NOVEL BIOMEDICAL APPLICATIONS
OF MALDI AND ELECTROSPRAY
MASS SPECTROMETRY
by
Kim Yoke Ching Fung
A dissertation submitted in fulfillment of the requirements for the degree of Doctor of Philosophy
University of New South Wales Sydney, Australia 2001 I hereby declare that this submission is my own work and to the best of my knowledge it contains no material previously published or written by another person, nor material which to a substantial extent has been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis.
I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.
December, 2001 ACKNOWLEDGEMENTS
I would like to express my appreciation to the following people:
• Prof. Mark Duncan for the support, advice and guidance with every aspect of my degree and for the many opportunities presented to me over the past four years.
• Dr. George Smythe for being my co-advisor and for the support you have given me throughout my degree.
• Dr. Carol Morris and Dr. Robert Sack for providing the tear samples and for your advice and insight regarding the data generated.
• Dr. David Friedman for your help with the prostate fluid experiments.
• Martin Bucknall for your help with the studies on quantitative MALDI.
• Dr. Joseph Zirrolli for your day-to-day support, and for sharing your vast knowledge of mass spectrometry with me.
• Staff and fellow students (past and present) from the labs I have interacted with during the course of my work for the great times experienced both in the lab and socially.
Finally, I would like to thank my family and close friends for their continual love and support as well as for all the good times we have shared. ABSTRACT
Over the last decade, developments in mass spectrometry have made the analysis of high molecular weight involatile biomolecules, including peptide and proteins, a reality.
Concurrent expansions in protein and genomic databases, as well as progress in bioinformatics, have enabled proteins to be unambiguously identified using sensitive mass spectrometric techniques such as matrix assisted laser desorption ionisation
(MALDI) and electrospray ionisation (ESI).
This thesis investigates the application of mass spectrometry, in combination with techniques such as gel electrophoresis and liquid chromatography, for the analysis of peptides and proteins in biological fluids. Peptides and proteins in human tear fluid were characterised using a combination ofMALDI-TOFMS and ESI-LC/MS/MS. Direct analysis of tear fluid by MALDI-TOFMS detected over 30 peptides and proteins and
MALDI-PSD identified homologous peptides derived from the C-terminus oflacrimal proline-rich protein. ESI-LC/MS/MS of tryptic peptides identified many more proteins, including known constituents of human tear and proteins previously not reported as components of the tear film.
Seminal fluid proteins were separated by gel electrophoresis and identified by peptide mass fingerprinting. Although over 300 protein spots were detected, only 32 unique proteins were identified including semenogelin I, semenogelin II, prostate specific
antigen and prostate secreted seminal plasma protein. The remaining proteins were
identified as protein isoforms or modified proteins. Additional analysis by MALDI- TOFMS and ESI-LC/MS/MS identified many proteolytic products of semenogelin I and
semenogelin II.
The utility of mass spectrometry for the quantification of proteins and other biomolecules was also explored. The relative abundance of more than 20 proteins in open and closed eye tear fluid was measured using ESI-LC/MS following esterification of proteolytic peptides with isotopomers of butanol.
Also, the potential ofMALDI-TOFMS for the absolute quantification of various biomolecules is explored. Rat growth hormone, human insulin, LW-hemorphin- 7, the
catecholamines epinephrine and norepinephrine, and homovanillic acid were quantified
in biological tissue or fluid using stable isotopomers or structural homologues as
internal standards. The role of mass spectrometry in global protein identification and
quantification is also discussed. TABLE OF CONTENTS
LIST OF FIGURES ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• V
LIST OF TABLES •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• VIII
CHAPTER 1: INTRODUCTION 1
1.1. Introduction .•.••.•.••.•.••.•.••..•.•.•••.•...... •...... •...•.••.•.••.•..••.••.•.••.••..•.••.•.....••.••..•.••.••.. 2 1.2. Matrix assisted laser desorption ionisation ...... 3 1.3. Electrospray mass spectrometry ...... 10 1.4. Ion dissociation and tandem mass spectrometry ...... 16 1.5. MALDI and ESI in the biological sciences ...... 19 1.5.1. Quantification of biomolecules by mass spectrometry ...... 19 1.5.2. Analysis ofbiomolecules in complex mixtures ...... 21 1.6. The emergence of Proteomics ...... 25 1.7. Aims ••••••••••••••••••••••••••••••••••••.•.••.•.••..•..•.•.••.••.••••.••.•.••.•.••.•.••.•.••..••••.••.•.•••••••••••••••••••.•• 27
CHAPTER 2: METHODS 31
2.1. Instrumentation················································~······················································ 32 2.2. MALDI matrices •.••••••••••••••••••••••••••••••••••••••••••••••••••••••••.•.•••••••••••.••••.•.••.•.••.•.•••••••••••• 33 2.3. Proteolytic en.zymes •.••••••.•••••.•.••.•.••.•.••.••.•.••.•.•.••...•••.••••••••••••••••.••••••••..••••.••••.•.••••••• 33 2.4. Protein identification criteria .••.•.••.•.••.••.•.•••••••••••••••.••.•.••.•..•.•.••.•..••••..•••.••••••••••••••• 34 2.4.1. MALDI-TOF mass spectrometry ...... 34 2.4.2. Electrospray mass spectrometry ...... 34 2.S. Database search criteria •.••..••.•.•••••••••••••....•.•.•••••••••••••••.••.•.••.•.••.•.••.•.••.•.••.•.••.•.•..•.• 35 2.6. Identification of protein constituents in human tear ...... 36 2.6.1. Sample collection ...... 36 2.6.2. Analysis of whole tear sample...... 36
i 2.6.2.1. MALDI analysis ...... 36 2.6.2.2. Electrospray mass spectrometry...... 37 2.6.3. Isolation and detection oflacrimal proline-rich protein ...... 37 2.6.4. Quantification of tear fluid proteins ...... 38 2.6.4.1. Apomyoglobin ...... 38 2.6.4.2. Tear fluid proteins ...... 39 2. 7. Analysis of the peptide and protein components in human seminal plasma ..... 41 2. 7 .1. Sample collection ...... 41 2.7.2. Two dimensional gel electrophoresis ...... 41 2.7.3. One dimensional gel electrophoresis ...... 42 2.7.4. Mass spectrometry ofunfractionated seminal fluid ...... 43 2. 7 .5. Protein identification ...... 43 2.7.5.1. MALDI-TOF mass spectrometry ...... 43 2.7.5.2. ESI mass spectrometry ...... 44 2.8. Quantification of biomolecules by MALDI-TOFMS ...... 45 2.8.1. Analysis of growth hormone in rat pituitary tissue ...... 45 2.8.2. Quantification of insulin in human pancreatic tissue ...... 45 2.8.3. Analysis ofhemorphins in human adrenal and pheochromocytoma tissues ...... 46 2.8.4. Analysis of catecholamines in human adrenal and pheochromocytoma tissue ...... 47 2.8.5. Analysis ofhomovanillic acid in human urine samples ...... 48 2.8.6. Data acquisition and processing ...... 49
CHAPTER 3: MASS SPECTROMETRY AND PROTEIN IDENTIFICATION:
APPLICATION TO HUMAN TEAR FLUID 50
3.1. Introduction ...... 51 3.2. Methods ...... 53 3.3. Results ...... 54 3.3 .1. The peptide components of human open eye tear ...... 54 3.3.2. The detection and identification oflacrimal proline-rich protein ...... 76 3.3.3. Analysis ofunfractionated human tear proteins by ESI-LC/MS/MS ...... 80 3.4. Discussion ...... 108
11 CHAPTER 4: COMPREHENSIVE PEPTIDE AND PROTEIN IDENTIFICATION:
APPLICATION TO THE ANALYSIS OF HUMAN SEMINAL FLUID 111
4.1. Introduction ...... 112 4.2. Methods ...... •...... 115 4.3. Results ...... 115 4.3.1. Detection and identification of proteins by two dimensional gel electrophoresis 115 4.3.2. Detection and identification of proteins by one dimensional gel electrophoresis 130 4.3.3. Direct analysis of seminal fluid by MALDI-TOFMS and ESI-MS ...... 145 4.4. Discussion ...... 153
CHAPTER 5: QUANTIFICATION OF BIOMOLECULES BY MALDI-TOF MASS
SPECTROMETRY 157
S.1. Introduction ...... 158 5.2. Methods ...... 160 5.3. Results ...... 161 5.3.1. Quantification of proteins in biological tissue ...... 161 5.3.2. Quantification of peptides in biological samples ...... 166 5.3.2.1. Insulin in human pancreatic tissue ...... 166 5.3.2.2. LVV-hemorphin-7 in human adrenal gland ...... 173 5.3.3. Quantification oflow mass analytes in biological samples ...... 175 5.3.3.1. Catecholamines in human adrenal gland ...... 175 5.3.3.2. Homovanillic acid in human urine ...... 178 5.4. Discussion ...... 182
iii CHAPTER 6: ALTERNATIVE APPROACHES TO PROTEIN QUANTIFICATION 187
6.1. Introduction ...... 188 6.2. Methods ...... 192 6.3. Results ...... 193 6.3.1. Detn.onstration of the approach ...... 193 6.3.2. Identification of esterified peptides in open and closed eye tear...... 200 6.3.3. Relative quantification of proteins in open and closed eye tear fluid ...... 203 6.4. Discussion ...... 211
CHAPTER 7: DISCUSSION 214
7.1. Discussion ...... 215 7.2. Protein identification strategies ...... 216 7 .2.1. Two dimensional gel electrophoresis and peptide mass fingerprinting ...... 218 7.2.2. Direct analysis of proteins by ESI-LC/MS/MS ...... 220 7.2.3. Detection and identification of endogenous peptides in biological samples ...... 222 7.3. Characterising protein post-translational modifications ...... 224 7 .3 .1. Detection and isolation of modified proteins ...... 225 7.3.2. Identifying post-translational modifications ...... 227 7 .4. Protein quantification ...... 229 7.4.1. Relative quantification of proteins ...... 230 7.4.2. Quantification of intact proteins ...... 232 7.5. Alternative technologies for proteomic studies ...... 234 7.6. Conclusions ...... 237 7.7. Summary ...... 238
CHAPTER 8: REFERENCES 245
References ...... 246
iv LIST OF FIGURES
CHAPTERl Figure 1.1. A schematic diagram of the MALDI ionisation process...... 5 Figure 1.2. A schematic diagram of a MALDI-TOF mass spectrometer with delayed extraction...... 9 Figure 1.3. A schematic diagram of the electrospray ionisation process...... 12 Figure 1.4. A comparison ofESI and MALDI spectra of horse apomyoglobin...... 13
CHAPTER3 Figure 3.1. A MALDI-TOF mass spectrum of human tear...... 55 Figure 3.2. Post-source decay spectra for the abundant tear peptides...... 57 Figure 3.3. The amino acid sequence for the intact lacrimal proline-rich protein...... 75 Figure 3.4. An example of a MALDI-TOF mass spectrum for one of the SEC fractions of human tear fluid ...... 77 Figure 3.5. Amino acid coverage of the lacrimal proline-rich protein following its isolation by size exclusion chromatography...... 79 Figure 3.6. The base peak chromatogram of the tryptic peptides detected in human tear plotted over four distinct mass ranges ...... 81
CHAPTER4 Figure 4.1. An annotated silver-stained two dimensional gel of seminal fluid proteins separated over the pi range 4 - 7 ...... 116 Figure 4.2. An annotated silver-stained two dimensional gels of seminal fluid proteins separated over the pi range 6 - 11 ...... ·...... 117 Figure 4.3. Base peak chromatogram for 4 different regions of the 1D SDS-PAGE gel of seminal fluid proteins ...... 131 Figure 4.4. The amino acid sequences of the histone 2A family of proteins and the tryptic peptides that were detected by ESI-LC/MS/MS ...... 141
V Figure 4.5. The amino acid sequences of the histone 2B family of proteins and the tryptic peptides that were detected by ESI-LC/MS/MS ...... 143 Figure 4.6. A MALDI mass spectrum ofunfractionated seminal fluid ...... 146 Figure 4.7. The amino acid sequence of semenogelin I showing those peptides identified by ESI-LC/MS/MS ...... 149 Figure 4.8. The amino acid sequence of semenogelin II showing those peptides identified by ESI-LC/MS/MS ...... 150
CHAPTERS Figure 5.1. A representative MALDI mass spectrum for growth hormone in a rat pituitary extract...... 163 Figure 5.2. A representative standard curve obtained for methionyl rat growth hormone without an internal standard ...... 164 Figure 5.3. A representative standard curve obtained for methionyl rat growth hormone using ~-lactoglobulin as the internal standard ...... 165 Figure 5.4. Representative MALDI-TOF mass spectra for the analysis of a mixture of human insulin and porcine insulin...... 167 Figure 5.5. The amino acid sequence for human and porcine insulin...... 169 Figure 5.6. Representative standard curves obtained for human insulin using porcine insulin as the internal standard ...... 170 Figure 5. 7. A comparison of LVV-hemorphin- 7 concentrations in human adrenal gland determined by MALDI-TOFMS and ESI-MS ...... 174 Figure 5.8. A representative MALDI-TOF mass spectrum for norepinephrine, epinephrine and their respective internal standards in human adrenal extracts...... 17 6 Figure 5.9. A representative MALDI mass spectrum for homovanillic acid detected in human urine ...... 179 Figure 5.10. Homovanillic acid concentrations in human urine determined by MALDI TOFMS vs homovanillic acid values determined by a commercial clinical laboratory ...... 180
VI CHAPTER6
Figure 6.1. A schematic showing the addition of a butyl ester to the C-terminus of a tryptic peptide...... 195 Figure 6.2. A representative MALDI mass spectrum of horse apomyoglobin following digestion with trypsin...... 196
Figure 6.3. A MALDI-TOF mass spectrum showing do-butylated and d10-butylated tryptic peptide pairs derived from the proteins present in open and closed eye tear respectively...... 201 Figure 6.4. An example of a fragment ion spectrum for an esteri:fied tryptic peptide detected in open eye tear...... 202 Figure 6.5. An example of a mass spectrum of esterified open and closed eye tear showing at least three different co-eluting tryptic peptide pairs ...... 204 Figure 6.6. The extracted total ion chromatogram for one of the co-eluting peptide pairs at a retention time window of 60 - 62 minutes ...... 206
vu LIST OF TABLES
CHAPTER2 Protein database search criteria ...... 35
CBAPTER3 Table 3.1. Fragment ions detected in the post-source decay spectra of the peptide [M+H]+ 1,629.69 Da...... 59 Table 3.2. Fragment ions detected in the post-source decay spectra of the peptide [M+H]+ 1,443.74 Da...... 62 Table 3.3. Fragment ions detected in the post-source decay spectra of the peptide [M+H]+ 1,330.52 Da...... 65 Table 3.4. Fragment ions detected in the post-source decay spectra of the peptide [M+H]+ 1,105.51 Da...... 68 Table 3.5. Fragment ions detected in the post-source decay spectra of the peptide [M+H]+ 848.37 Da...... 71 Table 3.6. The amino acid sequence of five of the most abundant peptides detected in human tear...... 74 Table 3.7. Proteins identified by ESI-LC/MS/MS that have been previously reported as components of the human tear film ...... 84 Table 3.8. Proteins that have been detected in human ocular tissue but not in the tear film ...... 93 Table 3.9. Proteins identified by ESI-LC/MS/MS that are reportedly elevated in the tear fluid of patients with various pathological conditions...... 94 Table 3.10. Proteins identified by ESI-LC/MS/MS that have been reported in the tear film of animal species other than human...... 95 Table 3.11. Proteins identified by ESI-LC/MS/MS that have not previously been reported as components of the human tear film ...... 96
Vlll CHAPTER4 Table 4.1. Proteins in seminal fluid that were identified by 2DE (pi range 4 - 7) ...... 118 Table 4.2. Co-migrating proteins in seminal fluid that were identified by 2DE (pi range 4 - 7) ...... 124 Table 4.3. Proteins in seminal fluid that were identified by 2DE (pi range 6- 11) ...... 126 Table 4.4. Co-migrating proteins in seminal fluid that were identified by 2DE (pi range 6 - 11 ) ...... 129 Table 4.S. Proteins found in seminal fluid following separation by 1D gel electrophoresis, in-gel digestion and ESI-LC/MS/MS analysis ...... 132 Table 4.6. Peptides that were detected by MALDI-TOFMS in unfractionated seminal fluid and subsequently identified by ESI-LC/MS/MS ...... 148 Table 4.7. Peptides in unfractionated seminal fluid that were identified by ESI LC/MS/MS and database searching...... 151
CHAPTERS Table S.1. Insulin concentrations measured in human pancreatic tissue obtained from two cadavers ...... 172 Table S.2. Concentrations of norepinephrine and epinephrine in human adrenal tissue and pheochromocytoma tissue...... 177
CHAPTER6 Table 6.1. The relative abundance oftryptic peptides derived from apomyoglobin ...... 199 Table 6.2. The relative abundances oftryptic peptides derived from tear lipocalin ...... 208 Table 6.3. Proteins that were found to be more abundant in open eye tear in comparison to closed eye tear...... 209 Table 6.4. Proteins that were found to be more abundant in closed eye tear in comparison to open eye tear...... 210
ix CHAPTER 1
INTRODUCTION
I 1.1. Introduction
Recent technical advances have established the importance of mass spectrometry in the biological sciences. In particular, the development of sensitive and versatile ionisation techniques in the late 1980s, primarily matrix assisted laser desorption ionisation
(MALDI) [Karas and Hillenkamp, 1988] and electrospray ionisation (ESI) [Whitehouse
et al., 1985], and their coupling to various mass analysers have lead to affordable, powerful and versatile analytical instruments. Prior to the development of techniques
such as plasma desorption (PDMS) and fast atom bombardment (F AB) mass
spectrometry, only molecules that were oflow mass (i.e.,< 1,000 Da), volatile, or able to be made volatile by chemical derivatisation procedures, could be analysed easily
[Macfarlane and Torgerson, 1976; Barber et al., 1981]. The introduction ofMALDI and
ESI have allowed the mass limitations of these techniques to be overcome and many
additional classes of molecules can now be analysed, including high mass biomolecules
(up to 1,000,000 Da) [Beavis and Chait, 1990; Schriemer and Li, 1996]. This has had
tremendous impact in the biological sciences because molecules such as peptides,
proteins and oligonucleotides can now be routinely examined by mass spectrometry.
Most importantly, both of these techniques, described as soft ionisation processes, result
in minimal fragmentation, and have enabled accurate intact mass determinations of
biomolecules to be performed for the first time [Karas and Hillenkamp, 1988; Fenn et
al., 1989].
