Aptamer-Based Affinity Methods for Mass Spectrometry


Material Information

Aptamer-Based Affinity Methods for Mass Spectrometry
Physical Description:
1 online resource (182 p.)
Gulbakan, Basri
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Committee Chair:
Tan, Weihong
Committee Members:
Polfer, Nicolas Camille
Wei, Wei (David)
Powell, David H
Gregory, Jesse F


Subjects / Keywords:
Chemistry -- Dissertations, Academic -- UF
Chemistry thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation


Capturing rare proteins and metabolites from complex biological mixtures is essential to understanding the key functions of biological systems. As such, the development of new techniques for their isolation and subsequent detection/identification by mass spectrometry (MS) is becoming increasingly more important. While identification of pure proteins and simple biological mixtures using MS has become a routine and relatively simple task utilization of this powerful tool in analyzing complex mixtures and real biological samples is still in its infancy. One approach to the analysis of complex biological samples employs chromatographic extraction and fractionation methods, before MS is performed. However, current separation methods suffer from numerous limitations, including time-consuming procedures, the difficulties involved in handling complex samples, and, especially, the lack of selective molecular isolation. Therefore, the next best option utilizes affinity reagents tethered on a substrate which, in turn, could be used as a sample treatment tool or as a substrate to obtain direct MS readouts. A major obstacle to this strategy is finding efficient and robust capturing agents for biomarker detection. Although antibodies have been the gold standard as capturing reagents, commercial antibodies do not exist for all proteins, and developing high- affinity and selective antibodies is very expensive and time-consuming. Moreover, since antibodies are proteins, they are very prone to irreversible degradation and cannot be easily modified. As an alternative to antibodies, aptamers provide the specificity lacking in many extraction matrixes. This thesis discusses the development of aptamer based MS platforms. We have developed four different platforms for this purpose. First, nanowell array surfaces were prepared and applied in MS. Second graphene oxide and graphene oxide-metal conjugates were prepared and modified with aptamers. Third a unique nanoflower shaped nanostructure was developed for MS and applied for the extraction of adenosine triphosphate (ATP) in cancer cells. Finally aptamer-based affinity mass spectrometry was applied for the biomarker discovery of liver cancer. All these results demonstrate the utility of the approach for analysis of small molecules and discovery of new biomarkers in real biological samples.
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility:
by Basri Gulbakan.
Thesis (Ph.D.)--University of Florida, 2012.
Adviser: Tan, Weihong.
Electronic Access:

Record Information

Source Institution:
Rights Management:
Applicable rights reserved.
lcc - LD1780 2012
System ID:

This item is only available as the following downloads:

Full Text




2 2012 Basri Gulbakan


3 To my lovely family


4 ACKNOWLEDGMENTS This work would not have been possible without the guidance and encouragement I received from my academic advisors, Dr. Weihong Tan and Dr. D avid H. Powell. I got great experience in professional aspects during my doctoral studies and grown as a better scientist I would like to extend my thanks to Dr. Nick Polfer, Dr.David Wei and Dr.Jess e F. Gregory for their assistance and for spending their valuable time serving on my committee. I also want to thank the members of the Tan group especially Ismail, Ibrahim, Emir Judy, Mingx u, Sena, Tahir, Parag and Kwame and to Powell group especially Julia, Soledad and Noelle for their friendship and helpful a dvice s The help from the ICBR proteomics core lab director Dr. Sixue Chen and the scientific manager of the core lab Carolyn Diaz is also greatly appreciated. I cannot end without thanking my family for giving me the strength and the opportunity to achiev e one of the most important dreams in my life


5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ .......... 9 ABSTRACT ................................ ................................ ................................ ................... 13 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 15 Biomarker Discovery ................................ ................................ ............................... 15 Protein Biomarkers ................................ ................................ ........................... 16 P4 Medicine ................................ ................................ ................................ ...... 18 Methods for Protein Biomarker Discovery ................................ ............................... 19 Mass Spectrometry Based Protein Biomarker Discovery ................................ 19 Array Based Protein Biomark er Discovery ................................ ....................... 23 Dynamic Range Problem ................................ ................................ ........................ 24 Affinity Guided Approaches for Mass Spectrometry ................................ ............... 28 Role of Nanotechnologies in Affinity Based MS Applications ................................ 30 Nanoporous Materials ................................ ................................ ...................... 31 Nanoparticle s as Substrates for MS ................................ ................................ 32 Carbon Based Materials and Graphene ................................ ........................... 34 Aptamers ................................ ................................ ................................ ................ 35 Aptamers versus Antibodies ................................ ................................ ............. 35 Cell SELEX ................................ ................................ ................................ ...... 36 Cell SELEX Derived Aptamers for Biomarker Discovery ................................ .. 37 Overview of the Dissertation ................................ ................................ ................... 38 2 LASER DESORPTION IONIZATION ON SILICON NANOSTRUCTURES ............. 48 Experimental Methods ................................ ................................ ............................ 50 Materials ................................ ................................ ................................ ........... 50 Preparation of the Porous Alumina Mask ................................ ......................... 51 Fabrication of D esorption/Ionization on Silicon (DIOS) Surfaces ..................... 51 Characterization of Porous S urfaces ................................ ................................ 52 Synthesis of DNA Aptamers ................................ ................................ ............. 52 Slide Scanning and Data Analysis ................................ ................................ .... 53 Formation of Fluorous Derivatized Glass Slides ................................ .............. 53 Formation of Fluorous Based Aptamer Arrays on Glass Slides ....................... 53 NIMS Surface Preparation ................................ ................................ ................ 54 Mass Spectrometry ................................ ................................ .......................... 54 Results and Discussion ................................ ................................ ........................... 55


6 Characterization of the Alumina Mask ................................ .............................. 55 Fabrication and Morphology of Porous Silicon Substrates ............................... 55 Mass Spectrometry Analyses ................................ ................................ ........... 56 Application of the Nanowell Arrays for Complex Biological Mixture Analysis ... 59 Unifying NIMS and Aptamer Assisted Capturing ................................ .............. 59 3 A DUAL PLATFORM FOR SELECTIVE ANALYTE ENRICHMENT AND IONIZATION IN MASS SPECTROMETRY USING APTAMER CONJUGATED GRAPHENE OXIDE ................................ ................................ ................................ 84 Experimental ................................ ................................ ................................ ........... 85 Mass Spectrometry ................................ ................................ .......................... 85 Transmission Electron Microscopy ................................ ................................ ... 86 PEGylation of Graphene Oxide ................................ ................................ ........ 86 Aptamer Synthesis ................................ ................................ ........................... 86 Aptamer Conjugation to PEGylated Graphene Oxide ................................ ...... 87 Aptamer Assist ed Target Extraction ................................ ................................ 87 Synthesis of Au, Cu, Pt, and Au/Cu/Pt Alloy and CdTe Derivatives of GO ....... 88 Au GO synthesis ................................ ................................ ........................ 88 Cu GO and Pt GO synthesis ................................ ................................ ...... 89 Au/Cu/Pt alloy GO ................................ ................................ .................... 89 CdTe GO synthesis ................................ ................................ .................. 89 Synthesis of Benzylpyridinium Salt (BP) and SY Experiments ......................... 89 LDI MS Analysis of Proteins on CdTe GO ................................ ....................... 90 Results and D iscussion ................................ ................................ ........................... 90 Testing GO as M atrix for LDI ................................ ................................ ............ 90 Characterization of Aptamer Modi fied GO ................................ ........................ 90 Aptamer Assisted LDI on GO ................................ ................................ ........... 91 Formation of Au, Cu, Pt, and Au/Cu/Pt Alloy and CdTe on GO ........................ 93 Survival Yield Calculations ................................ ................................ ............... 94 Analysis of Proteins Using CdTe GO ................................ ............................... 95 4 HYBRID NANOFLOWERS FOR MASS SPECTROMETRY ................................ 113 Experimental Section ................................ ................................ ............................ 115 Chemicals ................................ ................................ ................................ ....... 115 Synthesis of Hybrid Nanoparticles ................................ ................................ .. 115 Au@MnO nanoflowers ................................ ................................ ............. 115 Au@Fe 3 O 4 nanoflowers ................................ ................................ ........... 115 Au Fe 3 O 4 dimer ................................ ................................ ........................ 116 Fe 3 O 4 @Au core shell ................................ ................................ ............... 116 Transfer of Au@MnO FNPs into Aqueous Phase ................................ .......... 116 Characterization ................................ ................................ ............................. 117 Synthesis of Aptamers ................................ ................................ ................... 118 Functionalization of Au@MnO FNP s ................................ .............................. 118 Cell Culture ................................ ................................ ................................ ..... 119 Mass Spectrometry ................................ ................................ ........................ 119


7 Results and Discuss ion ................................ ................................ ......................... 120 Survival Yield Calculation on Hybrid Nanoparticles ................................ ........ 120 Testing Au@MnO FNPs as a Substrate for Ionization ................................ ... 122 Modification of Au@MnO FNPs with Aptamers ................................ .............. 123 Internalization of Aptamer Modified Au@MnO FNPs ................................ ..... 124 Extraction of ATP from Cancer Cells Using Aptamer C onjugated Au@Mn O 125 5 BIOMARKER DISCOVERY OF HEPATOCELLULAR CARCINOMA USING CELL SPECIFIC APTAMER PROBES AND MASS SPE CTROMETRY ............... 144 Experimental ................................ ................................ ................................ ......... 148 Cell Line ................................ ................................ ................................ ......... 148 Synthesis of Aptame rs ................................ ................................ ................... 149 Biomarker Identification ................................ ................................ .................. 149 Protein Identification by Nano LC ESI MS ................................ ...................... 150 Data Analysis ................................ ................................ ................................ 151 Results and Discussion ................................ ................................ ......................... 151 6 CONCLUDING REMARKS AND FUTURE WORK ................................ ............... 167 LIST OF REFERENCES ................................ ................................ ............................. 169 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 182


8 LIST OF TABLES Table page 2 1 Name of the carnitines analyzed and their respective molecular weights ........... 83


9 LIST OF FIGURES Figure page 1 1 Sche matic diagram of MALDI and ESI ................................ .............................. 39 1 2 Number of publications between 2007 2012 found through the Web of Science database ................................ ................................ ............................... 40 1 3 Sche matic representation of Top do wn versus Bottom up proteomics .............. 41 1 4 Fragment ion types produc ed following either CAD or ETD .............................. 42 1 5 Database search in a typical MS based proteomics experiment ........................ 43 1 6 Array based proteomics ................................ ................................ ..................... 44 1 7 Levels of plasma proteins ................................ ................................ ................... 45 1 8 Instruments u sed for protein identification ................................ ......................... 46 1 9 Schematics of cell SELEX ................................ ................................ .................. 47 2 1 Scanning electron micrographs of the alumina mask ................................ ......... 64 2 2 Tapping mode AFM images of nanowell arrays on silicon substrates ................ 65 2 3 Nanowell depth versus etch time ................................ ................................ ........ 66 2 4 Workflow for the preparation of nanowell arrays and MS analysis. .................... 67 2 5 Mass spectra of adenosine acquired on 10 nm, 30 nm, 50 nm deep nanowells and a DIOS surface ................................ ................................ ........... 68 2 6 Mass spectra of adenosine acquired on 10 nm, 30 nm, 50 nm deep nanowells and a D IOS surface ................................ ................................ ........... 69 2 7 Mass spectra of adenosine acquired on 10 nm, 30 nm, 50 nm deep nanowells and a DIOS surface ................................ ................................ ........... 70 2 8 Comparison of atmospheric pressure and vacuum regime laser desorption ionization on 30 nm deep nanowell arrays for adenosine. ................................ .. 71 2 9 Comparison of atmospheric pressure and vacuum regime laser desorption ionization on 30 nm deep nanowell arrays for Pro Leu Gly. ............................... 72 2 10 Comparison of atmospheric pressure and vacuum regime laser desorption ionization on 30 nm deep nanowell arrays for [Des Arg 9 ] bradykinin ................. 73


10 3 1 Analysis of glucose on GO A) No matrix B) HCCA matrix C) GO ....................... 97 3 2 Analysis of caffeine on GO A) No matrix B) HCCA matrix C) GO ....................... 98 3 3 Analysis of glutathione on GO A) No matrix B) HCCA matrix C) GO .................. 99 3 4 FTIR analysis of aptamer conjug ated GO ................................ ........................ 100 3 5 Schematics of aptamer assisted LDI on GO ................................ ..................... 101 3 6 Analysis of aptamer assisted capture of cocaine ................................ ............. 102 3 7 S/N ratios aptamer assisted capture of cocaine on GO ................................ .... 103 3 8 Analysis of aptamer assisted capture of adenosine on GO .............................. 104 3 9 S/N ratios aptamer assisted capture of adenosine on GO. ............................... 105 3 10 TEM images of (A) GO (B) Au GO,(C) Cu GO (D) Pt GO E) Au Cu Pt GO f) CdT e GO ................................ ................................ ................................ .......... 106 3 11 Fragmentation of BP ions ................................ ................................ ................. 107 3 12 Fragmentation of BP ions on different GO derivatives ................................ ...... 108 3 13 Survival yield calculations on GO derivatives ................................ ................... 109 3 14 Analysis of bradykinin acetate on CdTe GO ................................ ..................... 110 3 15 Analysis of insulin beta chain on GO and CdTe GO ................................ ........ 111 3 16 Analysis of bovine serum a lbumin on GO and CdTe GO ............................... 112 4 1 TEM images of hybrid nanostructures. ................................ ............................. 130 4 2 Survival yield calculations on metal oxide Au heteronanostructures ................ 131 4 3 UV spectra of the hybrid NPs ................................ ................................ ........... 132 4 4 LDI analysis of glucoseamine, phenylalanine,mannitol and dopamine on FNPs ................................ ................................ ................................ ................ 1 33 4 5 L DI analysis of sarcosine, reserpine, MIF 1 and serotonin on FNPs ................ 134 4 6 LDI analysis of cholesterol on FNPs ................................ ................................ 135 4 7 Comparison of LDI analysis of glutatione using HCCA matrix and FNPs ......... 136


11 4 8 Comparison of LDI analysis of melatonin and n lauryl sarcosine in positive and negative ion mode ................................ ................................ ..................... 137 4 9 Comparison of LDI analysis of glutatione in positive and negative ion mode ... 138 4 10 Schematic diagram of aptamer modification of FNPs and MS analyses ......... 139 4 11 Fluorescence spectra of FNPs after aptamer conjugations .............................. 140 4 12 Flow cytometric assay to monitor the binding ................................ ................... 141 4 13 Images of cancer cells ................................ ................................ ..................... 141 4 14 LDI analysis of CEM cell lysate after metabolite extraction by cold methanol using FNPs ................................ ................................ ................................ ....... 142 4 15 LDI analysis of CEM cell lysate after metabolite extraction by hot water using FNPs ................................ ................................ ................................ ................ 142 4 16 L DI analysis of CEM cell lysate after metabolite extraction by hot water using FNPs after quenching the metabolism ................................ .............................. 143 5 1 Flow cytometry assay for the binding of the HCC aptamers TLS9a and TLS911a( 137 ) ................................ ................................ ................................ ... 156 5 2 Aptamer based affinity mass spectrometry for cancer biomarker discovery ..... 157 5 3 1D gel electrophoresis image of HCC cell lysate after aptamer based affinity enrichment. (Coamassie staining) ................................ ................................ .... 158 5 4 1D gel electrophoresis image of HCC cell lysate after aptamer based affinity enrichment. (Silver staining) ................................ ................................ ............. 159 5 5 Protein ID results of the excised band after aptamer based affinity enrichment.(coammassie stained gel) ................................ .............................. 160 5 6 Protein ID results of the excised ba nd after aptamer based affinity enrichment. (Silver stained gel) ................................ ................................ ........ 161 5 7 Protein ID results of the excised band after aptamer based affinity enrichment (in solution digestion) ................................ ................................ ..... 162 5 8 Protein ID results of the excised band after aptamer based affinity enrichment. (Library treated) ................................ ................................ ............ 163 5 9 Protein ID results of the exci sed band after aptamer based affinity enrichment. (Library+TLS9 control aptamer treated) ................................ ........ 164


12 5 10 Protein ID results of the excised band after aptamer based affinity enrichment. (library+TLS11 a HCC aptamer treated) ................................ ........ 165 5 11 Analysis of interaction maps of Plexin B3 ................................ ......................... 166


13 Abstract Of Dissertation Presented To The Graduate School Of The University Of F lorida In Partial Fulfillment Of The Requirements For The Degree Of Doctor Of Philosophy APTAMER BASED AFFINITY METHODS FOR MASS SPECTROMETRY By Basri Gulbakan May 2012 Chair: Weihong Tan Major: C hemistry Capturing rare proteins and met abolites from complex biological mixtures is essential to understanding the key functions of biological systems. As such, the development of new techniques for their isolation and subsequent detection/identification by mass spectrometry (MS) is becoming in cr easingly more important. While identification of pure proteins and simple biological mixtures using MS has become a rout ine and relatively simple task u tilization of this powerful tool in analyzing complex mixtures and real biological samples is still in its infancy. One approach to the analysis of complex biological samples employs chromatographic extraction and fractionation methods, before MS is performed. However, current separation methods suffer from numerous limitations, including time consuming pr ocedures, the difficulties involved in handling complex samples, and, especially, the lack of selective molecular isolation Therefore, the next best option utilize s affinity reagents tethered on a substrate which, in turn, could be used as a sample treat ment tool or as a substrate to obtain direct MS readouts. A major obstacle to this strategy is finding efficient and robust capturing agents for biomarker detection. Although antibodies have been the gold


14 standard as capturing reagents, commercial antibodi es do not exist fo r all proteins, and developing high affinity and selective antibodies is very expensive and time consuming. Moreover, since antibodies are proteins, they are very prone to irreversible degradation and cannot be easily modified. As an alt ernative to antibodies, aptamers provide the specificity lacking in many extraction matrixes This thesis discusses the development of aptamer based MS platforms. We have developed four different platforms for this purpose. First, nanowell array surfaces w ere prepared and applied in MS. Second graphene oxide and graphene oxide metal conjugates were prepared and modified with aptamers. Third a unique nanoflower shaped nanostructure was developed for MS and applied for the extraction of adenosine triphosphate ( ATP ) in cancer cells. Finally aptamer based affinity mass spectrometry was applied for the biomarker discovery of liver cancer. All these results demonstrate the utility of the approach for analysis of small molecules and discovery of new biomarkers in r eal biological samples


15 CHAPTER 1 INTRODUCTION Biomarker Discovery Fundamental understanding of many biological processes has been greatly influenced by the completion of the human genome project and this initiated a new era for biological research. Ho wever, while genomic information is very important but it is not enough to fully understand the biological processes especially when they relate to dis ease. Therefore the focus wa s then shifted to the interactions and roles of other biomolecules such as pr oteins and metabolites in cells that is, to new fields called proteomics and the small molecule complement of proteomics metabolomics. ( 1 2 ) Proteins and small molecules are very important constituents of biological systems. They can have diverse functions such as cytoskleletal building blocks, as enzymes whic h control biochemical reactions, or as antibodies that contribu te to immune system or signaling molecules that provide communication between cells and organ systems. Their enormous versatility in structure, f olding, and modification enable them to carry out very complex tasks within the cells a nd higher cellular assoc iations. ( 3 ) Proteins and metabolites are also very rich sources of biomarkers for many different diseases. For example, overexpression of a number of serum marker proteins, such as fetoprotein for liver cancer ( 4 ) carcino embryonic antigen (CEA) for colon cancer ( 5 ) and prostate specific ant igen (PSA) for prostate cancer ( 6 ) are well established markers strongly related to tumor initiation and growth. Also, several growth factor proteins, such as epidermal gro wth factor recept or 2 (EGFR2), v ascular enhanced growth factors (VEGF), platelet derived growth factor (PDGF) and insulin like growth factors (IGF) are also tumor related proteins that play important roles in tumor initiation. ( 7 ) It is estimated that


16 approximately 85% of breast cancer patients have significantly elevated levels of EGFR 2 p rotein and this elevation is strongly correlated with disease recurrence, metastasis or shortened survival. ( 8 ) On the metabolomics side, sarcosine a small molecule has recently been linked t o prostate cancer. ( 9 ) Propionyl carnitine has been found as a biomarke r for methylmalonic acidemia (MMA) and propionic acidemia (PA). ( 10 ) These studies have all shown that disease processes will ult imately result from proteins proteomics and also from metabolites metabolomics Protein Biomarkers C ontrary to the impressive and rapid progress in genomics with more than 800 organisms having been sequenced, including the human genome; proteom ics and met abolomics research are still in its very early stages. ( 11 ) Proteomics by de finition is the systematic determination of protein sequence, quantitation, modification state, interaction partners, activity, subcellular localization, and structure in a given cell type at a partic ular time. There are estimated 20,000 to 25 ,000 human ge nes. ( 12 ) However, the and today we know that one gene does not produce one protein and once proteins are made, many of them are modified by phosphate, carbohydrates, or lipid groups in different configurations, thus adding another level of complexity to the proteome. Similar to the human genome project the human proteome p ro ject was initiated by a group of scientists in 2005 by human proteome o rganization (HUPO). ( 13 ) This was followed by twelve other proteomics initiatives including the human liver proteome project, the human brain proteome project and the human ki dn ey and urine proteome project. However the scientists must deal with approximately more than 1 0 000, 000 proteins, which ca n then be further modified by many post translational modifications. Because of the time and


17 effort and money it takes for a prote in to be fully sequenced, identified and validated; such proteome project eff orts are extremely challenging and therefore are not expected to give promising results and will not be feasible in the very near future at least with the current technology that is used in proteomics. For that reason the very early hope of characterizing the whole human proteome failed too quickly and researchers in the proteomics field are more focused on trying to find molecular differences between one functional state of a bio logical system to another rather than trying to understand the systems biology as whole which certainly will give more and more precise information but this is very difficult to realize. It is noteworthy that differences between different cellular state s are also reflected in changes in gene expression that also can be monitored at the genome and transcriptome level. For instance transcriptomic arrays and deoxyribonucleic acid ( DNA ) methylation studies have shown great potential for biomarker discovery. ( 14 15 ) While the genome is fairly static, proteome is highly dynamic Therefore the data suggested by genomics about diseases may not be completely true as it does not reflect the status of the system at any given time. Because of the common post translational modifications such as phosphorylation, glycosylation and lipidation ; the status of the cellular organism changes continuously. F or these reasons the protein domain is likely the most affected part in disease response and recovery. The main application of proteomics is therefore on the biomarker discovery. ( 16 17 ) Proteomics itself cannot heal a person but it does have the potential to make a sizeable impact in medicine. The starting hypo thesis in a pr oteomics based biomarker study is tha t if there is a disease progression then the protein make up of the diseased organism should change both in quality and in quantity


18 or sometimes in both. So if this information can be extracted and interpreted appropriately then it will be more useful for biomarker discovery and complemantary to the genomics or transcriptomics data. It is fo r that reason that many of the food and drug a dministra tion (FDA) approved drugs target the processes mediated by proteins and by protein protein interactions ( 18 ) I t will be even more useful if this information can be ob tained at the early stage of disease progression since the early diagnosis and treatment result in the best prognosis of many diseases. Over the past 20 years or so, tha nks to the advances in different analytical technologies there has been tremendous increase in our understanding of how normal cells become diseased cells and which of the signaling pathways are more affected in disease initiation and progression. ( 19 ) However in searching for new tools for diagnostics, progress has been very slow in bringing the biomarkers to clinical practice. Biomarkers are becoming increasingly more and more important, and it is clear that patients would benefit by a greater av ailability of such effective molecular indicators that can be monitored noninvasively from readily accessible bodily fluids. This will also solve the problem that the pharmaceutical industry has been facing for many years. The current research and developm ent (R&D) cost for developing a new therapeutic drug takes millions of dollars and it takes an average of 12 years to get a new drug to market. ( 20 ) P4 Medicine A ccurate diagnosis of diseases will also permit the development of more effective drugs and more effective therapies and wil l also enhance the success of clinical trials. Biomarkers also fit perf ectly with the new vision of clinicians called P4 medicine. This is a new concept coined by biologist Leroy Hood, and shortly stands for Predictive, Preventive, Personalized, and Partic ipatory Medicine. ( 21 ) Key to the success of P4


19 medicine is to detect disease at an earlier stage, when it is easier and less expensive to treat effectively This is wh y biomarker research has been a central focus in many research labs across academia, government agencies, and the pharmaceutical industry. The definition of biomarker is an ongoing debate among scientists and clinicians. There are many different ways to de fine biomarkers based on molecular properties, applications, and methods. The National Institutes of Health (NIH) suggested an inclusi a characteristic that is objectively measured and evaluated as an indicator of normal biol ogic processes, pathogenic processes, or ( 22 ) This is a very broad definition it does not exclude any particular molecule therefore a biomarker can be DNA, protein, metabolite, mRNA (messenger ribonucleic acid), or lipid or even an ion. It is fair to say that full understanding will be possible with the combination of all the Methods for Protein Biomarker Discovery Biomarker discovery methods vary a lot depending on th e diseas e type, but generally they can be classified as mass spectrometry based biomarker discovery and array based biomarker discovery M ass Spectrometry Based Protein Biomarker Discovery ionization techniques namely, matrix assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) revolutionized proteomics and biomarker discovery research by rendering the study of macromolecules in the gas phase feasible. ( 23 ) A schematic diagram for both of these ionization t echniques are given in Figure 1 1. The se innovative mass spectrometry


20 techniques have found widespread use in many different areas including genomics, transcriptomics, proteomics and metabolomics and used in all based biomarker discovery efforts as well. Mass spectrometry techniques are particularly useful for proteomics applications and have been a workhorse for peptide and protein identification. Therefore the principal enabling te chnology of proteomic biomarker discovery is mass spectrometry (MS). As demonstrated in Figure 1 2 a recent web of science statistics clearly shows this fact. All mass spectrometers, regardless of the type, ionization mode or performance characteristics pr oduce mass spectra which plot the mass to charge ratio of the ions (x axis) observed versus dete cted ion abundance (y axis). ( 24 ) There are many differe nt ways to realize MS based proteomics biomarker discovery but the methods are down ( 25 ) The cartoon representation of both processes is sh own in Figure 1 3 In bottom up approaches, the protein s can be first separated by gel electrophoresis or chromatography, in whic h the samp le will contain separated proteins S pecific bands or fractions are first subjected to proteolytic cleavage and the peptide products are then further fragmentated and analyzed by MS. Alternatively, a complex protein mixture initially can be digested to the peptide level, and then separated by on line chromatography coupled to electrospray mass spectrometry (LC ESI MS/MS) or MALDI (LC MALDI MS/MS). The identity of the original protein is determined by comparison of the peptide mass spectra with theoretical p eptide masses calculated from a proteomic or genomic database. Bottom up proteomics is the most mature and the most widely used approach for protein identification and characterization.


