were washed with M9 medium then normalized to an OD of 1.0. 10 l of the indicated dilution was plated on M9 medium plus 0.2% arabinose. A) Strains were plated on M9 medium without EDTA (M9) or with 1, 1.25, 1.5, 1.75, or 2 mM EDTA and imaged at 48 or 67 hrs B) Strai ns were plated on M9 medium without TPEN (M9) or with TPEN at either 1 M (1) or 5 M (5) and imaged after 48 hrs. C) Strains were plated on M9 medium without EDTA (M9) or with 1.25 mM EDTA (EDTA) +/ 25 M of the indicated metals. Plates were imaged at the indicated time after incolulation. The images are composites of individual plates. Each plate was composed of one medium type. All six strains were plated on the same plate.
189 CHAPTER 6 SUMMARY AND OVERALL CONCLUSIONS The overall goal of this study was to advance our understanding of microbial zinc homeostasis as it relates to the adaptation of cells to zinc depletion, with specific attention on the uncharacterized yeiR gene from E. coli and the uncharacterized dksA2 gene from P. aeruginosa Additionally, a secondary goal was to advance our understanding of the COG0523 protein family t hrough phylogenomic techniques. A broad question, that remains mostly unanswered, is how do cells ensure proper allocation of metals? As of yet, we do not have a complete pict ure of how each metal is trafficked in the bacterial cell and most likely the question will have a different answer depending on the organism. Because of its potential impact on answering this question, a phylogenomic analysis of the COG0523 family was per formed to gain a deeper understanding of this family. Since the discovery of the first copper metallochaperone (Pufahl et al. 1997) the perception of how metal proteins acquire their cofactor was revolutionized and researchers have begun to look for these factors. Based on the results from the phyl ogenomic analysis presented here, the COG0523 family may represent a rich source of metal chaperones that aid in the acquisition of metal by metal dependent enzymes. Specifically, the YeiR protein of E. coli may be the missing zinc chaperone that is involv ed in ensuring a yet unknown protein or proteins acquire zinc, a function that may be essential only when the intracellular zinc concentration is severely depleted. Two significant studies in the past decade have led to a reevaluation and advancement of our understanding of how bacteria respond when deprived of zinc. First, was the discovery that bacteria encode a highaffinity zinc transporter and that the
190 corresponding genes are specifically regulated through a zinc sensing transcription factor (Patzer and Hantke, 1998, Gaballa and Helmann, 1998) The second discovery was the realization that a pool of unliganded zinc in the cytoplasm of E. coli does not exist (Outten and O'Halloran, 2001) Since these two discoveries, researchers have sought to discover additional mechanisms that enable growth in the face of zinc limitation and decip her the mechanism by which the bacterial cell ensures proper allocation of zinc among metal dependent proteins. During growth in zinc replete or moderately zinc deplete conditions, expression of the highaffinity zinc transporter (Patzer and Hantke, 1998) coupled with liberation of zinc from the dissociable ribosomal pool (Graham et al. 2009) may be adequate for ensuring that the appropriate zinc dependent enzymes are metallated and growth is sustained. E. coli is known to encode one zinc independent ribosomal paralog. Expression of this gene and integration into the ribosome would theoretically lead to the potenti al release of 50,000 zinc ions. It is difficult to estimate how many doublings this pool of zinc would sustain in the absence of exogenous zinc. The zinc quota for E. coli is 200,000 zinc ions per cell (Outten and OHalloran, 2001), so in the absence of exogenous zinc, 50,000 zinc ions would not last very long. There would also be an increasing pressure from competing metals as the zinc concentration within the cytoplasm drops. It would be beneficial if a chaperone was present to direct this pool of zinc to essential zinc dependent proteins to the exclusion of nonessential zinc binding proteins. The phylogenomic analysis of COG0523 proteins combined with the YeiR study leave open the possibility that YeiR could serve as such a stress response factor. Further study with particular attention on
191 determining any interactions bet ween YeiR and other proteins during conditions of zinc replete and deplete conditions would need to be undertaken. A less controversial mechanism for sustaining growth when zinc becomes depleted is expression of a back up DksA protein. As DksA is a criti cal factor in maintaining homeostasis in response to nutrient limitation, one can imagine its importance in zinc deplete growth conditions, which are most likely poor in other nutrients. As DksA is dependent on the presence of zinc for maintenance of struc ture, it may be inactive or less active in zinc deplete conditions leading to pleotrophic disregulation of homeostasis. The model proposed here is that a zinc independent DksA backup, DksA2, is produced to compensate for the lack of the main DksA protein. This study provides evidence that, at least for the conditions tested, DksA2 can functionally replace DksA. Additionally, DksA2 appears to be present in the cell specifically when zinc is depleted and regulation of the dksA2 gene is mediated through the z inc sensing repressor Zur. Concurrent work in the Artsimovitch lab at the Ohio State University supports the role of DksA2 serving as a back up DksA. DksA2 was found to bind in the secondary channel of RNAP and, based on in vitro transcription assays, DksA 2 and DksA affected transcription in a similar manner at tested promoters (Blaby Haas et al. 2011) This study has provided evidence for two novel strategies used by bacteria to sustain growth when deprived by zinc. The previously uncharacterized YeiR protein from E. coli is involved in sustaining growth in the presence of EDTA, which can be suppressed specifically by the addition of exogenous zinc. Additionally, YeiR is involved in sustaining growth in the presence of cadmium. The exact function of YeiR in these
192 processes, however, is still unknown. The previously uncharacterized DksA2 protein from P. aeruginosa is also involved in sustaining growth in the presence of EDTA, which can be suppressed specifically by the additions o f exogenous zinc. The function of DksA in this process is better understood but whether DksA2 functions outside the proposed model is not known. For instance, as a RNAP binding factor that is specifically expressed when zinc is depleted, DksA2 is, in essence, a zinc responsive transcription factor. Further exploration of the role of DksA2 in the cell specifically when zinc is limited will provide further insight.
193 APPENDIX A SUBSYSTEMS Due to the size of subsystems, screenshots are provided here that provide examples for reference by the main text. The reader is directed to view the full subsystems at http://theseed.uchicago.edu/FIG/SubsysEditor.cgi A brief description is provided, to enable the reader to navigate the website and the provided subsystems. Th e link provided will bring the reader to the main directory for subsystems stored on the SEED database. The two subsystems built by the author are located in this directory and can be accessed by following the link for G3E family of P loop GTPases (metall ocent er biosynthesis) or COG0523. On the SEED website, the subsystem is divided into multiple tabs: Subsystem Info gives a description of the subsystem including user provided backgr ound and relevant publications. Functional Roles gives a list of th e functional roles included in the subsystem. This page lists the user defined gene abbreviations used for each functional role in the subsystem. Links to relevant publications for each functional role are provided if available. The Spreadsheet is the main element of the subsystem and provides a visual tool to discern the presence of specific functional roles among the various genome sequences provided by the SEED database. Organism names and the domain to which that organism belongs are provided to the l eft. The Variant column is used by the user to differentiate between organisms based on their interpretation of the spreadsheet. For instance, genomes that do not encode the pathway of interest can be assigned a variant code that differentiates those genomes from ge nomes that contain the pathway.
194 The presence of a gene with a certain functional role is represented by a number. The number provides a link to the gene page of that gene in that organism. The gene page provides more information such as gene se quence, protein sequence, links to other databases, and gene clustering information. If a cell in the spreadsheet is empty, then that gene is missing in that genome. Sometimes the gene is missing because it is mis annotated. There are tools within SEED to find these genes and re annotate them. Subsystems, therefore, commonly are used to find mis annotations and repair them. Clustering between genes in the spreadsheet is shown with coloring. In an organism, each gene cluster is represented by a different col or because multiple gene clusters may exist that contain genes belonging to the functional roles added to the subsystem.
195 Figure A 1. Comparative genomic analysis of ureG containing gene clusters. A screnshot of the G3E family of P loop GT Pases (metallocenter biosynthesis) subsystem is shown. The urease maturation pathway is composed of UreA, UreB and UreC (structural subunits of urease), UreD and UreF (urease accessory factors), UreG (GTPase component and G3E family member) and UreE (prop osed metallochaperone compoenent). Most genomes that encode urease, also encode UreD, UreE, UreF and UreG, as shown for the genomes of Corynebacterium afficiens and Corynebacterium glutamicum Some genomes however are missing the gene for UreE, as shown for multiple Mycobacterium spp. genomes.