The versatility of time-of-flight (TOP) and ESI mass spectrometry (ESI-MS) has
increased considerably due to factors such as the implementation of delayed extraction
(time-lag focusing) [Wiley and McLaren, 1955; Brown and Lennon, 1995; Whittal and
Li, 1995; Bahr et al., 1997; Takach et al., 1997] and incorporation of an electrostatic
2 mirror (reflectron) [Mamyrin et al., 1973; Takach et al., 1997]. These have lead to dramatic improvements in resolution and mass accuracy for MALDI sources coupled to
TOF mass analysers (MALDI-TOFMS). In addition, electrospray ionisation has enabled the introduction of samples in a liquid phase and hence has facilitated the coupling of on-line separation techniques to mass spectrometry [Banks, 1997; Niessen, 1998;
Choudhary et al., 2000; Dalluge, 2000]. Consequently, mass spectrometry has emerged as a popular and versatile analytical tool in the biomedical sciences. Utilised together with other techniques, mass spectrometry now enables molecules involved in disease processes to be characterised and potential biomarkers for diagnostic, prognostic or therapeutic purposes to be identified.
1.2. Matrix assisted laser desorption ionisation
Desorption and ionisation of molecules from solid sample supports was first described
in the 1970s by Macfarlane et al. (1976) and Posthumus et al. (1978). These processes,
known as plasma desorption and laser desorption, employed the use of radioactive
decay products of californium-252 or a laser emitter, respectively, to promote ionisation
of sample molecules. Together with the introduction of F AB in 1981 [Barber et al.,
1981 ], analysis of involatile molecules, including proteins and oligonucleotides, became
possible for the first time [Sundqvist et al., 1984a; Sundqvist et al., 1984b;
Tsarbopoulos, 1989; Tsarbopoulos et al., 1991].
Advances in and refinements of these ionisation techniques resulted in the advent of
MALDI. MALDI, first described by Karas and Hillenkamp [Karas and Hillenkamp,
1988] and independently by Tanaka and coworkers (1988), involves the co-
3 crystallisation of the analyte with a matrix followed by laser ablation of the
sample/matrix mixture. By employing a vast excess of a matrix molecule, the extensive
fragmentation observed with plasma desorption and laser desorption ionisation is overcome. Molecules employed as the matrix are typically small organic acids, such as
cinnamic acid derivatives, capable of absorbing energy at the wavelength (usually in the
UV spectrum) of the laser being used [Beavis and Chait, 1989a; Beavis and Chait,
1989c; Juhasz et al., 1993]. The matrix serves to absorb the initial energy of the laser
and then to transfer this energy to the analyte molecule, resulting in ablation of both the
sample and matrix molecules and their ejection into the gaseous phase [Talrose et al.,
1999; Karas et al., 2000b]. During this process ions are formed, however, the exact mechanism involved with ion formation is still unclear [Talrose et al., 1999; Karas et al., 2000b]. Figure 1.1 shows a mechanistic diagram describing the MALO I ionisation process. Although the matrix serves to promote ionisation and detection of the intact
analyte molecule, it has also been observed that ion signals derived from the matrix can
suppress the signal for the analyte of interest, or lead to the formation of analyte-matrix
adducts [Beavis and Chait, 1989b].
4 Figure 1.1. A schematic diagram of the MALDI ionisation process.
Ti rne-of- f Ii grit t·1ass Ana l_yser
• ••••••••••••••
Desorbed 'pi ume' of _,,.,--- m':itrix 3nd analyte ions • /_,/..-,/ = An31~.ite • • = M':itrix • -• = Cation (e.g. Na+ or H+) • • • ...... Sample • • - •. - • • pl11te - . - • . -- .. \I • ;, • • • • • . • -·• . . • \ ..- . • • • • • · . • . . ·- .. · -·- .- ·- . . -.• ..- - . . -...... - ·. - . ·•. . -~
© 2000 PAUL GATES
Source: http://www-methods.ch.cam.ac.uk/meth/ms/theory/maldi.html
5 Characteristic of desorption/ionisation techniques, MALDI also requires samples to be introduced into the mass spectrometer in the solid phase and this hinders interfacing
MALDI to on-line separation techniques such as high performance liquid chromatography (HPLC). Because MALDI predominantly forms the singly protonated molecule and induces minimal fragmentation [Karas and Hillenkamp, 1988], the resulting mass spectrum is easy to interpret: the predominant ion in a MALDI mass spectrum corresponds to the singly protonated analyte (i.e., [M+Ht in positive ion mode). The simplicity of the MALDI mass spectrum, the sensitivity of the technique and the speed of analysis make this an ideal tool for quality control analysis of synthetic compounds, such as recombinant proteins, where both the intact mass of the analyte and the relative purity of the sample can be rapidly determined [Kanazawa et al., 1999;
Villanueva et al., 2001]. Many other classes of molecules are amenable to analysis by
MALDI-TOF mass spectrometry (MALDI-TOFMS), including synthetic polymers [Wu and Odom, 1998; Marie et al., 2000], a wide range oflow molecular weight natural products [Duncan et al., 1993; Gimon et al., 1994; LeRiche et al., 2001], lipids
[Fujiwak:i et al., 1999; Schiller et al., 1999; Ayorinde et al., 2000; Petkovic et al., 2001],
oligosaccharides [Stahl et al., 1994; Harvey, 1996; Papac et al., 1996; Dai et al., 1997;
Harvey et al., 1998; Mo et al., 1998; Charlwood et al., 1999a; Charlwood et al., 1999b;
Colangelo and Orlando, 1999; Finke et al., 1999; Geyer et al., 1999; Pfenninger et al.,
1999; Sato et al., 2000; Sumi et al., 2000; Jacobs and Dahlman, 2001], peptides and
proteins [Nguyen et al., 1995; Zaluzec et al., 1995; Roepstorff, 2000], as well as
oligonucleotides [Nordhoff et al., 1992; Pieles et al., 1993; Tang et al., 1993a;
Hathaway, 1994; Nordhoff et al., 1994; Wang and Biemann, 1994; Wu et al., 1994;
Christian et al., 1995; Fitzgerald and Smith, 1995; Bentzley et al., 1996; Dai et al.,
1996; Fu et al., 1996; Juhasz et al., 1996; Roskey et al., 1996; Smimov et al., 1996;
6 Ball and Packman, 1997; Faulstich et al., 1997; Haff and Smirnov, 1997; Hahner et al.,
1997; Miketova and Schram, 1997; Zhu et al., 1997; Bleczinski and Richert, 1998; Fei et al., 1998; Owens et al., 1998; Van Ausdall and Marshall, 1998; Cotter et al., 1999;
Langley et al., 1999; F ei and Smith, 2000; Ragas et al., 2000; Bray et al., 2001].
Although MALDI is not easily coupled to on-line separation techniques, it offers many other advantages including tolerance toward contaminants such as high concentrations of salts, buffers and detergents common to many biochemical preparations, and it is able to detect numerous components in complex mixtures in a single analysis and over an extended mass range [Beavis and Chait, 1990; Wang and Chait, 1994]. Also, the uniqueness of this process has inspired numerous novel applications ofMALDI
TOFMS. For example, researchers have described direct sampling from membrane supports [Strupat et al., 1994; Vestling and Fenselau, 1994; Blackledge and Alexander,
1995; Liu et al., 1995; Gharahdaghi et al., 1996; Schreiner et al., 1996; McComb et al.,
1997; Guittard et al., 1999; Shen et al., 2001], the direct analysis of single cells and microorganisms [Holland et al., 1999; Lynn et al., 1999; Li et al., 2000a] and the direct
analysis of constituents from intact biological tissue [Caprioli et al., 1997; Chaurand et
al., 1999b; Jespersen et al., 1999; Li et al., 1999; Stoeckli et al., 1999; Stoeckli et al.,
2001]. This has enabled characterisation of abundant endogenous peptides as well as
regional molecular mapping of protein components in biological tissues and organisms.
In addition, MALDI-TOFMS has been utilised for the examination of non-covalent
complexes, such as protein-protein interactions and DNA-protein complexes [Tang et
al., 1995; Jensen et al., 1996; Farmer and Caprioli, 1998; Lin et al., 1998; Thiede and
von Janta-Lipinski, 1998; Kiselar and Downard, 2000].
7 Since its inception, MALDI has been successfully interfaced to several different types of mass analysers, including the quadrupole ion trap [Lee and Lubman, 1995; Qin et al.,
1996; Qin and Chait, 1997; Doroshenko and Cotter, 1998] and fourier transform
[Mciver et al., 1994], but the most popular combination is with the time-of-flight (TOF) mass analyser. Additionally, MALDI has been coupled to hybrid mass analysers, such as the quadrupole time-of-flight [Harvey et al., 2000; Krutchinsky et al., 2000; Loboda et al., 2000; Shevchenko et al., 2000; Baldwin et al., 2001; Griffin et al., 2001;
Kirpekar and Krogh, 2001]. However, the MALDI-TOFMS combination is affordable, practical, offers high mass accuracy, high resolution and high sensitivity over an unlimited mass range. The practical utility has also been enhanced significantly due to the advent of delayed extraction [Wiley and McLaren, 1955; Brown and Lennon, 1995;
Whittal and Li, 1995; Bahr et al., 1997]; and with the implementation of the reflectron which refocuses ions based on their energy (and effectively increases the flight length
and time), superior mass resolution (FWHM > 10000) and therefore improved mass
accuracy, are routinely achieved [Mamyrin et al., 1973; Kinsel et al., 1997; Takach et
al., 1997]. Mass errors of less than 10 ppm are routine for the characterisation of low
mass pharmacologically active compounds as well as for peptides and proteins [Fukai et
al., 2000; Lake et al., 2000; Andalo et al., 2001]. Figure 1.2 shows a schematic of a
MALDI-TOF mass spectrometer.
8 Figure 1.2. A schematic diagram of a MALDI-TOF mass spectrometer with delayed extraction.
Variable-voltage Laser grid attenuator Reflector Reffeotor (electrostallc detector mirror) Sample plate ~
Main ,ource chamber
.,_...... ~ Video carMra Linear Timed Ion detector Aperture {grounded) $elector Collision ·celt (optiOnal)
- - .... Ion path in ren.ct.or mode · • • ·...,. Lasorpeth
Source: Perseptive Biosystems. This is the configuration of the Perseptive DE-STR
system used throughout this project. This system differs only in detail from the DE-PRO
that was also employed for a portion of the work described in this thesis.
9 1.3. Electrospray mass spectrometry
In contrast to MALDI, electrospray ionisation involves the introduction of a sample in the liquid phase. Figure 1.3 shows a schematic of the electrospray process. Prior to the development of electrospray ionisation, analytes in solution could only be introduced into the mass spectrometer and analysed using techniques such as continuous flow F AB or thermospray [Blakley et al., 1980; Caprioli et al., 1986; Caprioli, 1990]. Although the principles of electrospray ionisation were originally described by Dole et al. (1968), its application to mass spectrometry was first demonstrated by Whitehouse and coworkers (1985) when they successfully detected biomolecules such as gramicidin S, cyclosporin and substance P. They also proposed the potential ofESI for interfacing liquid chromatography to a mass spectrometer [Whitehouse et al., 1985; Fenn et al.,
1989].
The formation of ions by this process has been widely studied and involves the
application of a voltage to an electrospray capillary, thereby imparting a charge to the
liquid stream carrying the analyte(s) of interest. The application of an electric field leads
to the formation of a Taylor cone at the capillary tip and dispersion of charged droplets.
Desolvation results in smaller droplets thereby increasing the charge density on the
surface of each. As the radius of the droplet continues to decrease, the charge repulsion
(i.e., Coulombic repulsion) of each individual droplet exceeds the cohesive surface
tension (i.e., the charge density approaches the Rayleigh limit) forcing it to disintegrate
into numerous droplets of smaller radii, a process known as Coulomb fission [Gaskell,
1997; Cole, 2000; Karas et al., 2000a; Kebarle, 2000]. This process ultimately leads to
each analyte molecule retaining multiple charges (protons). The mass spectrum
generated is characterised by multiple mass to charge (m/z) ratios for the population of
10 analyte molecules [Fenn et al., 1989; Smith et al., 1990; Cole, 2000]. Figure 1.4 shows an example of an ESI mass spectrum for myoglobin compared with a MALDI mass spectrum of the same molecule.
11 Figure 1.3. A schematic diagram of the electrospray ionisation process.
Taylor cone
Ca1hodo
Electrospray capillary maintained at high voltage I .., ~"--. . T . .,~ • ,+• .. + - • "" ....Y - •• + / ••• .. + " •.,.,./ • .. t- t .. .. 4 // ..' ... / -~. Anode
I/\ .. 0...,_
Powot Supply
Coulomb fission occurs as the Desolvation of charged droplets charge density exceeds the surface tension of each droplet
Source: Griffiths et al. , 2001
12 Figure 1.4. A comparison ofESI and MALDI spectra of horse apomyoglobin.
A. An ESI mass spectrum showing the multiple charge states detected for horse
apomyoglobin (16,951 Da). The insert shows the deconvoluted mass spectrum.
16951.0 ..... C a, u C Ill '0 C :I .0cc a, > i ai +16 a: 0 1 .5 15500 16000 16500 17000 17500 18000 18500 19000 100 Mass (Da) +15 +17 1131.1 +14 .2 1211.9 +1 94 .9 +13 1 .o ;;e !!.. +1 8 .3 +12 a, u ffi.s 141 .5 C Ill '0 C :I .0 cc +21 .2 +11 t 1541.9 i ai +22 a: 77 .5
+9 1 .2
0 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 inh.
13 Figure 1.4. A comparison ofESI and MALDI spectra of horse apomyoglobin.
B. A MALDI mass spectrum obtained for horse apomyoglobin showing the singly
([M+Ht 16,952 Da) and doubly ([M+2H]2+ 8,476 Da) charged species.
16952.56 100
8476.78 -0~
9200 12400 15600 18800 22000 Mass (mlz)
14 When compared to MALDI mass spectra, those generated by ESI are generally more
difficult to interpret, especially when analysing large molecules, e.g., proteins, oligonucleotides, and other polymers. Due to the more complex nature of ESI mass
spectra, multicomponent samples are usually examined only after separation. However, because this ionisation mode is compatible with on-line separation techniques, such as
HPLC and capillary electrophoresis, it offers a distinct advantage over MALDI [Banks,
1997; Niessen, 1998; Choudhary et al., 2000; Dalluge, 2000]. For example, facile
identification of endogenous peptides and proteins in biological fluids such as urine and blood filtrate has been reported [Evershed et al., 1993; Valaskovic et al., 1996; Heine et al., 1997; Raida et al., 1999]. Similar to MALDI, this mode of ionisation is also
amenable to the analysis of many different classes of molecules (e.g., peptides, proteins,
oligonucleotides, lipids, drug molecules and alkaloids), and the accurate intact mass of molecules can also be determined [Gelpi, 1995]. Because ESI is a soft ionisation
technique, it has also been employed for the characterisation of non-covalent complexes
[Jaquinod et al., 1993; Bayer et al., 1994; Bakhtiar and Steams, 1995; Pocsfalvi et al.,
1997; Pramanik et al., 1998]. By combining ESI with tandem mass spectrometry, or in
source collision induced dissociation (CID), structural information for various organic
molecules, such as natural products, drug metabolites and peptides can also be acquired
with relative ease [Smith et al., 1990; Griffiths et al., 2001].
The most noticeable recent advancement in ESI is the development oflow flow rates ( <
1 µL/min) for sample introduction, commonly termed nano-electrospray (nano-ESI,
nanospray) [Gale and Smith, 1993; Andren et al., 1994; Emmett and Caprioli, 1994;
Davis et al., 1995; Wilm and Mann, 1996; Griffiths, 2000; Karas et al., 2000a]. This
substantial reduction in flow rate contributes to less sample consumption and has been
15 shown to offer greater sensitivity. For instance, only a few microlitres of a sample
solution is required to obtain molecular weight and structural information [Wilm and
Mann, 1996; Karas et al., 2000a]. Routine analysis of trace levels of peptides, carbohydrates and lipids have been reported and as a result, nanospray has been readily adopted in the biological sciences [Stenfors et al., 1997; Gatlin et al., 1998; Lhoest et al., 1998; Griffiths, 2000; Karas et al., 2000a; Rafatro et al., 2000; Zamfir et al., 2000].
Because nanospray allows the investigator to work with low volumes and consumes less
sample, it is ideally suited to applications where the sample is limited and multiple MS
experiments are performed. For instance, one area of interest is the mapping of phosphorylation sites of proteins involved in signal transduction pathways [Neubauer
and Mann, 1999; Ogueta et al., 2000].
1.4. Ion dissociation and tandem mass spectrometry
Both MALDI and ESI are soft ionisation techniques that result in minimal
fragmentation because of the low internal energy of the analyte ion [Karas and
Hillenkamp, 1988; Fenn et al., 1989]. In order to obtain structural information, these
ionisation techniques have been coupled with processes capable of increasing the
internal energy of ions and thereby inducing fragmentation [Griffiths et al., 2001]. For
ESI the most commonly employed analysers are currently the triple quadrupole and the
quadrupole ion trap [Griffiths et al., 2001]; however, commercially available hybrids,
such as the quadrupole time-of-flight [Shevchenko et al., 1997; Doroshenko and Cotter,
1998; Harvey et al., 2000; Krutchinsky et al., 2000; Loboda et al., 2000; Shevchenko et
al., 2000; Griffin et al., 2001; Shevchenko et al., 2001] are increasingly popular. TOF
TOF instruments incorporating a collision cell between the two flight tubes are now
16 commercially available and have generated considerable interest [Medzihradszky et al.,
2000].
Since its inception, tandem mass spectrometry (MS/MS) has been applied in the pharmaceutical industry to characterise bioactive natural products and their metabolites,
and in quantitative drug studies; more recently, however, it has had tremendous impact
in the area of peptide sequencing and protein identification. Peptide sequencing by tandem mass spectrometry was first demonstrated in the mid-1980s [Tomer et al., 1984;
Cody et al., 1985; Hunt et al., 1985; Hunt et al., 1986; Hunt et al., 1987; Biemann,
1988] and this has lead to the refinement of many strategies, based on the generation of peptides by enzymatic or chemical cleavage, to unambiguously identify proteins. In
addition, the ability of tandem mass spectrometry to overcome some of the difficulties
associated with Edman sequencing - N-tenninally blocked or post-translationally
modified peptides - has contributed to its widespread use in protein analysis [Biemann
and Scoble, 1987; Biemann, 1988]. The recent explosion in the number of protein
sequences that are widely available, coupled with the development of powerful
computer search algorithms, has enabled rapid identification of proteins in biological
samples based on the sequence of relatively few(< 10) amino acids [Larsen and
Roepstorff, 2000].
The maturation of the quadrupole ion trap mass spectrometer over the last decade has
facilitated interest and development in MS/MS analysis [March, 1997]. In contrast to
the triple quadrupole mass spectrometer, the quadrupole ion trap is able to isolate and
store ions of interest (precursor ion) by manipulation of the radio frequency (RF)
potential and direct current (DC) voltage applied to the ring electrodes and end cap
17 respectively [Cooks et al., 1991; Jonscher and Yates, 1997]. The selected trapped precursor ions are subsequently decomposed prior to their ejection and detection.