21 Commercial in struments with control software and bioinformatics tools optimized for bottom up applications are available from several vendors. T he bottom up strategy using multidimensional capillary LC MS/MS has been the most successful method in identifying proteins in digests derived from very complex mixtures such as cel l lysates. This method is also known as MudPIT (Multidimensional Protein Identification Technology) relies on bottom up proteomics approaches and high performance separation ( 26 ) In top down proteomics, as opposed to the bottom up approach, intact protein ions or large protein fragments are directly subjected to gas phase fragmentation for MS analysis. However top down prot eomi cs is a fairly new field in proteomics and its application to biomarker discovery is also very limited. The biggest drawback of top down proteomics is the necessity for highly sophisticated and very expensive instrumentation which requires great expert ise to operate and maintain. Therefore the top down approach is still mainly used as a technique for analyzing purified proteins. In addition, automated hardware and software dedicated to top down approaches are currently in development stages and few prod ucts have entered to the market so far. Hence, the top down approach is not competitive enough with bottom up approaches for whole proteome analysis and biomarker discovery. In addition, the sensitivity of the mass spectrometers for proteins is much lower than for peptides, and the proteins might be processed and modified such that the combinatorial effect makes determining the masses of the numerous resulting isoforms impossible. On the other hand there are two major advantages of the top down strategy: th e potential access to the complete protein sequence and the ability to locate and characterize post translational modifications


22 (PTMs). In addition, the time consuming protein digestion required for bottom up methods is also eliminated. Overall, whatever approach is under taken for proteomics based biomarker discovery, the success is totally dependent on the quality of the MS data and the quality of the MS data is highly dependent on how well the sample is prepared and how well it is fragmentated in the mas s spectrometer. The classical method for breaking ions apart involves colliding them with a neutral gas such as helium or argon, a process known as collision activated dissociation (CAD or CID). This is also the fundamental ion activation technique in whi ch today`s proteomics methodologies are mostly built on. Newer methods use electrons instead of collisions. These methods are electron capture dissociation (ECD) and electron transfer dissociation (ETD). The fundamental difference between these two is actu ally very simple; the CAD method primarily breaks the amide bond whereas ECD and ETD mainly break the N C bond. This is depicted in Figure 1 4. Recent data showed that when these two methods are applied for protein identification even though a great porti on of the peptides ide ntified overlaps certain portions can be identified either by CAD only or ETD only method. So to get good proteome coverage and to get more confident peptide identification for more reliable biomarker discovery implementation of bo th methods is definitely be advantageous ( 27 ) The last and maybe the most important part of the biomarker identification process is the use of proper bioinformati cs tools. After all the data has been generated by the mass spectrometer, data is then processed by many different databases which are available with the instruments or can be obtained from different commercial vendors


23 such as Mascot, Sequest and Probid. T he basic drawback of t he database searching for biomarker identification experiments is that it can only be carried out using the organisms that have had their genome sequenced so that all possible peptides are known in S ilico. ( 28 ) The o verall workflow of datab ase search ing is shown in Figure 1 5. Otherwise a manual data interpretation way which is called as de novo sequencing should be app lied. However considering the amount of data generated in a typical proteomics experiment the success of the de novo approach is very much limited and for larger scale identification studies is totally impossible Array Based Protein Biomarker Discovery M icroarrays can be defined as a functional element (DNA, RNA, antigen, antibody, aptamer, and small molecules) being attached to a solid substrate in an ordered manner at high density. Hundreds to thousands of these products can be immobilized on a very sm all area with a specialized robotic arraying tool. The immobilized products (i.e., the array) serve as interaction targets for a labeled probe. ( 2 9 ) This probe is generated by labeling it with a fluorescence dye, radioisotope, or chemiluminescence agent. A schematic diagram of the array based approaches is shown in Figure 1 6. The labeled probe then interacts with the sample and after washing and drying steps ; a high resolution image is created using a specialized image scanner. Software is then used to determine the intensity of each spot. The main steps of the growth and maturation of array platforms for proteomics are to a big extent similar and related to those of the genomics. The sequencing of the whole genome began with the development of the S anger method nearly 30 years ago. This method enabled sequencing a few short DNA strands for the determination of whole chromosomes. Then the next impo rtant challenge was to develop software capable of managing all the data. Using an oligonucleotide


24 microarray containing a series of gene specific oligonucleotides or cDNA sequences on a slide or a chip, one can probe the expression of thousands of genes a t once. Even though the application of the array platforms for genomics was quite wide and successful it is very slowly becoming a complement to proteomics and its application to proteomic biomarker discovery is fairly new and different formats have recen tly begun to emerge. Since antibodies not DNA or RNA are used as the probes for screening the proteome it is very difficult to maintain the folded properties of proteins and this poses a potential problem in the fabrication of protein microarrays. Furtherm ore, relative to hybridization reactions, folded proteins have greater sequence dependence and are prone to nonspecific interactions. The complexity is additionally increased by the inability to draw an absolute correlation between abundance of mRNA and th e level of its corresponding protein. This, in turn, depends on a number of factors such as post translational modifications, proteolysis, and compartmentalization. Another reason is that there are no analogous tools available for protein analysis. There i s no protein equivalent of polymerase chain reaction ( PCR ) It is currently not possible to induce polypeptide molecules to replicate themselves in a manner analogous to oligonucleotide replication through PCR. So unlike the DNA microarrays, the necessity for the sensitivity is far greater. Because even if a small amount of DNA piece is isolated it can be amplified through PCR, whereas a small amount of a polypeptide must be detected and analyzed without any amplification. ( 30 ) Dynamic Range Problem As outlined in details above, there are basically two important platforms for biomarker discovery namely mass spectrometry and microarrays. Each of th em has its own challenges but for both approaches the challenge in protein biomar ker discovery


25 can be condensed into two distinct categories. The f irst one is detection, identification and quantification of low abundance proteins from complex biological sa mples. The s econd one is the development of a high throughput; low cost mass spectrometry solution to validate promising protein markers identified in proteo mics experiments. Unfortunately, the dynamic range of the biological mixtures is far beyond the dyn amic range of the current instrumentation. Currently mass spectrometers are at a dynamic range of about 10 4 however; biological mixtures including plasma, urine, cell lysates contain proteins in a range of concentrations that, by some estimates, extend o ver 12 orders of magnitude as shown in Figure 1 7. This poses the greatest challenge for successful biomarker identification because while mass spectrometry (MS) has evolved as a tool to detect and identify femtomoles of peptides, the dynamic range of dete ction is still a limiting factor for comprehensive profiling of biological mixtures. ( 31 ) In the current status of the technology and the speed of the innovations in the instrumentation side, covering a dynamic ra nge of 10 8 or 10 10 will not be very likely in the near future. To put this problem into perspectiv e a model calculation will be given here ( 32 ) Serum has a total protein concentration of approximately 80 mg mL 1 or 1.6 mM for a 50 kDa protein. Most of the prese ntly used tumor markers have cut off values around 1 10 ng mL 1 (20 200 pM for a 50 kDa protein). If it is assumed that a given nano HP LC MS method has a limit of detection of 1 fmol, then it will take 5 50 L of serum to have 1 fmol of a putative cancer b iomarker present to start with. However, 50 L of serum contains 4 mg total protein, which is far too much to be loaded on a nanoLC column (capacity 5 10 pmol). It is thus indispensable to fractionate the sample in order to cover a wider dynamic range. Dep letion of high abundance proteins by affinity


26 chromatography is a widely used approach to reduce the total amount of protein in serum by a factor 10 20 reducing the initial protein load to approximately 0.2 mg or 4 nmol. It has to be mentioned that this de pletion step does also remove non target proteins due to adsorption to albumin or other high abundance proteins. It appears, however, that the depletion step can be performed with good repeatability despite this shortcoming. Even after depletion there is s till a discrepancy of about 1000 fold between the loading capacity of a nanoLC column and the amount of protein present. Further fractionatio n is thus required, for example, by strong cation exchange HPLC (often done after trypsin digestion) or high temper ature reversed phase HPLC of intact proteins. Assuming that 50 fractions will be taken and that the amount of protein distributes evenly over each fraction (an assumption that is made to facilitate calculation), there will be approximately 80 pmol protein (or protein digest) per fraction leaving a 10 fold discrepancy between the loading capacity of a typical nano HP LC column and the amount present. It is obvious that further fractionation could easily overcome this gap but at the expense of extremely long a nalysis times per sample. If one considers that an LC run takes 1 h, then analyzing 50 fractions will take 50 h (approximately 2 days without considering any downtime of the instrument) and a further fractionation into 10 fractions would lead to a total an alysis time of 500 h (approximately 21 days). It is very clear that this is not a very feasible or acceptable time line for biomarker discovery research, where large numbers of samples have to be processed. On top of everything putative biomarkers for disea ses are present at vanishingly small concentrati ons generally fall ing into ng/ml range. ( 33 )


27 I t is generally accepted that in most cases two MS instruments are required for unambiguous protein id entification. The analytical performance of different instrum ents as illustrated in Figure 1 8 clearly shows that no single instrument has the capacity to simultaneously meet all the biological and analytical requirements of biomarker identification. ( 34 ) So if one totally relies on what mass spectrometry data can give the rate of success in biomarker discovery will be less than the failure rates. The first problem is also related to the sensitivity of the mass spectrometry instruments. Even though it is highly dependent upon the analyte being analyzed, it is generally accepted that ionization yields are around 10 percent in electrospray ionization and around 5 percent in matrix assisted laser desorption io nization So a very big portion of the analytes that is present in the original samples is never introduced into the mass spectrometer in the form of ions. The problem is also associated to the lack of mechanistic understanding of the ionization process bo th methods. In neither ESI nor MALDI no clear and solid understanding yet exists about the ionization mechanisms. There are detailed reviews on these topics but the physical chemistry associated with ionization is extremely complex therefore it is very h ard to dr aw a mechanistic understanding. ( 35 ) This has been an active field of research among mass spectrometrists and many reports were published claiming big increases in ionization efficiency but most of them were successful only in certain cases and with limited analyte classes which are far from being generalized. The losses during the ion transf er process into the mass analyzer also contributes to the loss of sensitivity and in essence a very tiny portion of the sample can be ionized transferred through the ion optics, reach the detector, be detected and recorded as an ion signal. Recent techno logies


28 such as ion funnels and off axis ion beam technologies have brought some improvements but they are still insufficient. ( 36 ) Another difficulty is to establish which differences are the most important and likely to survive downstream pre clinical validation. It is therefore necessary to conduct validation studies on identified proteomic differences. These candidate proteins are often selected based on the biological knowledge and the quality of the quantitative MS approach. In conclusion it is fair to say that the improvement that will come from the instrumentation side will be quite limited and to meet the challenges of biomarker discovery new approaches are certainly needed. Affinity Guided Appr oaches for Mass S pectrometry While many technical and experimental difficulties still exist in the MS based techniques, it is the most powerful discovery and identification tool and no other analytical technology has yet the capability to be an alternative making MS as a gold standard. Because of the limitations as explained in previous sections, most of the current efforts focus on more systematic and targeted approaches to use MS more effectively as a more sensitive, more selective and high throughput ana lytical tool. Therefore affinity captur e, enrichment and detection have become the new direction of the MS based studies Many different strategies have been employed for selective capture, enrichment followed by mass spectrometry analysis. In this contex t surface enhanced laser desorption mass spectrometry (SELDI) has emerged as the most successful method for affinity mass spectrometry applications. ( 37 ) While the actual method of preparation of the ProteinChip surface(s) is proprietary, the approach


29 involves the covalent attachment of surface modification compounds to alter the surface chemistry of capillary chromatogra phy columns. SELDI has been applied to proteomics, especially in cancer biomarker identification and disease diagnoses. ( 38 ) In the SELDI approach a small number of integrated surface chemistries are used to selectively bind va rious proteins from complex mixtures obtained from biological samples. The used to establish a database of responses for clinical diagnosis of disease states, i.e. an aver spectra obtained from a large set of healthy patients and deviation in the fingerprint MALDI mass spectra for a given patient is taken as a diagnostic indicator of a disease state. H owever although very promising reports have been published in the literature the SELDI resu lts are also have poor diagnostic power and the success of SELDI as a clinically viable tool is highly debated. In addition to this patent protected technology se veral other studies ha ve demonstrated the efficacy of using an affinity capture tool combined to MS to improve selectivity and sensitivity. Both both proteins and DNA may be captured using beads via avidin biotin interactions, immobilized metal affinity ca pture (IMAC), and antibody antigen affinity interactions. In one of the earliest examples of affinity mass spectrometry, monoclonal antibody modified agarose beads were used to selectively capture the peptide containing the linear epitope of the antigen fr om the proteolytic digest of the antigen and then characterized the epitope by MS. ( 39 ) In practice the affinity capture structures may either be manipulated dir ectly (e.g by placing surface chemically modified magnetic beads into a protein mixture and then depositing the withdrawn beads directly on the MALDI target) or loaded within a pipette tip and the


30 protein containing solution manipulated (e.g. by passing th e protein solution through the affinity capture material and then eluting the captured protein. Both approaches are attractive but the choice highly d epends on the molecular weight and hydrophobicity of the captured species. Affinity purification coupled t o mass spectrometry has not only been used to capture analytes of interest from complex biological mixtures but also used as a very efficient tool for studying the interactions between different proteins. In this type of experimental setting, the protein o f interest is first expressed in a cell line as a recombinant fusion protein and immobilized on a solid surface. ( 40 ) Int eracting proteins can then be precipitated by applying a cellular lysate to the column. An obvious advantage of this method is that it is robust, easy to use and capable of retrieving even weakly interacting and low abundant proteins owing to the fact that large amounts of recombinant protein are present on the column. However, not all proteins can be easily overexpressed as a fusion protein. Sample complexity is largely dictated by the interactions established by the tagged protein, the number and nature o f the purification steps and the stringency of the washes. Despite its limitations this method has successfully been applied for many different problems. ( 41 ) Role of Nanotechnologies in A ffinity Based MS A pplications Nanotechnology is defined as the systematic study of a particular system at the nanoscale level at length scales between 1 and 100 nm. Considering that averag e bond lengths are in the picometer range; this is basically the limit of the metrics where molecules cannot be further manipulated at the molecular level. Therefore, nanotechnology opened up very unique opportunities not only for materia l research but als o for biology, medicine and many other disciplines by manipulating individual atoms and molecules in a specific way that can fit a certain application. In the last decade


31 nanostructures have attracted great attention owing to their unique physical, chemica l and structural properties. As discussed previously, MS technology is challenged by a number of limitations (dynamic range, PTMs, instrument sen sitivity, biological complexity etc). The field of nanotechnology has been recently associated with several MS based affinity applications. ( 42 ) While a diverse array of MS applications for nanostructures exist, they be can be condensed in to three basic categories: (a) scaffold for biosensing (b) sample pu rification and enrichment tool (c) substrate for mass spectrometry analysis. Nanoporous M aterials Changing the morphology of a surface from plain to a nanostructured form changes the sensing properties of that particular material. S urface enhanced laser desorption ionization (SELDI) was applied on a nano structure surface (2 20 nm), and spectral features were completely different with different sized nanopores. ( 43 ) Similarly mesoporous silica chips were used in proteome fractionation based on enhanced sieving properties of t hese nanostructure surfaces for l ow molecular weight peptides which were specifically isolated and fractionated from complex biological sample s. ( 44 ) After fractionation, the response of mass spectrometry greatly improved by achieving better sensitivity in detecting low molecular weight peptides. Another nanostructured material, porous silicon which was first discovered by Bell laboratories in 1960`s, has been highly used for many MS applications in different formats. Unique fluorescence pro perties and the huge surface area of porous silicon (500 800 m 2 /g) makes it an ideal candidate for MS applications. Porous silicon was used a scaffold for antibody arrays and obtained detection limits down to 1 picomolar for IgG and 20 picomolar for PSA in clinical samples. ( 45 ) As an a lternative to classi cal sample preparation methods,


32 nanoporous silicon was used to trap trypsin protein and the sequence coverage for prostate specific antigen (PSA) and human glandular kallikrein 2 protein was achieved within 30 sec which usually takes up to 24 hrs using lo w sample amounts (fmol levels). ( 46 ) Porous silicon surfaces were also used as a sour ce for ionization. In recent studies nanostructured porous silicon was used in two different formats called desorption ionization on silicon ( DIOS) and nanostructure initiator mass spectrometry (NIMS) which have proven to be useful for proteomics and meta bolomics. The surface modification of porous silicon also allowed DIOS MS to be used for sample capture and enrichment in LDI MS analysis through the analyte specific interaction by using immobilized ligands on the porous silicon for isolating the target m olecules from the background in complexes. ( 47 ) N anoparticles as S ubstrates for MS NPs were also tested for their applicability in MALDI MS as substrates for ionization. The idea of using nanoparticles as a tool for ionization dates back to the early years of the soft ionization mass spectrometr y. In the seminal work which finally resulted in The 2002 Nobel Prize in Chemistry a suspension of cobalt nanoparticles 30 nm in glycerol was used to analyze proteins and synthetic polymers by using a pulsed UV laser. ( 48 ) However because of the problems in handling glycerol and not being widely useful this method has largely been omitted until the recent advancements in nanotechnology and MS. In contrast to traditional organic matrices, NPs allow a greater number of molecules to adsorb to t heir surfaces, thus more analytes can desorb and ionize from the ir surfaces per laser shot, theoretically and practically leading to excellent sensitivity. Nanomaterials having low thermal conductivity, high molar absorption coefficients and large surface area s and are favorable in MALDI MS, mainly because


33 they efficiently absorb laser energy to induce desorption/ionization of greater number of analytes per unit area. ( 49 ) Some of these nanomaterials were reported to provide excelle nt sensitivity values in the range of zeptomole. ( 50 ) These sensitivity levels are very promising because as explained in previous sections above, ma ny biomarker candidates exist in very rare amounts. Therefore, these sensitivity values (zeptomole) by pure MALDI MS or ESI MS are not yet possible in the absence of nanostructures. Moreover, in the case of MALDI MS analyses the ct causes irreproducible results. Nanostructures, on the other hand, overcome this problem to a great extent and improve shot to shot reproducibility. Moreover unlike MALDI matrices, NPs do not intr oduce any background ions, making metabolite analysis poss ible and greatly simplifying the spectra. NPs and their conjugates with recognition elements can, in some cases, are used as affinity probes for MALDI MS to concentrate analytes of interest from complex sample matrixes. For example, carboxylated/oxidized d iamond NPs having a nominal size of 100 nm have been employed to capture proteins from highly dilute and contaminated solutions; preconcentration of the proteins through hydrophilic interactions with the diamond NPs improved the sensitivity five fold. ( 51 ) Antib ody modified Fe 3 O 4 NPs have also been used to selectively capture multiple disease associated antigens, including serum amyloid A, C reactive protein, and serum amyloid P from human serum samples; the concentrated analytes were then mixed with sinapinic ac id and myoglobin (internal standard) prior to MALDI MS analysis. Relative to the signals obtained without employing this concentration strategy, the sensitivity for the analytes was improved 100 fold. ( 52 ) In a very recent work, a unique nanostructure was


34 developed that can ionize proteins as big as IgG (~150 kDa) and demonstrated that the interactions of pro teins with other biomolecules can be monitored ( 53 ) Carbon Based Materials and G raphene Elemental carbon in the sp 2 hybridization can form a variety of different structures. G rap hite, nanodiamond, carbon nanotubes, fullerene, graphene and graphene oxide, which are different forms of carbon nanostructures that have been well studied in different applications. ( 54 ) The r ationale behind using such kind of structures for affinity enrichment and matrix free laser des orption ionization is that they provide high ionization efficie ncy with minimal ba ckground, are readily available in large quantities are water soluble, have a high surface area and the surface chemistry is very straightforward As important examples carbon nanotubes were used as a substrate for ionization as well a s screening long chain fatty acids in patient samples ( 55 ) In another study, sputter coated nanostructure d diamond like carbon on commercially available DVD disks were used this substrate for laser desorption ionization of peptides and femtomolar level sensitivity has been reported. ( 56 ) G raphene (G ) and graphene oxide (GO), are other recently developed interesting materials which are used as substrates for ionization in the analysis of small p eptides and small metabolites. Enriching DNA and proteins in solution al so s howed high recovery yields c ompared to conventional MALDI matrices G raphene exhibited higher desorption ionization efficiencies with very low background ions. ( 57 ) Furthermore, it eliminated fragmentation and provided better tolerance to salts. ( 58 )