196 Figure A 2. Gene clustering of hypB, ureG and meaB with their target metalloenzyme or other accessory factors. A screenshot of the G3E family of P loop GTPases (metallocenter biosynthesis) subsystem is shown. The gene encoding HypB is commonly found in a gene cluster encoding the [NiFe] hydrogenase accessory factors HypA, HypC, HypD, HypE, HypF and HypG. The gene encoding UreG is commonly found in a gene cluster encoding urease ( ureABC ) and other accessory factors ( ureDEF ). The gene encoding MeaB is commonly found nect to the gene encoding methylmalonly CoA mutase, meaB
197 Figure A 3. Gene clusters involving COG0523 genes in bacterial genomes. A screenshot of the COG0523 su bsystem is shown. As an example, in the Cyanothece sp. ATCC 51142 genome, 11 COG0523 genes are found. Of these, 4 genes cluster physically on the genome with genes involved in zinc uptake (zinc). Three genes cluster with three of four genes for GTP cyclohy drolase I proteins (FolE). Two genes cluster with a gene for phosphoribosyl AMP cyclohydrolase (HisI).
198 Figure A 4. Gene clusters involving COG0523 genes in archaeal genomes. A screenshot of the COG0523 subsystem is shown. Among archaeal genomes that contain homologs of COG0523, gene clusters are found between a COG0523 gene and a creatine amidohydrolase gene ( Haloarcula marismortui ), a COG0523 gene and a carbon starvation gene ( Haloarcula marismortui ), a COG0523 gene and genes for uroporphyrinogen dec arboxylase genes ( Natronomonas pharaonis ) COG0523 genes and methylcobalamin:coenzyme M methyltransferase genes ( M. acetivorans M. barkeri and M. mazei ), and a COG0523 gene and a ribosomal protein gene and zinc transport genes ( M. mazei ).
199 Figure A 5. Eukaryotic genomes that contain COG0523 genes. A screenshot of the COG0523 subsystem is shown.
200 APPENDIX B DETAILED DESCRIPTION OF COG0523 GENE CLUSTERS Table B 1. Subgroup 2. Identified Fenitrile hydratase activator sequences. Genome Loc us tag Genbank accession no. Reference Microbacterium sp. AJ115 nha3 CAG29801.1 (O'Mahony et al. 2005) Pseudomonas chlororaphis B23 P47K P31521.1 (Nishiyama et al. 1991) Pseudomonas sp. K 9 nhr BAD98534.1 (Kato et al. 2005) Rhodococcus erythropolis A4 nhr3 CAQ16890.1 (Kubc et al. 2008) Rhodococcus sp. N 771 nha3 BAA36599.1 (Lu et al. 2003, Nojiri et al. 1999) Rhodococcus sp. N 774 ORF1188 BAA06274.1 (Hashimoto et al. 1994) Rhodococcus globerulus A 4 nhr3 BAC99082.1 (Xie et al. 2003) Rhodococcus jostii RHA1 RHA1_ro00362 ABG92198.1 A. baylyi ADP1 ACIAD1614 YP_046285.1 P. putida F1 Pput_2730 ABQ78864.1 Burkholderia ambifaria AMMD Bamb_6542 YP_778420.1 B ambifaria MC40 6 BamMC406_625 6 ACB68689.1 Burkholderia cenocepacia AU 1054 Bcen_4084 YP_623946.1 B cenocepacia MC0 3 Bcenmc03_3235 YP_001776881. 1
201 Prochlorococcus marinus str. MIT 9312 Synechococcus sp. CC9902 Synechococcus sp. WH 8102 COG1641 COG0523 HieC FutB COG2154 UPF0047 M32 PPase COG1641 COG0523 HieC FutB COG2154 UPF0047 M32 PPase COG1641 COG0523 HieC FutA COG2154 UPF0047 PPase FutB M32 Figure B 1. Genome context of subgroup 3 members. Subgroup 3 genes colocalize on the genom e with homologs of uncharacterized conserved proteins (COG1641), putative transmembrane protein (HieC), Ferric iron ABC transporter, permease protein (FutB) and periplasmic binding protein (FutA), Pterin 4 alphacarbinolamine dehydratase (COG2154), protein of unknown function (UPF0047), carboxypeptidase Taq (M32) metallopeptidase (M32), and inorganic pyrophosphatase (PPase). Characterized members of COG2154 from animals have been shown to be responsible for recycling pterin cofactors generated by aromatic a mino acid hydroxylases (AAHs) (for a review see (Thny et al. 2000) ). In bacteria, the absence of AAH in many COG2154 encoding genomes suggests its role in the recycling of pterin cofactors from other pterin dependent enzymes (Naponelli et al. 2008) UPF0047 appears to be a metalloenzyme; the crystal structure of UPF0047 from Sulfolobus tokodaii has been solved and found to co crystalize with a zinc ion in a potential catalytic site(Tanaka et al. 2005) Over expression of the UPF0047 homolog from E. coli as well as Thermotoga, Sulfolobus, and Pyrococcus was found to complement the thiamine auxotrophy of a thiEE. coli mutant (Morett et al. 2008) Table B 2. Genomes that contain the subgroup 3 gene cluster. Genome Locus_tag Synechococcus sp. CC9311 Sync_2045 Synechococcus sp. CC9605 Syncc9605_0672 Synechococcus sp. RS9917 RS9917_09326 Synechococcus sp.WH 7805 WH7805_13878 Synechococcus sp. WH 8102 SYNW1795 P. marinus (5 genomes) PMT9312_0491 (str. MIT 9312)
202 Burkholderia cepacia R18194 and Burkholderia cenocepacia J2315COG0523 UraA UbiX AtzB MH UbiD MHBurkholderia multivorans ATCC 17616 and Pseudomonas fluorescens PfO 1 COG0523 UraA UbiX AtzB MH UbiD MH COG0523 UbiX CoxS CoxL CoxMRalstonia eutropha JMP134 Sinorhizobium meliloti 1021 COG0523 UbiX CoxS CoxL CoxM UraA UbiD MH MH UraA UbiD MH MH Figure B 2. Genome context of subgroup 4 members. Subgroup 4 genes colocal ize on the genome with genes encoding metal dependent hydrolases (MH), xanthine/uracil permease (UraA), 3polyprenyl 4 hydroxybenzoate carboxy lyase (UbiX and UbiD), hydroxyatrazine ethylaminohydrolase (AtzB), molybdenum containing hydroxylase (CoxLSM). Several of these genes encode various proteins involved in the metabolism and degradation of aromatic compounds. In addition to molybdenum, Mocontaining hydroxylases have been found to contain [2Fe 2S] clusters (For a review see (Hille, 2005) ). Table B 3. Genomes that contain the subgroup 4 gene cluster. Organism Locus_tag Sinorhizobium meliloti 1021 SMb20133 Burkholderia cenocepacia J2315 BCAM2270 B. cepacia R18194 Bcep18194_B0634 Ralstonia eutropha JMP134 Reut_A3078 P. fluorescens PfO 1 Pfl_3432
203 Table B 4. Genomes that contain the subgroup 5 gene cluster. Genome Locus_tag Synechococcus sp. WH 8102 SYNW2482 Gloeobacter violaceus PCC 7421 glr0534 A. variabilis ATCC 29413 Ava_0285 Nostoc punctiforme PCC 73102 Npun_R3841 Nostoc sp. PCC 7120 all1751 P. marinus (5 genomes) P9211_15201 (str. MIT 9211) Caulobacter sp K31 Caul_0196 Caulobacter crescentus CB15 CC0321 Aurantimonas sp. SI85 9A1 SI859A1_00649 Bartonella henselae str. Houston1 BH12980 B. japonicum USDA 110 bll7768 Nitrobacter hamburgensis X14 Nham_3425 Nitrobacter winogradskyi Nb 255 Nwi_0917 Rhodo pseudomonas palustris (4 genomes) RPE_4794 (str. BisB53) Brucella abortus biovar 1 str. 9941 BruAb2_0247 Brucella canis ATCC 23365 BCAN_B1006 Brucella melitensis 16M BMEII0308 B. suis 1330 BRA0987 Brucela suis ATCC 23445 BSUIS_B0982 Mesorhizobium l oti MAFF303099 mll5156 Mesorhizobium sp. BNC1 MBNC02001409 Rhizobium leguminosarum bv. viciae 3841 RL4148 Sinorhizobium meliloti 1021 SMc02978 A. tumefaciens str. C58 Atu4502 Acidiphilium cryptum JF 5 Acry_1304 Gluconobacter oxydans 621H GOX1617 Gra nulibacter bethesdensis CGDNIH1 GbCGDNIH1_0170 Bordetella bronchiseptica RB50 BB0682 Bordetella parapertussis 12822 BPP0675
204 COG0523 Ama DacC COG3034 AccA XerD COG0523 Ama DacC COG3034 AccA XerD COG0523 Ama DacC COG3034 AccA XerD COG0523 Ama DacC Brucella suis 1330 Sinorhizobium meliloti 1021 Bartonella henselae str. Houston 1 Aurantimonas sp. SI85 9A1 Rhizobium leguminosarum bv. viciae 3841 COG0523 DacC COG3034 AccA XerD Figure B 4. Genome context of subgroup 6 members. Subgroup 6 genes colocalize with genes encoding integrase/recombinase (X erD), acetyl coenzyme A carboxyl transferase alpha chain (AccA), uncharacterized protein (COG3034), D alanyl D alanine carboxypeptidase (DacC), and N acyl L amino acid amidohydrolase (Ama).