Because newly generated fragment ions can also be selectively isolated and stored, multiple fragmentation cycles are possible (MSn) [Cooks et al., 1991]. In addition, the high efficiency with which quadrupole ion trap mass spectrometers can trap and fragment ions has contributed to their popularity in the area of protein and peptide characterisation [Davis and Lee, 1998; McGinley et al., 2000].
The mechanism involved in generating fragment ion information by MALDI-TOFMS differs to that described for the triple quadrupole or quadrupole ion trap mass
spectrometers. This process, termed post-source decay (PSD), involves the detection of
fragment ions formed by the metastable decomposition of precursor ions following their
acceleration into the first field-free region of the TOP mass spectrometer [Spengler et al., 1992; Kaufmann et al., 1993; Chaurand et al., 1999a]. Excess intramolecular energy
gained by the precursor ion during the ionisation process is released by decomposition
of the molecule. Because the fragment ions are formed in the field-free region and retain
the original velocity of the precursor ion, they contain a distribution of kinetic energies
dependant on their mass (KE = ½ mv2) and can only be detected following refocusing in
an electrostatic mirror (i.e., by reflectron TOP mass spectrometry) [Spengler et al.,
1992; Kaufmann et al., 1993; Cornish and Cotter, 1994; Cordero et al., 1995; Chaurand
et al., 1999a]. Post-source decay analysis has been used extensively for both peptide and
oligonucleotide sequencing [Bentzley et al., 1996; Mo et al., 1997; Gross et al., 1998;
Owens et al., 1998; Fournier et al., 2000; Gevaert et al., 2001; Gross et al., 2001; Talbo
et al., 2001], as well as for the characterisation of other biomolecules such as
oligosaccharides and small drug molecules [Lemoine et al., 1996; Garozzo et al., 1997;
18 Okamoto et al., 1997; Mo et al., 1998; Rouse et al., 1998; Yamagaki et al., 1998;
Yamagaki and Nakanishi, 1998; Mizuno et al., 1999; Viseux et al., 1999; Broberg et al.,
2000; Garozzo et al., 2000; Spina et al., 2000; Yamagaki and Nakanishi, 2000].
1.5. MALDI and ESI in the biological sciences
1.5.1. Quantification of biomolecules by mass spectrometry
Prior to the availability of ESI, quantitative analysis by mass spectrometry was mostly limited to low mass molecules amenable to separation by gas chromatography (GC)
[Ragunathan et al., 1999]. However, the introduction ofFAB and the subsequent development of continuous flow F AB enabled direct quantification of compounds such
as peptides and steroids and their metabolites [Barber et al., 1981; Gaskell et al., 1983;
Caprioli et al., 1986; Lisek et al., 1989; Gaskell, 1990; Kusmierz et al., 1990; Chen et
al., 1991; Dass et al., 1991; Ikarashi et al., 1991; Ikarashi and Maruyama, 1991;
Desiderio, 1992; Davoli et al., 1993]. Although GC-MS is still widely applied in
quantitative analysis in many areas (e.g., clinical testing, forensic or toxicological
sciences, and environmental analyses) the introduction ofESI coupled to on-line liquid
chromatography has overcome many of the obstacles associated with both GC-MS and
F AB analysis, such as mass limitations and the thermal lability and/or limited volatility
of some molecules [Niwa, 1986; Weykamp et al., 1989; Dehennin, 1990; Goldberger
and Cone, 1994; Gleispach et al., 1995; Lehrer, 1998; Risby and Sehnert, 1999;
Shindelman et al., 1999; Nexo et al., 2000; Richardson, 2000; Speed et al., 2000;
Kikuchi et al., 2001; Takayasu et al., 2001]. As a result, quantitative analyses by ESI
coupled to liquid chromatography have become routine in many settings, notably the
pharmaceutical industry, where it is predominantly applied to pharmacokinetic studies
19 [Gelpi, 1995; Tiller et al., 1997; Ayrton et al., 1998; Maurer, 1998; Lee and Kerns,
1999; Muck, 1999; Rashed et al., 1999; Vreken et al., 1999; Wong et al., 1999; Jemal et al., 2000; Jemal and Mulvana, 2000; Kato et al., 2000a; Kato et al., 2000b; Kissmeyer et al., 2000; Lau et al., 2000; Miketova et al., 2000; Riffel et al., 2000; Valentin-Blasini et al., 2000; Van Eeckhout et al., 2000; Xu et al., 2000; Holstege et al., 2001].
MALDI is an alternative ionisation technique to ESI that is also compatible with non volatile and/or high molecular weight analytes. Although it is not widely used for quantitative analysis, it possesses advantages that make it a potentially useful quantitative tool. For example, it allows analysis of molecules over an extensive mass range and it is capable of analysing complex sample mixtures without the need for
extensive sample preparation. In addition, almost any class of molecule can be analysed
and MALDI mass spectra are relatively easy to interpret, i.e., the predominant species is
the singly charged molecule. Also, analyses are fast: a single sample can be examined
within minutes and chemical modification of analytes prior to analysis is unnecessary.
These properties make quantitative MALDI-TOFMS attractive in many different areas,
for example, for rapid clinical testing and for quantification of large intact biomolecules
such as polypeptides and oligonucleotides [Duncan et al., 1993; Gusev et al., 1993;
Tang et al., 1993b; Muddiman et al., 1994; Nelson et al., 1994; Bruenner et al., 1996;
Gusev et al., 1996; Muddiman et al., 1996; Ling et al., 1998; Desiderio et al., 2000;
Gobom et al., 2000].
There has been a limited number of studies exploring the applicability of MALO1-
TOFMS as a quantitative tool [Duncan et al., 1993; Gusev et al., 1993; Harvey, 1993;
Tang et al., 1993b; Muddiman et al., 1994; Nelson et al., 1994; Jespersen et al., 1995;
20 Abell and Spoms, 1996; Bruenner et al., 1996; Gusev et al., 1996; Muddiman et al.,
1996; Tang et al., 1996; Camafeita et al., 1997; Wu et al., 1997; Kazmaier et al., 1998;
Ling et al., 1998; Sugiyama et al., 1999; Wang et al., 1999; Desiderio et al., 2000;
Gobom et al., 2000; Wang and Spoms, 2000; Horak et al., 2001]. These studies highlight many potential problems that have restricted its application including the
limited dynamic range, the incompatibility of the ionisation mode with on-line
chromatography, and the variability in the ion current measured between successive
laser shots and from sample-to-sample. Together, these factors limit its utility and
compound the errors involved with quantitative determinations. In addition, non uniform co-crystallisation of matrix and sample can also lead to poor reproducibility of results. Numerous approaches, such as electrospray deposition of sample and matrix to
improve matrix/analyte homogeneity [Preston et al., 1993; Vorm et al., 1994; Gusev et
al., 1995; Nicola et al., 1995; Hensel et al., 1997] and extensive studies concerning
matrix and internal standard selection [Gusev et al., 1993; Gusev et al., 1996;
Wilkinson et al., 1997; Horak et al., 2001], have been undertaken to increase the
applicability ofMALDI-TOFMS for quantitative analysis.
1.5.2. Analysis of biomolecules in complex mixtures
The ready availability of MALDI and ESI instruments has permitted a change in focus
from the analysis of low molecular weight organic biomolecules to the examination of
higher mass, involatile biomolecules, such as proteins. These molecules are responsible
for cell structure, cell growth and division, as well as intra- and inter- cellular regulation
and communication [Alberts, 1998]. Prior to the implementation ofMALDI and ESI,
the mass analysis of intact peptides and proteins was restricted to an upper mass limit of
21 approximately 20,000 Da at best [Hakansson et al., 1983; Fales et al., 1985; Craig et al.,
1987; Andrews et al., 1988; Jonsson et al., 1988; Roepstorff et al., 1988; Nielsen and
Roepstorff, 1989; Nielsen et al., 1989; Roepstorff, 1989; Tsarbopoulos et al., 1991].
The concurrent development of MALDI and ESI ionisation modes, and on-going refinements in mass analysers such as the time-of-flight and quadrupole ion trap, have
enabled vast expansions in the mass range capabilities of mass spectrometry, as well as improvements in mass resolution, accuracy and sensitivity.
The development of MALDI and ESI has revolutionised the way proteins are examined.
Previously, proteins were characterised using a combination of physical and biochemical methods, such as isolation and purification by HPLC, immunoaffinity
chromatography and gel electrophoresis [Hage, 1999; Weller, 2000]. Techniques such
as X-ray crystallography, nuclear magnetic resonance, amino acid analysis and Edman
sequencing were typically employed to determine properties such as the amino acid
sequence, mass, and three dimensional structure. Although these techniques are still
widely used today, they require large amounts of highly purified material and are not
suitable for the analysis of trace components in complex biological samples.
Today, separation and visualisation of proteins in complex biological samples by two
dimensional gel electrophoresis (2DE) has become a pivotal process preceding analysis
by mass spectrometry [Hanash et al., 1991]. This technique, first developed by
O'Farrell (1975), involves separation of proteins in a sample by their isoelectric point
(first dimension), followed by their molecular weight (second dimension). In addition to
aiding in protein separation, this procedure can be used to detect post-translational
modifications [Neubauer and Mann, 1999; Sickmann et al., 2001], or to provide an
22 estimate of the relative amounts of each protein in matched sample sets [Lahm and
Langen, 2000; Grus et al., 2001]. The protein(s) of interest are then excised, chemically or enzymatically cleaved at specific sites, and then the accurate mass capabilities of
MALDI-TOFMS are utilised to generate unique peptide mass maps or fingerprints
[James et al., 1993; Mann et al., 1993]. These data are then used to search databases containing the sequences of known proteins, permitting unambiguous identification of proteins [Henzel et al., 1993; James et al., 1993; Cottrell, 1994]. Aside from masses alone, structural information (sequence) can also be obtained by either ESI-LC/MS/MS or MALDI-PSD, and this provides further information that identifies a protein
[Shevchenko et al., 1996b; Wilm et al., 1996; Chaurand et al., 1999a; Keough et al.,
2000; Medzihradszky et al., 2001].
One of the first large scale studies involving protein identification by 2DE and mass
spectrometry was described using yeast as the model system [Shevchenko et al., 1996a].
This study demonstrated that given a completely sequenced genome, up to 90% of
visualised proteins can be identified with high confidence by peptide mass
fingerprinting and database searching alone. Partial amino acid sequences obtained by
nanospray tandem mass spectrometry were also employed to search databases
containing expressed sequence tags (ESTs) and this enabled additional, and some novel
proteins, to be identified.
Alternative strategies for global protein analysis based on mass spectrometry are
emerging. The most notable include the analysis of complex protein mixtures by ESI
mass spectrometry following enzymatic digestion. Peptides are first separated by
reverse phase liquid chromatography, or by multiple chromatographic separations in
23 series, then analysed by tandem mass spectrometry [McCormack et al., 1997; Yates et al., 1997; Link et al., 1999; Yates et al., 2000; Davis et al., 2001; Washburn et al.,
2001]. This approach aims to identify every protein in a sample in a single chromatographic analysis and bypasses the need for prior electrophoretic separation.
Although this technique is capable of rapidly identifying proteins, post-translational modifications are usually not detected or identified, and the in vivo form of each protein is assumed but not determined.
The protein identification strategies outlined above assume the primary structure of proteins and peptides based on limited data and do not offer any insight into their biological role in a chosen system. With the knowledge that each gene is capable of
expressing multiple forms of the same protein, mass spectrometric techniques are
continuously being developed and applied to provide additional information such as the
nature, site and extent of post-translational modifications (e.g., phosphorylation,
glycosylation, oxidation, truncation), and both covalent and non-covalent protein
protein interactions (e.g., protein complexes) [Miyazaki et al., 1996; Vinh et al., 1997;
Kamo et al., 1998; Terazaki et al., 1998; Zand et al., 1998; Boeshans et al., 1999;
Borchers and Tomer, 1999; Bordini and Hamdan, 1999; Jaquinod et al., 1999; Vinh et
al., 1999; Wilkins et al., 1999; Jonsson et al., 2000; Pritzker et al., 2000; Song et al.,
2000; Woods and Huestis, 2001]. To define biological functions of an individual
protein, established biochemical techniques such as enzyme activity assays and
bioassays are still required.
24 1.6. The emergence of Proteomics
The completion of the draft form of the Human Genome Project has encouraged interest in the expressed gene products as scientists scramble to determine the biological
function of each gene as well as its potential importance in health and disease.
Proteomics is a global term used to describe the process of identifying the total protein content of an organism or system (e.g., cell culture system, biological tissue or fluid), as well as determining the function or interaction of these proteins [Wasinger et al., 1995].
Traditionally, the biological activity of proteins in a chosen disease is deciphered one by one, but the emergence of proteomics has shifted the focus toward the examination of overall protein expression in a given system, i.e., the concurrent analysis of multiple proteins in the same sample. Differential or comparative proteomics has also developed
so that differences in protein expression between two (or more) different states of a biological system can be monitored and identified.
Proteomics has expanded beyond the health sciences to include areas such as plant
biology, virology, microbiology and parasitology [Thiellement et al., 1999; Barrett et
al., 2000; Cash, 2000; Gutierrez, 2000; Jan van Wijk, 2000; Panter et al., 2000; Peltier
et al., 2000; Gallardo et al., 2001; Peck et al., 2001]. This progression in proteomic
studies has been fueled by rapid expansions in the genomic databases of various
organisms, the ready availability of these data, and on-going developments in
bioinformatics. Completion of the genomic sequences of various organisms such as C.
elegans, S. cerevisiae, D. melanongastor and the availability of the draft sequence of the
human genome [Goffeau et al., 1996; Consortium, 1998; Adams et al., 2000; Venter et
al., 2001], has enabled cross-species homology searches that have aided in the
identification of unknown proteins in organisms with incomplete genomes, as well as
25 tentative assignment of protein structure and function [Cordwell et al., 1997]. Progress in bioinformatics has led to the implementation of computer search algorithms that
enable mass spectrometric data to be searched directly against both the protein and
genomic databases [Pappin et al., 1993; Yates et al., 1993; Eng et al., 1994; Mann and
Wilm, 1994; Yates et al., 1995a; Yates et al., 1995b; Taylor and Johnson, 1997; Clauser
et al., 1999; Perkins et al., 1999; Zhang and Chait, 2000]. It is therefore now feasible to rapidly identify almost any protein in a sample, and to gain some insight into biological
function. For example, the molecular events within a cell (e.g., signal transduction pathways, cell signaling) can be elucidated, potential biomarkers of disease can be
discovered, and protein-protein interactions (e.g., protein complexes) can be studied
[Rasmussen et al., 1997; Celis et al., 1999; Godovac-Zimmermann et al., 1999;
Ostergaard et al., 1999; Page et al., 1999; Soskic et al., 1999; Cans et al., 2000; Celis et
al., 2000; Fung et al., 2000; Lewis et al., 2000; Li et al., 2000b; Verma et al., 2000;
Guillonneau et al., 2001; Rohlff, 2001].
Proteomics is primarily descriptive in nature at this time (i.e., it is directed toward the
identification of proteins), and challenges still remain to develop strategies capable of
identifying and quantifying proteins at low copy numbers. An even greater challenge is
precisely determining differences in protein expression between two different states of
the same biological system. Such strategies are becoming increasingly important as the
applications of proteomics in the biomedical sciences escalate.
To measure the relative quantities of proteins, techniques have emerged that involve
protein labeling with differential mass tags and subsequent detection of the derivatised
peptides by mass spectrometry. For example, changes in protein expression that occurs
26 between two different states of the same biological system can be monitored using isotope coded affinity tags (ICAT} [Gygi et al., 1999]. Proteins in each sample are quantified following proteolytic digestion and derivatisation with differential mass tags.
Peptides containing the mass tag are then isolated and analysed by ESI-LC/MS/MS. A
similar technique has been described where C-terminal residues and acidic side chains of amino acid residues such as aspartic acid and glutamic acid are converted to methyl
esters prior to analysis [Goodlett et al., 2001]. Other approaches involve quantification of gel isolated proteins, for instance, by N- or C- terminal labeling oftryptic peptides
[Munchbach et al., 2000; Wang et al., 2001; Yao et al., 2001; Wang et al., 2002]. While these techniques are able to determine modest changes in the relative expression of
individual proteins, there is currently no practical method to accurately determine the
absolute quantities of the hundreds of proteins in a sample.
1.7. Aims
This thesis focuses on the development of mass spectrometric techniques to identify and
quantify peptides and proteins in complex biological systems and also evaluates the
utility of current proteomic approaches such as 2DE and direct analysis by ESI
LC/MS/MS. Although these existing strategies aim to detect and identify proteins in
biological tissue or fluid, there are still difficulties associated with the identification of
low abundant proteins and the quantification of biologically relevant proteins. The
utility ofMALDI-TOFMS and ESI-MS for the detection and analysis of peptides in
biological fluids was explored, and mass spectrometric methods for the absolute and
relative quantification of proteins and other biomolecules were developed.
27 Because it is recognised that 2DE and peptide mass fingerprinting allow the visualisation and identification of multiple proteins in a given biological system, it is the preferred approach for protein analysis. This technique, however, is not applicable to the detection and identification of several protein classes, such as membrane proteins, basic proteins, as well as high mass proteins. Therefore, in order to provide a complete description of the protein complement of a biological system, 2DE must be integrated with other protein identification strategies. Consequently, during this work several
strategies were applied to the separation of proteins in biological fluids such as human tear and seminal plasma, and a combination of mass spectrometric approaches was
employed to examine the peptide and protein constituents.
To overcome the difficulties associated with 2DE, other techniques have been proposed
such as the direct analysis of proteins by ESI-LC/MS/MS following proteolytic
digestion [Yates et al., 1997; Link et al., 1999]. Even though this technique can be used
to identify multiple proteins in a single analysis, it does not provide quantitative
information and only establishes the presence of a protein or parts of a protein in a
sample. Additionally, information on possible protein modification is not easily
determined. Therefore, in this work this approach was combined with gel
electrophoresis (1D and 2D) and MALDI-TOFMS to characterise peptides and proteins
in biological fluids.
The ability to quantify changes in protein expression, whether in absolute or relative
terms, is an important aspect of proteomics and there are some emerging techniques that
attempt to address this issue. For example, metabolic labeling of proteins for in vitro
studies [Oda et al., 1999; Conrads et al., 2001; Smith et al., 2001] and the adoption of
28 differential mass tags such as ICAT [Gygi et al., 1999], have shown some promise for
accurately estimating the relative changes in protein expression in a biological system.
While these techniques take advantage of the sensitivity and specificity offered by mass
spectrometry, they are limited in their applicability to particular sample types, or are targeted toward selected proteins. Therefore, protein quantification methods that can be universally applied, either to quantify specific proteins or to quantify proteins on a
global scale, and that enable accurate and precise measurements are still needed. An
approach for the global quantification of proteins involving esterification of proteolytic peptides with isotopomers ofbutanol and analysis by ESI-LC/MS was developed. This technique was employed to measure the relative abundances of proteins in open and
closed eye tear fluid.