35 Aptamers In the last two decades, the potential of using oligonucleotides as molecular probes and recognition el ements has expanded greatly as a resul t of the discovery of aptamers. They are single stranded oligonucleotides (DNA or RNA), which have the ability to bind to other molecules with high affinity and specificity. They typically contain fewer than 100 bases and have a unique three dimensional structure for target recognition through interactions such as van der Waals surface contacts, hydrogen bonding and base stacking. ( 59 ) T hey are evolved from random oligonucleotide pools by a process called Systematic Evolution of Ligands by EXponential enrichment (SELEX). Aptamers have been generated for a wide variety of targets, including small molecules, such as metal ions, organic dyes and amino acids, antibiotics, and peptides, as well as proteins of various sizes and functions, whole cells, viruses and virus infected cells and bacteria. ( 60 ) The selective interactions between apt amers and these diverse targets have been exploited for applications in a variety of disciplines, including biotechnology, medicine, pharmacology, cell biology, microbiology and chemistry. In each of these cases, the aptamer can be uniquely designed to mee t specific goals, by taking advantage of the robust nature of these molecules. For example, aptamers have been effectively used for therapeutic applications such as targeted therapy detection and diagnostics. With the FDA approved drug Mucagen now availa ble, others, such as AS1411, (nucleolin aptamer in clinical trial), will contribute to cancer therapy. ( 61 ) Aptamers versus Antibodies Based on their target recognition capabilities, selective binding, and affinity, aptamers have been likened to antibodies. However, aptamers, by their unique features, have more flexibility in their development and range of applications. Also t he


36 time needed for the generation of aptamers by the SELEX process is comparatively short. In addition, the use of animals for antibody production can lead to batch to batch variation. However, aptamers are chemically synthesized, which eliminates the poss ible batch to batch variations associated with antibodies. Furthermore, chemical synthesis of aptamers permits the biochemical manipulation required to incorporate various functional groups and specific moieties without compromising the function of most ap tamers. ( 62 ) This phenomenon has been adopted for aptamer conjugation with drug molecules and nanomaterials and for the modifi cation of nuclease resistant bases, such O meth yl nucleotide analogues, to further enhance nuclease resistance when adopted for in vivo studies. Other attribute s, such as long shelf life and controllable or cyclical denaturation and renaturation, have expanded the flexibility of aptamers in various exp erimental designs. Even with improved nuclease resistance, aptamers have low blood residence times compared to antibodies, as well as low toxicity or immunogenicity (if any), and these are important features when used for in vivo applications such as imagi ng. ( 60 ) Cell SELEX As explained above aptamer have very similar attributes to antibodies and in many ways are superior affinity tools Tan Lab has pioneered a strategy called Cell SELEX, in which liv e cells are used as target to select aptamers for cell recognition and identification. This strategy is a particularly promising scheme for various diseases including cancer research and therapy. Specifically, by adopting cell SELEX, useful probes can be d eveloped to potentially differentiate tumor cells from normal cells, as well as differentiate between two different types of cancers and probably to characterize disease staging. Thus far, live cells of many different cancers such as T Cell, B Cell


37 leukemi a, lung cancer, liver cancer, ovarian cancer, prostate cancer, colon cancer and glioblastoma have been used in th is process, and, as a result, over 300 different aptamers have been gen erated for most cancers studied ( 59 ) Apart from serving as a molecular recognition tool they are also very promising tools for cancer biomarker discovery for a number of reasons. First p rior knowledge of the target is unnecessary. The need to know the molecular composition of the cell surface does not play an important role in cell SELEX. Instead, the different type of cells used in the selection is a critical parameter as the selected aptamers will be useful for the specific recognition of th ese cells. Second a ptamers can be generated for many targets. The cell membrane surface is a complex system which has a countless number of molecules, especially proteins. In cell SELEX, each of these molecules is a potential target. At the end of a succe ssful selection, aptamers are generated for many different targets. This feature is very important, as any one of these molecules may play one or more roles in the development of the cell or the disease they cause. C ell SELEX Derived Aptamers for B ioma rke r D iscovery Aptamers have very significant advantages in terms of biomarker discovery because cell SELEX derived aptamers recognize proteins on the cell membrane which constitutes the most challenging subclass of the proteo me. To date very few methods ex ist for their targeting, isolation and idenfitication. The r ecognition part has largely been accomplished using monoclonal antibodies however as explained above antibody production also has many limitations. Furthermore membrane proteins are intrinsical ly very difficult to isolate and to identify as they are buried in a highly dense pack of lipid bilayers and membrane proteins are highly hydrophobic which poses a difficulty in MS based identification platforms. ( 63 ) In contrast to the technical difficulties to analyze


38 them, they are very important for disease diagnosis and therapeutic s and they have been extensively targeted for drug design, and it accounts for about 70% of all known drug targets (e.g., HER 2 and G protein coupled receptors) Since selection is done blindly i. e without any bias towards a particular protein target the fished out proteins will likely have important functions in disease diagnosis and therapatics. Overview of the D issertation The research data presented in this dissertation demonstrate how aptamer s wi th appropriate modifications, can be applied to the development of affinity based MS platforms in three different nanostructure based systems. Chapter 2 outlines the laser desorption ionization on silicon nanowell arrays and aptamer enhanced nanostruct ure initiator mass spectrometry for isolation of targets from biological mixture s. Chapter 3 discusses discovery of a new nanostructure based matrix graphene and graphene derivatives for aptamer based MS Chapter 4 explains how a ratioanally designed nanos tructure based mass spectrometry p robe is developed and applied to aptamer based mass spectrometry. Chapter 4 discusses the discovery of a new membrane protein biomarker for hepatocellular carcinoma. The chapters further assess the possible areas in whic h these aptamer based MS can be further exploited. The concluding chapter summarizes the overall significance of this research, and exam ines future directions of the research based on aptamer based MS strategies.


39 Figure 1 1 Schematic diagram of MALDI and ESI ( 23 )


40 Figure 1 2 Number of publications between 2007 2012 found through the Web of Science database using the search terms biomarker AND mass spectrometry


41 Figure 1 3 Schematic representation of Top down versus Bottom up proteomics ( 64 )


42 Figure 1 4 Fragment ion types produced following either CAD or ETD ( 27 )


43 Figure 1 5 Database search in a typical MS based proteomics experiment ( 28 )


44 Figure 1 6 Array bas ed proteomics ( 65 )


45 Figure 1 7 Levels of plasma proteins ( 11 )


46 Figure 1 8 Instruments used for protein identification ( 34 )


47 Figure 1 9 Schematics of cell SELEX ( 59 )


48 CHAPTER 2 LASER DESORPTION ION IZATION ON SILICON N ANOSTRUCTURES Matrix assisted laser desorption/ionization (MALDI) has been utilized in the study of large biomolecules, such as peptides, proteins, carbohydrates and DNA. ( 66 ) The broad success of MALDI MS is related to the ability of the matrix to incorporate and transfer energy to an analyte, thereby ionizing it in a very soft manner However, MALDI is complicated because the presence of the matrix often causes heterogeneous cocrystallization of the matrix and analyte, resulting in significant background ion intensity in the low mass range (<500 m/z). ( 67 ) As a complementary alternative, Siuzdak and co wor kers have developed desorption/ionization on silicon (DIOS) using nanoporous silicon substrates for the detection of small peptides and antiviral drugs without any mass interference due to matrix ions In DIOS MS, the analytes in solution are directly depo sited on a nanoporous silicon surf ace without a chemical matrix. Compared to MALDI, this approach provides simplified sample preparation, more uniform surfaces, and less background noise at masses below 600 Da. Although the DIOS mechanism is not fully unde rstood, porous silicon was found to be an effective medium for desorbing compounds and generating intact ions in the gas phase It is suggested that porous silicon effectively absorbs and transfers the energy from the UV irradiation laser to the adsorbed a nalytes, while also protecting these molecules from fragmentation caused by direct laser exposure. ( 68 ) Most existing DIOS platforms are prepared by electrochemical anodization of crystalli ne silicon necessitating the use of toxic HF solution. In addition, it is difficult to obtain reproducible surfaces with the same nanostructures, because pore size and pore


49 density are not well controlled by chemical etching. ( 69 ) To overcome this issue, Vertes et.al reported the use of silicon microcolumn arrays ( 70 ) and silicon nanopost arrays used as alternative DIOS substrates and showed that structure specific fragmentation can be also be induced. ( 71 ) In another study He et al. have used electron beam lithography (EBL) and nanosphere lithography to investigate the impact of the surface morphology of porous silicon on an alyte desorption and ionization. ( 72 ) Electron b eam lithography allows accurate fabrication of sub 100 nm features, but the serial nature of the technique makes it very slow. In the nanosphere technique, the self assembly can be very time consuming, and long range order is still not achieved. Self order ed porous alumina substrates have also been used as useful platforms for laser desorption/ionization MS. Because Wada et al. found that surface electroconductivity was one of the requirements for a porous alumina chip to be effective for laser induced des orption/ionization, the surface was coated with gold or platinum ( 73 ) Masuda et al. suggested that the porous alumina layer beneath the surface metal probably acted as a thermal insulator ( 74 ) In this chapter the fabrication of porous silicon by a non lithographic method using a self ordered porous alumina membrane and its application for laser desorption ionization mass spectrometry is discussed The self ordered pore pattern of the alumina membrane is transferred into the silicon substrate via the plasma etching method, resulting in rapid, low cost and reproducible fabrication without the use of toxic chemicals. Pore size and porosity are comparable to that of the alumina mas k and the pore depth can be controlled in the range of 10 nm to 50 nm by changing the etch time. The porous silicon platforms with 10 nm, 30 nm and 50 nm depth nanowells were used


50 for laser desorption/ionization (LDI) MS detection of biomolecules. To the b est of our knowledge laser desorption ionization at this depth regime has not been reported before and the submicrometer porosity limit to induce ionization is yet unclear. The utility of nanowell arrays under atmospheric pressure and vacuum regimes were s tudied. Experimental Methods Materials Aluminum foil (99.99%) was obtained from Alfa Aesar. Single side polished P/Boron t ype silicon wafers, having 100 orientation, low resistivity (0.01 thicknesses and 100 mm diameter were obtaine d from Silicon Valley Microelectronics, Inc. (Santa Clara, CA). Phosphoric acid, sulfuric acid, chromium trioxide, oxalic acid and hydrogen peroxide were obtained from Fisher Scientific. Triton X 100, adenosine, Pro Leu Gly tripeptide and [ Des Arg 9 ] bradyk inin were obtained from Sigma Aldrich. Stock solutions (500 pmol/L) of these analytes were prepared by dissolving each compound in 1:1 acetonitrile:aqueous 0.1 % trifluoroacetic acid solution. Bovine serum albumin (BSA) was obtained from Sigma Aldrich. In Solution tryptic digestion and guanidination Kit was obtained from Pierce and digestion of 10 g of BSA was carried out using manufacturer's instructions. A carnitine metabolite cocktail containing carnitine, butyrylcarnitine, octanoylcarnitine decanoylca rnitine, myristoylcarnitine, palmitoylcarnitine, stearoylcarnitine (5 ppm each) and red blood cell extracts were provided by Dr.Peggy Borum (University of Florida) as a kind gift and used without any further treatment. Reference standard solution of fentan yl (1.0 mg/mL in methanol) was obtained from Restek and used with further dilution in methanol.


51 Preparation of the Porous Alumina M ask The alumina mask was an in house prepared nanopore alumina film. The electrochemical anodization method used to prepare these films has been described previously. ( 75 ) The same procedure was followed for preparation of the alumina masks. Fabrication of the nanowell arrays on silicon substrates.Silicon wafers were cleaned in a piranha solution (3:1 (v/v) 98% H 2 SO 4 : 30% H 2 O 2 ) for 30 min. The silicon substrates were rins ed with deionized water, followed by drying under a stream of nitrogen. The alumina mask was mounted on top of the silicon wafer with the barrier layer side of the mask facing up using a drop of Triton X 100 solution as an adhesive. The masked substrate wa s then inserted into the vacuum chamber of a reactive ion etching apparatus (Samco model RIE 1C). Ar plasma was used to etch the substrate surface through the mask with the following etching parameters (13.56 MHz, 100 W, 10 Pa, 12 sccm Ar flow). The etch time was varied (5, 10, 15, 20, and 25 mins, respectively) in order to determine the etch rate of silicon under these conditions. The alumina mask was removed by the use of sonication in water for 10 min. The silicon substrates were rinsed with nanopure wa ter and ethanol followed by drying with a stream of nitrogen gas. Porous silicon substrates were stored in ethanol and they were re dried by N 2 flow just prior to mass spectrometry experiments. Fabrication of d esorption/I onizat ion on Silicon (DIOS) S urface s To provide a benchmark for comparison, standard DIOS surfaces have been prepared Briefly, low resistivity (0.01 sputter coated with 30 with a Desk II Cold Sputter instrument (Denton Vacuum, LLC) and chemically etched using the HOME method with a solution of 1:1:2 EtOH/HF (49%)/H 2 O 2 (30%) for 30 s.


52 Cha racterization of P orous S urfaces Tapping mode Atomic Force Microscopy (AFM) was used to examine the morphology and depth of the nanowell array on silicon substrates. In order to investigate the etch rate, three porous silicon samples were prepared at each etch time. Average depth of wells (at least 450 nanowells) for each etching time was obtained from three different positions of each sample. AFM experiments were performed using a Multimode AFM with a NanoScope IIIa controller (Digital Instruments, Santa B arbara, CA) and MPP 11200 Si tips (Veeco, manufacture suggested tip radius is r < 10 nm). Height images were obtained in the tapping mode under dry N 2 gas. The nanowell depth was assessed using the profile analysis made by the WSxM image analysis package ( Nanotec Electronica, Madrid, Spain). A Hitachi S4000 FE SEM was used to obtain the pore diameter and the thickness of the alumina mask. Both the top view and the cross section of the alumina membrane were investigated. All samples were coated with an Au/Pd film by a Desk II Cold Sputter instrument (Denton Vacuum, LLC). Synthesis of DNA Aptamers GGTTGGTGTGGTTGG GAC AAG GAA AAT CCT TCA ATG AAG TGG GTC 3` wa s used as a negative control. Both of the aptamers were coupled fluorous modifier and FTIC flurophore dye An ABI 3400 DNA/RNA synthesizer (Applied Biosystems, Foster City, CA) was used for the synthesis of all DNA sequences. A ProStar HPLC instr ument (Varian, Walnut Creek, CA) with a C18 column (Econosil, 5u, 250 4.6 mm) from Alltech (Deerfield, IL) was used to purify all aptamers A Cary Bio 300 UV spectrometer (Varian, Walnut Creek, CA) was used to measure absorbances to quantify the manufact ured sequences. All oligonucleotides were


53 synthesized by solid state phosphoramidite chemis sequences were then deprotected in AMA (ammonium hydroxide/40% aqueous methylamine 1:1) at 65 C for 20 min and further purified with reverse phase HPLC on a C 18 column. Slide Scanning and Data A nalysis After being spu n dry, the fluorescence signals were recorded with a microarray scanner (Agilent) or epifluorescent m icroscope ( Leica ) equipped with FTIC filter cube The gain of the photomultiplier tube (PMT) was set to a fixed value while comparing different spots For mation of Fluorous Derivatized Glass S lides Glass slides were first cleaned by immersion in to piranha solution ( 3:1 mixture of concentrated sulfuric acid H 2 SO 4 with hydrogen peroxide H 2 O 2 for 1 h. This was followed by washing with copious amounts of water. The slides were then immersed into a s olution of 60% ethanol containing NaOH (10 g/100 mL). The slides were washed twice in distilled water and then submerged in 95% ethanol. Cleaned slides were immersed thre e times in a solution of RF 8 ethyl SiC l 3 (10 % s olution 100 mL in methanol) and then dried for a few minutes; the process was repeated two more times. The slides were then washed twice by immersion in MilliQ filtered water and baked at 120C then dried in a dessicator at room temperature. Formation of F luorous Based Aptamer Arrays on Glass S lides Fluorous tagged aptamers were dissolved in a buffer resembling physiological conditions which contains 25 mM Tris HCl at pH 7.4, 150 mM NaCl, 5 mM KCl, 1mM MgC l 2 1mM CaCl 2 tion dissolved in binding buffer was spotted manually with a manual pipettor on the the fluorous glass slide as


54 just explained and kept in a humifying chamber overnight for incubation. After that slides were washed with SSC ( saline sodium citrate) buffer a nd d e ionized water respectively by simply pipetting 1 l of each up and down S ubsequent slide processing steps were performed in dark to prevent bleaching of the fluorophores. After 30 mins of incubation time slides were washed with water and dried for su bsequent analysis. NIMS Surface Preparation Low resistivity (0.01 cm) P type (Boron) silicon from Silicon Quest was etched with 25% hydrofluoric acid in ethanol (these and other solvents were obtained from Fisher Scientific), using extreme caution a nd employing a Bio Rad Power Pack 1000 with 48 mA/cm 2 (2.5 x2.5 cm chip ) for 30 min. The etched surface was rinsed with methanol, dried with a jet of nitrogen. The initiator bis (heptadecafluoro 1, 1, 2, 2 tetrahydrooctyl) tetramethyldisiloxane, purchased from Gelest, was added to the surface for 2 hours an d then blown off with nitrogen. For aptamer enhanced NIMS analyses fluorous tag carrying cocaine aptamer was spotted onto the NI MS chip and incubated overnight in a humidifying chamber. After that, the s lides were washed with 100 l water and 100 l binding buffer. 1 l of cocaine spiked plasma sample spotted onto aptamer modified NIMS chips and incubated for 30 min to ensure complete binding at room temperature. After this step the N IMS chips were washed with 100 l of water 3 times and dried for mass spectrometry analyses. Mass Spectrometry Mass spectra at atmospheric pressure were acquired using an Agilent 6210 MSD time of flight (TOF) mass spectrometer configured for ESI (Agilent Technologies Inc., San ta Clara, CA, USA). Laser desorption/ionization experiments were conducted by installing an external MassTech atmospheric pressure/matrix assisted laser desorption


55 ionization pulse dynamic focusing (AP/MALDI PDF) ion source. The results were analyzed using Analyst software. Mass spectrometry experiments in the vacuum regime were conducted using either an ABI 4700 MALDI TOF/ TOF or ABI/SCIEX 5800 MALDI TOF/ TOF (Applied Biosystems, Framingham, MA) equipped with an Nd:YAG laser (355 nm, 3 7 ns pulses) which wa s operated in the reflector, positive ion mode with an acceleration voltage of 20 kV. The laser was operated at a fixed pulse rate at 200 Hz. The laser laser were aligned before spectral ac and baseline corrected with Data Explorer 4.0. Results and D iscussion Characterization of the Alumina M ask Figure 2 1 shows representative SEM images of the mask prepared for etching The pores were forme d in a hexagonally packed array. Image J software (Wayne Rasband, NIH, USA) was used to characterize the morphology of the alumina membrane: pore diameter (80 5 nm); pore density ((9.3 0.3) 109 po res/cm 2 ); porosity (48 2 %). These films have t wo di stinct surfaces. Figure 2 1 shows the surface that faced the solution during the anodization, and that faced the Al substrate initially has a film coating which mus t be removed du ring processing. In Figure 2 1 the cross section of the film indicates that the thickness was 2.3 m and that the pores were cylindrical. Fabrication and Morphology of Porous Silicon S ubstrates In Figure 2 2, AFM images show the surface characteristics of the silicon nanowell array: density (6.0109 nanowells/cm 2 ), diameter (937 nm), and porosity


56 (44%). According to surface characteristics from AFM images, the pore pattern of the alumina mask was successively transferred into silicon sub strates. The pore size, pore density and porosity of porous silicon are compatible to those of alumina mask. The pore diameter showed a narrow distribution. Moreover, as shown in Figure 2 3, as the etching time was increased the depth of nanowells increas ed linearly while the array pattern remained unchanged. Mass Spectrometry A nalyses Porous silicon substrates wer e prepared by etching for 5 min (depth = 10 nm) and 15 min (depth = 30 nm) and 25 min (50 nm). Silicon nanowells were spotted with 0.2 uL of 5 pmol/uL solutions of adenosine, Pro Leu Gly tripeptide and bradykinin, and the samples were dried in room temperature for 30 mins prior to analyses. For atmospheric pressure laser desorption versus vacuum laser de sorption comparison experiments, 0.2 uL of 500 pmol/uL solutions of the respective analytes were used. A schematic of the entire process is shown in Figure 2 4. The mass spectra of adenosine acquired on 10 nm, 30 nm, 50 nm nanowell surfaces and DIOS surface are shown in Figure 2 5 indicate s that an increase in etching time provides a significant improvement in the ion signal. Analyses with the 10 nm deep pores were repeated with concentrations from 1 pmol to 500 pmol and with various laser attenuations, but no significant improvement was observed. I n a recent report on the thermochemistry of adenosine, it was shown that a significant amount of energy has to be imparted to induce protonation. ( 76 ) The authors reported the proton affinity of adenosine as 979 1 kJ/mol in the gas phase by using nano ESI MS. In the light of these findings, we can hypothesize that for the surface etched to a depth of 10 nm, the surface induced heating does not provide sufficient energy to desorb the molecule from the surface and ionize it. However, when


57 the etching time was increased and the same experiment was conducted using 30 nm and 50 nm deep nanowel ls and DIOS surface, significant ion signals for protonated adenosine [M+H] + before (268.1054) and adenine after (136.0594) loss of the ribose group were observed. Similar behavior was observed on DIOS surfaces as well. After this experiment, analyses on the nanowell surfaces were extended to two different compounds: Pro Leu Gly ([M+H] + = 285.1921) and [ Des Arg 9 ] bradykinin ( ([M+H] + = 904.4691). Similar to adenosine, 0.2 uL of 5 pmol/u L of Pro Leu Gly and [ Des Arg 9 ] bradykinin were spotted on the nanowell s and the attenuation of the laser was fixed. The mass spectra are shown in Figures 2 6 and 2 7. The mass spectra for the two compounds clearly show that the ion signals significantly increase with increasing pore depth and electrochemically etched DIOS su rface gave higher intensities in all analyses. DIOS surfaces are well characterized previously and have surface features of 200 nm deep. This result led us to think about the events associated with laser desorption/ionization and the effect of increased na nostructuring on the ion signals. Northen et al.reported that the surface area is the key factor. ( 77 ) They demonstrated that the submicrometer surface porosity, irrespective of the substrate material, is the most important effect for desorption/ionization. In the most similar report to our work it was demonstrated that silicon wafers roughened with sandpaper can act as a surface for laser desorption. ( 73 ) An increase in surface porosity enhances ion signals via multiple effects: The surface is resupplied with analyte after a laser pulse, and a local environment for the laser induced fiel d is provided to facilitate physical separation of preformed analyte ions from their counterions. Also, the heat capacity and heat conductivity are decreased when rapid heating of the surface occurs,