205 Table B 5. Genomes that contain the subgroup 6 gene cluster. Rhizobium leguminosarum bv. viciae 3841 COG0523 PotA CIH GatA PotB PotC FabG FabG PotD PotA PotDVerminephrobacter eiseniae EF01 2 COG0523 PotA CIH PotB PotC FabG PotD PotA PotDSerratia marcescens Db11 COG0523 CIH FabG FabG PotD GatA Pseudomonas fluorescens Pf 5 COG0523 CIH FabG FabG PotD GatA Figure B 5. Genome context of subgroup 7 members. Subgroup 7 genes colocalize with genes encoding Asp tRNAAsn/Gu tRNAGln amidotransferase A subunit and related amidases family protein (GatA), spermine/putresci ne periplasmic binding protein (PotD), spermine/putrescine import ATP binding protein (PotA), spermine/putrescine transport permease protein (PotB and PotC), cyclic imide hydrolase (CIH), and 3ketoacyl (acyl carrier protein) reductase (FabG). Org anism Locus_tag Parvularcula bermudensis HTCC2503 PB2503_00115 Aurantimonas sp. SI85 9A1 SI859A1_02956 Bartonella henselae str. Houston 1 BH16310 Brucella abortus biovar 1 str. 9941 BruAb1_2010 Brucella canis ATCC 23365 BCAN_A2081 Brucella melitensi s 16M BMEI0036 B. suis (2 genomes) BR2035 (str. 1330) Methylobacterium extorquens PA1 Mext_1219 Mesorhizobium loti MAFF303099 mll3580 Mesorhizobium sp. BNC1 MBNC02000233 A. tumefaciens str. C58 Atu3633 Rhizobium leguminosarum bv. viciae 3841 RL4362 Sinorhizobium meliloti 1021 SMc00684
206 Table B 6. Genomes containing subgroup 7 gene cluster. Organism Locus_tag Rhizobium leguminosarum bv. viciae 3841 pRL120796 Verminephrobacter eiseniae EF01 2 Veis_1001 S. marcescens DB11 fig|615.1.peg.4294 P. fluorescens Pf 5 PFL_1367 Pseudomonas syringae (3 g enomes) PSPTO4198 (pv. tomato str. DC3000) Ralstonia solanacearum GMI1000 COG0523 Zur HslU HslV YciC DksA2Burkholderia spp. COG0523 HslU HslV DksA2 XerC Ralstonia eutropha JMP134 COG0523 Zur HslU HslV YciC DksA2 Bordetella spp.COG0523 Zur HslU HslV DksA2 ZnuC ZnuB ZnuA XerC Figure B 6. Genome context of subgroup 8 members. Subgroup 8 genes cluster with ATP dependent hsl protease ATP binding subunit (HslU), ATP dependent protease (HslV), C4type zinc finger DksA/TraR family protein (DksA2), zinc uptake regulation protein (Zur), high affinity zinc transporter (ZnuABC), integrase/recombinase (XerC), and the COG0523 Subgroup 2 paralog (YciC)
207 Table B 7. Genomes containing subgroup 8 gene cluster. Organism Locus_tag Bordetella avium BAV0145 Bordetella bronchiseptica RB50 BB0181 Bordetella parapertussis 12822 BPP0179 B. pertussis Tohoma I BP3084 Burkholderia ambifaria AMMD Bamb_3135 Burkholderia cenocepacia(4 genomes) Bcen_2475 (str. AU 1054) B. cepacia R18194 Bcep18194_A64 39 Burkholderia dolosa AUO158 BDAG_00307 Burkholderia multivorans ATCC 17616 Bmul_3084 B. cepacia R1808 Bucepa02001131 Burkholderia vietnamiensis strain G4 Bcep1808_3172 Burkholderia fungorum Bcep2993 Burkholderia mallei (3 genomes) BMA10229_A2171 (s tr. 10229) Burkholderia xenovorans LB400 Bxe_A4377 Burkholderia pseudomallei (4 genomes) BURPS1655_K0002 (str. 1655) C. metallidurans CH34 Rmet_0127 Ralstonia eutropha JMP134 Reut_A0163 Polynucleobacter sp. QLW P1DMWA 1 Pnuc_2015 Ralstonia solanacearu m GMI1000 RSc0047 Acidovorax avenae Aave_0807 Acidovorax sp. JS42 Ajs_3684 Delftia acidovorans SPH 1 Daci_1456 Polaromonas sp. JS666 Bpro_1063 Rhodoferax ferrireducens DSM 15236 Rfer_3439 Verminephrobacter eiseniae EF01 2 Veis_4556 Herminiimonas ars enicoxydans HEAR2959 Leptothrix cholodni SP 6 Lcho_3834
208 Proteus mirabilis HI4320 COG0523 YjiX CstA2Pseudomonas aeruginosa PAO1 COG0523 YjiX CstA2 Figure B 7. Genome context of subgroup 9 members. Subgroup 9 genes colocalize with genes encoding a carbon starvation protein paralog (CstA2) and a protein of unknown function (YjiX). Table B 8. Genomes containing subgroup 9 gene cluster. Genome Locus_tag Enterobacter sp. 638 Ent638_0509 E. coli (17 genomes) YjiA K. pneumoniae MGH 78578 KPN_04774 Erwinia carotovora subsp. atroseptica SCRI1043 ECA1189 P. mirabilis HI4320 PMI0144 Salmo nella bongori 12149 fig|12149.1.peg.4488 S. enterica (5 genomes) STY4888 (subsp. Enterica serovar Typhi str. CT18) S. typhimurium LT2 STM4530 S. marcescens Db11 fig|615.1.peg.4294 Serratia proteamaculans 568 Spro_0580 Shigella dysenteriae Sd197 SDY_4 605 Shigella flexneri 2a (2 genomes) S4640 (str. 2457T) Shigella sonnei (2 genomes) SSO_4485 (str. Ss046) A. vinelandii Avin3722 P. aeruginosa PA4604 (str. PAO1) P. entomophila L48 PSEEN0805 P. fluorescens (3 genomes) PFL_5350 (str. Pf 5) P. putida (4 genomes) Pput_4501 (str. F1) Pseudomonas syringae (3 genomes) Psyr_4271 (pv. Syringae B728a)
209 COG0523 RH PAS GGDEF EAL COG0523 RH GGDEF COG0523 RH COG0523 MtlD Spr LpxT Rtn OppA OppB OppC OppD COG0523 MtlD Spr LpxT Rtn OppA OppB OppC OppD COG0523 Spr LpxT Rtn OppA OppB OppC OppD Vibrio vulnificus CMCP6 Shewanella spp. Yersinia pseudotuberculosis IP 32953 Yersinia pseudotuberculosis IP 32953 Shigella flexneri 2a str. 301 Salmonella typhimurium LT2 Figure B 8. Genome context of subgroup 10 members. Subgroup 10 genes colocalize with genes encoding signal transduction proteins (GGDEF, PAS GGDEF EAL, or Rtn) or an ATP dependent RNA helicase (RH). Abbreviations: MtlD, mannitol 1 phosphate/altronate dehydrogenases; LpxT, undecaprenyl pyrophosphate phosphatase; Spr, predicted peptidase; OppABCD, putative ATP dependent oligopeptide permease.