At this time, there are no established mass spectrometric methods for the absolute
quantification of proteins in biological samples. Currently, protein quantification
methods generally utilise specific antibody-based methods to determine in vivo levels.
As a consequence, only a limited number of targeted proteins can be quantified and
their identity must be known and an appropriate antibody available. Although
immunochemical techniques offer a sensitive approach to protein quantification, they
are not able to distinguish proteins that bind non-specifically and between multiple
forms of a protein that may arise in vivo. Mass spectrometry, however, offers the
sensitivity and specificity required for the absolute quantification of many different
biomolecules, including peptides and proteins. MALDI-TOFMS is able to detect
biomolecules over an extended mass range, requires minimal sample preparation prior
to analysis, and is able to analyse many classes of biomolecules. Therefore, the
application of MALDI-TOFMS to the absolute quantification of a wide range of
29 analytes in biological matrices was explored: homovanillic acid in human urine; epinephrine and norepinephrine in adrenal gland extract; insulin in human pancreatic tissue; LW-hemorphin- 7 in adrenal gland extract and growth hormone in rat pituitary gland. The outcomes and implications of these studies are presented and discussed in detail.
30 CHAPTER2
METHODS
31 2.1. Instrumentation
All MALDI analyses were performed on a Voyager DE-STR or DE-PRO time of flight mass spectrometer (Perseptive Biosystems, Framingham, MA). All spectra were acquired in positive ion mode using standard instrument parameters unless otherwise indicated. Each spectrum was composed of an average of 100 individual laser shots. For peptide analyses, spectra were collected in reflectron mode using an acceleration voltage of20 kV. When the DE-STR was employed, the extraction grid voltage was set to 63 % and a delay time of 225 nsec was used. Analysis on the DE-PRO was performed with the extraction grid set at 76 % and the delay time set to 100 nsec.
Post-source decay (PSD) analyses were performed at an acceleration voltage of20 kV
and a grid voltage of 70% was applied. A delay time of 100 nsec was employed.
Fragment ion spectra were collected at mirror ratio decrements of 0.85 and were
stitched together, using the software provided, to form the composite PSD spectrum.
Proteins were analysed in linear mode with the acceleration voltage set to 25 kV and the
grid voltage set to 92 %. A delay time of750 nsec was used. A standard 100 position
MALDI sample plate was used for all analyses.
All standards used for mass calibration were obtained from Perseptive Biosystems
(Framingham, MA) with the exception of substance P and bovine insulin oxidised B
chain (Sigma Chemical Co., St Louis, MO).
32 All electrospray mass spectrometry was performed on a quadrupole ion trap mass spectrometer (Finnigan LCQ DECA, San Jose, CA) operated in a data dependant mode with dynamic exclusion enabled. Ion trap parameters were optimised by tuning to the doubly charged ion of angiotensin II (m/z 523.7; 1 pmol/µL; Sigma Chemical Co., St
Louis, MO). The heated capillary was maintained at a temperature of 200°C. Tandem mass spectra were obtained using a collision energy of28 %. For flow rates greater than
10 µL/min, a voltage of 3.5 kV was applied to the electrospray needle. For analyses at
0.5 µL/min, the electrospray needle was maintained at 1. 75 - 2.0 kV.
2.2. MALDI matrices
All MALDI matrices were used as supplied and were obtained from Sigma Chemical
Co (St Louis, MO), with the exception of caffeic acid (ICN Biomedicals Inc., Aurora,
OH). MALDI matrices included: a.-cyano-4-hydroxycinnamic acid (5 mg/mL in 80 %
CH3CN: 0.1 % CF3COOH), caffeic acid, ferulic acid and sinapinic acid prepared at 10
mg/mL (80 % CH3CN: 0.1 % CF3COOH). 2,5-Dihydroxybenzoic acid was also
employed and was prepared at 10 mg/mL in 100 % CH3CN.
2.3. Proteolytic enzymes
Modified porcine trypsin was obtained from Promega (Madison, WI) and
endoproteinase Asp-N was obtained from Calbiochem (La Jolla, CA). Both proteolytic
enzymes were resuspended in NH4HCO3 (0.01 µg/µL, 25 mM, pH 8), and used as
supplied.
33 2.4. Protein identification criteria
2.4.1. MALDI-TOF mass spectrometry
Peptide mass fingerprints were searched against the non-redundant protein databases using MS-FIT (Protein Prospector, http://ucsf.prospector.edu/). Positive identifications were assigned when the significance score between the first and second match was greater than one order of magnitude. Fragment ion spectra generated by MALDI-PSD were searched against the non-redundant protein databases using MS-TAG (Protein
Prospector). (See below for database search criteria.)
2.4.2. Electrospray mass spectrometry
Fragment ion spectra generated by ESI-LC/MS/MS were searched against the human
subset of the non-redundant protein databases using SEQUEST (ThermoFinnigan, San
Jose, CA). Peptide matches were considered to be significant when XCorr scores
(matching efficiency between the experimentally generated spectrum and the theoretical
spectrum) exceeded 1.5, when the DCn scores (similarity between the best match and
subsequent matches) exceeded 0.1, and when the Sp value was greater than 100.
Positive protein identification also required that multiple peptides (> 2) were detected
for each protein.
34 2.5. Database search criteria
Protein databases were searched using the following criteria unless otherwise noted:
MS-FIT MS-TAG SEQUEST Enzyme Trypsin No enzyme Trypsin Max. number missed 1 NIA 1 cleavage sites Homo Homo Species Homo sapiens sapiens sapiens Protein molecular Unrestricted Unrestricted Unrestricted weight range Protein pi range Unrestricted NIA Unrestricted Cysteine modification carbamidomethyalation None None (static modification) Possible ( differential) None None None peptide modifications Peptide mass type Monoisotopic Monoisotopic Monoisotopic Fragment ion mass type NIA Monoisotopic Monoisotopic Peptide mass tolerance ± lO0ppm ±0.25 Da ± 1 Da Fragment ion tolerance NIA ±0.5 Da No error Min. number peptides 4 NIA 2 required for a match Min. number fragment NIA NIA 20 ion count Max.number unmatched fragment NIA 30% NIA ions b- andy- Fragment ion type NIA All series
35 2.6. Identification of protein constituents in human tear
2.6.1. Sample collection
Open eye reflex tear and closed eye tear were collected from healthy individuals using glass microcapillary tubes. Samples were then stored at -80°C until required.
2.6.2. Analysis of whole tear sample
2.6.2.1. MALDI analysis
Aliquots (0.1 - 0.2 µL) of untreated (unfractionated) tear samples were analysed by
MALDI-TOFMS using either a-cyano-4-hydroxycinnamic acid or sinapinic acid as matrix. Samples were analysed in linear and reflector positive ion modes. Spectra were
externally mass calibrated to substance P ([M+Ht 1,347.74 Da), bovine insulin
([M+Ht 5,734.74 Da) and horse apomyoglobin ([M+Ht 16,952.56 Da).
Post-source decay (PSD) was performed on the most abundant components with a mass
ofless than 2000 Da in the MALDI spectrum. Potential precursor peptide masses were
calibrated in reflector mode using the protonated monoisotopic mass of substance P
([M+Ht 1,347.74 Da) and bovine insulin oxidised B chain ([M+Ht 3,494.65 Da). The
timed ion selector was set to allow detection of the fragment ions derived from the
chosen precursor peptides. Multiple PSD spectra were obtained for each chosen peptide.
The fragment ions derived from each peptide was then searched against the non
redundant protein databases using MS-TAG (Protein Prospector) to determine the
peptide sequence and the parent protein.
36 2.6.2.2. Electrospray mass spectrometry
An aliquot (5 µL) of open eye tear was treated with trypsin (37°C, overnight), and an aliquot containing the resulting tryptic peptides (1 µL) was analysed by ESI
LC/MS/MS on an ion trap mass spectrometer. Chromatography was performed on a
Cl8 reverse phase column (150 x 1 mm ID) (Vydac, Hesperia, CA) using a binary solvent system. Peptides were eluted over an increasing linear gradient of acidified
CH3CN (0.01 % CF3COOH) (Solvent B) over two hours. Solvent A consisted of aqueous 0.01 % CF3COOH. A flow rate of50 µL/min was employed. The charge state of each eluting peptide was determined, and then each ion was fragmented to generate
MS/MS spectra. To identify the proteins in tear fluid, each MS/MS spectrum was
searched against the human subset of the non-redundant protein database (SEQUEST,
ThermoFinnigan, San Jose, CA).
2.6.3. Isolation and detection of lacrimal proline-rich protein
(This section of the experimental work was undertaken in collaboration with Dr. Robert Sack.)
Open eye tear was fractionated by size exclusion chromatography and selected fractions
were analysed by MALDI-TOFMS to determine the mass of each protein. Sinapinic
acid was used as the matrix. Spectra were externally mass calibrated to bovine insulin
([M+Ht 5,734.74 Da), thioredoxin ([M+Ht 11,674.48 Da) and horse apomyoglobin
([M+Ht 16,952.56 Da). Fractions were then incubated concurrently with trypsin (37°C,
2 hrs) and Asp-N (37°C, 2 hrs) and the resulting peptides analysed by MALDI-TOFMS
with a.-cyano-4-hydroxycinnamic acid used as the matrix. Spectra were internally mass
calibrated to known tryptic fragments of either lysozyme or tear lipocalin.
37 The digested HPLC fractions were also analysed by electrospray LC/MS/MS to determine the identity of each peptide detected by MALDI-TOFMS. Peptides were separated by on-line reverse chromatography using capillary columns (100 mm x 150
µm ID) packed with R2 POROS (Perseptive Biosystems, Framingham, MA). Peptides were eluted over 60 minutes using a linear gradient consisting of acidified CH3CN (0.05
% CF3COOH) (0 - 100 %). The charge state of each eluting peptide was determined before being fragmented to produce MS/MS spectra. Each MS/MS spectrum was then
searched against the human subset of the non-redundant protein database using
SEQUEST. SEQUEST search parameters were adjusted to enable both trypsin and Asp
N enzyme cleavage.
2.6.4. Quantification of tear fluid proteins
2.6.4.1. Apomyoglobin
Horse skeletal apomyoglobin (20 µg; 98 % purity; ICN Biomedicals Inc., Aurora, OH)
was resuspended in NRiHCO3 (20 µL, 25 mM, pH 8) and digested using trypsin (1 µg,
37°C, overnight). Tryptic peptides were divided into equal aliquots and then dried under
vacuum. Peptides were then esterified with either acidified butanol or d10-butanol (lM,
20 µL, 70°C, 3 hrs) under anhydrous conditions. Anhydrous butanol (Sigma Chemical
Co, St Louis, MO) or d10-butanol (Cambridge Isotope Laboratory, Andover, MA) was
acidified by the addition of anhydrous acetyl chloride (140 µL; Alltech Associates Inc.,
Deerfield, IL) to the respective alcohol (lM, 1 mL).
Following esterification, peptides were dried under vacuum and reconstituted into
aqueous 0.1 % CF3COOH (20 µL) prior to analysis by MALDI-TOFMS and ESI-MS.
38 To ensure complete esterification of the tryptic peptides, an aliquot (0.5 µL) of each
sample was first analysed by MALDI-TOFMS with a.-cyano-4-hydroxycinnamic acid
as the matrix. An aliquot (5 µL) of each was also analysed by ESI-LC/MS/MS. Each
MS/MS spectrum was searched against the non-redundant protein databases to determine the identity of each tryptic peptide (as the butyl ester). Peptides were separated by reverse phase chromatography using a capillary column (100 mm x 150
µm ID) packed with R2 POROS under the conditions previously described.
Following this, the two samples were combined and analysed by ESI-LC/MS under the
same chromatographic conditions. The relative amount of each tryptic peptide was
determined by comparing the peak area of each pair of co-eluting peptides from the respective extracted ion chromatogram.
2.6.4.2. Tear fluid proteins
Proteins in matched open and closed eye tear (n = 2) were precipitated (acetone; 10
volumes) and the protein pellet collected after centrifugation (10,000 g, 10 min). The
pellet was reconstituted in NRJHC03 (20 µL, 25 mM, pH 8) and an aliquot
( corresponding to 10 µg protein) of each sample was incubated with trypsin (0.1 µg,
37°C, overnight). Tryptic peptides were dried under reduced pressure prior to
esterification with either acidified butanol (open eye tear) or acidified d10-butanol
( closed eye tear). Each sample was then dried under vacuum and reconstituted in
aqueous 0.1 % CF3COOH (20 µL). An aliquot of the esterified peptides was then
analysed by ESI-LC/MS/MS on a capillary column (100 mm x 150 µm ID) packed with
R2 POROS under the conditions previously described. Esterified peptides from each
sample were identified by SEQUEST. SEQUEST parameters were adjusted to allow for
39 butanol esterification of the C-tenninal residues, aspartic acid and glutamic acid residues.
Following identification of the esterified tryptic peptides, equal amounts of the two samples were combined and analysed by ESI-LC/MS to determine the relative abundances of the chosen proteins in the sample. Co-eluting esterified peptide pairs were identified and their relative abundances were determined by calculating the peak area ratio for each peptide and its isotopomer in the extracted total ion chromatogram.
Multiple peptides were used to estimate the amount of each protein in the sample. To determine the precision with which these measurements could be made, the ratios obtained for multiple peptides derived from the same parent protein were averaged, and the standard deviation detennined.
40 2. 7. Analysis of the peptide and protein components in human
seminal plasma
2.7.1. Sample collection
Azospennic semen samples were collected from vasectomised human males (n = 7) and
stored at -80°C. Proteins were precipitated with CH3OH : CHCh : H2O ( 4: I :3) and centrifuged before analysis by two dimensional gel electrophoresis (2OE).
Seminal fluid was also collected from normal young males (n = 5) and pooled prior to incubation (37°C, 30 min). Proteins in this sample were separated by 10
electrophoresis, and analysed by ESI-LC/MS/MS and MALDI-TOFMS.
2. 7 .2. Two dimensional gel electrophoresis
(Experimental work detailed in this section was performed in collaboration with Dr. David
Friedman.)
The proteins (100 - 200 µg total) in pooled seminal fluid ( containing protease
inhibitors) were precipitated and the pellet isolated following centrifugation (10,000 g,
10 min). The protein pellet was then resuspended in 2OE rehydration buffer (200 µL,
8M urea, 2 % CHAPS, 18 mM OTT} and passively rehydrated into 18 cm immobilised
pH gradient strips (IPG 4-7 or 6-11; Amersham Pharmacia Biotech, Piscataway, NJ) for
at least 16 hours. First dimension isoelectric focusing was performed for 24 hours
(Multiphor II system; Amersham Pharmacia, Piscataway, IL). Cysteine side-chains were
then reduced by incubating the focused strips in equilibration solution (6 M Urea, 50
mM Tris, pH 8.8, 30% glycerol, 2% SOS, bromophenol blue) containing 1%
dithiothreitol {OTT; 20 min; Sigma Chemical Co., St Louis, MO) followed by
41 alkylation by incubation in equilibration solution containing 2.5% iodoacetamide (20 min; Sigma Chemical Co., St Louis, MO). Second dimension separation was performed
overnight (Protean II XL electrophoresis system, Bio-Rad Laboratories, Hercules, CA) using 8-16 % polyacylamide gradient gels. Proteins were stained with silver as
described by Shevchenko et al. (1996b).
Prior to in-gel digestion with trypsin, protein spots were excised and the silver removed
as described by Gharahdaghi et al. (1999). The gel pieces were then dehydrated with
50% CH3CN in NH.iHCO3 (50 mM) and 100 % CH3CN, followed by vacuum
centrifugation for 5 minutes. Gel pieces were then re-hydrated with trypsin (0.1 µg) in
NH4HCO3 (25 mM) and incubated overnight (30°C). Tryptic peptides were extracted
with CH3CN: 0.1% aqueous CF3COOH (60:40, 15 µL), and dried under vacuum. The
peptides were reconstituted in aqueous 0.1 % CF3COOH (8 µL) and de-salted with
ZipTip C18 pipette tips (Millipore Corporation, Bedford, MA). Peptide mass
fingerprints were then generated by MALDI-TOFMS.
2. 7 .3. One dimensional gel electrophoresis
Seminal fluid (corresponding to ea. 200 µg protein) was diluted into loading buffer (15
µL; 50 mM Tris pH 6.8, 5 % ~-mercaptoethanol, 10 % glycerol, 10 % SDS, 1%
bromophenol blue) before separation by 1D gel electrophoresis. Molecular weight
markers (Kaleidoscope prestained standards; Bio-Rad Laboratories, Hercules, CA) were
loaded into the adjacent lane. Proteins were separated for 50 min at a constant voltage
(180 V) and then visualised by incubation in Coomassie Brilliant Blue (CH3OH :
CH3COOH, 15 min; Fisher Scientific, Houston, TX). Discrete protein bands, as well as
42 regions ofless intense stain (i.e., 26 different bands in total), were excised and destained
(50 % CH3CN in NH.iHC03, 25 mM, pH 8) prior to in-gel digestion (trypsin, 0.3 µg, overnight, 37°C). An aliquot of each digest (5 µL) was then analysed by ESI
LC/MS/MS.
2. 7 .4. Mass spectrometry of unfractionated seminal fluid
Diluted seminal fluid collected from normal young males (1: 10, 25 mM NH.iHC03, pH
8) was analysed by MALDI-TOFMS with either a-cyano-4-hydroxycinnamic acid or
sinapinic acid (10 mg/mL, CH3CN: 0.1 % aqueous CF3COOH, 80:20) as the matrix.
Spectra were externally mass calibrated to the protonated monoisotopic masses of
angiotensin I ([M+Ht 1,296.68 Da), ACTH clip 18-39 ([M+Ht 2,465.19 Da) and
bovine insulin ([M+Ht 5,734.74 Da). To identify the peptides present in seminal fluid
an aliquot (5 µL) was also analysed by ESI-LC/MS/MS under the conditions described
below.
2. 7 .5. Protein identification
2.7.5.1. MALDI-TOF mass spectrometry
Proteins in seminal fluid (obtained from azospermic men) separated by 2DE were
analysed by MALDI-TOFMS following in-gel tryptic digestion. Peptide mass maps
were collected in reflectron mode with a-cyano-4-hydroxycinnamic acid as matrix and
spectra were internally calibrated to the protonated monoisotopic masses of several
trypsin autolysis peptides ([M+Ht 842.51, 1,045.55 and 2,211.42 Da). Proteins were
43 identified by searching protonated peptide masses (i.e., the [M+Ht values) against the non-redundant protein databases using Protein Prospector (MS-FIT).
2. 7.5.2. ESI mass spectrometry
Peptides derived from tryptic digestion of bands visualised by one dimensional gel electrophoresis, and whole unfractionated seminal fluid, were analysed in a data dependant mode on a quadrupole ion trap mass spectrometer fitted with a nanospray source. Peptides were separated by reverse phase chromatography using a capillary column (100 mm x 150 µm ID) packed with POROS R2. Peptides were eluted with an increasing linear gradient of acidified CH3CN (0.05 % CF3COOH) over one hour at a flow rate of - 0.5 µL/min. The second solvent consisted of aqueous 0.05 % CF3COOH.