58 resulting in effective sublimation of analytes by laser irradiation as well as effective absorption of the laser light. Recently Hsu et al. showed that laser desorption ionization can occur even on metals. ( 78 ) They showed that although ion signals greatly improve with surface roughness ionization can occur even on a commercial non porous aluminum film. Our results are in good agreement with these previous findings. In addition to unique energy absorbing properties of porous surfaces, nanostructuring also helps to create a thin layer when analytes are spotted and thereby the interaction between the surface and analyte is facilitated resulting in more efficient ionization. This fact has been shown very recently. ( 79 ) Significant dimer and trimer signals are observed in Figures 2 6 and 2 7. Since the ionization event occurs at atmospheric pressure, it is possible that ion ion reactions occur after the desorption event, and that dimerization and trimerization are favored. Desorption ionization on porous silicon is mostly carried out in MALDI instruments operating under vacuum regime and only a few reports exist about atmospheric pressure DIOS and to d ate no comparision yet exists. Since the concentrations of the analyte solutions are low, this is probably not due to the concentration effect. To investigate this factor, a vacuu m MALDI instrument was used both to check the effectiveness of the surfaces in vacuum conditions and to make a comparison between atmospheric pressure and vacuum MALDI regimes. Comparison of atmospheric pressure and vacuum spectra, shown in Figure 2 8 Fig ure 2 9 and Figure 2 10 indicates that a significant difference exists between atmospheri c pressure and vacuum regimes. Because the dimer and trimer signals did not appear in vacuum regime, these peaks were due in part to atmospheric pressure conditions


59 Application of the Nanowell Arrays for Complex B iological Mixture A nalysis After investigating the ionization efficiencies with increasing pore depth, we applied our nanowell array surfaces for real biological sample analyses. Carnitines serve as important biomarkers for metabolic disorders and there is a growing interest in the analysis of carnitines in complex biological samples ( 80 ) Because of the much larger signal to noise ratios, the nanowells with 50 nm pores were used for these measurements. For this purpose, 0.2 L of the stan dard carnitine metabolite cocktail (contaning 5 ppm of each) was spotted on our surfaces. Theoretical masses of the carnitines are given in Table 2. 1 We can clearly see in Figure 2 11 that carnitine standard can be successfully analyzed with a very clear b ackground and no interfering peak which is the major drawback of the MALDI for metabolomics. We then analyzed 0.2 u L of 5 pmol/ u L tryptic digest of bovine serum albumin on 50 nm deep nanowells and many of the tryptic peptides were observed and it is worthn oting that no peak was observed at the low mass range as shown i n Figure 2 12 To further demonstrate the analytical applicability of nanowell arrays we spiked varying concentrations of the illicit drug fentanyl [M+H] + = 307.2220 (ranging from 10 ng/mL to 1. 5 g/mL) into red blood cell extract and by applied it onto our surfaces using Z touch method and then analyzed. Figure 2 13 shows spiked fentanyl in red blood cell extract (200 ng/mL) and the corresponding calibration curve. As can be seen in this data t he nanowell surfaces show good linearity for the analysis of fentanyl in complex biological mixtures Unifying NIMS a nd Aptamer Assisted C apturing Use of flurous chemistry for affinity mass spectrometry applications is a new approach that has been proven s uccessf ul in recent years. ( 81 82 ) The most notable


60 example is named nanostructure initiator mass spect rometry (NIMS) which relies on fabrication of a nanostructure d porous silicon sur f ace and modifying this surface with a ( 83 ) This resulted in a very sensitive platform for the analysis of metaboli has also been applied as a new noncovalent immbolization strategy to create sugar microarrays, to study histone deacetylases and also for assembling nanopart icles for DNA capture. ( 84 86 ) The main advantage of f luorous surface s is that they limit nonspecific interactions to a great extent but still allow the faci le noncovalent attachment of flurous modified compounds. So we wanted to tether aptamer s onto NIMS surfaces to create a mass spectrometry platform that will build upon the selectivity of the aptamers and sensitivity of NIMS. We also incorporated a spacer between the fluorous anchoring group and the aptamer to bring the aptamer away from the slide surface so that aptamers can interact with their targets similar to solution phase environment. The general structure of the fluorous tagged aptamers substrates u sed for immobilization onto NIM S surfaces is shown in Figure 2 14. As can be seen from the Figure 2 15 that aptamers can stick onto flourous glass surfaces and even after washing they do not get washed away. However the interactio ns were not very strong and we observed spiky spots This might be ascribed to the improper orientation of the aptamers to bind their targets. Even though fluorous fluorous interactions are very selective and binding onto fluorous surface s occur only by a fluorous group, strengt h of fluorous interactions are not compa rable to that of covalent bonds. Initial work using fluorous chemistry field were done by small molecules like carbohydrates, peptides so there is no existing literature report about immobilization of


61 bigger molecule s such as proteins or oligonucleotide on to fluorous surfaces through fluorous linkers. ( 87 88 ) Failure to get good immobilization onto fluorous glass led us to think about alternative ways about this immobilization strategy. The first option is to change the surface and the second option is to introduce multiple fluorous linkers on the aptamers ` s tructure Rece nt data has shown that multiple fluorus tag s significantly improve fluorous based immobilization. ( 89 ) We therefore introduced multiple fluorous tag to the aptamer structure to improve the immobilization The succesfull incorporat ion of double and triple fluorus tags into aptamer structure was monitored by using HPLC. The peak position at which the fluouros aptamers are eluted from the column shifted o n the ord er of single, double and triple fluorous linker carrying aptamers. The r esults are depicted in Figure 2 16 and Figure 2 17 and Figure 2 18. After showing that aptamers can be attached onto fluorous tags, the next step was to use in them in combination with NIMS. W e have spotted triple fluorus tag carrying cocaine aptamer onto NIMS surfaces as explained in the experimental part A fter washing step s we treated the aptamer modified NIMS surface with plasma samples containing 10 M cocaine. However the mass spectra as shown in Figure 2 19 were dominated with too m any background ion s in sharp contrast to literature findings about NIMS. The results and the source for background ions were initially unclear for us and we attributed this to unsuccessful capture or inproper washing conditions. We performed initial experiments using an at mospheric pressure MALDI instrument. As opposed to vacuum MALDI instruments the source region and ion transfer capillary is held at atmospheric pressure conditions and also kept at fairly high temperatures ( >200 C). The initiator bis (heptadecafluoro 1, 1, 2, 2 tetrahydrooctyl) tetramethyldisiloxane has a boiling


62 temperature of 306 C. Therefore we think that at this temperature volatile initiator molecules escape from the nanoporous silicon surfac e which leads to ionization of initiator and decompositio n products therefore no significant signal can be observed. We repeated the experiments as just discussed using 5800 ABI/SCIEX MALDI TOF/TOF instr ument which operates under vacuu m. As can b e seen in Figure 2 20 results greatly improved and we can clearly s ee the enrichment and clean up effect of aptamers in capturing target species from cocaine spiked plasma samples. T he applicability of nanowell silicon substrates for desorption/ionizatio n on silicon mass spectrometry has been demonstrated. The pore patte rn of an alumina mask has been successively transferred onto silicon substrates by means of Ar ion plasma etch This method has several advantages: (1) elimination of toxic HF ; (2) reproducibility (uniform p ore size, pore density, and poro sity); and (3) lo w cost and fast production. The n anowell depth is linearly related to etch time. The etch rate was determined to be 2.0 nm/min with about 2 m thick AAO mask. The pore depth requirement for inducing laser desorption ionization has not been well addressed b efore and our results show that very little porosity (10 nm) is sufficient to induce ion formation and the ion signals significantly improve with the change of the pore depth. We also showed that a reasonable level of sensitivity has been achieved with 50 nm deep nanowells. Comparison of nanowell arrays and DIOS surfaces show that ionization is more favored with nanostructures having deeper pores however even with a slightly nanostructured surface ionization takes place (10 nm deep nanowells.) The mechanis m of ion formation on nanowell arrays is still not clear but we attribute the ion formation to unique thermal and optical properties of silicon. We are in


63 the process of systematically investigating the effects of pore size pore depth and pore density by changing the AAO mask and by controlling the aspect ratio of the nanowells using different substrates. Our initial findings suggest that nanowell arrays are suitable substrates for laser desorption ionization of biomolecules and can be used for the analysi s of small molecules, metabolites and peptides. We also showed that fluorous chemistry can be used for immobilization of aptamers onto fluorous surfaces which could be potentially used as a new chemistry for making protein and DNA microarray surfaces. We a lso demonstrated that sensitivity and matrix free features of the NIMS method is compromised when experiments are conducted under atmospheric pressure conditions. Finally aptamer enhanced nanostructure initiator mass spectrometry has been demonstrated as a proof of concept experiment.


64 Figure 2 1 Scanning electron micrographs of the alumina mask: Top view of (A) outer surface and (B) barrier layer surface, and (C) cross section.


65 Figure 2 2 Tapping mode AFM images of nanowell arrays on silicon subs trates prepared by means of Ar ion plasma etching for: (A) 5 mins, (B) 15 mins, and (C) 25 mins.


66 Figure 2 3 Nanowell depth versus etch time


67 Figure 2 4 Workflow for the preparation of nanowell arrays and MS analysis.


68 Figur e 2 5 Mass spectra o f adenosine acquired on 10 nm, 30 nm, 50 nm deep nanowells and a DIOS surface


69 Figure 2 6 Mass spectra of adenosine acquired on 10 nm, 30 nm, 50 nm deep nanowells and a DIOS surface


70 Figure 2 7 Mass spectra of adenosine acquired on 10 nm, 30 nm, 50 nm deep nanowells and a DIOS surface


71 Figure 2 8 Comparison of atmospheric pressure and vacuum regime laser desorption ionization on 30 nm deep nanowell arrays for adenosine.


72 Figure 2 9 Comparison of atmospheric pressure and vacuum regime laser des orption ionization on 30 nm deep nanowell arrays for Pro Leu Gly.


73 Figure 2 10 Comparison of atmospheric pressure and vacuum regime laser desorption ionization on 30 nm deep nanowell arrays for [ Des Arg 9 ] bradykinin


74 Fig ure 2 11 Analysis of carniti ne standard solution on 50 nm deep nanowell array.


75 Figure 2 12 Analysis of tryptic digest of BSA on a 50 nm deep nanowell array. Peaks labeled with (*) denote tryptic peptides.


76 Figure 2 13 Mass spectrum of fentanyl in a red blood cell extract (20 0 ng/mL) obtained on a 50 nm deep nanowell array.


77 Figure 2 14 Schematic representation flu o rous aptamers. Figure 2 15 Immobilization of single fluorous tag carrying aptamers.


78 Figure 2 16 Seperation of single, double and triple fluorous tag containing aptamers


79 Figure 2 17 Sepa ration of single, double and triple fluorous tag containing aptamers


80 Figure 2 1 8 Immobiliization of triple flurous tag carrying aptamers onto glass slides


81 Figure 2 19 Aptamer enhanced NIMS under atmospheric pressure


82 Figure 2.20 Aptamer enhanced NIMS under vacuum Figure 2 20 Aptamer enhanced NIMS under vacuum


83 Table 2 1 Name of the carnitines analyzed and their respective molecular weights Name of the Carnitine Molecular weight (m/z) Carnitine (C1) 162.1125 Butyrylcarnitine (C4) 232.1543 Octanoylcarnitine(C5) 288.2169 Decanoylcarnitine(C6) 316.2482 Myristoylcarnitine(C9) 372.3108 Palmitoylcarniti ne(C10) 400.3421 Stearoylcarnitine(C11) 428.3734 Decanoylcarnitine(C6) 316.2482


84 CHAPTER 3 A DUAL PLATFORM FOR SELECTIVE ANALYTE EN RICHMENT AND IONIZAT ION IN MASS SPECTROMETRY US ING APTAMER CONJUGATED GRAPHENE OXIDE io nization techniques namely, matrix assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) revolutionized biological research by rendering the st udy of biomolecules feasible. These innovative mass spectrometry techniques have found w idespread use in many different areas including genomics, transcriptomics, p roteomics and metabolomics. However, despite the power of mass spectrometry, identification of species of interest among a vast number of other molecules for subsequent functional characterization still remains as one of the most challenging tasks. To address this problem extraction and fractionatio n methods are often applied However since they lack of specificity, the best option would be the use of affinity reagents tethered on a substrate which mass spectrometry readout can be obtained. So far different kinds of affinity reagents have been applied in different formats such as mass spectrometric immunoassay (MSIA) ( 90 ) nanoprobe affinity mass spectrometry ( 91 ) and surface enhanced laser de sorption/ionization (SELDI). Aptamers are single stranded oligonucleotides that bind target molecules with very high affinity similar to antibodies. They are generated by an iterative proc ess called against various targets including metal ions, metabolites, protein s and even whole cells. Aptamers have very distinct advantages over antibodies that they can be pr oduced without the need of an animal source, can be chemically modified with various functional groups, smaller size, non toxic, non immunogenic and have faster tissue penetration, all these unique properties make them ideal candidates among other affinity reagents. Aptamer modified nanomater ials as detection platforms for targeted


85 analyte capture have been previously used in mass spectrometry. Recently GO joined the bandwagon as a subs trate for analyte detection owing to its unique electronic, thermal and mechanical properties and so has been reported as an excellent subst rate for mass spectrometery (MS). In this chapter aptamer modified GO as a selective enrichment and matrix free detection platform for affinity mass spectrometry is discussed. Experiment al Mass Spectrometry Mass spectra under atmospheric pressure conditions were acquired using an Agilent 6210 MSD time of flight (TOF) mass spectrometer configured for ESI (Agilent Tech nologies Inc., Santa Clara, CA). Laser desorption/ionization experiments were conducted by installing an external MassTech atmospheric pressure/matrix assisted laser desorption ionization pulse dynamic focusing (AP/MALDI PDF) ion source. The results were analyzed using Analyst software. All mass spectra in the vacuum regime wer e acquired using a MALDI TOF/TOF mass spectrometer (ABI/SCIEX 5800, Applied Biosystems, Foster City, CA). A Nd:YAG laser at 355 nm was used. The spectra were recorded in reflection mode in either positive or negative mode usi ng an accelerating voltage of 2 5 kV, a 62% grid voltage, and a 100 ns delay extraction. Typically, 30 80 laser shots were collected per spectrum. Applied Biosystems c alibration m ixture 1 was used to calibrate the mass spectrometer. Data analy sis and was performed using Data Explorer sof tware


86 Transmission Electron Microscopy GO was treated by ultr a sonication for 24 hours before any surface modification, to ensure small size and homogeneous dispersibility. TEM images were taken with a JEOL TEM 2010F transmission electron microscope on a copper grid. PEGylation of Graphene Oxide Before starting the modifica tion, the GO solution (1mg/mL) was sonicated for approximately 24 hours. Then 100 L of GO solution (1mg/mL) wa s treated with 0.0022 M EDC and 0.0015 M NHS in PBS (pH =7.4) buffer. After the activation of ca rboxyl groups, the solution wa s treated with 130.6 M HS PEG NH 2 After 1h incubation, the solution is centrifuged and washed room temperature for 4 times at 14000 rpm and for 4 minutes to discard the supernatants, which consist of the unbound PEGs to the surface of GO, each time 450 L of PBS is added for each washing step and the last solution is prepared with 100L of PBS (pH = 7.4). Aptamer Synthesis The cocaine and adenosine aptamers have been used in aptamer assisted extraction e xperiments. ( Adenosine ACC TGG GGG AGT ATT GCG GAG GAA GGT Cocaine, GGG AGA CAA GGA AAA TCC TTC AAT GAA GTG GGT CGA CA 3 respectively.) thiol modifier for graphene oxide modification and also the same ap tamers are synthesized and labeled with (6 fluorescein) CPG to detect the modification on graphene oxide surface. An ABI 3400 DNA/RNA synthesizer (Applie d Biosystems, Foster City, CA) was used for the synthesis of all DNA sequences. A ProStar HPLC (Varian, Walnut Creek, CA) with a C18 column (Econosil, 5 m, 250 4.6 mm) from Alltech (Deerfield, IL) was used to purify all fabricated DNA. A Cary Bio 300 UV


87 spectrometer (Varian, Walnut Creek, CA) was used to measure absor bance to quantify the concentrations of the obtained sequences. All oligonucleotides were synthesized by solid state phosphoramidite chemistry at a 1 mol scale. The completed sequences were then deprotected in AMA (ammonium hydroxide/40% aqueous methylami ne 1:1) at 65 C for 20 min and further purified with reversed phase HPLC on a C 18 column. Aptamer C onjugation to PEGylated Graphene Oxide s modified with disulfide functional group during the aptamer synthesis process. So befo re the reaction with the thiol groups at the tips of aptamers should be cleaved to gi ve thiol groups. For this purpose, 100 M disulfide modified aptamers were treate d with 5 mM of TCEP in 50 mM Tris/HCl (pH=7.5) buffer for 1 hour at room temperature. Then the desired thiol modified aptamers are collected in small portions by eluting the TCEP mixture through a NAP 5 column. The concentrations of these portions are calc ulated by taking their UV absorption spectra. The 100 L of the PEGylated GO that is obtained at the first step is incubated with 1 M of thiol modified aptamers that is obtained in the third step, in 200 L of PBS (pH= 7.4) buffer for 2 hours. After this incubation the unbound aptamers were removed by excessive centrifuging and washing steps. Aptamer Assisted Target E xtraction Universal Coagulation Reference Plasma (UCRP) was obtained from Thermo Scientific 500 L of the plasma sample was spiked with 500 L of 20 M of cocaine and 500 L 20 M adenosine separately i n two different eppendorf tubes. They are then vortexed to ensure complete mixing. In all experiments 100 L of GO (1 mg/ml in water) was first centrifuged at 4000 rpm for 15 mins and supernatan t was taken out and then


88 GO was redispersed in 100 uL of the binding buffer ( 20 mM Tris HCl, 140 mM NaCl, and 2 mM MgCl 2 pH: 7.5 ). For target extraction experiments 50 L of GO (with or without aptamer modification) was mixed with the 50 L of target spik ed plasma and gently mixed for 30 mins by occasional vortexing at every 10 mins. After that mixture was vortexed at 4000 rpm for 15 mins GO pelletted, supernatant was taken out and GO and washed with 100 L of binding buffer followed by 100 L of washing w ith water. Finally the GO was centrifuged at 14000 rpm for 10 mins, supernatant was taken out and resulting GO was redispersed in 10 L of H 2 0 (in %0.1 TFA) and 2 L of that GO suspension was pipetted onto the sample plate. It was left at room temperature for 20 min until dryness and laser desorption ionization experiments were carried out. Synthesis of Au, Cu, Pt, and Au/Cu/Pt Alloy and CdTe D erivatives of GO Au GO s ynthesis DNA 1: GCGCGCTT FITC 2 : TTACACGAGGGGGT 5 were m ixed together at the same concentration (1M) to obtain double stranded DNA(dsDNA) via hybridization in 10 mM HEPES buffer (50mM NaNO 3 pH 7.5) for 30 min. Then graphene oxide (GO) (final conc entration of graphene oxide was 20 g /mL in DNA solution), was added for adsorption of ds DNA on the GO After 30 min incubation, the mixture was centrifuged and excess DNA in the supernatant was decanted The gold precursor, HAuCl 4 .3H 2 O, was used with sodium citrate to form Au NPs on dsDNA GO. HAuCl 4 .3H 2 O solution was put in dsDNA GO mixture with final concentration of 100 M Au +3 and the mixture was stirred for 5 minute. The freshly pr epared reducing agent solution 500 M (s odium citrate ) was added in a dropwise manner for 30 min with vigorous stirr ing. Purification w as the same as described above.


89 Cu GO and Pt GO synthesis The pro tocol given above was followed except CuSO 4 and PtCl 4 were separately reduced on dsDNA GO using s o dium L ascorbate as reductant. The f inal concentration s of metal ions ( Cu +2 or Pt +4 ) and re ducing agent in mixtures were adjusted to 1 00 M and 500 M respectively. Au/Cu/Pt alloy GO The 100 M each metal ion, Au +3 Cu +2 and Pt +4 solutions were simultaneously added into the dsDNA GO mixture stated above with vigorous stirring. After 10 mi nut e incubation, reducing agent 500 M ( s odium L ascorbate) was added dropwise to mixture for 30 minute stirring CdTe GO synthesis For a typi cal CdTe synthesis, 400 ml CdCl 2 GSH stock solution was mixed with 0.8 ml of freshly prepared NaHTe solution in a 0 .7 ml eppendorf tube and then DNA solution containing 120 nmol nucleotides was added on GO. Synthesis of Benzylpyridinium S alt (BP) and SY E xperiments 12 mL of pyridine was mixed with benzyl chloride at a molar ratio 20:1 (pyridine/benzyl chloride), reflux ed at 60 C for 6 h. The BP was collected by removal of excess pyridine with rotary evaporation under vacuum and used to prepare 1 mM methanolic solution. GO metal conjugates were washed with copius amounts of water and ethanol and metal co njugate (1 mg/ ml for each ) was spotted onto MALDI plate and metal conjugates and analyzed by using the same instru mental conditions by only varying the laser fluence.


90 LDI MS Analysis of P roteins on CdTe GO Bradykinin acetate, Insulin beta chain, bovine serum albumin were used as the model compounds After spotting plate, 1 o f each ( 10 pmol / ) compound was spotted onto CdTe GO dried under ambient con ditions, subjected to LDI MS analysis under the same experimental conditions. Results and D iscussion Testing GO as M atrix for LDI The first step of the experiments in this part was to show that graphene can be used as a matrix for small molecule analysis Carbon nanotubes and diamond like carbon films have been previously used for LDI analysis. To demonstrate that graphene oxide (G O ) can be used as matrix for las er desorption ionization, a series of small molecules including glucose, caffeine glutathion e were analyzed using GO as an effic ient energy absorbing molecule. The mass spectra a re shown in through Figures 3 1 to 3 3 It can clearly be seen that GO serves as an excellent substrate for LDI of small molecules. To eliminate the possibility of self i onization we also spotted the same compounds on stainless steel plate and analyzed. The spectra show no discernible signal associated to these compounds. The results were also compared to the MALDI analyses. When LDI on GO is compared with MALDI, significa nt amount of background peaks are seen in MALDI spectra. Characterization of Aptamer M odified GO The results of FTIR spe ctroscopy is shown in Figure 3 4 I t can be seen that the aptamer modification occurred by covalent binding via the disulfide bond forma tion between the thiol groups of the corresponding aptamer and PEG that is previously


91 attached to the surface of the GO with amide bonds. Before aptamer or PEG modification FTIR spectrum of Graphene Oxide has a carboxyl (C=O) stretching peak at around 172 8 cm 1 but after the modification the peak is shifted to 1649 cm 1 which is representing the amide carbonyl stretching mode (a mide I vibrational stretch). Also at around 1557 cm 1 the N H bending and C N stretching vibrational frequencies can be seen ( a m ide II vibrational mode). Since graphene oxide has lots of reactive epoxy groups, its exposure to amine groups can lead to a ring opening reaction of the reactive three membered epoxide ring, forming new C N bonds. The ring opening reaction of the epoxy gr oup due to nucleophilic attack from amine g roups has been well established. After the modification, the increase of the peak intensity at around 1557 cm 1 and the decrease of the peak intensity of the epoxy mode is actually showing that the amine groups ar e not just attaching to the carboxylic group s of GO but also epoxide groups. All of these amide vibrational peaks are the proof for the amide bond formation during the PEGylation of Graphene Oxide. ( 92 ) Other vibrational modes are C O (epoxy) and C O (alkoxy) can be seen at 1203 cm 1 and 1051 cm 1 respectively Also differing from the FTIR spectrum of the GO only, the S S disulfide vibrational mode appeared at 535 cm 1 in the FTIR spectrum of the GO that is modified with the aptamer through the disulfide bond formation. This is also the proof of the aptamer modification by covalent binding via the disulfide bond formation. Aptamer A ssisted LDI on GO Next we immobil ized thiol functionalized cocaine and adenosine aptamers onto GO by activation of carboxyl ( COOH) rich groups using EDC / NHS chemistry and introducing a bifunctional PEG as a spacer molecule, which provides stability in physiological media like serum and blood. Furthermore, the PEG linker also provides


92 freedom to aptamers to obtain a 3D conformation to recognize their targets. ( 93 ) The bifunctional PEG linker carries amine ( NH 2 ) groups on one side to bind to the carboxyl on the GO surface and thiol (SH ) groups to help anchor the SH functionalized aptamers through di sulfide bond formation. Schematics of the whole p rocess can be seen in Figure 3 5 Next, aptamer conjugated GO was applied for selective enrichment and detection of cocaine spiked in human pl asma along with respecti ve control experiments. Figure 3 6 (a) shows the MS analysis of cocaine spiked plasma samples analyzed directly onto GO without any enrichment step (no aptamer modification) where it served only as a matrix. The cocaine peaks can be detected among huge background ions with an average S/N ratio of 15. Figure 3 6(b) also shows the analysis of cocaine spiked plasma extracted and ionized with unmodified GO. As can be seen, even in the presence of unmodified GO, enrichment of the sample w as observed to some extent along with a reduction in background ions. This can be due to the structure of cocaine experiment, GO with physically adsorbed cocaine aptamer wa s used for target extraction, where, following washing steps, no or scantily extracted cocaine with an S/N ratio of 5 was obtained. ( Figure 3 6 (c)). On contrary, GO was shown to physical ly adsorb DNA in high yields. We assume that surface coverage of GO b y physically adsorbed aptamer s prevent the loading of cocaine by means of nonspecific interactions (in case aptamer s upon target capture comes off the GO surface following washing steps due to the absence of any chemical functionalization. However, upon chemical modification of GO with the cocaine aptamer an efficient capture of target analyte was achived with an average S/N ratio of 52. Figure 3 6(d ).