210 Table B 9. Genomes containing subgroup 10 gene cluster. Genome Locus_tag Enterobacter sp. 638 Ent638_2769 E. coli (17 genomes) YeiR K. pneumoniae MGH 78578 KPN_02606 Erwinia carotovora subsp. atroseptica SCRI1043 ECA2733 Salmonella bongori 12149 fig|12149.1.pe g.2276 S. enterica (5 genomes) STY2448 (subsp. enterica serovar Typhi str. CT18) S. typhimurium LT2 STM2212 S. marcescens Db11 fig|615.1.peg.3296 Serratia proteamaculans 568 Spro_3241 Shigella dysenteriae Sd197 SDY_0906 Shigella flexneri 2a (2 genome s) SF2260 (str. 301) Shigella sonnei (2 genomes) SSO_2229 (str. Ss046) Yersinia bercovieri ATCC 43970 YberA_01001247 Yersinia enterocolitica 8081 YE1435 Yersinia frederiksenii ATCC 33641 YfreA_01001244 Yersinia intermedia ATCC 29909 YintA_01003502 Yersinia mollaretii ATCC 43969 YmolA_01001161 Yersinia pestis (7 genomes) YPA_0995 (str. Antiqua) Yersi nia pseudotuberculosis (3 genomes) YPTB1311 (str. IP 32953) Shewanella amozonensis SB2B Sama_2446 Shewanella baltica (4 genomes) Sbal_1338 (str. OS155) Shewanella denitrificans OS217 Sden_2575 Shewanella frigidimarina NCIMB 400 Sfri_2795 Shewanella hali faxensis HAW EB4 Shal_3090 Shewanella sp. PV 4 Shew_2776 Shewanella oneidensis MR 1 SO1502 Shewanella pealeana ATCC 700345 Spea_3001 Shewanella putrefaciens CN32 Sputcn32_1255 Shewanella sediminis HAW EB3 Ssed_3334 Shewanella sp. MR 4 Shewmr4_2751 Shewanella sp. MR 7 Shewmr7_2829 Shewanella sp. W3 18 1 Sputw3181_2849 Shewanella sp. ANA 3 Shewana3_2927 V. alginolyticus 12G01 V12G01_06973 Vibrio parahaemolyticus RIMD 2210633 VPA0589 Vibrio sp. Ex25 VEx2w_01001184 Vibrio sp. MED222 MED222_06985 Vibrio splendidus 12B01 V12B01_03988 Vibrio vulnificus (2 genomes) VV20385 (str. CMCP6)
211 Pseudomonas putida KT2440 YciC DUF1826 COG0523 DksA2 YciC Pseudomonas aeruginosa PAO1 DUF1826 COG0523 Figure B 9. Genome context of subgroup 11 members. Subgroup 11 genes colocalize with genes encoding an uncharacterized protein (DUF1826), COG0523 homolog from s ubfamily 2 (YciC), and C4 type zinc finger DksA/TraR family protein (DksA2). Table B 10. Genomes containing subgroup 11 gene cluster. Genome Locus_tag P. aeruginosa (3 genomes) PA5532 (str. PAO1) Pseudomonas mendocina ymp Pmen_4533 P. entomophila L 48 PSEEN5511 P. fluorescens (3 genomes) PFL_6171 (str. Pf 5) P. putida (4 genomes) Pput_5267 (str. F1) Pseudomonas syringae(3 genomes) Psyr_5072 (pv. Syringae B278a)
212 Table B 11. Genomes containing subgroup 12. Organism CobW Locus Tag first gene in operon (if operon is predicted to be regulated by riboswitch) A. tumefaciens str. C58 Atu2805 Atu2806* B. japonicum USDA 110 blr3261 blr3262* Bradyrhizobium sp. BTAi1 BBta_3143 BBta_3141 Brucella abortus biovar 1 str. 9941 BruAb1_1308 BruAb1_1311 Bruc ella canis ATCC 23365 BCAN_A1330 BCAN_A1333 Brucella melitensis 16M BMEI0694 BMEI0691* B. suis 1330 BR1307 BR1310 Dinoroseobacter shibae DFL 12 Dshi_0160 Dshi_0162 Granulibacter bethesdensis GbCGDNIH1_0657 GbCGDNIH1_0657 Loktanella vestfoldensis SKA53 SKA53_10074 SKA53_10069 Mesorhizobium loti MAFF303099 mlr1375 mlr1374* Methylobacterium sp. 4 46 M446_2436 M446_2433 Novosphingobium aromaticivorans Saro_0343 Saro_0343 Oceanicola batsensis HTCC2597 OB2597_10309 OB2597_10304 Paracoccus denitrificans PD1222 Pden_2531 Pden_2530 Rhizobium leguminosarum RL2831 RL2832 Rhodobacter sphaeroides 2.4.1 RSP_2828 RSP_2829* Rhodobacterales bacterium RB2654_11398 RB2654_11383 Rhodopseudomonas palustris RPE_2235 RPE_2233 Roseobacter denitrificans OCh 114 RD1_3828 RD1_3829 Roseobacter sp. MED193 MED193_19609 MED193_19614 Roseovarius nubinhibens ISM ISM_12605 ISM_12600 Roseovarius sp. 217 ROS217_08014 ROS217_07994 Silicibacter pomeroyi DSS 3 SPO2862 SPO2861 Silicibacter sp. TM1040 TM1040_2209 TM1040_2208 Si norhizobium meliloti 1021 SMc04304 SMc04305* Sulfitobacter sp. EE 36 EE36_05363 EE36_05358 Sulfitobacter sp. NAS 14.1 NAS141_10286 NAS141_10281 Burkholderia ambifaria AMMD Bamb_1556 Bamb_1556 B. cepacia R18194 Bcep18194_A4805 Bcep18194_A4805 Burkho lderia cenocepacia Bcen_1176 Bcen_1176 Burkholderia dolosa AUO158 BDAG_01599 BDAG_01600 Burkholderia multivorans Bmul_1583 Bmul_1584 B. cepacia R1808 Bucepa02000286 Bucepa02000285 Burkholderia vietnamiensis Bcep1808_1601 Bcep1808_1600 Burkholderia fu ngorum Bcep1785 Bcep1785 Burkholderia mallei 10399 BMA10399_E0832 BMA10399_E0831 Burkholderia xenovorans LB400 Bxe_B1647 Bxe_B1647 B. pseudomallei 1655 BURPS1655_A1847 BURPS1655_A1848* Chromobacterium violaceum CV1561 CV1573 Delftia acidovorans SPH 1 Daci_5747 Daci_5752 Ralstonia solanacearum GMI1000 RSp0617 RSp0628*
213 Table B 1 1. Continued. Organism CobW Locus Tag first gene in operon (if operon is predicted to be regulated by riboswitch) P. aeruginosa PAO1 PA2945 PA2945* Pseudomonas mendocina ymp Pmen_4587 Pmen_4587 P. entomophila L48 PSEEN2432 PSEEN2432 P. fluorescens PfO 1 Pfl_3099 Pfl_3099* P. putida F1 Pput_2268 Pput_2268* Pseudomonas syringae PSPPH_2224 PSPPH_2224* Cyanothece sp. ATCC 51142 cce_1187 Synechococcus elongatus syc0712_d Synechocystis sp. PCC 6803 slr0502 Thermosynechococcus elongatus tll1624 Gloeobacter violaceus PCC 7421 gvip013 A. variabilis ATCC 29413 Ava_3407 Nostoc punctiforme PCC 73102 Npun_F0650 Trichodesmium erythraeum Tery_1027 Magnetospirillum gryphiswaldense MGR_0093 Magnetospirillum magneticum amb4426 Rhodospirillum rubrum Rru_A0671 Table B 12 Genomes containing subgroup 13 gene cluster. Genome Locus_tag M. maripaludis S2 MMP0833 M. ace tivorans C2A MA4382 MA4381 M. barkeri str. fusaro Mbar_A1056 M. mazei Go1 MM1072 D. hafniense DCB 2 Dhaf_0359 D. hafniense DCB 2 Dhaf_3562 Clostridium botulinum CLB_1516 Syntrophomonas wolfei subsp. wolfei str. Goettingen Swol_0421
214 FeoBStaphylococcus epidermidis RP62A COG0523 TrxB ZnuA Crocosphaera watsonii WH 8501 FeoB COG0523 TrxB Cyanothece sp. ATCC 51142 FeoB COG0523 TrxB Staphylococcus aureus subsp. aureus N315 TrxB FeoB COG0523 Figure B 1 0 Genome context of subgroup 14 members. Subgroup 14 genes colocalize with genes encoding zinc ABC transport periplasmic binding protein (ZnuA), thioredoxin reductase (TrxB), and iron transport protein (FeoB). Table B 13 Genomes containing subgroup 14 gene cluster. Genome Locus_tag S. aureus (13 genomes) SAOUHSC_02901 (subsp. aureus NCTC 8325) Staphylococcus epidermidis (2 genomes) SE0188 ( ATCC 12228) Crocosphaera watsonii WH 8501 CwatDRAFT_5580 Cyanothece sp. ATCC 51142 Cce_4848
215 Staphylococcus aureus subsp. aureus Mu50 COG0523 4989 CitT PhrB CydD CydCStaphylococcus saprophyticus s ubsp. saprophyticus ATCC 15305 COG0523 4989 CydD CydCStaphylococcus epidermidis RP62A COG0523 CitT PhrB CydD CydC Bacillus anthracis COG0523 4989 Bacillus cereus ATCC 14579 and Bacillus thuringiensis serovar konkukian str. 97 27 COG0523 4989 ZnuA Figure B 1 1 Genome context of subgroup 15 members. Subgroup 15 genes colocalize with genes encoding a putative oxidoreductase COG4989 (4989), ABC type transport s ystem involved in cytochrome bd biosynthesis (CydD and CydC), sodium/di and tricarboxylate cotransporter (CitT), and deoxyribodipyrimidine photolyase (PhrB).