The charge state of each eluting peptide was determined prior to fragmentation to produce a product ion spectrum. Proteins were identified by searching each fragment
ion spectrum against the human subset of the non-redundant protein database using the
SEQUEST software. For the identification of peptides in unfractionated seminal fluid,
SEQUEST parameters were adjusted to allow searches with 'No enzyme' specified.
44 2.8. Quantification of biomolecules by MALDI-TOFMS
2.8.1. Analysis of growth hormone in rat pituitary tissue
Male Sprague-Dawley rats (n = 2, > 300 g body weight) were decapitated and their pituitary glands (ea. 15 -20 mg) were surgically removed and stored at -20°C until required. Whole glands were homogenised (probe sonication) and the protein
components extracted into aqueous 0.1 % CF3COOH (1.5 mL). The internal standard,
~-lactoglobulin (15 nmol; Sigma Chemical Co., St. Louis, MO), was then added.
Recombinant methionyl rat growth hormone(> 97 % monomer, 21,943 Da, Gropep Pty.
Ltd., Adelaide, Australia) was used in place of rat growth hormone to generate the
standard curve. Standard solutions containing the recombinant methionyl rat growth
hormone (0, 10, 20, 40, 100, 150 and 200 pmol) and ~-lactoglobulin (100 pmol) were
prepared in aqueous 0.1 % CF3COOH (20 µL). Standard solutions and samples were
diluted 1:5 in caffeic acid solution before analysis, and 1 µL of the final solution was
applied to the MALDI target. Spectra were acquired in linear mode across the mass
range 5,000 - 40,000 Da.
2.8.2. Quantification of insulin in human pancreatic tissue
(This section of the experimental work was undertaken in collaboration with Martin Bucknall.)
Control human pancreatic tissue was obtained from cadavers (n = 2) and frozen at
-20°C until analysis. Sections of each tissue (3 x ea. 50 mg) were homogenised and the
proteins extracted into aqueous 0.1 % CF3COOH (1 mL). Porcine insulin (2.5 nmol;
Sigma Chemical Co., St Louis, MO) was added as the internal standard. The extracts
were passed through C18 solid phase extraction cartridges (Sep-Pak; Waters
45 Corporation, Milford, MA) pre-conditioned with CH3CN: H2O: CF3COOH (80:20:0.1;
5 mL) and equilibrated with aqueous 0.1 % CF3COOH (10 mL). Insulin was eluted in
· CH3CN: H2O: CF3COOH (80:20:0.1; 1 mL). Samples were evaporated under reduced pressure to yield aliquots of ea. 50 µL. These were diluted in sinapinic acid matrix
solution (1 :20).
Standard solutions containing human insulin (0, 40,120,400, 1,200, 2,800, 4,000 pmol)
and porcine insulin (200 pmol) were prepared in aqueous 0.1 % CF3COOH (20 µL)
containing bovine serum albumin (5 nmol/mL; Sigma Chemical Co., St Louis, MO).
Aliquots (1 µL) of each sample and standard solution were applied to the MALDI target
for analysis. Spectra were acquired in both linear and reflector modes.
2.8.3. Analysis of hemorphins in human adrenal and pheochromocytoma tissues
(This section of the experimental work was undertaken in collaboration with Martin Bucknall.)
Control adrenal glands (n = 10) and surgically removed, histologically verified
pheochromocytoma (n = 3) were collected and the peptides extracted as described in
Cerpa-Poljak et al. (1997). The extracts were stored at-20°C until required. Prior to
analysis, the extracts were mixed with the internal standard rat LVV-hemorphin- 7 (300
pmol/mg tissue; Chiron Technologies Pty., Ltd., Clayton, Australia), and diluted 1 :30
with a.-cyano-4-hydroxycinnamic acid solution. All MALDI-TOFMS was performed in
linear mode.
A single tissue extract, previously found to have the lowest endogenous
LVV-hemorphin- 7 concentration, was employed as the matrix for the preparation of a
46 standard addition calibration curve. Aliquots of this sample were spiked with human
LVV-hemorphin- 7 (0, 10, 30, 60, 100, 300 and 600 pmol/mg tissue; Chiron
Technologies Pty., Ltd., Clayton, Australia) and a fixed amount of the internal standard
(300 pmol/mg tissue). Control samples (n = 3) were also included in the analysis. These were prepared from each of the pheochromocytoma extracts by adding internal standard and spiking with human LVV-hemorphin- 7 (100 pmol/mg tissue). The hemorphin content of each extract had previously been determined by electrospray mass spectrometry [Cerpa-Poljak et al., 1997].
2.8.4. Analysis of catecholamines in human adrenal and pheochromocytoma tissue
(This section of the experimental work was undertaken in collaboration with Martin Bucknall.)
Frozen tissue samples (-70°C; ea. 100 mg each) from control adrenal glands (n = 3) and histologically verified pheochromocytoma (n = 3) were extracted into aqueous 0.1 %
CF3COOH (1 mL) as previously described [Cerpa-Poljak et al., 1997].
Aliquots (10 µL) from each tissue extract were mixed with the internal standards [2H3]
epinephrine (2 nmol) and [2H3]-norepinephrine (3 nmol) (Cambridge Isotope
Laboratories, Andover, MA) and diluted 1 :25 in ferulic acid matrix solution. Samples
were mixed, cooled (4°C, 10 minutes) and centrifuged (14,000 g, 10 min) to precipitate
protein. Aliquots (0.25 µL) of the supernatant were applied directly on the MALDI
target for analysis.
An extract of surgically resected adrenal cortex was employed as the matrix for the
preparation of a standard addition calibration curve. Aliquots of this sample, each
47 corresponding to 5 mg of tissue, were spiked with 0, 0.5, 1.5, 3, 5, 15, 30, 45, 60, 90 nmol of both epinephrine (Sigma Chemical Co., St Louis, MO) and norepinephrine
(Sigma Chemical Co., St Louis, MO), together with fixed amounts of the internal
standards ([2H3]-epinephrine (20 nmol) and [2H3]-norepinephrine (30 nmol)). These
spiked extracts were diluted 1 :25 in ferulic acid solution prior to analysis. All mass
spectra were acquired in reflector mode at a reduced acceleration voltage (6 kV).
2.8.S. Analysis of homovanillic acid in human urine samples
Urine samples were collected from 19 healthy volunteers and adjusted to pH 2.5 (HCl,
lM). The internal standard, [2Hs]-homovanillic acid ([2H5]-HVA; 100 nmol; Cambridge
Isotope Laboratory, Andover, MA), was added to aliquots of each sample (50 µL) and
the mixture extracted into ethyl acetate (4 volumes, 3 times). Extracts were combined,
dried under reduced pressure, and the residue reconstituted into dilute HCI (0.1 M, 50
µL ). Samples were diluted 1: 10 in 2,5-dihydroxybenzoic acid matrix solution and
applied to the MALDI target. Each urine sample was also independently analysed for
homovanillic acid (HVA} content at a commercial clinical chemistry laboratory.
Standard solutions containing HVA (0, 25, 50, 100, 500 and 1,000 pmol; Sigma
Chemical Co., St. Louis, MO) and [2H5]-HVA (100 pmol) were prepared in water and
diluted 1 :5 in the matrix solution (2,5-dihydroxybenzoic acid) prior to analysis (final
volume 20 µL). An aliquot (1 µL) of each sample and standard solution was applied to
the MALDI target. Spectra were acquired in reflectron mode at a reduced acceleration
voltage (6 kV) and over the mass range 180-190 Da.
48 2.8.6. Data acquisition and processing
Spectra were acquired in autosampler mode with the laser operated at a fixed fluence.
Laser firing patterns started at the center of each sample spot and spiraled progressively outwards to the spot perimeter. The laser was programmed to fire once at each location in the firing pattern. For each sample spot, spectra obtained from 256 laser shots, and meeting the specified acceptance criteria, were averaged to form a single spectrum.
Acceptance criteria consisted of a signal-to-noise ratio (S / N) greater than 3 and absolute ion intensities between 5,000 and 62,000 counts over a restricted mass range inclusive of both the analyte and internal standard. Spectra from ten sample spots were
collected for each standard solution and biological sample.
From each individual spectrum the heights of the relevant peaks (i.e., analyte and
internal standard) were determined and the analyte to internal standard peak height ratio
was calculated. Each standard curve was constructed by plotting the calculated peak
height (or peak area) ratio (y-axis) against the molar ratio of analyte to internal standard
(x-axis). The mean value and standard deviation for each standard were determined and
plotted to generate the standard curve.
For homovanillic acid, peak area ratios of analyte to internal standard were also
determined to construct a standard curve. The equation for each standard curve was
calculated using an unweighted linear regression.
49 CHAPTER3
MASS SPECTROMETRY AND
PROTEIN IDENTIFICATION:
APPLICATION TO HUMAN TEAR
FLUID
50 3.1. Introduction
The human tear film is believed to be composed of three layers: a superficial layer composed of lipids secreted by the Meibomian gland, a middle aqueous component consisting primarily of peptides and proteins, and an inner mucosa! layer [Coyle et al.,
1989; Wollensak: et al., 1990]. Together these components are believed to play an essential role in the protection of the external ocular surface from potential pathogens, as well as to provide nourishment to the corneal surface [Coyle et al., 1989; Wollensak: et al., 1990]. The blinking action serves to spread the tear film over the entire surface of the eye, as well as to remove contaminants and waste products by drainage into the nasolacrimal duct.
There are many physiological factors that can alter the balance of the protein components in the tear film, or affect the rate of tear production from the lacrimal gland or its accessory glands. These include specific ocular pathologies such as glaucoma, dry eye syndrome, Sjorgren's syndrome and conjunctivitis, as well as systemic diseases such as diabetes and rheumatoid arthritis [Jensen et al., 1986; Coyle and Sibony, 1987;
Coyle et al., 1987; Khalil et al., 1988; Mavra et al., 1990; Domingo et al., 1998;
Goebbels, 2000; Thakur and Willcox, 2000]. In addition to these, it is also believed that procedures routinely undertaken to improve visual acuity, such as laser eye surgery or the use of contact lenses, can alter the constituents of the tear film [Tervo et al., 1995;
Tervo et al., 1997; Tuominen et al., 1999; Thakur and Willcox, 2000]. Currently, little information is available concerning the nature and extent of changes in protein expression in various disease states.
51 Although it has been proposed that changes in protein expression in tear fluid can be used for diagnostic purposes [Molloy et al., 1997], the protein composition of the normal tear film is poorly defined. Large scale studies involving the identification of tear proteins by two dimensional gel electrophoresis have been conducted employing either amino acid analysis or Edman sequencing [Mii et al., 1992; Molloy et al., 1997].
Although many proteins were detected by this approach, only a small subset of these
could be identified due to post-translational processing such as glycosylation and N terminal processing.
Other studies have focused on the identification of protein components by techniques
such as radioimmunoassay, gel electrophoresis, high performance liquid
chromatography, immunochemical techniques, and enzyme activity assays [Coyle and
Sibony, 1986; Boukes et al., 1987; Fullard, 1988; Coyle et al., 1989; Baier et al., 1990;
Wollensak: et al., 1990; Kuizenga et al., 1991b; Mii et al., 1992; Molloy et al., 1997;
Behndig et al., 1998; Jumblatt et al., 1999]. As a result of these investigations,
lactotransferrin, tear lipocalin (von Ebner's gland protein), secretory IgA and lysozyme
have been identified as the major protein components of the normal tear film [Janssen
and van Bijsterveld, 1983b; Kijlstra et al., 1983; Fullard and Kissner, 1991]. In addition
to these, various enzymes and serum proteins have also been detected and identified
[Crouch et al., 1991].
As discussed earlier in this thesis, advances in mass spectrometry have contributed to
substantial progress in peptide and protein identification in biological tissues and fluids.
Both MALDI-TOFMS and ESI-MS provide the sensitivity and specificity required to
detect and identify multiple components in trace quantities of complex biological
52 samples. Post-translational modifications can also be characterised, and many proteins
can be identified in a single analysis.
In this study, the peptide and protein constituents of the normal human tear film were
investigated by a combination ofMALDI-TOFMS and ESI-LC/MS. Because MALDI
TOFMS enables the intact mass of molecules to be accurately determined, it was
employed to survey samples and establish a profile of the peptides and proteins present
in untreated human tear. In addition, MALDI-PSD was used to identify several of the major peptide constituents of tear. Signal suppression effects are significant when
MALDI-TOFMS is employed to examine complex samples, and this limits the amount
of information available. Therefore, ESI-LC/MS/MS was also employed to identify
protein constituents following proteolytic digestion.
3.2. Methods
The methods employed for this study are detailed in Chapter 2 (pages 36- 38).
53 3.3. Results
3.3.1. The peptide components of human open eye tear
Human tear fluid (n = 7) was directly analysed by MALDI-TOFMS using, separately, both a.-cyano-4-hydroxycinnamic acid and sinapinic acid as the matrix. Over 30
components were detected by this technique (Figure 3.1). Lysozyme and tear lipocalin, two of the most abundant proteins in the tear film, were detected and tentatively identified based on their theoretical molecular weight. In addition to these, numerous other components were detected below 5,000 Da.
To establish the identity of the major low mass constituents(< 2,000 Da), sequence information for five of the more abundant peptide species was obtained by post-source
decay (PSD). The PSD spectrum for each of the five peptides is shown in Figure 3.2.
Indicated on each PSD spectrum are the b- and y- series ions. In addition to these,
internal sequence ions and immonium ions were also detected. The mass and amino acid
sequence for the fragment ions detected for each peptide are listed in Tables 3.1 - 3.5.
54 Figure 3.1. A MALDI-TOF mass spectrum of human tear.
An aliquot of human tear (0.2 µL) was analysed by MALDI-TOFMS using a-cyano-4- hydroxycinnamic acid as the MALDI matrix. Multiple components were detected in the mass range of 500 - 20,000 Da including proteins such as lysozyme ([M+Ht 14,678
Da) and tear lipocalin ([M+Ht 17,438 Da), as well as many other peptide constituents.
(As shown, the mass range 2,000- 5,000 Dais magnified by a factor 10.) The peptides
selected for post-source decay analysis are indicated.
55 56
5000
lipocalin
4400
(17438.1)
Tear
I
l
4049.2
3800
3749.3
10
X
(14687.8)
Lysozyme
3336.9
14906.4
3200 /
II
2940.1
2876.5
272315 I
I I I
2600
2423.7
12411.7
I
I
(m/z)
~7·
I
....
:
.
!2J4.5 :I
I
2000
Mass
I
1786.9
tear.
1629.9
human
of
1400 1700
8713.4
1330.7
1326.8
for
\
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Peptides
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'ii - .5 - a: Figure - Figure 3.2. Post-source decay spectra for the abundant tear peptides.
A. A post-source decay spectrum for the peptide [M+Ht 1,629.69 Da.
B. A post-source decay spectrum for the peptide [M+Ht 1,443.74 Da.
C. A post-source decay spectrum for the peptide [M+Ht 1,330.52 Da.
D. A post-source decay spectrum for the peptide [M+Ht 1,105.51 Da.
E. A post-source decay spectrum for the peptide [M+Ht 848.45 Da.
Indicated on each spectrum are the fragment ions corresponding to either b- and y
series ions as well as immonium ions specific to particular amino acids. The mass and
amino acid sequence for the fragment ions detected for each peptide are listed in Tables
3.1 - 3.5.