93 The S/N ratio is shown in Figure 3 7 To further demonstrate the analytical utitily of our approach we applied the same concept to adenosine aptamer. As can clearly be seen in Figure 3 8 we observed a very similar trend. This result proves that even if some extraction can be achived with pristine GO, aptamer conjugation yields significantly better extraction efficiency with an increase in S/N increase as shown in Figure 3 9 Formation of A u, Cu, Pt, and Au/Cu/Pt A lloy and CdTe on GO In the previous section we have shown that GO can be a very efficient material for small molecule analysis and by proper chemical modification it can also be tuned as a selective capture and ionization matrix b y aptamers. However the mass range at which GO can perform well is limited to compounds that are below 1000 Da in molecular weight. It is obvious that it will be very useful for metabolomics applications but its use for protein analysis will be limited. T herefore we sought to develop a GO based hybrid material which could also be used for the analysis of proteins To accomplish this u niformly sized Au, Cu, Pt nanoparticles and Au/Cu/Pt alloy structures and GO CdTe structures were produced by reduction of cationic metal ions (Au +3 Cu +2 Pt +4 CdTe ) bound to and accumulated on the main groove of dsDNA with reducing agents. The reaction temperature, reaction time, stirring rate, concentration of each metal ion (100 M) and reductant (500 M) were kept cons tant to synthesize each metal nanoparticle graphene oxide ( MNP GO ) hybrid structures. The TEM images of Au GO and Cu GO and Au Cu Pt GO and CdTe GO samples given in Figure 3 10 show well order ed nanoparticle distributions. T he long reaction time and the i ncrease of concentration of metal ions ma y cause the large particles from aggregative growth of small particles. In other words, when the reaction time is extended and highly concentrated metal ion s olutions are used, small nucleated particles randomly coa lesce with each other or with


94 generated particles before separate growth process and start aggregative growth in dime r, trimers form under stirring. Using considerably concentrated metal ions solutions limits the free space between metal ions and hinders t o nucleate and form single dispersed nanoparticles because there is a favorably strong Van der waals in ter actio n between metal nanoparticles inducing agglom era tion There is no formation of MNPs during the 30 min reaction time at room temp erature in the ab sence of dsDNA. TEM image of pristine GO is inc luded for comparison. The dsDNA provides a homogeneous distribution of Au nanoparticles on the GO surface, but previous studies without dsDNA using different techniques and experimental conditions resulted in nanoparticles on the randomly pre existing f unctional groups on GO surface. Survival Yield C alculations After the synthesis of various GO metal heteroconjugates b enzylpyridinium salt s (BP) w as employed as a model anal yte to determine survival yield to est imate how well the generated intact molecular ions survive avoiding fragmentation under the given condition and how efficiently the analytes are desorbed from the given substrate, respectively. ( 94 96 ) A t ypical fragmentation pattern of B P salt is given in Figure 3 11 It is well known that high survival yield is favored for the development of good LDI system s In our system, survival yield were calculated from th e mass spectra of BP obtained with different graphene derivatives, by dividing the peak intensity of the parent ion by the total mass peak intensities of the fragment and parent ions, and by summing the absolute intensities of the fragment and parent ions, respectively. According to our results we found that CdTe GO gave the best results with a survival yield of 80% whereas GO Cu giving the wor st results as shown in Figure 3 1 2 and Figure 3 1 3


95 Analysis of Proteins U sing CdTe GO Motivated by the high surviv al yield of CdTe GO heterostructures we next sought to apply this for the analysi s of proteins. While we used cocaine and adenosine as the model compounds to demonstrate the aptamer based affinity mass spectrometry aptamer targeting proteins are becoming m ore available and finding a new platform to analyze proteins in the dual format (capture and ionization on the same substrate) will be highly innovative will be very useful for not only metabolomics applications but also proteomics. The results are shown in Figu re 3 1 4 to 3 1 6 As can easily be seen from these data that CdTe incorporation into GO significantly improve s the ionization efficiency of GO. CdTe is an important example of quantum dot (QDs). These materials are nanometer sized crystals made of m etallic or mostly of semiconductor materials QDs have found widespread use in the bioimaging field as highly bright fluorescent materials. Their applications in disease diagnostics, proteomics, genomics, drug delivery, and even drug candidates screening a re increa sing to a great extent. ( 97 ) Very recently QDs were proposed as matrices for laser desorption ionization experiments. ( 98 ) In a similar study to our work HgTe was used to dete ct high molecular weight protein complexes ( 99 ) So our results are ver y consistent with the literature. However mechanistic studi es of the ionization process were not performed in the context of this dissertation so it is yet to be determined. Our results show that GO, whe n combined with aptamer based affinity capture provides an efficient platform for selective enrichment of target analytes and getting direct mass spectrometric readout even from very comp lex media with improved signal t o noise ratios. Since a huge repertoi re of aptamers exist for different targets including proteins, metabolites, and cell surface markers, we believe that the above introduced


96 methodology may also enable multiplexing when screening different biological samples. We also investigated the struct ural factors of alternating by synthesizing different GO hybrids on the LDI MS efficiency of small molecules. Based on the results, we found that by changing the metal identity rather than GO it is possible to obtain more effective substrates which can the n be used for aptamer immobilization and for better performance in protein analysis. The present study is meaningful and serves as an important basis for the development of efficient LDI MS analysis platform by using graphene. Future studies will include d evelopment LDI MS platforms based on graphene optimized for specific samples, for example, oligosaccharides, hydrophobic molecules, and phosphopeptides and also for cell SELEX derived aptamers to capture thei r targets from cellular samples. Investigation o f the ionization mechanism on GO based substrates is another exciting area which might open up new venues and provide some guideline for developing rationally designed nanostructure based materials.


97 Figure 3 1 Analysis of gl ucose on GO A) No matrix B) HCCA matrix C) GO


98 Figure 3 2 Analysis of caffeine on GO A) No matrix B) HCCA matrix C) GO


99 Figure 3 3 Analysis of glutathione on GO A) No matrix B) HCCA matrix C) GO

PAGE 100

100 Figure 3 4 FTIR analysis of aptamer conjugated GO

PAGE 101

101 Figure 3 5 Schematics of aptamer assisted LDI on GO

PAGE 102

102 Figure 3 6. Analysis of aptamer assisted capture of cocain e on GO A) Pla sma B) plasma enrichned by GO (no aptamer) C) Plasma analysis by physically adsorbed aptamer on GO ) D ) Plasma enriched by chemicall y modified aptam er on GO

PAGE 103

103 Figure 3 7. S/N rati os aptamer assisted capture of coc aine on GO (1) spiked int o plasma (2) extracted with GO (3) extracted with non covalently aptamer modified GO and (4) extracted with covalently aptamer modified GO.

PAGE 104

104 Figure 3 8 Analysis of aptamer assisted capture of adenosine on GO A) Plasma B ) plasma enrich ed by GO (no aptamer) C) Plasma analysis by physically adsorbed aptamer on GO) D) Plasma enriched by chemicall y modified aptamer on GO

PAGE 105

105 Figure 3 9 S/N ratios aptamer assisted capture of adenosine on GO 1) spiked into plasma, (2) extracted with GO, (3) extracted with noncovalently aptamer modified GO, and (4) extracted with covalently aptamer modified GO.

PAGE 106

106 Figure 3 10 TEM images of (A) GO (B) Au GO,(C) Cu GO (D) Pt GO E) Au Cu Pt GO f) CdTe GO

PAGE 107

107 Figure 3 11 Fragmentation of BP ions

PAGE 108

108 Figure 3 1 2 Fragmentation of BP ions on different GO derivatives

PAGE 109

109 Figure 3 13 Survival y ield calculations on GO derivatives

PAGE 110

110 Figure 3 1 4 Analysis of bradykinin acetate on CdTe GO

PAGE 111

111 Figure 3 15 Analysis of insulin beta chain on GO (top) and CdTe GO (bottom)

PAGE 112

112 Figure 3 1 6 Analysis o f bovine serum albumin on GO (top) and CdTe GO (bottom)

PAGE 113

113 CHAPTER 4 HYBRID NANOFLOWERS FOR MASS SPECTROMETR Y The analysis of biologically important small molecules and their subsequent detection in complex biolog ical matrices is an area of growing interest This challenging task has traditionally been achieved by optical spectroscopy or electrochemistry techniques such as fluorescence, surface plasmon resonance voltammetry. For example a protocol was developed for label free quantitative analysis of intrac ellular carotenoids in cells of red yeast ( Phaffia rhodozyma ), which makes use of the auto fluorescence of these compounds. ( 100 ) In another study a protein based nanosensor for was developed for the detection of maltose uptake by living yeast cells. ( 101 ) The nanosensor was expressed in yeast cells, allowing direct monitoring of changes in cytosolic maltose concentrations in response to the external supply of nutrient Techniques base d on elect rochemical measurements were also studied extensively. T hey can be used as intra or extracellular probes for label free detection of metabolites present in the cell and those released to the extracellular microenvironment. However, only electroac tive species can be analyzed, which makes the electrochemical methods applicable only to t hose compounds. Moreover oxidation potentials of coexisting species are generally very close to each other and differentiating their electrochemical response is often times very challenging. For example dopamine which is a very important neurotransmitter coexists with other species such as uric acid and ascorbic acid. The oxidation potentials of these molecules interfere with the each other and create a so in overlapping voltammetric response, poor selectivity and reproducibility ( 102 ) O ptical techniques such as fluorescence and surface plasmon resonance generally require fluorescent tags and

PAGE 114

114 surface immobilization which impede their broad applicability. Electrochemistry techniques as just noted a re mostly limited to certain classes of compounds Mass spectrometry methods have emerged as promising alternatives based on their high sensitivity, speed, reproducibility and label free readout they offer. MS techniques have also been shown to be capable of detecting biologically important molecules even in single cells ( 103 ) On the other hand signal suppression effects and need for very careful sample preparation still limit their overall use. N anomaterials have been developed and applied as a tool fo r sample preparation. They ha ve also been used as probes for io nization which allows interference free detection of small molecules especially for metabolomics applications Various different nanomaterials such as gold, platinum, magnetic nanoparticles and carbon based materials suc h as graphite, carbon nanotubes and graphene have been tested in this context This has opened up a relatively d s discussed in previous chapters because of the complexity of the processes a ssociated to ionization mechanistic understanding is still v ery poor. Therefore this recently emerging field req uires new nanomaterials to improve their efficiency in MS and to bet ter understand the ionization with nanostructures. In this chapter t w o iss ues a re addressed. F irst different hybrid nanoparticles were systematically investigated to find an efficient nanoparticle based i onization substrate Second an aptamer based affinity mass spectrometry method was developed to extract important bio molecule s in very complex biological environments such as cancer cells.

PAGE 115

115 Experimental Section Chemicals All chemical were used as received without further purification. Manganese (II) acetylacetonate, oleic acid, oleylamine and phenyl ether, 99%, were obtained f rom Sigma Aldrich. Gold (III) acetate,>99.9% was purchased from Alfa Aesar. Toluene, >99%, from Sigma Aldrich and hexane were provided from Fisher For the synthesis of dopamine PEG COOH, Succinic anhydride, N, N Dicyclohexylcarbodiimide (DCC) and 3,4 Dih ydroxyhydrocinnamic acid (3 (3,4 Dihydroxyphenyl)propionic acid were obtained from Alfa Aesar. O O Bis(2 aminopropyl) polypropylene glycol block polyethylene glycol block polypropylene glycol, 2,3,4,5,6 Pentafluorophenol (Pentafluorophenol, PFP) and 1,4 Dioxane (Diethylene oxide, Dioxane) were purchased from Sigma Aldrich Synthesis of Hybrid N anoparticles Au@MnO nanoflower s Au@MnO nanoparticles were synthes ized following the protocol given elsewhere ( 104 ) with minor modif ications. Briefly, all reactions were completed in standard Schlenk line techniques. The solution of 10 mL of phenylether with 1 mL of oleic acid and 2 mL of oleylamine were injected into 100 mL of three necked flaks containing 1 mM of manganese (II) acety lacetonate and 0.05 mM of gold (III) acetate. The resulting mixture was reflux for 60 min under vigorous stirring. After refluxing, it was allowed to cool down to room temperature. The mixture was precipitated by addition of ethan ol and collected by centri fugation. The precipitated product was re dispersed in toluene. Au@Fe 3 O 4 n anoflowers Au@Fe 3 O 4 nanoparticles were synthesized by following Xie et. al, with minor modification. The solution containing 15 mL of octadecene and 1 mL of oleic acid was

PAGE 116

116 heated at 120 0 C for 20 min under argon flow. Sequentially, 0.3mL of Fe ( CO) 5 and 5 mL of pre synthesized 8 nm Au NPs in hexane were injected. The temperature was raised up to 220 0 C for 15 min and refluxed for 20 min. After refluxing, the mixture was cooled room tem perature and washed with 2 propanol three times by centrifugation. The fin al product was dispersed in hexane. Au Fe 3 O 4 dimer Au@Fe 3 O 4 nanoparticles were synthesized by following ( 105 ) with minor modification. The solution containing 15 mL of octadecene, 1 mL of oleic acid and oleylamine was mixed with 1mL of pre synthesized 5 nm Au NPs, then was heated at 120 0 C under argon flow. Under argon blanket, 0.1 mL of Fe (CO ) 5 was injected. Thereafter, the solution was refluxed f or 30 min before it was cooled room temperature. The nanoparticles were washed with 2 propanol three times by centrifugation. The fin al product was dispersed in hexane. Fe 3 O 4 @Au core shell Fe 3 O 4 @Au nanoparticles were synthesized using the following protoc ol. The solution containing 0. 2075 g of gold acetate, 0,775 g of 1, 2 hexadecanediol, 0.125 mL of oleic acid, 0.75 mL of oleylamine and 8 mL of phenyl ether was mixed with 2.5 mL of phenyl ether reaction solution of Fe 3 O 4 NPs. Then resultant mixture was heated up 19 0 0 C and kept at this temperature for 2 hr. After 2hr, it was allowed to cool down to room temperature. The mixture was precipitated by addition of ethanol and collected by centrifuging. The precipitated product was re dispersed in toluene Tra nsfer of Au@MnO FNPs into Aqueous P hase 10 mg of Au@MnO flower nanoparticles were dissolved in 5 mL of te t rahydrofuran anhydrous (THF) and flashed with argon for 15 mins After degassing, the solution

PAGE 117

117 transferred to a drop ping funnel. After 150 mg of het er obiofunctional dopamine terminated PEG was dissolved in 20 mL of THF anhydrous in 100 mL of three necks flask, nanoparticle solution in dropping funnel was added into PEG ligand solution in a dropwise manner The resultant mixture was stirred under argon b lanket at 500 C for overnight. The NP PEG ligand conjugation was terminated via addition of ~ 3mL of hexane and collected by centrifugation at 10000 rpm for 20 min. The supernatant was discarded and the product, NPs, at bottom of centrifuge tube was washed with ethanol and centrifuged twice to remove excess and unre acted of PEG ligands. Finally, NP precipitate was dispersed in ultrapure water or PBS buffer for aptamer conjugation. Characterization One drop of nanoparticles dispersed in hexane was deposited on carbon coated copper grids and it was allowed to dry for at least two hours. Transmission electron microscopy (TEM) on a Hitachi H 7000 transmission electron microscope with a working voltage of 100 kV was used to obtain images of nanoparticles. The hi gh resolution TEM (HRTEM) instrument coupled with spatially resolved energy dispersive X ray spectroscopy (EDX) was also used for magnified images and further characterization of nanoflowers. The 1800 UV Vis spectrophotometer (Shimadzu Scientific Instrumen ts, Columbia, MD) was used to show the absorption spectrum of nanoflowers and to determine the concentration of DNA aptamers. Fluorescence measurements were carried out on a Fluoromax 4 (Horoba Jobin Yvon, Edison, NJ, USA) was also used for validation of dye labeled aptamer nanoflower conjugation. An an Olympus FV 500 IX81 confocal microscope (Olympus, Center Valley, PA, USA) having a 40 oil dispersion objective was used to image cancer cells incubated with nanoparticles. The demonstration of binding of fu nctionalized nanoparticles to targeting cells was carried

PAGE 118

118 out with a FACScan cytometer (Becton Dickinson Immunocytometry Systems, San Jose, CA, USA). Synthesis of A ptamers An ABI 3400 DNA/RNA synthesizer (Applied Biosystems, Foster City, CA) was operated for the synthesis of all aptamer sequences (sgc8: 5` NH2 ATC TAA CTG CTG CGC CGC CGG GAA AAT ACT GTA CGG TTA GA FITC 3` and ATP aptamer: 5' SH ACC TGG GGG AGT ATT GCG GAG GAA GGT TMR 3') at the 1 mol scale. Deprotection was performed in AMA (ammonium hydr oxide/ 40% aqueous methylamine 1:1) at 65 C for 30 min, and deprotected sequences were purified by reversed phase HPLC (ProStar, Varian, Walnut Creek, CA) with a C 18 column (Econosil, 5 m, 250 4.6 mm) from Alltech (Deerfield, IL). Immediately after HPLC purification, purified DNA solution was dried in acid resistant centriVap centrifugal vacuum concentrators (Labconco, Kansas City, MO). The dried DNA was dissolved in 50 L DNA grade water, and the concentration of each sequence was determined based on abs orbance value at nm using an 1800 UV Vis spectrophotometer (Shimadzu Scientific Instruments, Columbia, MD). Functionalization of Au@MnO FNPs T ransferring of Au@MnO FNPs from toluene or hexane to ultrapure water or PBS buffer wa s completed using dopamine t erminated of heterobicofunctional ligand, dopamine PEG carboxylic acid. The OH groups on the dopamine side of PEG ligand preferentially bind to surface of MnO domain of FNPs, and the other side, carboxyl group contributes water solubility of FNPs and is fr ee to react with biofunctional groups, aptamers in the presence of 1 ethyl 3 (3 dimethylaminopropyl) carbodiimide), EDC and N hydroxys ulfosuccinimide (Sulfo NHS). C onventional protein labeling chemistry was

PAGE 119

119 utilized to attach two diff erent aptamers, sgc8 a nd ATP, to the surface of two different domains, MnO and Au, of FNPs. 30L of 0.1 M EDC was added to 1.5 mg/mL concentration of 150 L of FNPs in 10 Mm PBS buffer to activate carboxyl group on PEG ligand for 20 min while gently shaking. After that, 13.1 L of 228 M sgc8 aptamer and 30 L of 0.12 M NHS in 10 Mm PBS buffer were added and incubated 1 h while gently shaking to functionalize the MnO domain of FNPs. After 1 h incubation, to resultant mixture, 7.45 L of 300 M ATP aptamer and 77 L of 10 mM PBS buffer were added and the mixture was placed on shaker for overnight incubation at room temperature to functionalize Au domain of FNPs. After immobilization of the aptamers onto FNPs, the resultant mixture was washed three times with PBS buffer and finally redispersed in 300 L of PBS buffer. Cell Culture CCRF CEM cells (CCL 119 T cell, human acute lym phoblastic leukemia) were obtained from ATCC (American Type Culture Collection). RPMI medium supplemented with 10% fetal bovine serum (FBS) and 100 IU/mL penicillin streptomycin was used to culture the cells in. A hemocytometer provided the cell density before experiment performed. After suspending two million cells in RPMI cell media buffer, the mixture was centrifuged at 970 rpm for 5 min and redisperse d them in [4.5 g/L glucose and 5 mM MgCl 2 incubation. During the experiments, the cells were stored in an in incubator at 37 C. Mass S pectrometry All mass spectra were acquired using a MA LDI TOF/TOF mass spectrometer (ABI / SCIEX 5800, Applied Biosystems, Foster City, CA). A Nd:YAG laser at 355 nm was used. The spectra were recorded in reflection mode in either positive or negative

PAGE 120

120 mode using an accelerating voltage of 20 kV, a 66% grid volt Applied Biosystems Cal ibration Mix ture 1 was used to calibrate the mass spectrometer Data analysis and was per formed us ing Date Explorer software. Results and Discussion Survival Yield Calculation on Hybrid N anoparticles In the first set of experiments Fe 3 O 4 NPs, Fe 3 O 4 Au core shell NPs, Fe 3 O 4 Au dimer NPs, Fe 3 O 4 Au flower NPs and MnO Au flower NPs were studied as probes for ionization. The TEM images of the se particles are given Figure 4 1. The primary motivation in choosing metal oxide gold particles was the following; first both metal oxide s and gold have been reported to be efficient materials for nanoparticle based laser desorption ionization second the y have relatively easy synthesis procedures and are easily amenable to bioconjugation finally hybr id nanoparticles made up of metal oxide s and gold have not been previously been studied as a substrate for LDI MS. Driven by this primary mo tivation thermom eter ions used were used to determine the best hybrid nanoparticle As extensively discussed in the previous chapter, benzylpyridium ions are ideal molecules to calculate the internal energy deposition and calculation of survival yield in the laser desorpt ion ionization event. Therefore the mass spectrometry data derived from BP ions therefore serve s as a quantitative bench mark to assess the efficiency of different nanostructures and compare them in terms of laser desorption ionization The results of BP fragmentation experiments are shown in Figure 4 2 As can easily be seen from this figure survival yields of the studied nanoparticles greatly differ from each other There was an increasing trend in SY when the particle geometry changes from core shell t o dimer and then to nano flower. This was an