216 Table B 14 Genomes containing subgroup 15 gene cluster. Genome Locus_tag Bacillus anthracis (8 genomes) BA2021 (str. Ames) Bacillus cereus (5 genomes) BCE2101 (str. ATCC 10987) Bacillus thuringiensis (3 genomes) BT9727_1849 (serovar konkukian str. 9727) Bacillus weihenstephanensis KBAB4 BcerKBAB4_1883 Staphylococcus haemolyticus JCSC1435 SH2 206 S. aureus subsp. aureus Mu50 SAV0687 Staphylococcus saprophyticus subsp. saprophyticus ATCC 15305 SSP2031 Staphylococcus epidermidis RP62A SERP0344
217 APPENDIX C COG0523 DISTANCE TREE Figure C 1. Phylogenetic reconstruction of selected COG0523 proteins. Each designated subgroup is shaded and labeled. The branches representing proteins encoded by putative Zur regulated genes are marked with a black square. The branches representing C. reinhardtii COG0523 homologs encoded by the genes induced by zi nc deficiency are marked with a green square. Branches representing the Pseudomonas paralogs discussed in the text are labeled. Protein IDs for each branch can be found in Appendix D, Table D 3.
218 APPENDIX D PROTEIN IDENTIFIERS AND GENE ABBREVIAITONS Table D 1. Proteins used in COG0523 amino acid conservation analysis. Protein Internal identifier for SEED database (unless otherwise specified) YciC fig|224308.1.peg.337 ACIAD1741 fig|62977.3.peg.1665 Bcen_4084 fig|331271.3.peg.1276 nhr3 CAQ16890 (GenBank) PMT9312_0491 fig|74546.3.peg.853 SYNW1795 fig|84588.1.peg.1788 Bcep18194_B0634 fig|269483.3.peg.168 Smb20133 fig|266834.1.peg.4768 bll7768 fig|224911.1.peg.7768 all1751 fig|103690.1.peg.2058 RL4362 fig|216596.1.peg.4497 BR2035 fig|204722.1.peg.1967 BB3253 fig|257310.1.peg.3236 PFLU1078 fig|216595.1.peg.3357 BAV0145 fig|521.1.peg.1238 Rmet_0127 fig|266264.4.peg.532 Sm4294 fig|615.1.peg.4294 PMI0144 fig|584.1.peg.507 SO1502 fig|211586.1.peg.1391 Sb2276 fig|12149.1.peg.2276 PP535 9 fig|160488.1.peg.5290 PFLU6083 fig|216595.1.peg.113 PMT9312_0786 fig|74546.3.peg.895 SYNW1127 fig|84588.1.peg.1122 BR1307 fig|204722.1.peg.1267 PP3508 fig|160488.1.peg.3475 MA0856 fig|188937.1.peg.841 Desu2034 fig|49338.1.peg.1829 BT9727_176 5 fig|281309.1.peg.1737 SERP2386 fig|176279.3.peg.2036 SSP2031 fig|342451.4.peg.2183 BLi00765 fig|279010.5.peg.1115 BLi01933 fig|279010.5.peg.2636 BP3084 fig|257313.1.peg.2727 SPA0639 fig|295319.3.peg.2592 Pro0851 fig|167539.1.peg.849
219 Table D 2. Gene abbreviations for Figure 32. Subgroup Abbreviations Functional Roles 1 folE2 GTP cyclohydrolase I (EC 188.8.131.52) type 2 1 DUF1826 protein of unknown function 1 zur zinc uptake regulation protein 1 dksA2 C4 type zinc finger DksA/TraR family pr otein 2 nhaB Fe type nitrile hydratase beta subunit 2 nhaA Fe type nitrile hydratase alpha subunit 2 amdA amidase 3 futB Ferric iron ABC transporter. permease protein 3 pcd Pterin 4 alpha carbinolamine dehydratase 3 0432 COG0432, protein of unknown function, UPF0047 3 taqCP carboxypeptidase Taq (M32) metallopeptidase 3 ppa inorganic pyrophosphatase 4 atzB hydroxyatrazine ethylaminohydrolase 4 uraA xanthine/uracil permease 4 ubiX 3 polyprenyl 4 hydroxybenzoate carboxy lyase 4 ubiD 3 polyprenyl 4 hydroxybenzoate carboxy lyase 4 mh metal dependent hydrolase 8 hslU ATPdependent hsl protease ATP binding subunit 8 hslV ATP dependent protease 8 dksA C4 type zinc finger DksA/TraR family protein 8 zur zinc uptake regulation protein 8 znuC Zi nc ABC transporter, ATP binding protein 8 znuB Zinc ABC transporter, inner membrane permease protein 8 znuA Zinc ABC transporter, periplasmic binding protein 9 yjiX protein of unknown function 9 cstA2 carbon starvation protein paralog 10 oppD puta tive ATP dependent oligopeptide permease component 10 oppC putative ATP dependent oligopeptide permease component 10 oppB putative ATP dependent oligopeptide permease component 10 oppA putative ATP dependent oligopeptide permease component 10 rtn putat ive EAL domain containing lipoprotein 10 spr predicted peptidase 10 lpxT undecaprenyl pyrophosphate phosphatase 11 DUF1826 protein of unknown function 12 prp pentapeptide repeat protein 12 upp uracil phosphoribosyltransferase 12 ilvD dihydroxyacid d ehydratase/phopshogluconate dehydratase 13 cbiH Cobalt precorrin6x reductase 13 cbiL Cobalt precorrin 3b C17 methyltransferase 13 cbiC cobalt precorrin8x methylmutase 13 cobG Precorrin 3B synthase 13 cobN cobaltochelatase subunit 13 cobU Adenosylco binamide phosphate guanylyltransferase 13 pduO Cob(I)alamin adenosyltransferase 13 cbiP Cobyric acid synthase 14 ramA iron sulfur protein that mediates the ATP dependent reductive activation of Co(II) corrinoid to the Co(I) state 14 mtbA Methylcobalami n:coenzyme M methyltransferase, methylaminiespecific 14 mtaA Methylcobalamin:coenzyme M methyltransferase, methanol specific 14 mtaC corrinoidbinding protein 15 4989 putative oxidoreductase COG4989 16 znuA Zinc ABC transporter, periplasmic binding pr otein
220 Table D 3. Proteins used in COG0523 phylogenetic tree reconstruction. The proteins are listed in order that they appear in the COG0523 distance tree found in Appendix C starting with RV0106 and moving clockwise around the tree. Protein Internal identifier for SEED database (unless otherwise specified) Protein Internal identifier for SEED database (unless otherwise specified) RV0106 (outgroup) fig|83332.1.peg.106 101629 C. reinhardtii draft genome v. 3.0 520982 C. reinhardtii draft genome v. 4.0 At1g26520 fig|3702.1.peg.2968 123019 C. reinhardtii draft genome v. 3.0 YNR029c fig|4932.3.peg.5506 73360 C. reinhardtii draft genome v. 3.0 Taeniopygia guttata XP_002196540 (Genbank) 106402 C. reinhardtii draft genome v. 3.0 Rattus norvegicus fig|10116.3.peg.3919 Rmet_0125 fig|266264.4.peg.530 CBWD1 fig|9606.3.peg.30962 Reut_A0161 fig|264198.3.peg.673 CBWD2 fig|9606.3.peg.18530 RSc0045 fig|267608.1.peg.45 all1751 fig|103690.1.peg.2058 BURPS1710b_0218 fig|320372.3.peg.2822 SYNW2482 fig |84588.1.peg.2473 BCAL3529 fig|216591.1.peg.525 SMc03799 fig|266834.1.peg.4476 Bucepa02004096 fig|269482.1.peg.3952 CC0321 fig|190650.1.peg.320 XCC0257 fig|190485.1.peg.257 bll7768 fig|224911.1.peg.7768 XAC0276 fig|190486.1.peg.276 RPA0861 fig|2 58594.1.peg.858 XF1830 fig|160492.1.peg.1823 NB311A_16784 fig|314253.3.peg.2776 BH1790 fig|272558.1.peg.1790 Nham_3425 fig|323097.3.peg.3530 BT9727_1611 fig|281309.1.peg.1582 BH12980 fig|283166.1.peg.1162 BCE1836 fig|222523.1.peg.1825 BRA0987 fig| 204722.1.peg.3060 BLO5309 fig|279010.5.peg.800 Meso_2842 fig|266779.1.peg.1374 ABC4020 fig|66692.3.peg.3995 SMc02978 fig|266834.1.peg.4164 OB3429 fig|221109.1.peg.3433 RHE_CH03625 ABC92380(Genbank) BLO2348 fig|279010.5.peg.1115 Mfla_1230 fig|26507 2.7.peg.1253 YciC fig|224308.1.peg.337 Rru_A1611 fig|1085.1.peg.2756 SH0144 fig|279808.3.peg.157 Meso_3058 fig|266779.1.peg.225 SA0410 fig|158879.1.peg.422 BR2035 fig|204722.1.peg.1967 SERP0080 fig|176279.3.peg.352 mll3580 fig|266835.1.peg.2760 FTT1000c fig|177416.3.peg.1070 SMc00684 fig|266834.1.peg.3981 BMEII0179 fig|224914.1.peg.2238 RL4362 fig|216596.1.peg.4497 Atu3181 fig|176299.3.peg.3142 BB3253 fig|257310.1.peg.3236 RHE_CH02713 ABC91484 (Genbank) BAV2401 fig|521.1.peg.71 RL3179 fig|216596.1.peg.3284 pRL120138 fig|216596.1.peg.5848 GOX2212 fig|290633.1.peg.2148 PSPPH_3929 fig|264730.3.peg.4199