57 58
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decay spectrum / I ·- ::J: CD .0 uL~ > ..J I CD decay """ ,- .0 ::::,u,u,0) G) ..J CD CU 0 .. a. Post-source 0) .. I CD <( CU """ ,- ., so 3.2. 0 •J:""'""'"'·~ 100 100 post-source A C "#. i - - I 'tu -~ ~ Figure A. Table 3.1. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 1,629.69 Da. Experimental [M+Ht values are the average (± SD) of at least three separate determinations. A. Fragment ions corresponding to b- and y- series ions. THEORETICAL EXPT. THEORETICAL EXPT. BIONS YIONS [M+Ht [M+Ht [M+Ht [M+Ht B12 + H2O 1,443.7 1,444.4 ± 0.6 Y12 1,514.8 1,515.2 ± 0.6 B11+H2O 1,330.7 1,329.4 ± 0.9 Y12-NH3 1,497.8 1,498.6 ± 0.6 B11 1,312.7 1,312.2 ± 0.6 Y11 1,358.7 1,359.2 ± 0.4 B9 1,087.5 1,087.7 ± 0.3 Y9 1,190.6 1,190.6 ± 0.5 B9-NH3 1,070.5 1,071.2 ± 0.6 Y9-NH3 1,173.6 1,172.8 ± 0.5 A9-NH3 1,042.5 1,043.3 ± 0.6 Ys-NH3 1,017.5 1,018.4 ± 0.4 B6 733.4 734.1 ± 0.5 Ys 672.3 672.0 ± 0.9 B6-NH3 716.4 717.1±0.5 *Y1 205.1 205.4 A6 705.4 705.6 ± 0.2 ~-NH3 688.4 688.5 ± 0.4 Bs 596.3 597.2 ± 0.7 Bs-NH3 579.3 580.4 ± 0.9 B4 440.2 439.6 ± 0.1 B4-NH3 423.2 422.9 ± 0.8 *~ 412.2 412.4 B3-NH3 352.2 352.6 ± 0.2 B2 272.1 272.6 ± 0.4 B2-NH3 255.1 255.4 ± 0.1 • Due to the low abundance of this peptide in some samples, these fragment ions were detected in only one of the PSD spectra. 59 Table 3.1. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 1,629.69 Da. Experimental [M+Ht values are the average (± SD) of at least three separate determinations. B. Internal sequence ions. INTERNAL THEORETICAL EXPERIMENTAL SEQUENCE IONS rM+Ht [M+Ht PA 169.1 169.3 ± 0.1 PQ-28 198.1 198.5 ± 0.2 AR-NH3 211.1 211.6 ± 0.3 PQorQP 226.1 226.5 ± 0.1 HP 235.1 235.4 ± 0.4 EQorQE 258.1 258.4 ± 0.1 RPAorPAR 325.2 325.6± 0.2 RPA-NH3 308.2 308.7 ± 0.3 PAR-NH3 EQPorPQE 355.1 355.4 ± 0.2 QEQ 386.2 386.4 ± 0.3 PARH-NH3 445.2 445.3 ± 0.2 QEQPorPQEQ 483.2 483.6 ± 0.3 *HPQE 492.2 492.5 PQEQP 580.3 580.4 ± 0.9 HPQEQ 620.3 620.6 ± 0.4 RHPQE-NH3 631.3 630.8 ± 0.8 HPQEQP 717.3 717.0 ± 0.3 * Due to the low abundance of this peptide in some samples, this fragment ion was detected in only one of the PSD spectra. 60 61 61 750 750 1480 1480 .E .E I I \ \ ! ! vut vut [M+Ht [M+Ht 1443.74 1443.74 a, a, I I (U (U ...... ,... ,... LJ1 LJ1 I I + + :c :c :i :i ...... ,-- co co ,... ,... + + I I ...... ...... 610 610 1334 1334 1u 1u I I ...... ...... >> >> ...... ,... ,... v-- I I ...... ...... .0 .0 ,... ,... ~ ~ ¼~~~~ ¼~~~~ 470 470 1188 1188 0 0 ~ ~ : : I I ...... ,... ,... .d .d (m/z) (m/z) 0, 0, .0 .0 Da). Da). Mass Mass !I !I . . 0, 0, I I ! ! ! ! 0, 0, >.0 >.0 0) 0) I I I :I :I 1,443.74 1,443.74 (U (U ...... ,...,...,... ,...,...,... peptides peptides 330 330 1042 1042 tear tear a) a) I I > > ([M+Ht ([M+Ht N N I I 5 5 abundant abundant ...... .0 .0 ,... ,... peptide peptide X X the the tear tear for for a a for for 896 896 190 190 spectra spectra decay decay spectrum spectrum ~ ~ e> e> c( c( ...... I I > > ...... ,... ,... en en - :c :c decay decay Post-source Post-source ~ ~ 0 0 a. a. 1y~~~~AAh~~~~wv~~ 1y~~~~AAh~~~~wv~~ 3.2. 3.2. 750 750 0 0 post-source post-source 100 100 100 100 A A ~ ~ C C 0 0 a: a: i i ! ! 'i 'i ~ ~ 0 0 ::,!! ::,!! - - Figure Figure B. B. Table 3.2. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 1,443.74 Da. Experimental [M+Ht values are the average(± SD) of three separate determinations. A. Fragment ions corresponding to b- and y- series ions. THEORETICAL EXPT. THEORETICAL EXPT. BIONS YIONS [M+Ht [M+Ht [M+Ht [M+Ht B11 +H2O 1,330.6 1,329.8 ± 0.1 Yu 1,328.7 1,329.8 ± 0.1 * B11 -NH3 1,295.6 1,294.9 Y11 -NH3 1,311.7 1,311.6 ± 0.1 *B9 1,087.5 1,088.3 Y10 1,172.6 1,172.5±0.1 *B9-NH3 1,070.5 1,070.7 Y9-NH3 1,058.5 1,059.1 ± 0.5 A9-NH3 1,042.5 1,042.7 ± 0.2 Ys 1,004.5 1,004.8 ± 0.4 Bs 958.5 958.6± 0.4 Y1-NH3 831.4 831.2 ± 0.1 B6 733.4 733.3 ± 0.4 *Y6 711.4 712.4 ~-NH3 688.4 688.3 ± 0.4 *Y2 229.2 229.4 *Bs-NH3 579.3 579.8 *B4 440.2 440.1 *B4-NH3 423.2 423.1 *B2 272.1 272.1 B2-NH3 255.1 255.3 ± 0.1 • Due to the low abundance of this peptide in some samples, these fragment ions were detected in only one of the PSD spectra. 62 Table 3.2. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 1,443.74 Da. Experimental [M+Ht values are the average(± SO) of three separate determinations. B. Internal sequence ions. INTERNAL THEORETICAL EXPERIMENTAL SEQUENCE IONS [M+Ht [M+Ht PA 169.1 169.2 ± 0.2 PQ 226.1 226.4 ± 0.1 *PQ-28 198.1 198.3 HP 235.1 235.3 ± 0.1 PQEorEQP 355.2 355.3 ± 0.1 RPA-NH3 308.2 308.5 ± 0.2 PAR-NH3 PQEQ 483.2 483.5 ± 0.1 PARHPQ-NH3 670.3 671.7 ± 0.9 RHPQEQP 873.4 872.2 ± 0.1 • Due to the low abundance of this peptide in some samples, this fragment ion was detected in only one of the PSD spectra. 63 I 700 64 1370 I cl ..... ..... I~ ~/\ ~ I [M+Ht + 1330.78 co ..... ..... :c + 1~ i U') 11 .c ~~,,.~~ \ I U') >- 11 ..... ,... 0 ~ll~ + \ co ,... .c 570 1236 ~·~r~ \~ 0 .c I ~ I \ 0 ...... ..... ,... .c ~~ I 0 .... co ..... ..... ~~ . I\ 1 . l1 440 1102 en !1 .c c:n I Wl,M,)~~,;J ...... o, >-.0 I en (m/z) >- ...... . ~~y~~ I Mass Da) ~\ \ 1,330.52 310 968 peptides. I tear \~lm;~~~ I ([M+Ht ~ ...... i ..... w ~ ,.. >- abundant ! peptide the tear for a 180 834 for spectra en :i.. decay spectrum . \~~~~ ,,, ·- :c co ~~~~ decay .c 0 ... n. I co ...... .c Post-source 50 0 3.2. 100 1001 post-source A C C Cl) > ea ~ .! ,:::e. ~ ·;; - :;::; 'i a: Figure C. Table 3.3. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 1,330.52 Da. Experimental [M+Ht values are the average (± SD) of at least two separate determinations. A. Fragment ions corresponding to b- and y- series ions. THEORETICAL EXPT. THEORETICAL EXPT. BIONS YIONS [M+Ht [M+Ht [M+Ht [~+Ht B1o+H2O 1,233.6 1,233.7 ± 0.1 Y10 1,215.6 1,215.8 ± 0.1 B10 1,215.6 1,215.7 ± 0.1 *Y10-NH3 1,198.6 1,198.7 B10-NH3 1,198.6 1,198.7 ± 0.1 Y9 1,059.5 1,060.1 ± 0.4 A10-NH3 1,170.6 1,170.6±0.1 *Y9-NH3 1,042.5 1,042.6 B9 1,087.5 1,088.0 ± 0.6 *Y1 891.4 891.4 *B9-NH3 1,070.5 1,070.8 Ys-NH3 581.2 580.6 ± 0.4 A9 1,059.5 1,060.1 ± 0.4 Y4-NH3 484.2 484.1 ± 0.1 *A9-NH3 1,042.5 1042.6 Y2-NH3 227.1 226.9 ± 0.5 *B6 733.4 733.9 *B6-NH3 716.4 717.2 *A6-NH3 688.4 688.3 *~-NH3 598.3 597.5 Bs-NH3 581.3 580.6 ± 0.4 *B2 272.1 272.7 B2-NH3 255.1 255.5 ± 0.1 A2-NH3 227.1 226.9± 0.5 * Due to the low abundance of this peptide in some samples, these fragment ions were detected in only one of the PSD spectra. 65 Table 3.3. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 1,330.52 Da. Experimental [M+Ht values are the average (± SD) of at least two separate determinations. B. Internal sequence ions. INTERNAL THEORETICAL EXPERIMENTAL SEQUENCE IONS [M+Ht [M+Ht PA 169.1 169.3 ± 0.2 PQ-28 198.1 198.4 ± 0.3 *PQ-NH3 209.1 209.2 HP 235.1 235.4 ± 0.3 RPA-NH3 308.2 308.6 ± 0.2 PAR-NH3 PQE 355.2 355.7 ± 0.2 *HPQE 492.2 492.8 *ARHPQ-NH3 562.3 563.2 • Due to the low abundance of this peptide in some samples, these fragment ions were detected in only one of the PSD spectra. 66 570 1150 U'I 67 co [MtHt I 1105.51 + co 'I"" :c: ...... - :5 + 466 1034 co I >- Cl) + 'I"" co .0 I co >- r-- 'I"" Cl) .0 ;. 362 918 (m/z) ,.._ Da). >- "' .0 -~· Mass 258 802 I 1,105.51 ,.._ 'I"" .E peptides. tear ([M+Ht ,.._._, abundant -~~~~ij~,~~~ peptide the tear for a 154 686 for 0, ... spectra <( "' :c: ·- decay spectrum 0, <( U'I .0 0 ...... decay 0.. i Post-source 50 0570 0 100 100 3.2. >- C C > a, G) post-source s ~ - ~ 'i :;:::: - G) a: A Figure D. Table 3.4. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 1,105.51 Da. Experimental [M+Ht values are the average(± SD) of three separate determinations. A. Fragment ions corresponding to b- and y- series ions. THEORETICAL EXPT. THEORETICAL EXPT. BIONS YIONS [M+Ht [M+Ht [M+Ht [M+Ht Bs +H2O 976.5 976.5 ± 0.5 Ys 990.5 990.8 ± 0.5 Bs 958.5 959.9± 0.6 *Ys-NH3 973.5 973.6 * B6 733.4 734.8 Y1 834.4 834.6 ± 0.5 *A6 705.4 705.4 Ys 666.3 667.1 ± 0.1 A6-NH3 688.4 688.7 ± 0.4 Y4 510.2 510.6 ± 0.3 Bs 596.3 596.4 ± 0.6 Y4-NH3 493.2 492.8 ± 0.5 *B4 440.2 439.5 Y3 373.2 373.6 ± 0.3 B2 272.1 272.3 ± 0.1 B2-NH3 255.1 255.2 ± 0.2 * Due to the low abundance of this peptide in some samples, these fragment ions were detected in only one of the PSD spectra. 68 Table 3.4. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 1,105.51 Da. Experimental [M+Ht values are the average(± SD) of three separate determinations. B. Internal sequence ions. INTERNAL THEORETICAL EXPERIMENTAL SEQUENCE IONS [M+Ht [M+Ht PA 169.1 169.3 ± 0.1 *PQ-28 198.1 198.1 PQ 226.1 226.2 ± 0.1 HP 235.1 235.1 ± 0.3 RPAorPAR 325.2 325.5 ± 0.2 RPA-NH3 308.2 308.4 ± 0.2 PAR-NH3 ARHPorPARH 462.3 462.3 ± 0.4 • Due to the low abundance of this peptide in some samples, this fragment ion was detected in only one of the PSD spectra. 69 70 1 400 870 ~ 1 848.37 [M+Ht I + T"" a, == ..... :x: ..... + 330 n& ~~ CO a, T"" .c I ID >- ,_8 I I ,J I o T"" ..... 1,.8c5+ >- T"" r-,. COCOi.. I as (\I .c I CO as r-,. T"" I 260 (\I 682 T"" ..... .c (\I >- (m/z) Da). Mass 848.37 peptides. II) .c 190 588 tear II') >- ([M+Ht abundant peptide the tear for a for ~b~~~~ C, ... t' ~ spectra 120 ' 494 (I) :x: ·- ,-.d• decay ,. spectrum ... <:I' >- decay I <:I' > T"" ..... 0 ... 0.. Post-source 3.2. __;~fw~~,w~lw~~Jw~1 ~ post-source 400 0 100 A 100 Figure E. C i CU ~ '#- - ·;;; - I :;:: I Table 3.5. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht848.37 Da. Experimental [M+Ht values are the average (± SD) of at least two determinations. A. Fragment ions corresponding to b- and y- series ions. THEORETICAL EXPT. THEORETICAL EXPT. BIONS YIONS [M+Ht [M+Ht [M+Ht [M+Ht B6+H2O 751.4 751.4 ± 0.1 y6 733.4 733.5 ± 0.1 B6 733.4 733.5 ± 0.1 Y6-NH3 716.4 716.7 ± 0.1 B6-NH3 716.4 716.7 ± 0.1 Ys 577.3 577.6 ± 0.1 ¾, 705.4 705.7 ± 0.1 Y4 480.3 480.3 ± 0.1 A6-NH3 688.4 688.2 ± 0.2 Y4-NH3 463.2 463.1 ± 0.5 Bs + H20 614.3 614.5 ± 0.4 Y3 409.2 409.1 ± 0.1 Bs 596.3 596.4 ± 0.1 Y2 253.1 253.2 ± 0.1 As 568.3 568.3 ± 0.1 84 440.2 439.3 ± 0.1 B2 272.1 272.4 ± 0.1 B2-NH3 255.1 255.2 ± 0.1 71 Table 3.5. Fragment ions detected in the post-source decay spectra of the peptide [M+Ht 848.37 Da. Experimental [M+Ht values are the average (± SO) of at least two determinations. B. Internal sequence ions. INTERNAL THEORETICAL EXPERIMENTAL SEQUENCE IONS [M+Ht [M+Ht PA 169.1 169.2 ± 0.1 AR-NH3 211.1 211.8 ± 0.8 RPAorPAR 325.2 325.2 ± 0.2 RPA-NH3 308.2 308.2 ± 0.2 PAR-NH3 PARH-NH3 445.2 445.1 ± 0.4 RPARH 618.4 618.5 ± 0.2 72 Post-source decay primarily results in fragmentation about the amide bond of the peptide backbone resulting in the formation of b- and y- series ions [Roepstorff and Pohlman, 1984; Biemann, 1988; Biemann, 1992]. In addition to this, fragment ions corresponding to amino acid side chain losses, as well as low mass immonium ions specific to individual amino acids, are also often observed [Biemann, 1992]. The PSD spectra for all peptides analysed in this study revealed an almost complete b- and y series of ions, as well as several internal fragment ions and immonium ions. Comparison of each PSD spectrum revealed fragment ions that were common to each peptide, indicating that these shared at least some sequence homology. De novo sequencing, in addition to database searching using MS-TAG (Protein Prospector), indicated that these peptides share a common N-terminus and that the largest peptide ([M+Ht 1,629.83 Da) is sequentially cleaved from the C-terminus to give rise to the smaller peptides. The amino acid sequences of each of these peptides are shown in Table 3.6. To determine the origin of these peptides, the fragment ion data were searched against the NCBI non-redundant database using MS-TAG (Protein Prospector). These peptides matched the sequence of the C-terminus of a proline-rich protein reported to be synthesized by the lacrimal gland (Accession number 2135904) [Dickinson and Thiesse, 1995]. Previously, only the mRNA for this protein had been detected in the human lacrimal gland, and this is the first report of the presence of the protein itself in human tear fluid. The amino acid sequence for the lacrimal proline-rich protein is shown in Figure 3.3. 73 Table 3.6. The amino acid sequence of five of the most abundant peptides detected in human tear. These peptides were sequenced by post-source decay. Database searching revealed that these peptides originated from the C-terminus of a lacrimal proline-rich protein. Experimental [M+Ht values are the average (± SD) of seven determinations. THEORETICAL EXPERIMENTAL PEPTIDE SEQUENCE [M+Ht (Da) [M+Ht (Da) DRP ARHPQEQPLW 1,629.83 1,629.69 ± 0.40 DRPARHPQEQPL 1,443.75 1,443.74 ± 0.03 DRPARHPQEQP 1,330.66 1,330.52 ± 0.16 DRPARHPQE 1,105.55 1,105.51 ± 0.07 DRPARHP 848.45 848.37 ± 0.13 74 Figure 3.3. The amino acid sequence for the intact lacrimal praline-rich protein. This protein consists of 134 amino acid residues and has a theoretical molecular weight of 15,096 Da. Indicated is the C-terminal peptide (13 amino acids) that forms the largest of the five peptides detected in open eye tear. MLLVLLSVVL LALSSAQSTD NDVNYEDFTF TIPDVEDSSQ RPDQGPQRPP PEGLLPRPPG DSGNQDDGPQ QRPPKPGGHH RHPPPPPFQN QQRPPQRGHR QLSLPRFPSV SLQEASSFFR RDRPARHPQE QPLW Figure legend. C-te1minal peptide detected in the MALDI-TOF mass spectrum of open eye tear. 75 3.3.2. The detection and identification of lacrimal proline-rich protein To investigate the possible presence of the intact lacrimal proline-rich protein, tear fluid was separated by size exclusion chromatography (SEC) and the fractions of interest (i.e., those corresponding to the approximate theoretical mass of the protein of interest) were further characterised by mass spectrometry. MALDI-TOFMS analysis of each fraction indicated the presence of multiple components. The molecular weights of the proteins detected were consistent with the reported theoretical masses oflysozyme (14,693 Da) and tear lipocalin (17,444 Da). In addition to these, several other protein species consistent in mass to truncated forms of tear lipocalin were also detected in the fractions analysed [Fullard and Kissner, 1991]. Although a signal for the theoretical mass of the intact secreted form of the lacrimal proline-rich protein (13,458 Da) was not detected in any of the fractions analysed, a protein of mass 11,731 ± 3 Da (n = 10) was evident in some of these fractions. Figure 3.4 shows an example of a MALDI-TOF mass spectrum for one of the SEC fractions. 76 77 25000 lipocalin lipocalin tear of tear fluid. protein 21300 form tear Intact proline-rich Truncated ofhuman / ~.,11-r.;tw;t~~,rlvM\~~of.v'N./M¼, \ lacrimal ..... ,, ~ of /~ 17600 / fractions \!\; ! form I 1M~.O _!\\ SEC the (m/z) of Truncated Mass one for 13900 / ¼f#~~~~r1lv~~~~}/t 11733.1 spectrum /I I~ J I mass 10200 ~~~~ ~ ~~ I MALDI-TOF ofa 'flMRIMIJ 6500 O+------~ 100 U) C i example I ~ ~ a: "i ; - - An 3.4. Figure To confirm the identity of the proteins in the SEC fractions that were detected by MALDI-TOFMS, an aliquot from each was treated with both trypsin and Asp-N. Analysis detected peptide masses that are predicted to be derived from lysozyme and tear lipocalin, as well as peptides predicted to originate from lacrimal proline-rich protein. Following this, the amino acid sequence of the proteolytic peptides from these fractions was obtained by ESI-LC/MS/MS. Each MS/MS spectrum was searched against the non redundant protein databases, and this confirmed the presence oflysozyme and tear lipocalin, as well as the presence of the lacrimal proline-rich protein. Using this approach, greater than 50% coverage of the lacrimal proline-rich protein was obtained (Figure 3.5). The molecular weight of the intact secreted form of this lacrimal proline rich protein is reported to be 13,458 Da and this corresponds to residues 17 - 134, with residue 17 being pyroglutamic acid. Although the secreted form of the lacrimal proline-rich protein was not detected by MALDI-TOFMS in any of the SEC fractions analysed, a protein of mass 11,731.3 ± 3 .1 Da (n = 10) was detected in all of the fractions that showed evidence for the presence of the pro line-rich protein derived peptides. This same species (i.e., 11,731 ± 3 Da) is also evident in the MALDI-TOF mass spectrum of intact human tear. (See Figure 3.1, p 56.) This mass is consistent with the molecular weight of residues 18 - 121 (11,733 Da) of the intact lacrimal proline-rich protein, indicating that the N-terminal pyroglutamic acid residue is also removed. Additionally, residues 122- 134 (i.e., [M+Ht 1,629.83 Da), corresponding to the C-terminal peptide detected in tear, is found in all the tear samples examined (Figure 3 .5). 78 Figure 3.5. Amino acid coverage of the lacrimal proline-rich protein following its isolation by size exclusion chromatography. Coverage was determined by proteolytic cleavage using trypsin and Asp-N. The resulting peptides were detected by MALDI-TOFMS and ESI-LC/MS/MS was used to identify the parent protein. Also indicated is the portion of the lacrimal proline-rich protein that is detected in the MALDI-TOF mass spectrum of open eye tear fluid (i.e., residues 18 - 121). 18 MLLVLLSVVL LALSSAQETD NDVNYEDFTF TIPDVEDSSQ RPDQGPQRPP PEGLLPRPPG DSGNQDDGPQ QRPPKPGGHH 121 ~!~P!_!'9_!'1_~~~~~~~ g~~1:_P_!U'PSV SLQEASSwt DRPARHPQE QPLW Figure legend. C-terminal peptide detected in unfractionated tear. Peptides identified following Asp-N/trypsin digestion of SEC fractions. 