PAGE 121

121 interesting observation and led us to think us about the reasoning. The first experiment was to compare the UV spectra of the each NP. As can be seen in Figure 4 3 no clear difference exists in UV range of 200 40 0 nm which rules out the possibility of different UV absorption that might lead to this observation. Even though many studies have been published about nanostructure based MS, no previous data exist in the literature on similar hybrid particles On the oth er hand iron oxide gold particles were previously studied as probes for surf ace enhanced r aman spectroscopy (SERS) ( 106 ) It is evident that bare iron oxide NPs does not ha ve any intrinsic plasmonic property which can lead to enhancement in Raman signals. H owever when gold is introduced to the system it creates a multiple hot spots where nanogaps can be formed between gold particles which might lead to improved signals. The reason why the SYs improved going from core shell to nanoflower s can also be understood in the light of this enhancement effect where a large number of hot spots can be formed in flower shaped particles which may not be very operative in the case of cor e shell structures. Mor eover a great majority of the particles used for MS applications are also useful for SERS applications which might suggest that similar mechanisms govern the nanostructure based ionization and surface enhancement in Raman spectrosc opy. The second plausible reason is that nanoflower shaped structures can accommodate more analytes than that of others owing to a higher surface area. This leads to higher sens itivity and eventually improved ionization. A similar phenomenon was observed previously in the case of carbon nanotube /graphene conjugate materials where CNTs significantly improved the ionization capabilities of graphene in a synergistic manner. ( 107 ) However when th e petals around the gold core are changed from iron oxide to manganes e oxide that is

PAGE 122

1 22 Au@MnO FNPs is compared to Fe 3 O 4 @Au FNPs, the former one is superior to the latter one as can be seen from the SY data d epicted in Figure 4 2 Testing Au@MnO FNPs as a Substrate for I onization After selecting Au@MnO FNPs as a material for ionization we analyzed a series of different small molecules to show the utility of this particle as a n efficient substrate for ionizat ion. The mas s spectra are seen in F igure s 4 3 to 4 6 When the spectra are analyzed it can easily be seen that most of the analytes are seen as sodium or potassium adducts. As explained in the experimental part several salts and surfactants were used duri ng synthesis proce dure of Au@MnO FNPs Therefore even after extensive washing steps prior to MS analysis we were unable to eliminate salt effects. However we have to note here t hat even though cationization occurred, no significant background interferenc e wa s observed and the mass spectra were relatively very clean with very minor background io ns. This is especially important for metabolomics applications as most of the important metabolites lie in the m/z range of 50 1000. While MALDI MS has proven to be a very successful method for proteomics oriented applications its use has mostly been limited to small molecule analysis. Therefore nanoparticles are the best option for this purpose. We were able to analyze important cellular metabolites such as dopamin e, serotonin, melatonin, cholesterol very effectively. A comparison between MALDI MS and LDI on Au@ MnO FNPs is given in Figure 4 7 and significant backgroun d ions exist in the MALDI spectra. In the next set of experiments we tested Au@MnO FNPs in the negat ive ionization mode and a nd analyzed n lauryl sarcosine, glutathione and melatonin as the model compounds. As can be seen in Figure 4 8 and 4 9 cation adducts which was observed in the positive ion mode were eliminated and [M H ] ions were observed Thi s suggests that

PAGE 123

123 significant reduction of salt effects can be achieved in the negative ion mode This is important in the analysis of peptides f atty acids as well as nucleosides and nucleotides in negative ion mode. Mo dification of Au@MnO FNPs with A ptame rs In our experiments we used Au@MnO FNPs w ith various aptamer modificatio n s A s can be seen in Figure 4 10 Au@MnO FNPs is composed of a gold core surrounded by MnO petals. Therefore both of these domains can be easily modified with different ligands. We have selected acute myeloid leukemia cells (CCRF CEM) as our model Our group has previously selected an aptamer for t his cell line called sgc8. This aptamer with a K d value of picomolar, has been a gold standard for many aptamer based cancer cell assays Our group and others has extensively studied this aptamer for various different applications. Moreover cancer cells in particular leukemia cells are known to be energically more demanding therefore showing more ATP expression. O ur ultimate goal was to show that Au@MnO FNPs can be selectively internalized into CCRF CEM cells, ATP within the cells can be captured and finally ATP can be analyzed by using aptamer modified Au@MnO FNPs as the ionization matrix after cell lysis and washing. So to realize this goal we have modified the Au@MnO FNPs in different ways. In the first modification MnO petals were decorated with FITC labeled sgc8 aptamer and go ld core was decorated with TMR labeled ATP aptamer to enable fast cellular uptake and efficient ATP capture in the cell. MnO petals were modified with FITC labeled sgc8 aptamer and gold core was modified with a TMR labeled random aptamer and in the last control we have modified gold domain was not modified with ATP aptames. W e confirmed that FITC labeled sgc8 aptamer and TMR labeled ATP aptamer were successfully bound to surfa ce of MnO and Au domain of FNPs. These can be

PAGE 124

124 clearly seen in the fluorescence spectra shown in Figure 4 1 1 It is clearly seen that fluorescence intensity of FITC labeled aptamers attached onto surface of MnO pe t al s is enhanced with increase of amount of FNPs W hen we increase the amount of FNPs fluo rescence intensity is enhanced as more MnO nanoparticles hold a lar ge r number of FITC labeled scg8. TMR labeled ATP apt a mer immobilized on Au nanopa rticles of FNPs also exhibits higher fluorescence intensity with increas e of amount of FNPs There was no significant quenching effect generated from the surface of gold to influence fluorescence emission properties of TMR These two fluorescence spectra p roved that modification of two different aptamers onto FNPs were efficiently carried out without seeing a signific ant interference between the two ap tamers Internalization of Aptamer M odified Au@MnO FNPs The internalization and binding of aptamer modified Au@MnO FNPs were performed by following the established procedure in our lab at 37 C and 4 C respectively. Briefly 4 x10 6 cells were prepared and placed in separate tubes (2 x10 6 to each), 100 L of 20 ng, 200 ng and 800 ng aptamer conjugated FNPs were a dded to cell samples and the mixtures we re incubated in incubator at 37 C for 2 h for internalization and at 4 C (on ice) for 30 min for surface binding. The mixtures of cell par ticle were centrifuged washed three times and re dispersed in 0.5 mL of bind ing buffer, after incubation. The bindi ng of each sample incubated at 37 C and 4 C was monitored by using flow cytometry counting 10.000 events. ( 108 ) After incubation of two different benches of FITC sgc 8 aptamer FNPs conjugates at 37 C for 2h and 40 C for 30 min, internalization of FNPs into cancer cells (CCRF CEM) and binding of FNPs on surface of cancer cells were m onitored by flow cytometry. The results are shown i n Figure 4 12 A s can be seen in Figur e 4 12 (a) t here was a significant change in the fluorescence

PAGE 125

125 signal observed between lowest (20 ng/mL) and highest (800 ng/mL) amount of FNPs u sed for cell uptake study. The i nternalized FITC labeled sgc8 FNPs into CEM cells at 37 C do not show a strong fluorescence signal c ompared to incubation of CEM cells with FITC labele d sgc8 FNPs of carried out at 4 C When the FITC labeled sgc8 FNPs were uptake n by CCRF CEM cells, fluorescence emission intensity of FITC was weakened because of aggregation of particles and intrinsic auto fluorescence generation fro m the cells The same experiments were also performed at 4 C and f low cytometry data shows that of FITC labeled sgc8 aptamer FNPs bind to cell surface instead of internalization. ( 109 ) These results were also confirmed by using confocal microscopy a nd as can be seen in F igure 4 13 high florescence signals can be observed upon particle internalization. Extraction of ATP from C ancer C ells U sing A ptamer C onjugated Au@M nO FNPs Motivated by our success in using Au@MnO FNPs for LDI MS and functionalization of the particle surface with aptamers we then wanted to use this material to extract a very important cellular metabolite, ATP, from cancer cells. ATP is an important mo lecule for cellular metabolism which works as an intermediate in cellular processes. Many cellular reactions depend on ATP hydrolysis. In cell signaling, for example, the phosphate group is transferred from ATP to key regulatory proteins by protein kinases ( 110 ) Apart from its biological importance ATP was chosen for a couple of other reasons; first there is a very good aptamer available for AT P targeting, second ATP is one of the most abundant yet difficult metabolites to be analyze by MS and third molecular weight of ATP perfectly falls into the m/z range of where Au@MnO FNPs were very efficient. So for all these reasons it serves us as a very good model to demonstrate the aptamer based affin ity mass spectrometry concept in a very complex

PAGE 126

126 biological system. As has been shown in many different applications nanoparticles can be internalized into the cells by either receptor mediated endocytosis or a passive diffusion mechanism. ( 111 ) I n the first mechanism a ligand is tethered onto the surface of the nanoparticle and this moiety selectively interacts with one of the surface receptors A s a result of this interaction the particle is easily engulfed by the cell and is internalized. This has been the subject of very intense research an d many different particle systems with various molecular recognition ligands have b een developed. In the second mechanism the particle is not decorated with a ligand and particle uptake is simply governed by diffusion which is not selective. Moreover ful l uptake o f particles take s a long time (>8 h) which is not desirable for analytic al and biological applications. ( 112 ) Therefore our strategy is advantageous from all these respects. In order to confirm our hypothesis that dual aptamer conjugated Au@MnO FNPs can easily be internalized and used for ATP capture we used it together with the respective controls by following the cell internalization protocols explained in great detail above. After p article internalization, the next step was to test different cell lysis conditions that will enable the most efficient detection of metabolites. Extraction of metabolites from cell lysates is an area of great interest especially in the growing area of meta bolomics. ( 113 114 ) I n the past five years several methods were used with different conditions to release th e metabolites from the biological mixtures. ( 115 ) While many protocols were suggested in the literature success still depends on trial and error based optimization. Organic solvents such as cold acetone, methanol, and ethanol have been generally used for metabolite extraction. In our first attempts we used cold methanol for cell lysis and after 10 mins of treatment with cold methanol the final cell

PAGE 127

127 lysis was brought to room temperature and particles were centrifuged and removed from the cell lysate A fter several cycles of washing an aliquot of the particles were spotted on to the plate and analyzed. However in any of the particles we have been unable to observe a significant signal associated to ATP. The res ults are depicted in F igure 4 14 and t he molecular weight region for ATP and its secondary metabolites ADP and AMP is h ighlighted for clarity. This might have been for a couple reasons. First, not enough particles we re internalized second ATP aptamers were not functional with in the cells because of the cellular complexity or they are cleaved of by endonucleases .Third th e cell lysis with organic solvents might distrupt the interaction of the aptamer with its target. The first two reasons are very unlikely because aptamers can be easily internalized and can recognize their targets even in the cells. Although there is a po ssibility that aptamers might be cleaved of by cellular endonucleases, recent studies show ed that nanoparticles provide a strong barrier for such kind of unwanted enzymatic reactions. ( 116 ) Most notable example of th is phenomenon has recently been demonstrated. ( 117 ) ( 20 ) T he method developed to monitor mRNA activity nanoflares immobilizing an oligonucleotide and a reporter complementary strand onto a gold nanoparticle surface which fluoresces upon target binding. It has been shown endonucleases cannot cleave off nanoparticle immobilized oligonucleotides. This has also been exemplified in a simi ( 118 ) The last and t he most likely reason is the use of an organic solvent during the cell lysis and metabolite extraction. Aptamers are very stable molecules compared to antibodies against changes in pH, temperature, ionics strength but still their target recognition depend s on their 3D conformation. We think that that cold

PAGE 128

128 methanol treatment irreversibly disrupts the aptamer target interaction and therefore target cannot be captured by the aptamer as a result no significant signal was observed. In the next set of experime nts we therefore replaced cold methanol with boiling water for metabolite extraction and cell lysis. While aptamers can be denatured with heat they can easily refold to their proper 3D conformation upon cooling. The main workhorse for oligonu cleotide ampli fication, PCR, actually relies on thermal cycling and therefor e oligonucleotides can survive even at 100 C. Moreover previous studies have shown that boiling water is a better solvent for extracting nucleotides from the cells. We repeated the same experim r metabolite extraction solvent However, we were also challenged by the fast turnover rate of ATP molecule. ( 8 ) ATP is a very labile metabolite and can easil y be converted to ADP and AMP upon losing its phosphate groups The kinetics of the reaction is very fast and ATP binding aptamer can also capture ADP and AMP a nd as we can see in Figure 4 15 we were only able to detect ADP and AMP. To overcome this probl em we have slightly modified the metabolite extraction step by incorporating another step using cold NH 4 HCO 3 buffer and dipping the cells into liquid N 2 to quench the metabolism prior to metabolite extraction and cell lysis. This has previously been proven successful to quench metabolism. ( 119 ) Th e results are seen in Figure 4 16 and we can clearly see that AT P can be detected and no significant ATP d ecompositon i s observed. The respective control experiments show to a great extent that ATP can only be captured and detected by dual aptamer modified Au@MnO FNPs. In conclusion, we have developed a new a nd efficient nanoparticle based matrix for laser desorption ioniz ation through investigating the properties of different

PAGE 129

129 nanoparticles. The developed nanoparticles are the first such material to be used in laser desorption ionization mass spectrometry. The utility of Au@MnO FNPs have been demonstrated for sensitive dete ction of several different metabolites in both positive ion and negative ion mode s Moreover s elective detection of c ellular metabolites within c ancer cells can be achived t hrough utilizing the unique properties of Au@MnO FNPs and the excellent selectivit y of aptamers. The Au@MnO FNPs developed herein were used for mult iple tasks in one single system. First they are used as a novel ionization substrate, second the surface of the Au@MnO FNPs is decorated in such a way that they are used for fast and efficie nt internalization to cancer cells using molecular aptamers dir ectly selected from whole cells and at the same time can be used for extracting cellular metabolites Future work will include the further development of the assay including analyzing different cancer cell lines with varying degree of ATP expression. T he particle size, incubation times, and sample preparat ion methods for complex samples are also important variables that still need more optimization. Although we have used ATP to demonstrate the p otential and utility of the aptamer based affinity mass spectrometry, the assay can be easily extended to other cellular targets such as membrane proteins or cytoplasmic proteins such as lysozyme or insulin for which high quality aptamers exist. This assay has shown the potential t hat aptamers when combined with mass spectrometry provide a rapid, high throughput, sensit ive, and cost effective detection of targets of interest.

PAGE 130

130 Figure 4 1 TEM images of hybrid nanostructures.

PAGE 131

131 Figure 4 2 Survival yield calculations on metal oxide Au heteronanostructures

PAGE 132

132 Figure 4 3 UV spectra of the hybrid NPs

PAGE 133

133 Figure 4 4 LDI analysis of glucoseamine, phenylalanine,mannitol and dopamine on FNPs

PAGE 134

134 Figure 4 5 LDI analysis of sarcosine, reserpine, MIF 1 and serotonin on FNPs

PAGE 135

135 Figure 4 6 LDI analysis of cholesterol on FNPs

PAGE 136

136 Figure 4 7. Comparison of LDI analysis of glutatione using HCCA matrix and FNPs

PAGE 137

137 Figure 4 8 Comparison of LDI analysis of melatonin and n lauryl sarcosine in positive and negative ion mo de

PAGE 138

138 Figure 4 9 Comparison of LDI analysis of glutatione in positive and negative ion mode

PAGE 139

139 Figure 4 10 Schematic diagram of aptamer modification of FNPs and MS analyses

PAGE 140

140 Figure 4 11. Fluorescence spectra of FNPs after aptamer conjugations

PAGE 141

141 Figure 4 12 Flow cytometric assay to monitor the binding Figure 4 13. Images of cancer cells ( A) cells incubated with bare FNPs without aptamer functionalization (B) cancer cells incubated with aptamer functionalized FNPs (C)

PAGE 142

142 Figure 4 14 LDI analysis of CEM cell lysate after metabolite extraction by cold methanol using FNPs Figure 4 15 LDI analysis of CEM cell lysate after metabolite extraction by hot water using FNPs

PAGE 143

143 Figure 4 1 6 LDI analysis of CEM cell lysate after metabolite extraction by hot water using FNPs after quenching the metabolism A ) onl y sgc8 control B )sgc random control C ) sgc8 ATP particle

PAGE 144

144 CHAPTER 5 BIOMARKER DISCOVERY OF HEPATOCELLULAR CA RCINOMA USING CELL SPECIFIC APTAMER PRO BES AND MASS SPECTRO METRY Hepatocellular carcinoma (HCC) is one of the most common neoplasm s worldwide. It is ranked as the fifth most common cause of cancer related death s and approximately 500000 people died by complications caused by HCC. ( 120 ) According to the World Hea lth Organization, the deaths from HCC are expected to continue to increase until 2030, and these tumors are projected to have the secon d highest increase in overall death rates. ( 121 ) As other cancer types, exact mechanism o f cancer initiation and progression in HCC are largely unknown. Many different risk factors such as alcohol consumption, hepatitis B virus infection, exposure to toxic chemicals such as aflatoxin, unhealthy fat rich diet and rare genetic diseases suc h as a1 antitrypsin deficiency are assoc iated with HCC. ( 121 ) Liver is a very central organ in volved in hormonal regulation and digestion system. Therefore HCC can easily metastasize which is a very big complication as metastasis is not easily controllable and decreases the likelihood of survival. Currently, the disease status in HCC is usually de termined by physical assessment, either by ul trasound imagin g of the liver or pathological examination of biopsy samples. ( 122 ) Howev er as all other cancer types, early dete ction is of utmost importance. Accurate detection of HCC is necessary to identify the nee d for intervention because early surgical an d chemotherapeutic intervention is the best hope for patient survival. However, the interpreta tion of ultrasound imaging is subjective and can be dif ficult in persons who are obese or have underlying cirrhosis. Moreover pathological examination of biopsy cer cannot be accurately diagnosed until the tumor reaches to a certain size. (>1 cm) When

PAGE 145

145 it reaches that size and detected, it also often reaches to stage 2 or stage 3. On the other hand c urative therapy for HCC is possible if it is diagnosed early. Surg ical options, including resec tion and liver transplantation, offer the best chance of a successful outcome. ( 123 125 ) Local regional therapies, such as radiofre quency ablation and chemoembolization, provide effect ive local control in those with acceptable hepatic function. The multi kinase inhibitor sorafenib has also been the first molecul ar targeted oral agent that was recently shown to provide a survival benef it for selected patients with HCC. ( 126 ) However all these strategies can be successful only if early diagnosis can be achieved. A pplication of new technologies is therefore necessary to extend our knowledge about th e molecular pathogenesis, improve therapeutic approaches and patient life in HCC. Discove ry of new biomarkers which might lead to early diagnosis, and to d efine new therapeutic targets for HCC is of great interest. At present, only five biomarkers are used for HCC They are a lpha Fetoprotein (AFP) DCP (PIVKA II) AFP L3 Golgi phosphoprotein 2 and Glypican3 (GPC3) ( 127 ) AFP is the most common and classical tumor marker for HCC. In a dults, under normal conditions, the serum AFP concentration is approximately 5 10 mg/L. AFP is pres umed to function as a transport molecule for several li gands, such as bilirubin, fat ty acids, retinoid, steroids, heavy metals, dy es, flavonoids, phytoestrogens, dioxin, and vari ous drugs. AFP is also suggested to exhibit immunos uppressive activity and to play a role in the regulation of cell proliferation. Despite the uncertainty concern ing its bi ologic role, an increase in the serum concentration of AFP i s mainly used as a tumor marker for HCC. The AFP

PAGE 146

146 concentration is slightly increased in patients with active chronic liver diseases and the low specificity of AFP for a diagnosis for HCC is a clinical problem. ( 128 ) Changes in glycosylation are associated with the development of many types of cancer includi ng HCC. In particular, fucosylation is one of the most im portant models of glycosylation involved in hepat ocarcinogenesis. The amount of fucosylated N linked glyca ns in the sera of patients with advanced liver diseases including HCC is significantly increa sed compared with that of healthy controls or patients with mild liver diseases F ucosylated AFP (AFP L3) is a more specific marker for HCC compared with AF P alone. DCP is a protein induced by vitamin K absence or antagonist II (PIVKA II), DCP may be usefu l primarily as a p rognostic biomarker in HCC cell lines predictive of rapid tumor progr ession and poor prognosis. Glycoprotein GP73 (Golgi phosphoprotein 2), a potential biomarker for liver diseases, is elevated in the liver in acute hepatitis (51, 52). GP73 is a single membrane spanning domain near the short cy toplasmic amino terminus of the protein. GP73 and related protein G PP130 may also be redistributed to the cell surface and end osomes. ( 129 ) Although the biologic func tion of GP73 remains uncertain and it is unclear which cells are the source of circulating GP73 an d how it arrives in the circu lation in vivo, the correlation with HCC is sufficien tly high to warrant its further investigation as a potential disease mar ker. GPC 3 is an oncofetal protein being one of the members of heparan sulfate proteoglycans anchored to the plasma membrane through glycosylphosphatidyinositol ( 130 ) However even though all these markers are clinically practiced none of them has yet p roven to be an effective indicator of hepatocellular carcinoma. Therefore there is still a big gap in this fied and new biomarkers or panel of biomarkers are needed.

PAGE 147

147 As briefly discussed in the introduction chapter, our lab has developed a hybrid SELEX te chnique known as cell based SELEX, or cell SELEX, for aptamer selection to produce probes for molecular analysis of tumor cells. Instead of using a single type of molecule as the target, the cell SELEX process uses the whole cells as targets to select sing le stranded DNA aptamers that can distinguish target cells from control cells. In addition to the advantages of aptamers such as low molecular weight, easy and reproducible synthesis, easy modification, fast tissue penetration, low toxicity or immunogenici ty, easy storage, and high binding affinity and specificity comparable to antibodies, the most significant advantage of the cell SELEX technology is the absence of the requirement for prior knowledge about the potential biomarkers for cancer on these cells Also, under these circumstances, a group of cell specific aptamers can be selected using a subtraction strategy in a relatively short period without knowing which target molecules are present on the cell surface. Once the aptamers are selected, target mo lecules that might be important cancer biomarkers can be determined as the elucidation of the aptamer binding receptors on the cell surface will reveal the molecular structure of these receptors. This is very unique way to determine molecular characteristi cs of cells. Also, the generation of a group of aptamers during the process provides multiple molecular probe candidates for surface biomarker recognitions. On the other hand, there is no easy way to produce a similar panel of monoclonal antibodies in such a short time without purified antigens for any unknown antigens. Moreover most FDA approved clinically proven cancer drugs target cell surface proteins and inhibit their functions So the there is a great chance that discovered proteins have importance a s biomarkers or understanding the pathways involved.

PAGE 148

148 However membrane proteins constitute the most underrepresented family of proteins in proteomics studies. Because of their poor water solubility, high hydrophobicity, high molecular weight characteristic s they cannot easily be separated and identified by MS. Many methods have been proposed to address these issues but with very limited success has been achived so far. Our group has previously shown that aptamers can be used as pull down probes to identif y new biomarkers. In the most striking example protein tyrosine kinase PTK7 was identified as the binding receptor on the cell m embrane surface for aptamer Sgc8 which is selected against CCRF CEM leukemia cells. Protein tyrosine kinase 7 (PTK7), also know n as colon carcinoma kinase 4 (CCK4), is a relatively new and little studied member of the RTK superfamily. It was identified as a novel regulator of non canonical WNT or planar cell polarity (PCP) signaling ( 131 ) So it is very clear from this accumulating evidence that aptamer targets have important implications in cancer. This chapter discusses how the aptamer based affinity mass spectrometry is applied in the discovery of a new candidate biom arker for HCC. Experimental Cell Line LH86 human liver cancer cell line is cultured at 37 C and 5% CO 2 in DMEM ). Cells were washed before and after incubation with wash ing buffer (4.5 g/L glucose and 5 mM MgCl 2 in Dulbecco's phosphate buffered saline with calcium chloride a nd magnesium ch loride (Sigma).