221 Table D 3. Continued. Protein Internal identifier for SEED database (unless otherwise specified) Protein Internal identifier for SEE D database (unless otherwise specified) TM1040_0080 fig|292414.1.peg.1132 PFLU1078 fig|216595.1.peg.3357 ROS217_16055 fig|314264.3.peg.2684 PFL_1367 fig|220664.3.peg.3069 ISM_00325 fig|89187.3.peg.72 fig|615.1.peg.1489 fig|615.1.peg.1489 Mfla_1231 fig|265072.7.peg.1254 BAV0145 fig|521.1.peg.1238 PP3323 fig|160488.1.peg.3296 BURPS1710b_0389 fig|320372.3.peg.3067 LV196 fig|573.1.peg.161 Bcep18194_A6439 fig|269483.3.peg.7256 Rmet_1098 fig|266264.4.peg.1503 RSc0047 fig|267608.1.peg.47 Bcen_30 34 fig|331271.3.peg.590 Reut_A0163 fig|264198.3.peg.675 Bcep18194_B0316 fig|269483.3.peg.318 Rmet_0127 fig|266264.4.peg.532 ACIAD1741 fig|62977.3.peg.1665 PA4604 fig|208964.1.peg.4604 ABO_1679 fig|393595.12.peg.1684 PFLU5331 fig|216595.1.peg.7492 fig|615.1.peg.843 fig|615.1.peg.843 PMI0144 fig|584.1.peg.507 Csal_0192 fig|290398.4.peg.672 fig|615.1.peg.4294 fig|615.1.peg.4294 V12G01_06993 fig|314288.3.peg.2404 fig|54388.1.peg.219 fig|54388.1.peg.219 Mmwyl1_1446 fig|400668.6.peg.1471 STM4530 fig|99287.1.peg.4358 PatlDRAFT_1639 fig|342610.3.peg.1415 KPN_04774 fig|573.2.peg.3898 MED297_11295 fig|314283.3.peg.895 CV3067 fig|243365.1.peg.3067 HCH_02800 fig|349521.5.peg.2494 SO1502 fig|211586.1.peg.1391 PA5535 fig|208964.1.peg.5532 Shew_2 776 fig|323850.3.peg.814 Avin1667 fig|354.1.peg.3168 HCH_01308 fig|349521.5.peg.1191 Psyr_5075 fig|205918.4.peg.275 fig|198214.1.peg.2112 fig|198214.1.peg.2112 PFL_6173 fig|220664.3.peg.101 fig|12149.1.peg.2276 fig|12149.1.peg.2276 PP5361 fig|1 60488.1.peg.5292 YPTB1311 fig|273123.1.peg.1426 PSEEN5513 fig|384676.6.peg.4780 VV20385 fig|216895.1.peg.3313 nhr BAD98534 (Genbank) VF2370 fig|312309.3.peg.2370 P47K P31521 (Genbank) MED297_11310 fig|314283.3.peg.898 ACIAD1614 fig|62977.3.peg.143 1 V12G01_06973 fig|314288.3.peg.2400 Bcen_4084 fig|331271.3.peg.1276 PA5532 fig|208964.1.peg.5529 Bamb_6542 fig|339670.3.peg.5927 PSPPH_5154 fig|264730.3.peg.5102 RHA1_ro00362 ABG92198 (Genbank) PFLU6083 fig|216595.1.peg.113 nhr3 CAQ16890 (Genbank) PFL_6171 fig|220664.3.peg.99 nhr3 BAC99082 (Genbank) PSEEN5511 fig|384676.6.peg.4778
222 Table D 3. Continued. Protein Internal identifier for SEED database (unless otherwise specified) Protein Internal identifier for SEED database (unless otherwise specified) nha3 CAG29801 (Genbank) PP5359 fig|160488.1.peg.5290 nha3 BAA36599 (Genbank) PMT9312_0786 fig|74546.3.peg.895 ORF1188 BAA06274 (Genbank) Syncc9902_1218 fig|316279.3.peg.2255 V12G01_06988 fig|314288.3.peg.2403 Syncc9605_1264 fig|110662.3.peg.2 33 PMT9312_0491 fig|74546.3.peg.853 SYNW1127 fig|84588.1.peg.1122 Ava_3717 fig|240292.3.peg.4870 PMT0556 fig|74547.1.peg.556 Pro0489 fig|167539.1.peg.488 Pro0851 fig|167539.1.peg.849 PMT1284 fig|74547.1.peg.1279 PP3508 fig|160488.1.peg.3475 Syncc9 902_1690 fig|316279.3.peg.2158 BMA1171 fig|243160.4.peg.121 SYNW1795 fig|84588.1.peg.1788 BURPS1655_A1847 fig|331109.3.peg.1603 Syncc9605_0672 fig|110662.3.peg.1837 Bcep1808_1601 fig|269482.1.peg.277 Tery_4617 fig|203124.1.peg.4333 BR1307 fig|204722. 1.peg.1267 Ava_1948 fig|240292.3.peg.3028 RL2831 fig|216596.1.peg.2928 BCAM2270 fig|216591.1.peg.4280 SMc04304 fig|266834.1.peg.3252 Bcep18194_B0634 fig|269483.3.peg.168 blr3261 fig|224911.1.peg.3262 Bmul_3607 fig|395019.3.peg.3725 143868 C. reinha rdtii draft genome v. 3.0 SMb20133 fig|266834.1.peg.4768 Desu2034 fig|49338.1.peg.1829 Reut_A3078 fig|264198.3.peg.2234 Desu0949 fig|49338.1.peg.2656 EF3204 fig|226185.1.peg.2991 MM1072 fig|192952.1.peg.1072 OB3433 fig|221109.1.peg.3437 Meth3844 fig|2208.1.peg.3706 106748 C. reinhardtii draft genome v. 3.0 MA0856 fig|188937.1.peg.841 At1G80480 fig|3702.1.peg.7636 SERP2386 fig|176279.3.peg.2036 At1G15730 fig|3702.1.peg.1879 BT9727_1765 fig|281309.1.peg.1737 195946 C. reinhardtii draft geno me v. 3.0 SAV0687 fig|158878.1.peg.687 117458 C. reinhardtii draft genome v. 3.0 SERP0344 fig|176279.3.peg.657 122261 C. reinhardtii draft genome v. 3.0 SSP2031 fig|342451.4.peg.2183
223 APPENDIX E ANALYSIS OF PUTATIVELY ZUR REGULATED PARALOGS AmiA AmiA catalyzes amide bond cleavage between the lactyl group of muramic acid and the amino group of l alanine (Lupoli et al. 2009) In E. coli the three paralogs AmiA, AmiB, and AmiC are responsible for splitting the murein septum during cell division (Heidrich et al. 2001) The amiA paralogs found in Zur regulons share significant sequence similarity w ith amiA amiB and amiC including presence of the N terminal domain responsible for targeting the protein to the periplasm and localization at the septal ring (Figure E 1A ) (de Souza et al. 2008) A crystal structure of the AmiA h omolog CwlV from Paenibacillus polymyxa is available (PDB: 1JWQ) (Ishikawa et al. 1999) The catalytic zinc ion is chelated by two His and one Glu residues. These residues are conserved in t he AmiA paralogs whose corresponding genes are putati vely regulated by Zur (Figure E 1B ). HisI HisI catalyzes the third step in histidine biosynthesis, hydrolysis of the phosphoribosyl AMP adenine ring (D'Ordine et al. 1999) The proteins of the hisI par alogs found in Zur regulons of pro t eobacteria are closely related to the HisI homologs from proteobacteria (Figure E 2A ). T he only crystal structure available for a HisI homolog is from Methanobacterium thermoautotrophicum The crystallization methods included saturation with cadmium so the zinc binding residues were deduced from the cadmium binding residues. These residues are conserved in the His I paralogs analyzed (Figure E 2B ).