79 3.3.3. Analysis of unfractionated human tear proteins by ESI-LC/MS/MS To confirm the identity of the proteins detected by MALDI-TOFMS, and to identify other proteins present in tear film, ESI-LC/MS was performed. This was necessary because signal suppression - a common problem associated with MALDI-TOFMS of complex mixtures - limits what can be determined directly. Just as importantly, MALDI-TOFMS only provides molecular weight information, so at best offers tentative identification of proteins. Therefore, additional studies were undertaken. An aliquot of tear sample was digested with trypsin and the resulting tryptic peptides were then directly analysed by ESI-LC/MS/MS using reverse phase chromatography. In excess of 2,000 tryptic peptides were detected, matched by SEQUEST, and identified as constituent peptides of known proteins. The base peak chromatogram for the tryptic digest of human tear is shown in Figure 3.6. Positive protein identification was based on the detection and sequencing of multiple peptides derived from the same protein. Over 100 known tear constituents were detected and identified (Table 3.7, p 84), including serum-based proteins, cytokines, growth factors, immunoglobulins, proteins with antibacteriolytic or antimicrobial function, a large number of enzymes, and tear-specific proteins such as lactotransferrin and tear lipocalin. 80 Figure 3.6. The base peak chromatogram of the tryptic peptides (m/z 500-2,000) detected in human tear plotted over four distinct mass ranges. To identify proteins in human tear, an aliquot (10 µL) was digested with trypsin and analysed by ESI-LC/MS/MS. Shown is the total ion chromatogram obtained when the tryptic peptides were separated by reverse phase liquid chromatography and detected by mass spectrometry. This chromatogram has been divided into four mass ranges. The x axis indicates retention time (minutes) and the y-axis indicates the relative abundance of each chromatographic peak. 81 Fig ure 3.6. The base peak c hromatogram of the tryptic peptides (m/ z SOO - 2,000) detected in human tear p lotted over four distinct mas s ranges. 90.59 92.35 97.16 r06.184 106.84 84.87 106.21 110.00 104.06 90.59 137.20 m/z 1625 - 2000 92.35 100 84.87 m/z 1250- 1625 ::,g 25 -0 30.34 48.31 49.87 -Cl) I tl) \I 1,tj 1,.t__ _ 0 C: ea "C C: :::, .0 et Cl) > .:: ea 130.20 cii m/z500 - 875 139.15 a: 79.38 I 1II f 1.37 32.24 52.81 77.79 11 ij 111 64.95 \ I I I ' 35.90 51 ~ 1 I /\ I' 111 11 i.'I I' )' 1 \ I I I I' I I I I I I I I 1 I I I I I I j I I I I I I I I I I j I I I I I I I I I I I I I I I I I I I I I I I I I 50 30 40 60 70 80 90 100 110 120 130 140 150 Time (min) 82 This study has identified over 300 proteins not previously reported as a component of human tear. However, subsets of these proteins have been detected in various human ocular tissues (e.g., lacrimal gland, conjunctiva, cornea) or have been identified in the tear film of individual with pathological conditions (e.g., dry eye syndrome, rheumatoid arthritis). These proteins are listed in Tables 3.8 (p 93) and 3.9 (p 94) respectively. Proteins detected in the tear film or ocular tissue of other animal species are listed in Table 3.10 (p 95). In addition to these, proteins that have not previously been reported as components of human tear were detected and identified: these are listed in Table 3.11 (p 96). These include various plasma proteins, immunoglobulin receptor proteins, cytokines, growth factors, proline-rich proteins, mucins, enzymes and other biologically active peptides and proteins. 83 Table 3.7. Proteins identified by ESI-LC/MS/MS that have been previously reported as components of the human tear film. # PEPTIDES PROTEIN REFERENCE DETECTED van Haeringen and a.-N-acetylglucosaminidase precursor Glasius, 1976; van 2 Accession number: 4505327 Haeringen and Glasius, 1980 a.-1-antichymotrypsin precursor Prause, 1983; Sathe et 4 Accession number: 112874 al., 1998. a.-1-antitrypsin precursor ( a.-1- Berta, 1982; Prause, antiproteinase) 2 1983; Gupta et al., Accession number: 1703025 1988; Sathe et al., 1998 van Haeringen and Glasius, 1974; Van a-amylase precursor (salivary) 5 Haeringen and Glasius, Accession number: 1351933 1974; Van Haeringen et al., 1975 a.-2-macroglobulin precursor Prause, 1983; Sathe et 15 Accession number: 112911 al., 1998 van Haeringen and a.-mannosidase II 4 Glasius, 1980; Kitaoka Accession number: 3122380 et al., 1985 van Haeringen and a.-mannosidase IIX 5 Glasius, 1980; Kitaoka Accession number: 3123244 et al., 1985 van Haeringen and P-glucuronidase precursor 7 Glasius, 1980; Kitaoka Accession number: 114963 et al., 1985 P-2-microglobulin precursor Markusse et al., 1992; 3 Accession number: 114773 Markusse et al., 1993 84 # PEYrIDES PROTEIN REFERENCE DETECTED Amyloid protein precursor 3 Van Setten et al., 1996 Accession number: 112927 Angiotensin converting enzyme precursor 7 Vita et al., 1981 Accession number: 113045 Antileukoproteinase precursor 3 Sathe et al., 1998 Accession number: 113636 Arylsulfatase D precursor van Haeringen and 2 Accession number: 1703425 Glasius, 1980 Calcitonin gene related peptide I precursor or Calcitonin gene related peptide II precursor Mertaniemi et al., 1995; 2 Accession number: 115487 Tervo et al., 1995 Accession number: 115482 Ceruloplasmin precursor 11 Seal, 1985 Accession number: 116117 Complement C 1Q subcomponent precursor, Mondino and Zaidman, chain A 2 1983; Willcox et al., Accession number: 399139 1997 Complement Cl Q subcomponent precursor, Mondino and Zaidman, chainB 4 1983; Willcox et al., Accession number: 399140 1997 Complement CIR component precursor Mondino and Zaidman, 9 Accession number: 115205 1983 Imanishi et al., 1982; Complement C 1 Scomponent precursor Mondino and Zaidman, ( C 1esterase) 5 1983; Sack et al., 1992; Accession number: 115205 Willcox et al., 1997 Mondino and Zaidman, Complement C3 precursor 19 1983; Willcox et al., Accession number: 116594 1997 Mondino and Zaidman, Complement C4 precursor 15 1983; Willcox et al., Accession number: 116602 1997 85 # PEYfIDES PROTEIN REFERENCE DETECTED Complement C5 precursor 13 Willcox et al., 1997 Accession number: 116602 Complement C9 precursor 7 Willcox et al., 1997 Accession number: 116607 Complement decay accelerating factor precursor 3 Lass et al., 1990 Accession number: 1345942 Complement factor B precursor 7 Willcox et al., 1997 Accession number: 584908 Cystatin C precursor Barka et al., 1991; Reitz 3 Accession number: 118183 et al., 1998 Barka et al., 1991; Cystatin SN precursor 4 Isemura et al., 1991; Accession number: 118188 Molloy et al., 1997 Cytosolic phospholipase A2 Nevalainen, 1993; Qu 2 Accession number: 1352707 and Lehrer, 1998 Elafin 3 Sathe et al., 1998 Accession number: 119262 Eosinophil cationic protein precursor 2 Leonardi et al., 1995 Accession number: 119124 Eosinophil granule major basic protein precursor 2 Udell et al., 1981 Accession number: 11929 Eosinophil lysophospholipase 2 Udell et al., 1981 Accession number: 547870 Eosinophil peroxidase precursor Fullard, 1988; Fullard 10 Accession number: 1352738 and Tucker, 1991 Epidermal growth factor precursor Fullard, 1988; Fullard 7 Accession number: 119226 and Tucker, 1991 Fibroblast growth factor (basic 22kDa form) 2 van Setten, 1996 Accession number: 482272 Hayashi and Sueishi, Fibronectin precursor 16 1988; Sakata et al., Accession number: 2506872 1997; Sack et al., 1999 86 # PEPTIDES PROTEIN REFERENCE DETECTED Van Haeringen and Glutamate dehydrogenase I precursor 3 Glasius, 1974; van Accession number: 118541 Haeringen and Glasius, 1976 Granulocyte macrophage colony stimulating factor precursor 3 Thakur et al., 1998 Accession number: 117561 Heparin binding growth factor- I precursor 4 van Setten, 1996 Accession number: 122737 Heparin binding growth factor-2 precursor 3 van Setten, 1996 Accession number: 122742 Hepatocyte growth factor precursor 10 Li et al., 1996 Accession number: 123116 Van Haeringen and Hexokinase, type II Glasius, 1974; van 5 Accession number: 1708361 Haeringen and Glasius, 1976 Little et al., 1969; McClellan et al., 1973; Coyle and Sibony, 1986; Fullard, 1988; Coyle et Immunoglobulin alpha chain 1 7 al., 1989; Tchah, 1989; Friedman, 1990; Mii et al., 1992; Reitz et al., 1998 Brauninger and lmmunoglobulin epsilon chain C region Centifanto, 1971; 3 Accession number: 119512 McClellan et al., 1973; Friedman, 1990 87 # PEYfIDES PROTEIN REFERENCE DETECTED Little et al., 1969; McClellan et al., 1973; Seal, 1985; Coyle and Immunoglobulin gamma chain 1 2 Sibony, 1986; Fullard, 1988; Coyle et al., 1989; Friedman, 1990; Reitz et al., 1998 Immunoglobulin J chain 5 Friedman, 1990 Accession number: 400044 McClellan et al., 1973; Coyle and Sibony, 1986; Immunoglobulin mu precursor 1 17 Fullard, 1988; Friedman, 1990; Fullard and Tucker, 1991 Interleukin 2 precursor 3 Uchio et al., 2000 Accession number: 124325 Interleukin 6 precursor 3 Thakur et al., 1998 Accession number: 124347 Van Haeringen and Isocitrate dehydrogenase, mitochondrial Glasius, 1974; van precursor 4 Haeringen and Glasius, Accession number: 6166246 1976 Latent transforming growth factor ~ binding protein 19 Yoshino et al., 1996 Accession number: 1196439 Leukocyte elastase inhibitor precursor 3 Sathe et al., 1998 Accession number: 266344 Lipophilin A precursor Molloy et al., 1997; 2 Accession number: 6831580 Lehrer et al., 1998 88 # PEPTIDES PROTEIN REFERENCE DETECTED Berta, 1982; Janssen and van Bijsterveld, 1983b; Kijlstra et al., 1983; Seal, 1985; Jensen et al., 1986; Fullard, 1988; Coyle et al., 1989; Kijlstra et al., 1989; Lactotransferrin precursor 35 Baier et al., 1990; Accession number: 6175096 Fullard and Tucker, 1991; Kuizenga et al., 1991b; Kuizenga et al., 1991a; Mii et al., 1992; Sack et al., 1992; Molloy et al., 1997; Reitz et al., 1998 van Haeringen and Glasius, 1974; Van Haeringen and Glasius, L-Lactate dehydogenase M chain precursor 2 1974; Kahan and Accession number: 126047 Ottovay, 1975; van Haeringen and Glasius, 1976; Jacq et al., 1982 Lysosomal cx-glucosidase precursor van Haeringen and 4 Accession number: 3122374 Glasius, 1980 van Haeringen and Lysosomal cx-mannosidase precursor 3 Glasius, 1980; Kitaoka Accession number: 3122374 et al., 1985 Mammoglobin B precursor (lipophilin C) Molloy et al., 1997; 2 Accession number: 6831582 Lehrer et al., 1998 Muc5AC (gastric mucin) [Jumblatt et al., 1999; 6 Accession number: 15026993 McKenzie et al., 2000] 89 # PEPTIDES PROTEIN REFERENCE DETECTED Van Haeringen and Glasius, 1974; Stuchell etal., 1981; Berta, 1982; Lysozyme precursor Seal, 1985; Fullard, 19 Accession number: 126615 1988; Coyle et al., 1989; Baier et al., 1990; Molloy et al., 1997; Reitz et al., 1998 van Haeringen and Glasius, 1974; Van Malate dehydrogenase, cytoplasmic 3 Haeringen and Glasius, Accession number: 1708967 1974; van Haeringen and Glasius, 1976 Mucin 5 precursor (tracheobronchial) 11 Jumblatt et al., 1999 Accession number: 1346603 Mucin SB Jumblatt et al., 1999; 2 Accession number: 631466 McKenzie et al., 2000 Phospholipase A2 precursor, membrane Nevalainen, 1993; Qu associated 5 and Lehrer, 1998 Accession number: 129483 Plasminogen activator, precursor urokinase type 5 Schenkels et al., 1991 Accession number: 137112 Plasminogen precursor Thorig et al., 1983; 11 Accession number: 130316 Tozser and Berta, 1991 Polymeric immunoglobulin receptor Coyle and Sibony, 1986; precursor, secretory component 11 Kuizenga et al., 1991a Accession number: 1730570 Berta, 1982; Coyle et Prolactin-inducible protein precursor 5 al., 1989; Fullard and Accession number: 134170 Tucker, 1991 Prolactin precursor Frey et al., 1981; Frey et 3 Accession number: 130930 al., 1986 90 # PEPTIDES PROTEIN REFERENCE DETECTED van Haeringen and Glasius, 1974; Van Pyruvate kinase, isozymes R/L 2 Haeringen and Glasius, Accession number: 8247933 1974; van Haeringen and Glasius, 1976 van Haeringen and Pyruvate kinase, M 1 isozyme or Glasius, 1974; Van Pyruvate kinase, M2 isozyme 2 Haeringen and Glasius, Accession number: 266427 1974; van Haeringen Accession number: 125604 and Glasius, 1976 Stuchell et al., 1981; Berta, 1982; Prause, 1983; Fullard, 1988; Serotransferrin precursor Coyle et al., 1989; Baier 8 Accession number: 136191 et al., 1990; Fullard and Tucker, 1991; Kuizenga et al., 1991b; Mii et al., 1992 Serum albumin precursor Prause, 1983; Gupta et 12 Accession number: 113576 al., 1988 Superoxide dismutase precursor, extracellular 2 Behndig et al., 1998 Accession number: 134635 Transcobalamin I precursor 2 Carmel, 1972 Accession number: 135533 Transforming growth factor ~-1 precursor Gupta et al., 1996; 3 Accession number: 135674 Yoshino et al., 1996 Transforming growth factor ~-2 precursor Gupta et al., 1996; 8 Accession number: 135679 Yoshino et al., 1996 Vitronectin precursor 6 Sack et al., 1994 Accession number: 139653 Zn-cx-2-glycoprotein precursor 11 Molloy et al., 1997 Accession number: 141596 91 # PEPTIDES PROTEIN REFERENCE DETECTED Bonavida et al., 1969; Berta, 1982; Janssen and van Bijsterveld, 1983b; Janssen and van Bijsterveld, 1983a; von Ebner's gland protein precursor Fullard, 1988; Baier et (tear lipocalin) 14 al., 1990; Fullard and Accession number: 401346 Kissner, 1991; Fullard and Tucker, 1991; Kuizenga et al., 1991b; Baguet et al., 1992; Molloy et al., 1997; Reitz et al., 1998 1 Due to the high degree of homology between isoforms of these proteins the peptides detected could not be assigned to a unique protein without ambiguity. 92 Table 3.8. Proteins that have been detected in human ocular tissue but not in the tear film. No. PEPTIDES PROTEIN REFERENCE DETECTED P-defensin 1 precursor 2 Haynes et al., 1999 Accession number: 1705448 P-defensin 2 precursor 4 Haynes et al., 1999 Accession number: 3023383 Apolipoprotein D precursor 8 Holzfeind et al., 1995 Accession number: 114034 Basic proline rich protein Dickinson and Thiesse, 2 Accession number: 1836022 1996 CD44 antigen precursor 5 Yoshida et al., 1996 Accession number: 2507241 Clusterin Nishida et al., 1996; 2 Accession number: 116533 Dota et al., 1999 Immunoglobulin delta chain C region precursor 2 Friedman, 1990 Accession number: 118945 Interleukin 1-a. precursor 2 Pflugfelder et al., 1999 Accession number: 124297 Mucin 1 precursor ( epithelial) 2 Inatomi et al., 1995 Accession number: 547937 Mucin 2 precursor 12 McKenzie et al., 2000 Accession number: 2506877 pHL ElFl (lacrimal proline-rich protein) Dickinson and Thiesse, 2 Accession number: 2135904 1995 Platelet derived growth factor precursor, A chain 3 Nguyen et al., 1997 Accession number: 129719 Transforming growth factor-P-3 precursor Nishida et al., 1995; 6 Accession number: 135684 Nguyen et al., 1997 93 Table 3.9. Proteins identified by ESI-LC/MS/MS that are reportedly elevated in the tear fluid of patients with various pathological conditions. No. PEPTIDES PROTEIN REFERENCE DETECTED 52kDR052 (Sjogren syndrome type A antigen) 3 Pflugfelder et al., 1986 Accession number: 123250 FASL receptor precursor 3 Tuominen et al., 1999 Accession number: 119833 Granzyme A precursor Tsubota et al., 1994a; 2 Accession number: 121581 Tsubota et al., 1994b Perforin 1 precursor Tsubota et al., 1994a; 6 Accessionnumber: 129819 Tsubota et al., 1994b Sjogren syndrome Type B antigen (Lupus LA protein) 4 Pflugfelder et al., 1986 Accession number: 125985 94 Table 3.10. Proteins identified by ESI-LC/MS/MS that have been reported in the tear film of animal species other than human. No. PEPTIDES PROTEIN REFERENCE DETECTED Cysteine rich secretory protein 3 precursor 3 Haendler et al., 1999 Accession number: 1706135 Endothelin-1 precursor 2 Takashima et al., 1996 Accession number: 119610 Pancreatic lipase related protein 1 precursor 4 Remington et al., 1999 Accession number: 1708837 Pancreatic lipase related protein 2 precursor 3 Remington et al., 1999 Accession number: 1708840 Plasma retinol-binding protein precursor 5 Lee et al., 1992 Accession number: 132404 Retinoic acid binding protein I precursor, cellular 2 Lee et al., 1992 Accession number: 266904 Retinoic acid binding protein II precursor, cellular 3 Lee et al., 1992 Accession number: 132401 Retinol binding-protein II precursor, cellular 3 Lee et al., 1992 Accession number: 1710092 95 Table 3.11. Proteins identified by ESI-LC/MS/MS that have not previously been reported as components of the human tear film. No. PEPTIDES PROTEIN DETECTED cx-1-antitrypsin related protein precursor 2 Accession number: 112891 cx-1-acid glycoprotein 1 precursor 3 Accession number: 112877 cx-1-acid gl ycoprotein 2 precursor 4 Accession number: 231458 cx-1 b-glycoprotein precursor 6 Accession number: 112892 cx-1-microglobulin / inter-ex-trypsin inhibitor precursor, light chain 4 Accession number: 122801 cx-2-antiplasmin precursor 4 Accession number: 112907 cx-defensin 4 precursor 2 Accession number: 399352 cx-defensin 5 precursor 2 Accession number: 399353 cx-defensin 6 precursor 2 Accession number: 399354 cx-fetoprotein precursor 4 Accession number: 120042 ~-2-glycoprotein (hemopexin) 3 Accession number: 170182 ~-2-glycoprotein I precursor (apolipoprotein H) 3 Accession number: 543826 ~-mannosidase precursor 2 Accession number: 3024091 ~-secretase precursor 3 Accession number: 6685248 96 No. PEPTIDES PROTEIN DETECTED y-interferon inducible protein IP-30 precursor 3 Accession number: 280788 Afamin precursor ( a-albumin) 3 Accession number: 1168366 Aldehyde dehydrogenase 6 2 Accession number: 1352246 Aldehyde dehydrogenase, cytosolic ( class 1) 2 Accession number: 118495 Aldehyde dehydrogenase, mitochondrial precursor 2 Accession number: 118504 Aldehyde reductase ( al dose reductase) 2 Accession number: 113596 Amyloid-like protein 1 precursor 4 Accession number: 2829415 Amyloid-like protein 2 precursor 3 Accession number: 1703344 Androgen induced growth factor (FGF-8) 7 Accession number: 1206791 Angiogenin precursor 2 Accession number: 113873 Angiotensinogen precursor 5 Accession