PAGE 149

149 Synthesis of A ptamers An ABI 3400 DNA/RNA synthesizer (Applied Biosystems, Foster City, CA) was operated for the synthesis of all aptamer sequences for liver cancer :TLS11a: 5` ACAGCATCCCCATGTGAACAATCGCATTGTGATTGTTACGGTTTCCGCCTCATGGA CGTGC TG biotin 3` and ATP aptamer: 5' AGTCCATTTTATTCCTGAATATTTGTTAACCTCATGGAC biotin 3') at the 1 mol scale. Deprotection was performed in AMA (ammonium hydroxide/ 40% aqueous methylamine 1:1) at 65 C for 30 min, and deprotected sequences were purified by reversed phase HPLC (ProStar, Varian, Walnut Creek, CA) with a C18 column (Econosil, 5 m, 250 4.6 mm) from Alltech (Deerfield, IL). Immediately after HPLC purification, purified DNA solution was dried in acid resistant centriVap centrifugal vacuum concent rators (Labconco, Kansas City, MO). The dried DNA was dissolved in 50 L DNA grade water, and the concentration of each sequence was determined based on absorbance value at nm using an 1800 UV Vis spectrophotometer (Shimadzu Scientific Instruments, Columbi a, MD). Biomarker I dentification LH86 (100X106) cells were washed three times at 4 C with a PBS buffer and lysed in 5 mL of hypotonic buffer [50 mM Tris HCl (pH 7.5) containing protease inhibitors (0.1 mM PMSF and 2 g/mL pepstatin, leupeptin, and aproti nin)] at 4 C for 30 min. After centrifugation, the debris was washed three times with 5 mL of hypotonic buffer and dissolved in 1.5 mL of lysis buffer (PBS containing 5 mM MgCl2 and 1% Triton X 100) at 4 C for 30 min. In other cell experiments IP lysis k it from Pierce was used following manufacturer`s instructions.

PAGE 150

150 In a typical procedure the supernatant was incubated with with TLS11 sequence in the presence or absence of 1000 fold excess of random DNA sequence library as a nonspecific competitor, at 4 C by incubating it with 2 mg (200 L) of magnetic streptavidin beads at 4 C for 15 min and collected on a magnet ic stand. The collected magnetic beads were washed four times with 1 mL of PBS containing 5 mM MgCl2. The proteins were eluted by heating in 30 L of loading buffer and analyzed by polyacrylamide gel electrophoresis (12%) (SDS PAGE) stained with colloidal blue or mass spectrometry compatible silver stains. When in solution sample processing was p erformed the proteins were eluted by heating and supernatant was removed and transferred to another eppendorf tube for further processing. Protein Identification by N ano LC ESI MS Proteins captured by aptamers as described above were digested according to When gel samples are processed, the gel bands ex The peptides were loaded onto a C 18 capillary trap cartridge (LC Packings) and then separated on a 15 cm nano flow C 18 column (PepMap, 75 a flow rate of 200 nl/min. Q uadrupole time of flight ( QSTAR XL) MS system was used for protein identification. Two different chromatographic separation profiles were used: In the first o ne which is performed for in gel digested samples, peptides were eluted from the HPLC column by a linear gradient from 5 % Solvent B (96.9% acetonitrile (v/ v), 0.1% (v/v) acetic acid) to 2 0% Solvent B for 30 mins followed by ramping up to 80% Solvent B in 5 min. In the second one which is perfomed for in solution digestion samples 3% Solvent B (96.9% acetonitrile (v/v), 0.1% (v/v) acetic acid) to 40% Solvent

PAGE 151

151 B for 2 h followed by ramping up to 90% Solvent B in 10 min. Peptides were sprayed into the orifice of the mass spectrometer, which was operated in an information dependent data acquisition mode where an MS scan followed by three MS/MS scans of the five highest abundance peptide i ons were acquired in each cycle. S pectra and product ion spectra were acqui red using Analyst QS software. Data A nalysis The peptide tandem mass spectra were searched against using MASCOT search engine (http://www.matrixscience.com). The search was p erformed to allow for carbamidomethylation, oxidation, and a maximum of one misse d trypsin cleavage. Peptide tolerance and MS/MS tolerance were both 0.2 Da. Results and Discussion Our group had previously selected aptamers which can recognize HCC cells. The b inding profile of the ap tamers was depicted in Figure 5 1. As the first step of the protein identification procedure we applied the procedure reported by our group previously. A general workflow of the aptamer assisted membrane protein extraction and mass spectrometric identification procedure is schema tically represented in Figu re 5 2. Typically 100X10 6 cells were first lysed in hypotonic cell lysis buffer and incubated with TLS11a aptamer which recognizes human liver cancer cells. In a separate control experiment cell lysates were incubated with TLS9 control sequence (scrambled s equence) to differentiate the specific capture from non specific capturing. The r esults are depicted in Figure 5 3. As can be seen from the coomassie stained gel image, several proteins were observed in the total cell lysate and there was only a very fain t band around 50 kDa which did not show up with the control sequence. Th e results were seen in Figure 5 3 As can be seen from this western blot, there was indeed a band at

PAGE 152

152 around 50 Kd. We excised this band, performed in gel digestion and nano LC MS/MS ba sed protein identification. The protein list after the iden tification is shown in Figure 5 5 identified the same protein together with other non specifically bound proteins. H owever while our results consistently sh owed the same protein, vimentin we ruled out the possility that this is the target protein. Vimentin is a class III intermediate filament protein found in various non epithelial cells, especially mesenchymal cells. It is attached to the nucleus, endoplasmic reticulum, and mitochondria, either laterally or terminally While recent data suggest its role in cancer initiation and growth ( 132 ) it is a cytoplasmic protein not a membrane protein; therefore it probably interacted with the aptamer in a nonspecific manner. In the next set of experiments we performed the same pull down pr ocedure but performed the gel staining using silver. While coomassie blue has been shown to be more compatible with mass spectrometry it is also known to have poor sensitivity in staining rare proteins. While aptamers can recognize their targets with very high specificity, the expression levels of their membrane targets are unknown. Moreover besides their intrinsic difficulties in handling, membrane proteins have also low copy numbers on the cell surface. Silver staining has been shown to detect proteins as low as picogram levels. For this reason we have proceeded with silver staining to enable a more clear protein staining and to pick the band of interest more easily. The gel image stained w ith silver is shown in Figure 5 4 As we had previously seen in the coammassie staining we have seen a band around the same molecular weight region. When we excised the band and perfomed nano LC MS/MS based protein identification

PAGE 153

153 results were very similar. We also repeated the same experiment and performed in solution di gestion followed by nano LC MS/MS to confirm the validity of the experiments. Results of in gel and in solution digestion are seen in F igure 5 6 and Figure 5 7 While the results were consistent with the previous experiments, the protein hit was not a membr ane protein suggesting that: 1) protein target of the aptamer has a low copy number 2) binding is masked by cytoplasmic and nuclear proteins 3) the cell lysis protocol do not liberate membrane proteins sufficiently. The results also showed that running gel samples do not have any significant advantage in protein ID results as very similar results were obtained in both cases. Being unable to get any membrane protein identified after aptamer based membrane protein extraction, we have made small changes in the experimental procedure. To address the first issue we have first increased the cell number to 1X10 9 cells which would give sufficient proteins. Secondly, instead of using a hypotonic cell lysis buffer, immunoprecipitation lysis buffer (IP lysis buffer) wa s used in liberating the proteins from the cells. This buffer has successfully been used for antibody based pull down experiments. This buffer has a formulation to help maintain protein complexes for co immunoprecipitation As we have discussed previously, membrane proteins can easily lose their structural integrity and aptamer protein complexes might not be maintained when the proteins are extracted from the cell membrane. Third an additional clean up step was incorporated into aptamer based protein pull d own. As the aptamers are oligonucleotides there are many proteins in the cell lysate which have natural tendency to bind to oligonucleotides. To eliminate this and minimize the effect of non

PAGE 154

154 specifically bound proteins, cell lysate was first incubated with a 1000 fold excess the random DNA library. Aptamer was then incubated with this library treated lysate. The results of the protein identification of only random library tr eated samples are seen Figure 5 8 This protein list was largely dominated with dif ferent histones and other cytoplasmic proteins. Histones are the proteins which surround chromosomal DNA and control formation of nucleosomes. The results of the protein identification of after a non specific a ptamer (TLS9) are seen Figure 5 9 When the s ame experiment was performed using a human liver cancer specific as shown in Figure 5 10 This was a single pass trans membrane protein. Being the only membrane protein in the protein list this lead us to think that this might be the potential target of the TLS11a aptamer in LH86 HCC cell lysate samples. Plexin B3 is a 260 kDa type I transmembrane glycoprotein in the Plexin B subfamily of semaphorin receptors. Its identified li gand is the transmembrane semaphorin Sema5A, and are both expressed during differentiation and migration of central nervous system oligodendrocytes. Plexin B3 can interact with the transmembrane scatter factor receptors Met and Ron, activating these recept ors and the signaling molecule RhoA upon semaphorin engagement. Up to date, p lexin B3 were shown to be expressed specifically in pancreatic and prostate cancer cell lines derived from metastatic tumors which suggest its potential role in cancer growth. ( 133 135 ) A very recent report also suggests that Plexin B3 has very important roles in glioma which is a very aggressive type of brain cancer. ( 136 ) We have also mapped its interactions using the program Pathway Studio to get a clearer picture about its potential ro le. As

PAGE 155

155 can b e seen from this map in Figure 5 11 Plexin B3 interacts with GTP binding protein Rit2 and Sema5A and is involved in neoplast ic growth and cell metastasis. Our results also explain why the gel images didn`t show any differential band. As the molecular weig ht of Plexin B 3 is 260 Da it is difficult to isolate this protein by using a 1D gel. While the functional role of of Plexin B3 in is still elusive as there is no previous data in HCC our data suggests that it might be a very important novel biomarker for HCC and might shed light into complex cell ular mechanisms of hepatocellular carcinoma and identify new and more effective biomarkers and identify new drug targets. Here, we have presented novel aptamer based affinity mass spectrometry strategy for identif ying di fferentially expressed proteins in hepatocellular carcinoma (HCC). This method integrates the selection of molecular prob es targeting specific cells and the us e of cell specific aptamers for p revious work with apt amer selection for HCC has showed that selective targeting can be achieved through aptamer probes. In here we show that it is also feasible to discover previously unidentified protein s that may have a important role in transforming nor mal cells into diseased HCC cells As there is no previous data on the role of Plexin B3 in HCC, f uture work will involve validation of Plexin B3 in tumour tissue samples and screening this protein in proximal tumor tissue using targeted based protein iden tification methods such as MRM or ELISA.

PAGE 156

156 Figure 5 1 Flow cytometry assay for the binding of the HCC aptamers TLS9a and TLS911a ( 137 )

PAGE 157

157 Figu re 5 2 Aptamer based affinity mass spectrometry for cancer biomarker discovery

PAGE 158

158 Figure 5 3. 1D gel electrophoresis image of HCC cell lysate after aptam er based affinity enrichment. (C oamassie staining)

PAGE 159

159 Figure 5 4. 1D gel electrophores is image of HCC cell lysate after aptam er based affinity enrichment. (S ilver staining)

PAGE 160

160 Figure 5 5. Protein ID results of the excised band after apt amer based affinity enrichment. (coammassie stained gel)

PAGE 161

161 Fi gure 5 6 Protein ID results of the excised band after aptamer based affinity enrichment (Silver stained gel)

PAGE 162

162 Figure 5 7. Protein ID results of the excised band after ap tamer based affinity enrichment (in solution di gestion)

PAGE 163

163 Figure 5 8. Protein ID results of the excised band after aptamer based affinity enrichment. ( Library treated)

PAGE 164

164 Figure 5 9 Protein ID results of the excised band after aptamer based affinity enrichment. ( Library+ TLS9 cont rol aptamer treated)

PAGE 165

165 Figure 5 10 Protein ID results of the excised band after aptamer based affinity enrichment. ( Library+ TLS11a HCC aptamer treated)

PAGE 166

166 Figure 5 11 Analysis of interaction maps of Plexin B3

PAGE 167

167 CHAPTER 6 CONCLUDING REMA RKS AND FUTURE WORK In this dissertation different a ptamer based affinity methods were developed for improving the efficiency of mass spectrometry in identifying biological molecules of interest in complex biological mixtures The results clearly suggest t hat the use of both aptamers and mass spectrometry are complementary and can serve as an advantageous complement to conventional methods for separation. The method ologies described in the current thesis dealt with samples without any kind of derivatizatio n, thus achieving a less complex, less expensive, and less time consuming way to carry out the analysis of the biologically important molecules In addition, this fact differentiates this study and its procedures from other approaches normally reported in t he literature for the tedious separation and/or determination of important compounds in clinical samples. Using the fea tures provided by the proposed aptamer techniques plus the mass accuracy and sensitivity characteristics of the mass spectrometer, target ed analyt es were efficiently separated and accurately detected. The aim of this study was to achieve a comprehensive understanding of the aptamer based structures for mass spectrometry The development of a reliable analytical workflow based on the utiliza tion of cutting edge technology together with sophisticated data processing and analysis software tools enabled us to find a new biomarker candidate for HCC. In fact, the unequivocal identification of target compounds is still one of the bottlenecks of bio marker discovery studies In this sense, it is well known that tandem mass spectrometry provides the ability to positively identify the proteins the information provided by characteristics fragmentation patterns is far from being clinically useful. I t als o comes at the expense of enourmous amount of effort careful opti mization of

PAGE 168

168 experimental and instrumental paramaters. As we have demonstrated in four different examples aptamer based strategies can overcome many of the problems that the analytical chemist ry and biomarker discovery community has been facing for many years. Therefore, implementation of these aptamer based affinity mass spectrometry methodologies to improve the identification of the tentative biomarkers will be the part of the futur e work. In addition while working towards heavily on developing aptamer based strategies different nanostructures methodologies have also been demonstrated to contribute to the detection of unique analytes This study also generated many biological questions to be answered through further experimentation. Given the complexity and diversity of cancers, even within similar categories, multiple cancer specific molecular probes are needed to delineate unique fingerprints of tumor cells. In most of our investigations, ap tamers recognized their targets in very complex media such as cell lysates or plasma samples. However aptamers that are applied the as proof of concept using cultured cell lines should also be tested on real clinical specimens to determine their applica bility in clinical diagnosis. Considering that very big organizations such as Human Proteome Organization (HUPO) and National Institutes of Health (NIH ) support developing new protein capturing agents aimed at biomarker discovery, aptamer based affinity ma ss spectrometry method will gain more and more importance in the next 10 years. Most of the initial patents, which has been a roadblocker for their broad use, about aptamers will expire very soon and it is anticipated that aptamers will be more useful.

PAGE 169

169 LIST OF REFERENCES 1. Gao, J., Garulacan, L. A., Storm, S. M., Opiteck, G. J., Dubaquie, Y., Hefta, S. A., Dambach, D. M., and Dongre, A. R. (2005) Biomarker discovery in biological fluids, Methods 35 291 302. 2. Want, E. J., Nordstr m, A., Morita, H., and Siuzdak, G. (2006) From Exogenous Journal of Proteome Research 6 459 468. 3. Griffin, J. L., and Kauppinen, R. A. (2006) Tumour Metabolomics in Animal Model s of Human Cancer, Journal of Proteome Research 6 498 505. 4. Kurihara, K., Konishi, F., Kanazawa, K., Fujii, T., and Saito, K. (1997) Alpha Fetoprotein Producing carcinoma of the colon: Report of a case, Surgery Today 27 453 456. 5. Duffy, M. J. (2001 ) Carcinoembryonic Antigen as a Marker for Colorectal Cancer: Is It Clinically Useful?, Clinical Chemistry 47 624 630. 6. Makarov, D. V., Loeb, S., Getzenberg, R. H., and Partin, A. W. (2009) Biomarkers for Prostate Cancer, Annual Review of Medicine 60 139 151. 7. Forsberg, K., Valyi Nagy, I., Heldin, C. H., Herlyn, M., and Westermark, B. (1993) Platelet derived growth factor (PDGF) in oncogenesis: development of a vascular connective tissue stroma in xenotransplanted human melanoma producing PDGF BB, P roceedings of the National Academy of Sciences 90 393 397. 8. Dietmair, S., Timmins, N. E., Gray, P. P., Nielsen, L. K., and Krmer, J. O. (2010) Towards quantitative metabolomics of mammalian cells: Development of a metabolite extraction protocol, Analy tical Biochemistry 404 155 164. 9. Sreekumar, A., Poisson, L. M., Rajendiran, T. M., Khan, A. P., Cao, Q., Yu, J., Laxman, B., Mehra, R., Lonigro, R. J., Li, Y., Nyati, M. K., Ahsan, A., Kalyana Sundaram, S., Han, B., Cao, X., Byun, J., Omenn, G. S., Gho sh, D., Pennathur, S., Alexander, D. C., Berger, A., Shuster, J. R., Wei, J. T., Varambally, S., Beecher, C., and Chinnaiyan, A. M. (2009) Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression, Nature 457 910 914. 10. Wikoff, W. R., Gangoiti, J. A., Barshop, B. A., and Siuzdak, G. (2007) Metabolomics Identifies Perturbations in Human Disorders of Propionate Metabolism, Clinical Chemistry 53 2169 2176. 11. Aebersold, R., Anderson, L., Caprioli, R., Druker, B., Hartwel l, L., an d Smith, R. Biomarker Discovery for Cancer Journal of Proteome Research 4 1104 1109.

PAGE 170

170 12. Stein, L. D. (2004) Human genome: End of the beginning, Nature 431 915 916. 13. Hamacher, M., Stephan, C., Eisen acher, M., van Hall, A., Marcus, K., Martens, L., Park, Y. M., Gutstein, H. B., Herberg, F., and Meyer, H. E. (2007) Proteomics for everyday use: Activities of the HUPO Brain Proteome Project during the 5th HUPO World Congress, Proteomics 7 1012 1015. 14 Robertson, K. D. (2005) DNA methylation and human disease, Nat Rev Genet 6 597 610. 15. Alderton, G. K. (2010) Transcriptomics: Common disease pathogenesis pathways, Nat Rev Cancer 10 387 387. 16. Srivastava, S., and Srivastava, R. G. (2005) Proteomi cs in the Forefront of Journal of Proteome Research 4 1098 1103. 17. Good, D. M., Thongboonkerd, V., Novak, J., Bascands, J. L., Schanstra, J. P., Coon, J. J., Dominiczak, A., and Mischak, H. (2007) Body Fluid Proteomics for Biomarker Discovery: Lessons from the Past Hold the Key to Success in the Future, Journal of Proteome Research 6 4549 4555. 18. Flemming, A. (2012) Therapeutics: Opening the door to a new class of proteasome inhibitors, Nat Rev Cancer 12 5 5. 19. Levin son, S. S., Elin, R. J., and Yam, L. (2002) Light Chain Proteinuria and Lysozymuria in a Patient with Acute Monocytic Leukemia, Clinical Chemistry 48 1131 1132. 20. Prigodich, A. E., Seferos, D. S., Massich, M. D., Giljohann, D. A., Lane, B. C., and Mirk in, C. A. (2009) Nano flares for mRNA Regulation and Detection, ACS Nano 3 2147 2152. 21. Hood, L., and Friend, S. H. (2011) Predictive, personalized, preventive, participatory (P4) cancer medicine, Nat Rev Clin Oncol 8 184 187. 22. LaBaer, J. (2005) S o, You Want to Look for Biomarkers (Introduction to the Journal of Proteome Research 4 1053 1059. 23. Steen, H., and Mann, M. (2004) The abc's (and xyz's) of peptide sequencing, Nat Rev Mol Cell Biol 5 699 711. 24. Hawkridge A. M., and Muddiman, D. C. (2009) Mass Spectrometry Based Biomarker Discovery: Toward a Global Proteome Index of Individuality, Annual Review of Analytical Chemistry 2 265 277.

PAGE 171

171 25. JF, K., JC, T., JE, L., DR, A., and HM, T. (2010) The emerging process of top down mass spectrometry for protein analysis: biomarkers, protein therapeutics, and achieving high throughput, Mol. Biosyst. 6 1532. 26. MP, W., R, U., C, D., DM, S., and JR, Y. (2002) Analysis of quantitative proteomic data generated via multidime nsional protein identification technology, Anal. Chem. 74 1650. 27. Coon, J. J. (2009) Collisions or Electrons? Protein Sequence Analysis in the 21st Century, Analytical Chemistry 81 3208 3215. 28. Nesvizhskii, A. I., Vitek, O., and Aebersold, R. (2007 ) Analysis and validation of proteomic data generated by tandem mass spectrometry, Nat Meth 4 787 797. 29. Albala, J. S. (2001) Array based proteomics: the latest chip challenge, Expert Review of Molecular Diagnostics 1 145 152. 30. Gulmann, C., Sheeha n, K. M., Kay, E. W., Liotta, L. A., and Petricoin, E. F. (2006) Array based proteomics: mapping of protein circuitries for diagnostics, prognostics, and therapy guidance in cancer, The Journal of Pathology 208 595 606. 31. Rifai, N., Gillette, M. A., an d Carr, S. A. (2006) Protein biomarker discovery and validation: the long and uncertain path to clinical utility, Nat Biotech 24 971 983. 32. Horvatovich, P., Govorukhina, N., and Bischoff, R. (2006) Biomarker discovery by proteomics: challenges not only for the analytical chemist, Analyst 131 33. L, A., and CL, H. (2006) Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins, Mol. Cell Proteomics 5 573. 34. Han, X., Aslanian, A., and Yates Iii, J. R. (2008) Mass spectrometry for proteomics, Current Opinion in Chemical Biology 12 483 490. 35. Knochenmuss, R. (2006) Ion formation mechanisms in UV MALDI, Analyst 131 966 986. 36. Tang, K., Shvartsburg, A. A., Lee, H. N., Prior, D. C., Buschbach, M. A., Li, F., To lmachev, A. V., Anderson, G. A., and Smith, R. D. (2005) High Sensitivity Ion Mobility Spectrometry/Mass Spectrometry Using Electrodynamic Ion Funnel Interfaces, Analytical Chemistry 77 3330 3339. 37. Mland Nilsen, M., Uleberg, K. E., Janssen, E. A. M., Baak, J. P. A., Andersen, O. K., and Hjelle, A. (2011) From SELDI TOF MS to protein identification by on chip elution, Journal of Proteomics 74 2995 2998.

PAGE 172

172 38. Zhang, H., Kong, B., Qu, X., Jia, L., Deng, B., and Yang, Q. (2006) Biomarker discovery for ov arian cancer using SELDI TOF MS, Gynecologic Oncology 102 61 66. 39. Hutchens, T. W., Magnuson, J. S., and Yip, T. T. (1989) Interaction of Human Lactoferrin with DNA[colon] One Step Purification by Affinity Chromatography on Single Stranded DNAAgarose, Pediatr Res 26 618 619. 40. Forler, D., Kocher, T., Rode, M., Gentzel, M., Izaurralde, E., and Wilm, M. (2003) An efficient protein complex purification method for functional proteomics in higher eukaryotes, Nat Biotech 21 89 92. 41. Bauer, A., and Kus ter, B. (2003) Affinity purification mass spectrometry, European Journal of Biochemistry 270 570 578. 42. Johnson, C. J., Zhukovsky, N., Cass, A. E. G., and Nagy, J. M. (2008) Proteomics, nanotechnology and molecular diagnostics, Proteomics 8 715 730. 43. Bischoff, S., Kahn, M., Powell, M., and Kirlin, W. (2002) SELDI TOF MS Analysis of Transcriptional Activation Protein Binding to Response Elements Regulating Carcinogenesis Enzymes, International Journal of Molecular Sciences 3 1027 1038. 44. Terracc iano, R., Casadonte, F., Pasqua, L., Candeloro, P., Di Fabrizio, E., Urbani, A., and Savino, R. (2010) Enhancing plasma peptide MALDI TOF MS profiling by mesoporous silica assisted crystallization, Talanta 80 1532 1538. 45. Ressine, A., Ekstrm, S., Mark o Varga, G., and Laurell, T. (2003) Macro /Nanoporous Silicon as a Support for High Performance Protein Microarrays, Analytical Chemistry 75 6968 6974. 46. Finnskog, D., Jaras, K., Ressine, A., Malm, J., Marko Varga, G., Lilja, H., and Laurell, T. (2006) High speed biomarker identification utilizing porous silicon nanovial arrays and MALDI TOF mass spectrometry, Electrophoresis 27 1093 1103. 47. Meng, J. c., Siuzdak, G., and Finn, M. G. (2004) Affinity mass spectrometry from a tailored porous silicon su rface, Chemical Communications 48. Tanaka, K., Waki, H., Ido, Y., Akita, S., Yoshida, Y., Yoshida, T., and Matsuo, T. (1988) Protein and polymer analyses up to m/z 100 000 by laser ionization time of flight mass spectrometry, Rapid Communications in Ma ss Spectrometry 2 151 153.