224 CysRS and ThrRS CysRS and ThrRS are aminoacyl tRNA synthetases for cysteine and threonine, respectively. For both proteins, the zinc ion is essential in amino acid discrimination (Zhang et al. 2003b, Sankaranarayanan et al. 2000) CysRS proteins whose genes belong to the putative Zur regulon in C. metallidurans and B. pseudomallei spp. have highest similarity to the CysRS orthologs from proteobacteria (Fi gure E 3A). The zinc binding residues observed in the crystal structure of E. coli CysRS (PDB: 1LI5) are conserved in these paralogs (Figure E 3B ). thrS genes are found in the putative Zur regulons of cynobacterial and proteobacterial genomes (Figure E 4A ). The zinc binding residues observed in the E. coli ThrRS (PDB: 1QF6) are also conserved in the ThrRS paralogs whose genes are putatively regulated bv Zur (Figure E 4 ) FolE Several cyanobacterial genomes, Cyanothece sp. ATCC 51142, Cyanothece sp. PCC 8 801 Microcystis aeruginosa, Nostoc sp. PCC 7120 Synechococcus sp. PCC 7002, Trichod esmium erythraeum, and A. variabilis contain at least two folE genes, which are proposed to encode GTP cyclohydrolase I Type A. One of these folE genes is predicted to be regulation by Zur. However, the zinc binding ligands observed in the FolE protein from H. sapiens are conserved in these proteins (Figure E 5).
225 A B Figure E 1. Phylogenetic and sequence analysis of the AmiA paralogs. A) Neighbor joining tree of AmiA protein sequences Red indicates that the corresponding gene is putatively regulated by Zur. B) P rotein sequence alignment of AmiA proteins whose corresponding genes are putatively regulated by Zur with CwlV from P. polymyxa The metal binding residues are marked with a star. The N terminal periplasmic targeting domain is marked with a green box. Secondary structural elements were derived from the crystal structure of P. polymyxa CwlV (PDB: 1JWQ ).
226 0.25 A B Figure E 2. Seque nce and phylogenetic analysis of HisI paralogs. A) Neighbor joining tree of HisI protein sequences Red indicates that the corresponding gene is putatively regulated by Zur. The class of proteobacteria to which the genome belongs in shown on the right. B) P rotein sequence alignment of HisI proteins whose corresponding genes are putatively regulated by Zur with HisI from M. thermoautotrophicum The metal binding residues are marked with a star. Secondary structural elements were derived from the crystal structure of M. thermoautotrophicum HisI (PDB: 1ZPS ).
227 A B Figure E 3. Sequence and phylogenetic analysis of CysRS paralogs. A) Neighbor joining tree of CysRS protein sequences Red indicates that the corresponding gene is putatively regulated by Zur. The class of proteobacteria to which the genome belongs in shown on the right. B) P rotein sequence alignment of CysRSproteins whose corresponding genes are putatively regulated by Zur with CysRS from E. coli. The metal binding residues are marked with a star. Secondary structural elements were derived from the crystal structure of E. coli CysRS (PDB: 1LI5 ).
228 A B Figure E 4. Sequence and phylogenetic analysis of ThrRS paralogs. A) Neighbor joining tree of ThrRS protein sequences Red indicates that the corresponding gene is putatively regulated by Zur. B) P rotein sequence alignment of ThrRS proteins whose corresponding genes are putatively regulated by Zur with ThrRS from E. coli The metal binding residues are marked with a star. Secondary structural elements were derived from the crystal structure of E. coli ThrRS (PDB:1EVK ).
229 Figure E 5. Amino acid sequence comparison between the FolE from H. sapiens and cyanobacterial genomes. The cyanobacterial proteins are predicted to be e ncoded by Zur regulated genes. The zinc binding ligands observed in the crystal structure of human FolE (PDB: 1FB1) are pointedout with a star.
230 Figure E 6. Amino acid sequence alignment between the class carbonic anhydrase s. Alignment between Cam from M. thermophila and the carbonic anhydrase proteins, whose genes are found in the putative Zur regulons of Xyella fastidiosa, A. vinelnadii, P. aeruginosa, P. fluorescens, B. cenocepacia and C. metall idurans Secondary structural elements were derived from the crystal structure of M thermophila Cam (PDB: 1QRE).
231 Figure E 7. Protein sequence alignment HemB proteins. Alignment of the P. putida HemB2 with the Mg(II) dependent HemB from P. aeruginosa and the Zn(II) dependent HemB from E. coli. Secondary structural elements were derived from the crystal structure of P. aeruginosa HemB (PDB: 1B4K). The respective metal binding residue are highlighted: blue boxes outline the Mg binding residues observed in the crystal structure of P. aeruginosa HemB (PDB: 1B4K); green boxes outline the Znbinding residues observed in the crystal structure of E. coli HemB (PDB: 1I8J).
232 APPENDIX F STRAINS, PLASMIDS AND OLIGONUCLEOTIDES Table F 1. Strains used in Chapter 3. Strain Genotype Source E. coli K12 MG1655 F, rph1 E. coli Genetic Stock Center E. coli BW25113 JW2161 yeiR::kan (Baba et al. 2006) E. coli GR352 znuABC ::cam (Grass et al. 2002) VDC4286 MG1655 yeiR::kan This study VDC4311 MG1655 yeiR This study VDC4320 VDC4311 pBAD24 This study VDC4325 VDC4311 pCH011 This st udy VDC4352 VDC4311 pCH090 This study VDC4358 MG1655 pBAD24 This study VDC4361 VDC4311 znuABC ::cam This study VDC4683 VDC4311 pCH141 This study VDC4684 VDC4311 pCH137 This study VDC4685 VDC4311 pCH138 This study VDC4686 VDC4311 pCH145 This study V DC4705 VDC4361 pBAD24 This study VDC4706 VDC4361 pCH011 This study VDC4713 MG1655 znuABC ::cam This study VDC4716 VDC4713 pBAD24 This study VDC4721 VDC4311 pCH150 This study VDC4732 VDC4311 pCH151 This study
233 Table F 2. Strains used in Chapter 4. S train Genotype Source E. coli K12 MG1655 F, rph1 E. coli K12 MG1655 P. aeruginosa PAO1 Wild type strain P. aeruginosa type strain (ATCC 33351) VDC4098 MG1655 dksA:: Tet R This study VDC4133 VDC4098 pBAD24 This study VDC4241 VDC4098 pCH078 This stud y VDC4263 VDC4098 pCH080 This study VDC4614 VDC4098 pCH040 This study VDC4239 VDC4098 pCH071 This study VDC4240 VDC4098 pCH075 This study VDC4489 PAO1 PA4723 This study VDC4525 VDC4489 PA5536:: Gm R This study VDC4499 VDC4489 PA5499 This study VDC4510 VDC4499 PA5536:: Gm R This study VDC4607 PAO1 pHERD20T This study VDC4666 VDC4489 pHERD20T This study VDC4667 VDC4489 pCH115 This study VDC4610 VDC4525 pHERD20T This study VDC4611 VDC4525 pCH115 This study VDC4612 VDC4510 pHERD20T This study VDC4613 VDC4510 pCH115 This study VDC4640 PAO1 PA5499:: Gm R This study VDC4615 PAO1 PA5536 This study VDC4635 VDC4615 PA5498 :: Gm R This study VDC4650 PA5498 :: Gm R pHERD20T This study VDC4652 VDC4635 pHERD20T This study VDC4653 VDC4635 pCH115 This st udy
234 Table F 3. Plasmids used in Chapter 3. Plasmid Description Reference pBAD24 E. coli expression vector, AmpR (Guzman et al. 1995) pCH011 yeiR cloned into the Nco I/Xba I sites of pBAD24 This study pCH090 P roduct of YeiR C63A mutagenesis cloned into pBAD24 This study pCH137 Product of YeiR C65A mutagenesis cloned into pBAD24 This study pCH138 Product of YeiR C66A mutagenesis cloned into pBAD24 This study pCH140 Product of YeiR H207A mutagenesis cloned int o pBAD24 This study pCH141 Product of YeiR M64A mutagenesis cloned into pBAD24 This study pCH145 Product of YeiR H209A mutagenesis cloned into pBAD24 This study pCH150 Product of YeiR H207A H209A H211A mutagenesis cloned into pBAD24 This study pCH151 P roduct of YeiR H211A mutagenesis cloned into pBAD24 This study Table F 4. Plasmids used in Chapter 4. Plasmid Description Reference pBAD24 E. coli expression vector, AmpR (Guzman et al. 1995) pHERD20T P. aeruginosa shuttle vector, Amp R (Qiu et al. 2008) pCH078 PA4723 cloned into Nco I/ Xba I sites of pBAD24 This study pCH080 EC dksA cloned ineto Nco I/ Xba I sites of pBAD24 This study pCH040 PA5536 cloned into Nco I/Xba I sites of pBAD24 This study pCH071 Product of PA4723 C114T mutagenesis cloned into Nco I/ Xba I sites of pBAD24 This study pCH075 Product of PA4723 C135A mutagenesis cloned into Nco I/ Xba I sites of pBAD24 This study pCH115 PA5536 cloned into Nco I/Xba I sites of pHERD20T This study pCH103 pEX18Tc derivative carrying PA4723 deletion construct This study pCH107 pEX18Tc derivative carrying PA5536 deletion construct This study pCH108 pEX18Tc derivative carrying PA5499 deletion construct This study pCH131 pEX18T c derivative carrying PA5498 deletion construct This study
235 Table F 5. Oligonucleotides used in Chapter 3. Name Sequence (written 5 to 3) chkout yeiR outFor CATCGAACAAGCCTGCAAC chkout yeiR outRev ATCAATCGGCAACCAGAATCC chkin yeiRFor CGGTAGTCGCTAAACGAAGC chkin yeiRFor ACCGCACCAGTCTATGAACC chkout znu outFor GGCGATTTTGTCATCCAGTT chkout znu outRev AATTGTTGCTGGCGGTAATC chkin znu For ACATGCATCTTTGGCTTTCC chkinznuRev CTCGTTACCAACCTGCGTTT yeiRFor Nco I TAACCATGGCCACCAGGACCAACCT yeiRRev Xba I CGTCTAGATTACGCGGTAGTCGCTA A YeiRC63AFor GAGATCCCCGGCGGCGCCATGTGCTGCGTTAATGG YeiRC63ARev CCATTAACGCAGCACATGGCGCCGCCGGGGATCTC YeiRC65AFor GCGGCTGCATGGCCTGCGTTAATGG YeiRC65ARev CCATTAACGCAGGCCATGCAGCCGC YeiRC66AFor CGGCTGCATGTGCGCCGTTAATGGTTTAC YeiRC66ARev GTAAACCATTAACGGCGCACAT GCAGCCG
236 Table F 6. Oligonucleotides used in Chapter 4. Oligonucleotide Sequence (written 5 to 3) dksAFor Nco I CCATGGAAGAAGGGCAAAACCGT dksARev XbaI TCTAGATTAGCCAGCCATCTGTTTTTC PA4723For Nco I CCATGGCCACCAAAGCAAAACAACA PA4723Rev Xba I TCTAGATCAGGAGCCGAGT TGCTTCTC PA5536For Nco I TATATACCATGGCCGAACAGGAACTGCTTGCC PA5536Rev Xba I TATTTATCTAGATCAGTTGTGCCGCACGTG PA4723mutC114 CGACTCCACCGGCGTC PA4723mutC135 CATCGACGCGAAGACCC ExternalFor CGACTCACTATAGG ExternalRev GAATTCGCCCTTCCATGGCCACCAAAGC FRT/GmFor GAAGTTC CTATACTTTCTAGAGAATAGGAACTTCGGAATAG GAACTTCTTAGGTGGC GGTACTTGGGT FRT/GmRev GAAGTTCCTATTCCGAAGTTCCTATTCTCTAGAAAGTATAG GAACTTCAGCGGTGGTAACGGCGCA 5PA4723For EcoR I TTTTTGAATTCATGACATGGAAAGGCTCGAT 5PA4723RevFRT CTTCGGAATAGGAACTTCTTTGCTTTGGTGGACATGAA 3PA4723F orFRT AGAAAGTATAGGAACTTCAAATCCGCGAGAAGCAACT 3PA4723Rev Hind III TTTTTAAGCTTAGCAAGTGCAGGCGTAGG 5'PA5536For EcoR I TTTTTGAATTCCGTAGCGCGTATTGGTCTG 5'PA5536RevFRT CTTCGGAATAGGAACTTCAGCAGTTCCTGTTCGGTCAT 3'PA5536ForFRT AGAAAGTATAGGAACTTCCGGCACAACTGAAGAGGTTA 3 'PA5536Rev Hind III TTTTTAAGCTTGGTGGACTCAATCAGC AGGT 5'PA5499For EcoR I TTTTTGAATTCCCTCTTCCTCGAAATTGACG 5'PA5499RevFRT CTTCGGAATAGGAACTTCGTCTTGGGCGCAATCTTGTA 3'PA5499ForFRT AGAAAGTATAGGAACTTCGGACGCCTGATGGACAAC 3'PA5499Rev Hind III TTTTTAAGCTTATGAGGCGGTAGAGTT CAGC 5PA5498For EcoR I TTTTTGAATTCCTGATATCCGGCTGTTCCAG 5PA5498RevFRT CTTCGGAATAGGAACTTCGGCGGCACTCACATGAAAG 3PA5498ForFRT AGAAAGTATAGGAACTTCAAACCCGTGACTGATGGC 3PA5498Rev Hind III TTTTTAAGCTTACACGGTGCAGTTGATGGT chkECdksAFor CGATAGTGCGTGTTAAGGAG chkECdksARev CGTGATGGAACGGCTGTAAT chkoutPA4723For GAGATCCGGTGTCAGTTGGT chkoutPA4723Rev GCCAGTTGGTAGGCGTAGAG chkoutPA5536For GTATATGCCCTCTCCGAGCA chkoutPA5536Rev GGAGATCAGGTCGATCTTGC chkoutPA5499For TCGTGGAAGACGAAGAAAGG chkoutPA5499Rev GTGCTTGTGGACAGGAGTGA chkinPA5499For GGTGGTCCAT GGACAAGATTGCGCCCAAGA C chkinPA5499Rev GGTGGTCTGCAGTCAGGCGTCCTTCTGGTCCC chkoutPA5498For CGATCAGGGTGACGATCTG chkoutPA5498Rev AGGGTGCTGAACTCATAGCC chkinPA5498For GAGAACTTCCTGCCCAAGGT
237 Table F 6. Continued. Oligonucleotide Sequence (written 5 to 3) chkinPA5498Rev CCTCTTCCTCGAAATTGACG PA4723RTFor TCCACCAAAGCAAAACAACA PA4723RTRev TACGGTCGACCTCTTCCATC PA5536RTFor AAGCCCAGCAGGACTTCTTC PA5536RTRev TGTCGAGCAGCTTCTTCTCC PA5499For Nde I GGTGGTCATATGTACAAGATTGCGCCCA PA5499Rev Hind III G ATCAAGCTTTCAGGCGTCCTTCTGGTC Zur dksA2 EMSAFor /5Biosg/CAGGCAGTAAAGGCGGAGGA Zur dksA2 EMSARev CAGCAGGTCGCGGAAGAAGT PA5536EMSAZursiteFor TTGTGGTGTTAATTGTTATAGTATAACGTTTTAAATTTC CCA PA5536EMSAZursiteRev TGGGAAATTTAAAACGTTATACTATAACAATTAACACC ACAA PA4457EMSAFor CGGTCTGAGCGAAACCGGCCTTGGTCAGCCGTTCCT CATGCA PA4577EMSARev TGCATGAGGAACGGCTGACCAAGGCCGGTTTCGCTC AGACCG
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281 BIOGRAPHICAL SKETCH Crysten Elizabeth Blaby Haas was born October of 1983 in Gainesville, Florida. She received a Bachelor of Science in microbiology and cell science from the University of Florida in May of 2006. She worked as an undergraduate research assistant in the laboratory of Prof. James F. Preston on developing Paenibacillus JDR 2 and Bacillus subtilis for the conversion of plant biomass to fermentable substrates that can be used in the production of alternative fuels In January of 2007, she joined the laboratory of Dr. Val rie de Cr cy Lagard, whose expertise she drew upon to employ comparative genomics and construct hypothesis for testing gene function using genetics. She has presented work at several national and international conferences and received a fellowship to attend the 59th Meeting of Nobel Laureates in Germany. In 2010, she married Dr. Ian Blaby, with whom she will continue research in the laboratory of Prof. Sabeeha Merchant at the University of California, Los Angeles.