PAGE 173

173 49. Chiang, C. K., Chen, W. T., and Chang, H. T. (2011) Nanoparticle based mass spectrometry for the analysis of biomolecules, Chemical Society Reviews 40 1269 1281. 50. Trauger, S. A., Go, E. P., Shen, Z., Apon, J. V., Compt on, B. J., Bouvier, E. S. P., Finn, M. G., and Siuzdak, G. (2004) High Sensitivity and Analyte Capture with Desorption/Ionization Mass Spectrometry on Silylated Porous Silicon, Analytical Chemistry 76 4484 4489. 51. Kong, X. L., Huang, L. C. L., Hsu, C. M., Chen, W. H., Han, C. C., and Chang, H. C. (2004) High Affinity Capture of Proteins by Diamond Nanoparticles for Mass Spectrometric Analysis, Analytical Chemistry 77 259 265. 52. Wang, K. Y., Chuang, S. A., Lin, P. C., Huang, L. S., Chen, S. H., Ouard a, S., Pan, W. H., Lee, P. Y., Lin, C. C., and Chen, Y. J. (2008) Multiplexed Immunoassay: Quantitation and Profiling of Serum Biomarkers Using Magnetic Nanoprobes and MALDI TOF MS, Analytical Chemistry 80 6159 6167. 53. Chiang, C. K., Yang, Z., Lin, Y. W., Chen, W. T., Lin, H. J., and Chang, H. T. Nanostructure Matrixes in Surface Assisted Laser Desorption/Ionization Mass Spectrometry, Analytical Chemistry 82 4543 4550. 54. Thakare, V. S., Das, M., Jain, A. K., Patil, S., and Jain, S. (2010) Carbon nanotubes in cancer theragnosis, Nanomedicine 5 1277 1301. 55. Hsu, W. Y., Lin, W. D., Hwu, W. L., Lai, C. C., and Tsai, F. J. Screening Assay of Very Long Chain Fatty Acids in Human Plasma with Multiwalled Carbon Nanotube Based Su rface Assisted Laser Desorption/Ionization Mass Spectrometry, Analytical Chemistry 82 6814 6820. 56. Najam ul Haq, M., Rainer, M., Huck, C. W., Hausberger, P., Kraushaar, H., and Bonn, G. n. K. (2008) Nanostructured Diamond Like Carbon on Digital Versati le Disc as a Matrix Free Target for Laser Desorption/Ionization Mass Spectrometry, Analytical Chemistry 80 7467 7472. 57. Tang, L. A. L., Wang, J., and Loh, K. P. (2010) Graphene Based SELDI Probe with Ultrahigh Extraction and Sensitivity for DNA Oligome r, Journal of the American Chemical Society 132 10976 10977. 58. Dong, X., Cheng, J., Li, J., and Wang, Y. (2010) Graphene as a Novel Matrix for the Analysis of Small Molecules by MALDI TOF MS, Analytical Chemistry 82 6208 6214. 59. Sefah, K., Shanggua n, D., Xiong, X., O'Donoghue, M. B., and Tan, W. (2010) Development of DNA aptamers using Cell SELEX, Nat. Protocols 5 1169 1185.

PAGE 174

174 60. Keefe, A. D., Pai, S., and Ellington, A. (2010) Aptamers as therapeutics, Nat Rev Drug Discov 9 537 550. 61. Ng, E. W. M., Shima, D. T., Calias, P., Cunningham, E. T., Guyer, D. R., and Adamis, A. P. (2006) Pegaptanib, a targeted anti VEGF aptamer for ocular vascular disease, Nat Rev Drug Discov 5 123 132. 62. Tim, S. (2003) Aptamers and SELEX: the technology, World Pat ent Information 25 123 129. 63. Wu, C. C., and Yates, J. R. (2003) The application of mass spectrometry to membrane proteomics, Nat Biotech 21 262 267. 64. Siuti, N., and Kelleher, N. L. (2007) Decoding protein modifications using top down mass spectro metry, Nat Meth 4 817 821. 65. Phizicky, E., Bastiaens, P. I. H., Zhu, H., Snyder, M., and Fields, S. (2003) Protein analysis on a proteomic scale, Nature 422 208 215. 66. F, H., M, K., RC, B., and BT, C. (1991) Matrix assisted laser desorption/ionizat ion mass spectrometry of biopolymers, Anal. Chem. 63 A1193. 67. Towers, M. W., McKendrick, J. E., and Cramer, R. (2010) Introduction of 4 Chloro cyanocinnamic Acid Liquid Matrices for High Sensitivity UV MALDI MS, Journal of Proteome Research 9 1931 1 940. 68. Shen, Z., Thomas, J. J., Averbuj, C., Broo, K. M., Engelhard, M., Crowell, J. E., Finn, M. G., and Siuzdak, G. (2000) Porous Silicon as a Versatile Platform for Laser Desorption/Ionization Mass Spectrometry, Analytical Chemistry 73 612 619. 69. Shenar, N., Martinez, J., and Enjalbal, C. (2008) Laser desorption/ionization mass spectrometry on porous silica and alumina for peptide mass fingerprinting, Journal of the American Society for Mass Spectrometry 19 632 644. 70. Walker, B. N., Razunguzwa T., Powell, M., Knochenmuss, R., and Vertes, A. (2009) Nanophotonic Ion Production from Silicon Microcolumn Arrays, Angewandte Chemie International Edition 48 1669 1672. 71. Walker, B. N., Stolee, J. A., Pickel, D. L., Retterer, S. T., and Vertes, A. ( 2010) Tailored Silicon Nanopost Arrays for Resonant Nanophotonic Ion Production, The Journal of Physical Chemistry C 114 4835 4840.

PAGE 175

175 72. Finkel, N. H., Prevo, B. G., Velev, O. D., and He, L. (2005) Ordered Silicon Nanocavity Arrays in Surface Assisted Des orption/Ionization Mass Spectrometry, Analytical Chemistry 77 1088 1095. 73. Okuno, S., Arakawa, R., Okamoto, K., Matsui, Y., Seki, S., Kozawa, T., Tagawa, S., and Wada, Y. (2005) Requirements for Laser Induced Desorption/Ionization on Submicrometer Stru ctures, Analytical Chemistry 77 5364 5369. 74. Wada, Y., Yanagishita, T., and Masuda, H. (2007) Order ed Porous Alumina Geometries and Surface Metals for Surface Assisted Laser Desorption/Ionization Analytical Chemistry 79 9122 9127. 75. Li, N., Mitchell, D. T., Lee, K. P., and Martin, C. R. (2003) A Nanostructured Honeycomb Carbon Anode, Journal of The Electrochemical Society 150 A979 A984. 76. Touboul, D., Bouchoux, G., and Zenobi, R. (2008) Gas Phase Protonation Thermochemistry of Adenosine, The Journal of Physical Chemistr y B 112 11716 11725. 77. Northen, T., Woo, H. K., Northen, M., Nordstrm, A., Uritboonthail, W., Turner, K., and Siuzdak, G. (2007) High surface area of porous silicon drives desorption of intact molecules, Journal of the American Society for Mass Spectr ometry 18 1945 1949. 78. Hsu, N. Y., Tseng, S. Y., Wu, C. Y., Ren, C. T., Lee, Y. C., Wong, C. H., and Chen, C. H. (2008) Desorption Ionization of Biomolecules on Metals, Analytical Chemistry 80 5203 5210. 79. Chen, S. Y., Li, K. I., Yu, C. S., Wang, J S., Hu, Y. C., and Lai, C. C. (2010) A Radiate Microstructure MALDI Chip for Sample Concentration and Detection, Analytical Chemistry 82 5951 5957. 80. Jones, L. L., McDonald, D. A., and Borum, P. R. (2010) Acylcarnitines: Role in brain, Progress in Li pid Research 49 61 75. 81. Brittain, S. M., Ficarro, S. B., Brock, A., and Peters, E. C. (2005) Enrichment and analysis of peptide subsets using fluorous affinity tags and mass spectrometry, Nat Biotech 23 463 468. 82. Curran, D. P. (2008) Fluorous Tag s Unstick Messy Chemical Biology Problems, Science 321 1645 1646.

PAGE 176

176 83. Northen, T. R., Yanes, O., Northen, M. T., Marrinucci, D., Uritboonthai, W., Apon, J., Golledge, S. L., Nordstrom, A., and Siuzdak, G. (2007) Clathrate nanostructures for mass spectrom etry, Nature 449 1033 1036. 84. Valls Miret, M., and Bradley, M. (2011) A generic small molecule microarray immobilization strategy, Tetrahedron Letters 52 6819 6822. 85. Lu, Z., Zhou, X., Hu, S., Shu, X., Tian, Y., and Zhu, J. (2010) Interfacial Asse mbly of Nanoparticles with Fluorous Tagged Organic Molecules, The Journal of Physical Chemistry C 114 13546 13550. 86. Cametti, M., Crousse, B., Metrangolo, P., Milani, R., and Resnati, G. (2012) The fluorous effect in biomolecular applications, Chemical Society Reviews 41 87. Mamidyala, S. K., Ko, K. S., Jaipuri, F. A., Park, G., and Pohl, N. L. (2006) Noncovalent fluorous interactions for the synthesis of carbohydrate microarrays, Journal of Fluorine Chemistry 127 571 579. 88. Collet, B. Y. M., Naga shima, T., Yu, M. S., and Pohl, N. L. B. (2009) Fluorous based peptide microarrays for protease screening, Journal of Fluorine Chemistry 130 1042 1048. 89. Edwards, H. D., Nagappayya, S. K., and Pohl, N. L. B. (2012) Probing the limitations of the fluoro us content for tag mediated microarray formation, Chemical Communications 48 90. Whiteaker, J. R., Zhao, L., Lin, C., Yan, P., Wang, P., and Paulovich, A. G. (2011) Sequential multiplexed analyte quantification using peptide immunoaffinity enrichment cou pled to mass spectrometry, Molecular & Cellular Proteomics 91. Chou, P. H., Chen, S. H., Liao, H. K., Lin, P. C., Her, G. R., Lai, A. C. Y., Chen, J. H., Lin, C. C., and Chen, Y. J. (2005) Nanoprobe Based Affinity Mass Spectrometry for Selected Protein P rofiling in Human Plasma, Analytical Chemistry 77 5990 5997. 92. Shen, J., Shi, M., Yan, B., Ma, H., Li, N., Hu, Y., and Ye, M. (2010) Covalent attaching protein to graphene oxide via diimide activated amidation, Colloids and Surfaces B: Biointerfaces 81 434 438. 93. Chattopadhyay, J., de Jesus Cortez, F., Chakraborty, S., Slater, N. K. H., and Billups, W. E. (2006) Synthesis of Water Soluble PEGylated Single Walled Carbon Nanotubes, Chemistry of Materials 18 5864 5868. 94. Barylyuk, K., Chingin, K., Balabin, R., and Zenobi, R. (2010) Fragmentation of Journal of the American Society for Mass Spectrometry 21 172 177.

PAGE 177

177 95. Greisch, J. F., Gabelica, V., Rem acle, F., and De Pauw, E. (2003) Thermometer ions for matrix enhanced laser desorption/ionization internal energy calibration, Rapid Communications in Mass Spectrometry 17 1847 1854. 96. Pak, A., Lesage, D., Gimbert, Y., Vkey, K., and Tabet, J. C. (2008 ) Internal energy distribution of peptides in electrospray ionization : ESI and collision induced dissociation spectra calculation, Journal of Mass Spectrometry 43 447 455. 97. Medintz, I. L., Uyeda, H. T., Goldman, E. R., and Mattoussi, H. (2005) Quantu m dot bioconjugates for imaging, labelling and sensing, Nat Mater 4 435 446. 98. Liu, C. W., Chien, M. W., Chen, G. F., Chen, S. Y., Yu, C. S., Liao, M. Y., and Lai, C. C. (2011) Quantum Dot Enhancement of Peptide Detection by Matrix Assisted Laser Desor ption/Ionization Mass Spectrometry, Analytical Chemistry 83 6593 6600. 99. Chen, W. T., Chiang, C. K., Lee, C. H., and Chang, H. T. (2012) Using Surface Assisted Laser Desorption/Ionization Mass Spectrometry to Detect Proteins and Protein Protein Complex es, Analytical Chemistry 84 1924 1930. 100. An, G. H., Suh, O. S., Kwon, H. C., Kim, K., and Johnson, E. A. (2000) Quantification of carotenoids in cells of Phaffia rhodozyma by autofluorescence, Biotechnology Letters 22 1031 1034. 101. Fehr, M., Fromm er, W. B., and Lalonde, S. (2002) Visualization of maltose uptake in living yeast cells by fluorescent nanosensors, Proceedings of the National Academy of Sciences 99 9846 9851. 102. Kim, Y. R., Bong, S., Kang, Y. J., Yang, Y., Mahajan, R. K., Kim, J. S. and Kim, H. (2010) Electrochemical detection of dopamine in the presence of ascorbic acid using graphene modified electrodes, Biosensors and Bioelectronics 25 2366 2369. 103. Amantonico, A., Oh, J. Y., Sobek, J., Heinemann, M., and Zenobi, R. (2008) Ma ss Spectrometric Method for Analyzing Metabolites in Yeast with Single Cell Sensitivity, Angewandte Chemie International Edition 47 5382 5385. 104. Schladt, T. D., Shukoor, M. I., Schneider, K., Tahir, M. N., Natalio, F., Ament, I., Becker, J., Jochum, F. D., Weber, S., Khler, O., Theato, P., Schreiber, L. M., Snnichsen, C., Schrder, H. C., Mller, W. E. G., and Tremel, W. (2010) Au@MnO Nanoflowers: Hybrid Nanocomposites for Selective Dual Functionalization and Imaging, Angewandte Chemie Internationa l Edition 49 3976 3980.

PAGE 178

178 105. Wei, Y., Klajn, R., Pinchuk, A. O., and Grzybowski, B. A. (2008) Synthesis, Small 4 1635 1639. 106. Zhai, Y., Zhai, J., Wang, Y., Guo, S., Ren, W., and Dong, S. (2009) Fabrication of Iron Oxide Core/Gold Shell Submicrometer Spheres with Nanoscale Surface Roughness for Efficient Surface Enhanced Raman Scattering, The Journal of Physical Chemistry C 113 7009 7014. 107. Kim, Y. K., Na, H. K., Kwack, S. J. Ryoo, S. R., Lee, Y., Hong, S., Hong, S., Jeong, Y., and Min, D. H. (2011) Synergistic Effect of Graphene Oxide/MWCNT Films in Laser Desorption/Ionization Mass Spectrometry of Small Molecules and Tissue Imaging, ACS Nano 5 4550 4561. 108. Estvez, M., dye doped silica nanoparticles increase flow cytometry sensitivity for cancer cell monitoring, Nano Research 2 448 461. 109. Chen, T., Shukoor, M. I., Chen, Y., Yuan, Q. A., Zhu, Z., Zhao, Z L., Gulbakan, B., and Tan, W. H. (2011) Aptamer conjugated nanomaterials for bioanalysis and biotechnology applications, Nanoscale 3 546 556. 110. Acin Perez, R., Gatti, Domenico L., Bai, Y., and Manfredi, G. (2011) Protein Phosphorylation and Preventi on of Cytochrome Oxidase Inhibition by ATP: Coupled Mechanisms of Energy Metabolism Regulation, Cell metabolism 13 712 719. 111. Jiang, W., KimBetty, Y. S., Rutka, J. T., and ChanWarren, C. W. (2008) Nanoparticle mediated cellular response is size depend ent, Nat Nano 3 145 150. 112. Zhu, Z. J., Ghosh, P. S., Miranda, O. R., Vachet, R. W., and Rotello, V. M. (2008) Multiplexed Screening of Cellular Uptake of Gold Nanoparticles Using Laser Desorption/Ionization Mass Spectrometry, Journal of the American C hemical Society 130 14139 14143. 113. Sellick, C. A., Hansen, R., Stephens, G. M., Goodacre, R., and Dickson, A. J. (2011) Metabolite extraction from suspension cultured mammalian cells for global metabolite profiling, Nat. Protocols 6 1241 1249. 114. Shin, M. H., Lee, D. Y., Liu, K. H., Fiehn, O., and Kim, K. H. (2010) Evaluation of Sampling and Extraction Methodologies for the Global Metabolic Profiling of Saccharophagus degradans, Analytical Chemistry 82 6660 6666.

PAGE 179

179 115. Yanes, O., Tautenhahn, R., P atti, G. J., and Siuzdak, G. (2011) Expanding Coverage of the Metabolome for Global Metabolite Profiling, Analytical Chemistry 83 2152 2161. 116. Cutler, J. I., Auyeung, E., and Mirkin, C. A. (2012) Spherical Nucleic Acids, Journal of the American Chemic al Society 134 1376 1391. 117. Seferos, D. S., Giljohann, D. A., Hill, H. D., Prigodich, A. E., and Mirkin, C. A. (2007) Nano Cells, Journal of the American Chemical Society 129 15477 15479. 118. Zheng, D., Seferos, D. S., Giljohann, D. A., Patel, P. C., and Mirkin, C. A. (2009) Aptamer Nano flares for Molecular Detection in Living Cells, Nano Letters 9 3258 3261. 119. Sellick, C. A., Hansen, R., Maqsood, A. R., Dunn, W. B., Stephens, G. M. Goodacre, R., and Dickson, A. J. (2008) Effective Quenching Processes for Physiologically Valid Metabolite Profiling of Suspension Cultured Mammalian Cells, Analytical Chemistry 81 174 183. 120. El Serag, H. B. (2011) Hepatocellular Carcinoma, New Engl and Journal of Medicine 365 1118 1127. 121. Villanueva, A., Minguez, B., Forner, A., Reig, M., and Llovet, J. M. (2010) Hepatocellular Carcinoma: Novel Molecular Approaches for Diagnosis, Prognosis, and Therapy, Annual Review of Medicine 61 317 328. 12 2. Kudo, M. (2011) Diagnostic Imaging of Hepatocellular Carcinoma: Recent Progress, Oncology 81 73 85. 123. Murakami, T., Imai, Y., Okada, M., Hyodo, T., Lee, W. J., Kim, M. J., Kim, T., and Choi, B. I. (2011) Ultrasonography, Computed Tomography and Mag netic Resonance Imaging of Hepatocellular Carcinoma: Toward Improved Treatment Decisions, Oncology 81 86 99. 124. Lee, I. J., and Seong, J. (2011) Radiotherapeutic Strategies in the Management of Hepatocellular Carcinoma, Oncology 81 123 133. 125. Yu, L., Dai, Z., Wang, Z., Fan, J., and Zhou, J. (2011) Prognostic Indicators for Tumor Recurrence after Liver Transplantation in Hepatocellular Carcinoma and Related Molecular Targeted Therapy, Oncology 81 116 122. 126. Llovet, J. M., Ricci, S., Mazzaferro, V., Hilgard, P., Gane, E., ., Hussinger, D., Giannaris, T., Shan, M., Moscovic i, M., Voliotis, D., and Bruix, J. (2008) Sorafenib in Advanced Hepatocellular Carcinoma, New England Journal of Medicine 359 378 390.

PAGE 180

180 127. Mnguez, B., and Lachenmayer, A. (2011) Diagnostic and prognostic molecular markers in hepatocellular carcinoma, D isease Markers 31 181 190. 128. Zinkin, N. T., Grall, F., Bhaskar, K., Otu, H. H., Spentzos, D., Kalmowitz, B., Wells, M., Guerrero, M., Asara, J. M., Libermann, T. A., and Afdhal, N. H. (2008) Serum Proteomics and Biomarkers in Hepatocellular Carcinoma and Chronic Liver Disease, Clinical Cancer Research 14 470 477. 129. Llovet, J. M., Pena, C., Lathia, C., Shan, M., Meinhardt, G., and Bruix, J. (2012) Plasma Biomarkers as Predictors of Outcome in Patients with Advanced Hepatocellular Carcinoma, Clinica l Cancer Research 130. Shafizadeh, N., Ferrell, L. D., and Kakar, S. (2008) Utility and limitations of glypican 3 expression for the diagnosis of hepatocellular carcinoma at both ends of the differentiation spectrum, Mod Pathol 21 1011 1018. 131. Perad ziryi, H., Kaplan, N. A., Podleschny, M., Liu, X., Wehner, P., Borchers, A., and Tolwinski, N. S. (2011) PTK7/Otk interacts with Wnts and inhibits canonical Wnt signalling, EMBO J 30 3729 3740. 132. Lahat, G., Zhu, Q. S., Huang, K. L., Wang, S., Bolshako v, S., Liu, J., Torres, K., Langley, R. R., Lazar, A. J., Hung, M. C., and Lev, D. (2010) Vimentin Is a Novel Anti Cancer Therapeuti c Target; Insights from In Vitro and In Vivo Mice Xenograft Studies, PLoS ONE 5 e10105. 133. Balakrishnan, A., Penachioni, J. Y., Lamba, S., Bleeker, F. E., Zanon, C., Rodolfo, M., Vallacchi, V., Scarpa, A., Felicioni, L., Buck, M., Marchetti, A., Comoglio, P. M., Bardelli, A., and Tamagnone, L. (2009) Molecular profiling of Human Mutation 30 1167 1174. 134. Sadanandam, A., Varney, M. L., Singh, S., Ashour, A. E., Moniaux, N., Deb, S., Lele, S. M., Batra, S. K., and Singh, R. K. (2010) High gene expression of semaphorin 5A in pancreatic cancer is associated with tumor growth invasion and metastasis, International Journal of Cancer 127 1373 1383. 135. Li, X., and Lee, A. Y. W. (2010) Semaphorin 5A and Plexin B3 Inhibit Human mediated Inactivation of Rac1 GTPase, Journal of Biological Chemistry 285 32436 32445. 136. Li, X., Law, J. W. S., and Lee, A. Y. W. (201 2) Semaphorin 5A and plexin B3 regulate human glioma cell motility and morphology through Rac1 and the actin cytoskeleton, Oncogene 31 595 610.

PAGE 181

181 137. Shangguan, D., Meng, L., Cao, Z. C., Xiao, Z., Fang, X., Li, Y., Cardona, D., Witek, R. P., Liu, C., and Tan, W. (2008) Identification of Liver Cancer Specific Aptamers Using Whole Live Cells, Analytical Chemistry 80 721 728.

PAGE 182

182 BIOGRAPHICAL SKETCH Basri Gulbak an was born in Balikesir, Turkey After completing the high school, he attended the Hacettepe University to get his B.S degree. He obtained his B. S. (2004) in chemistry and his master of science (2006) in physical c hemistry. He joined the University of Florida in 2007 and pursued his Ph D training under the supervision of Dr. Weihong Tan and co supervision of Dr.David H.Powell