number: 113880 Angiotensinogen - mutant 2 Accession number: 4261988 Antithrombin III precursor 4 Accession number: 113936 Apolipoprotein A-I precursor 3 Accession number: 113992 Apolipoprotein B precursor 16 Accession number: 114014 Apolipoprotein E precursor 2 Accession number: 114039 97 NO. PEPTIDES PROTEIN DETECTED Azurocidin precursor ( cationic antimicrobial peptide, CAP3 7) 5 Accession number: 416746 Bacterial permeability increasing protein precursor 11 Accession number: 2822120 C4B binding protein ex chain precursor 2 Accession number: 416733 Carboxypepetidase Al precursor 2 Accession number: 399196 Carboxypepetidase A2 precursor 2 Accession number: 1352189 Carboxypepetidase B precursor (pancreas specific) 5 Accession number: 3915628 Carboxypeptidase D 3 Accession number: 4503007 Carboxypeptidase H precursor 2 Accession number: 115892 Carboxypeptidase M precursor 3 Accession number: 14916957 Carboxypeptidase N precursor 2 Accession number: 1154432 Caspase 9 precursor 2 Accession number: 1264432 Catalase 6 Accession number: 115702 Cathepsin E precursor 2 Accession number: 115723 Cathepsin G precursor 4 Accession number: 115725 Cathepsin K precursor 5 Accession number: 1168793 Cathepsin L2 precursor 2 Accession number: 12644075 98 NO. PEPTIDES PROTEIN DETECTED Cathepsin S precursor 2 Accession number: 115748 Cerebrin-50 2 Accession number: 2134902 Choriomammotropin like protein 2 Accession number: 106319 Chromogranin A precursor 4 Accession number: 6832905 Chymotrypsinogen B precursor 2 Accession number: 117617 Coagulation factor V precursor 16 Accession number: 462045 Coagulation factor VII precursor 4 Accession number: 119766 Coagulation factor VIII precursor 10 Accession number: 119767 Coagulation factor XI precursor 3 Accession number: 119762 Coagulation factor XII precursor 3 Accession number: 119763 Coagulation factor XIIIa precursor 5 Accession number: 119720 Complement C2 precursor 5 Accession number: 3915642 Complement C6 precursor 13 Accession number: 116609 Complement C7 precursor 10 Accession number: 87197 Complement C8 a chain precursor 5 Accession number: 729167 Complement C8 ~ chain precursor 5 Accession number: 116612 99 NO. PEPTIDES PROTEIN DETECTED Complement Factor H precursor 13 Accession number: 116131 Complement Factor I precursor 6 Accession number: 116133 Complement activating component of RA-reactive factor precursor 2 Accession number: 1352202 Cysteine proteinase 3 Accession number: 2134965 Cysteine rich protein 1 precursor 2 Accession number: 48161 Defensin HNP2 homologue (fragment) 1 Accession number: 2134986 Endothelin-converting enzyme 1 precursor 2 Accession number: 1706563 FALL-39 precursor (antimicrobial protein, CAP-18) 5 Accession number: 1706745 Fibroblast growth factor-4 precursor 4 Accession number: 122750 Fibroblast growth factor-6 precursor 2 Accession number: 1169676 Fibroblast growth factor-11 precursor 3 Accession number: 2494457 Fibroblast growth factor-12 precursor 3 Accession number: 2494459 Fibroblast growth factor-13 precursor 4 Accession number: 2494461 Fibroblast growth factor-14 precursor 3 Accession number: 2494463 Fibroblast growth factor-17 precursor 3 Accession number: 601514 7 Fibrinogen a/a.-E chain precursor 9 Accession number: 1706799 100 No. PEPTIDES PROTEIN DETECTED Fibrinogen ~ chain precursor 7 Accession number: 399492 Fibrinogen gamma-A chain precursor or Fibrinogen gamma-B chain precursor 5 Accession number: 120142 Accession number: 120146 Follistatin precursor 2 Accession number: 120547 Follistatin-related protein precursor 3 Accession number: 2498390 Fructose bisphosphate aldolase 2 Accession number: 113611 Glial cell line-derived neurotrophic factor precursor 2 Accession number: 729567 Glutamate decarboxylase, 67kDa isoform 3 Accession number: 1352213 Growth/differentiation factor 5 precursor 2 Accession number: 1346125 Hepatocyte growth factor activator precursor 2 Accession number: 547643 Hepatocyte growth factor-like protein precursor (macrophage stimulatory protein) 3 Accession number: 123114 Hepatoma-derived growth factor 3 Accession number: 1708159 Hepcidinprecursor 3 Accession number: 10720397 High affinity immunoglobulin E FC receptor ~-subunit precursor 2 Accession number: 232084 Immunoglobulin a. FC receptor precursor 5 Accession number: 119800 Immunoglobulin y FC receptor precursor 2 Accession number: 119871 101 NO. PEPTIDES PROTEIN DETECTED Immunoglobulin mu heavy chain disease protein precursor 3 Accession number: 127506 Immunoglobulin mu switch region binding protein 2 precursor 7 Accession number: 1082534 Inhibin 13 B chain precursor 2 Accession number: 1708437 Insulin degrading enzyme 3 Accession number: 124157 Insulin like growth factor II precursor 2 Accession number: 124255 Insulin like growth factor binding protein V precursor 3 Accession number: 124070 Insulin like growth factor binding protein complex acid labile chain precursor 4 Accession number: 543800 Interferon a-2 precursor 2 Accession number: 124449 Interferon a-8 (interferon a-b2) precursor 2 Accession number: 417188 Interleukin 1-13 convertase precursor 3 Accession number: 266321 Interleukin 7 precursor 4 Accession number: 124354 Interleukin 12 a chain precursor 3 Accession number: 266319 Interleukin 12 13 chain precursor 4 Accession number: 266320 Interleukin 13 precursor 2 Accession number: 462408 Interleukin 17 precursor 2 Accession number: 2498481 lnterphotoreceptor retinoid-binding protein precursor (interstitial) 3 Accession number: 124894 102 NO. PEPTIDES PROTEIN DETECTED Kallikrein (glandular kallikrein) 3 Accession number: 125170 Kallikrein (plasma prekallikrein, kininogen) 6 Accession number: 125184 Kallistatin precursor (kallikrein inhibitor) 3 Accession number: 1708609 Keratinocyte growth factor precursor (FGF-7) 4 Accession number: 122756 Kininogen precursor 5 Accession number: 125507 Lens epithelium-derived growth factor 3 Accession number: 11360305 Leucine-rich a-2-glycoprotein 2 Accession number: 16418467 Low affinity immunoglobulin yFC receptor 11-C precursor 3 Accession number: 399476 Lysosomal acid lipase/cholesterol ester hydrolase precursor 3 Accession number: 585405 Lysosomal protective protein precursor (cathepsin A, carboxypeptidase C) 3 Accession number: 131081 Macrophage colony stimulating factor- I precursor 6 Accession number: 117558 Macrophage inflammatory protein 2-a precursor 3 Accession number: 127085 Maspin precusor 4 Accession number: 547892 Mast cell carboxypeptidase A precursor 8 Accession number: 115887 Melanotransferrin precursor 9 Accession number: 136204 Membrane cofactor protein precursor 2 Accession number: 1708964 103 NO. PEPTIDES PROTEIN DETECTED Meprin A a-subunit precursor 2 Accession number: 2499910 Meprin A ~-subunit precursor 3 Accession number: 2499912 Monocyte chemotactic protein 3 precursor ( eotaxin precursor) 2 Accession number: 1706661 Myeloperoxidase precursor 4 Accession number: 129825 Neuromedin B precursor 3 Accession number: 1346684 Neutrophil cytosol factor 2 3 Accession number: 1346609 Pepsinogen A precursor 2 Accession number: 129792 Phosphatidylinositol transfer protein ~ precursor 2 Accession number: 1346772 Pigment epithelium-derived factor precursor 5 Accession number: 1352735 Plasminogen activator inhibitor 1 precursor 2 Accession number: 129576 Plasminogen activator inhibitor 2 precursor 5 Accession number: 1352712 Plasma protease C 1 inhibitor precursor 4 Accession number: 124096 Plasma serine protease inhibitor precursor 3 Accession number: 400068 Plastin precursor, L- 3 Accession number: 2493466 Plastin precursor, T- 3 Accession number: 2506254 Platelet-activating factor acetylhydolase 1B subunit 2 Accession number: 3024345 104 NO. PEPTIDES PROTEIN DETECTED Platelet derived epithelial cell growth factor precursor 2 Accession number: 129719 Proenk:ephalin A precursor 6 Accession number: 129770 Proline rich protein (PRCC) 3 Accession number: 2498802 Prostacyclin synthase precursor (prostaglandin 12 synthase) 2 Accession number: 2493373 Prostaglandin G/H synthase 1 precursor 3 Accession number: 129899 Prostaglandin D2 synthase precursor 3 Accession number: 730305 Prothrombin precursor ( coagulation factor II) 4 Accession number: 135807 Pyruvate carboxylase precursor 2 Accession number: 1709947 Renin precursor (angiotensinogenase) 2 Accession number: 132326 Salivary peroxidase or lactoperoxidase 9 Accession number: 2117625 Accession number: 4264341 Secretogranin I precursor (chromogranin B) 4 Accession number: 134461 Secretagranin II precursor ( chromogranin C) 7 Accession number: 134464 Semaphorin 3C precursor 2 Accession number: 8134685 Semaphorin 3F precursor 2 Accession number: 8134696 Serine hydroxymethyltransferase, cytosolic 3 Accession number: 462184 Serine protease hepsin 2 Accession number: 123057 105 No. PEPTIDES PROTEIN DETECTED Somatoliberin precursor (OH-releasing factor) 2 Accession number: 134521 Somatotropin precursor 10 Accession number: 134703 Stem cell factor precursor (mast cell growth factor) 3 Accession number: 4580470 Succinate dehydrogenase flavoprotein subunit, mitochondrial precursor 4 Accession number: 1169337 Tissue factor precursor precursor 2 Accession number: 135666 Tissue factor pathway inhibitor 1 precursor 3 Accession number: 125932 Transforming growth factor-~ 4 precursor 4 Accession number: 13124811 Transforming growth factor~ induced protein IG-H3 precursor 9 Accession number: 2498193 Tumour necrosis factor-C precursor (lymphotoxin ~) 3 Accession number: 549088 Tumour necrosis factor, a induced protein 1, B12 protein 3 Accession number: 2833248 Tumour necrosis factor inducible protein TSG-6 precursor 2 Accession number: 1351315 Tumour necrosis factor, a induced protein 3 3 Accession number: 112894 Vasoactive intestinal peptide precursor 3 Accession number: 138574 Vitamin K dependant protein C precursor 5 Accession number: 131067 Vitamin K dependant protein S precursor 3 Accession number: 131086 Vascular endothelial growth factor-B precursor 3 Accession number: 1718152 106 No. PEPTIDES PROTEIN DETECTED Vascular endothelial growth factor-C precursor 4 Accession number: 1718154 Vascular endothelial growth factor precursor 3 Accession number: 137821 von Willebrand factor precursor 13 Accession number: 401413 107 3.4. Discussion Mass spectrometry, in particular MALDI-TOFMS and ESI-LC/MS/MS, provides a sensitive and rapid approach to the detection and identification of protein components in complex biological samples. By utilising these techniques, several hundred peptides and proteins were detected and identified in a small volume of human tear: less than 10 µL was required for the entire study. Peptides in human tear were detected by MALDI TOFMS, sequenced by MALDI-PSD, then identified by database searching. Proteins were analysed by ESI-LC/MS/MS following enzymatic digestion with trypsin, and identified by searching fragment ion spectra against the non-redundant protein databases using SEQUEST. By combining the approaches ofMALDI-TOFMS and ESI-LC/MS/MS a comprehensive analysis of the peptide and protein components in biological tissues and fluids can be performed. MALDI-TOFMS is ideal for the detection of peptides and proteins in complex samples, but due to the signal suppression effects inherent to the MALDI ionisation process, not all components can be detected. Nevertheless, the mass of the most abundant endogenous peptides and proteins can be determined with accuracy. Over 30 peptides and proteins were detected in human tear using MALDI TOFMS, and the most abundant peptides were shown to be derived from the C-terminus of a lacrimal proline-rich protein previously not detected as a component of human tear [Dickinson and Thiesse, 1995]. In addition to these peptides, a truncated form of this protein corresponding to residues 18 - 121 of the full length protein was also detected. The biological significance of the cleavage of this protein to yield a homologous family of peptides is unknown. 108 By employing ESI-LC/MS/MS a more comprehensive characterisation of the protein constituents can be obtained. Although the direct analysis of peptides and proteins by ESI-LC/MS/MS aims to identify all the proteins in a given sample, it does not routinely detect or identify post-translational modifications such as phosphorylation, glycosylation or truncation to form bioactive products. For instance, the presence of glycoproteins and truncated proteins, such as truncated forms of tear lipocalin, in the tear film has been reported [Coyle et al., 1989; Fullard and Kissner, 1991; Kuizenga et al., 1991a; Jumblatt et al., 1999; McKenzie et al., 2000]. Although more than 400 proteins were identified in this study, it should be noted that ESI-LC/MS/MS can not identify all protein isoforms nor establish all protein modifications. There have been many investigations concerning the protein composition of the normal tear film and in total, approximately 100 proteins have been identified and reported. Previously, the protein components of human tear were characterised by techniques such as gel electrophoresis, HPLC and/or immunochemical techniques [Boukes et al., 1987; Fullard, 1988; Coyle et al., 1989; Baier et al., 1990; Wollensak et al., 1990; Kuizenga et al., 1991b; Mii et al., 1992; Behndig et al., 1998; Jumblatt et al., 1999]. These techniques require large amounts of sample and extensive purification of the proteins of interest. In this study over 400 proteins were detected and identified in a single ESI-LC/MS/MS analysis, including most of those that have been previously reported as components of the tear film. The biological function of many of the proteins identified by this approach, and their possible role in the pathogenesis of ocular disease is yet to be established. This study also identified proteins in normal tear fluid that have previously only been detected in pathological states, indicating that these proteins are 109 also present at low concentrations in normal tear. Further investigations involving analysis of tear film derived from individuals diagnosed with these conditions would be advantageous in establishing the utility of these proteins as potential biomarkers of disease. 110 CHAPTER4 COMPREHENSIVE PEPTIDE AND PROTEIN IDENTIFICATION: APPLICATION TO THE ANALYSIS OF HUMAN SEMINAL FLUID 111 4.1. Introduction Proteomics is the process of defining the proteome [Wasinger et al., 1995] of a biological system and is generally determined following the separation of a complex protein mixture by two dimensional gel electrophoresis (2DE), proteolytic digestion of the individual proteins, and subsequent identification by mass spectrometry and database searching [James et al., 1993; Mann et al., 1993]. Analysis of proteins by 2DE involves the separation and focusing of proteins in a biological sample based on their isoelectric point (pi; first dimension) and following this, migration through a polyacrylamide gel and separation according to molecular weight (second dimension). Although 2DE was first introduced in 1975 [O'Farrell, 1975], its popularity as a protein separation tool was enhanced considerably by two developments: improvements in isoelectric focusing (IEF) technology (i.e., the introduction of carrier ampholytes and immobilised pH gradient strips) enabling improved resolution of proteins in the first dimension [Bjellqvist et al., 1982; Qorg et al., 1988; Steinberg et al., 2000]; and improved ionisation methods for mass spectrometry, in particular, matrix assisted laser desorption ionisation (MALDI) and electrospray ionisation (ESI). These two techniques enabled rapid and unambiguous identification of subpicomole amounts of the separated protein. As a result, 2DE has become the most widely accepted technique for the· separation and simultaneous visualisation of multiple proteins in complex samples [Klose and Kobalz, 1995; Lopez, 1999]. A variety of different chemical staining techniques have been developed that are able to detect low amounts of protein following their separation by 2DE. The most widely employed stains include Coomassie blue and silver staining, but more recently a variety of fluorescent stains have been developed that reportedly offer greater sensitivity and 112 the ability to detect low nanograms of proteins [Shevchenko et al., 1996; Lopez et al., 2000; Lauber et al., 2001]. Because many hundreds of proteins can be resolved by 2DE and then detected using these stains, relative changes in protein expression can be estimated on a global scale (i.e., alterations in the levels of many different proteins can be monitored simultaneously). For example, changes in protein expression between cells maintained under different conditions, or between normal and disease tissue can be quantified [Kuster et al., 1997; Neubauer and Mann, 1999; Lahm and Langen, 2000; Sickmann et al., 2001]. Prior to the use of mass spectrometry, techniques such as Edman degradation and amino acid analysis were employed to identify proteins separated on gels. The success of these techniques, however, was limited because relatively large quantities of pure proteins were required and even then, post-translational modifications presented a serious obstacle. Developments in mass spectrometry, primarily MALDI-TOFMS and ESI-MS, have overcome these limitations because they allow peptides and proteins to be ionised with high efficiency. Currently, the most widely accepted technique for protein identification following 2DE involves the use ofMALDI-TOFMS to generate a peptide mass fingerprint or mass map of the proteolytically digested protein of interest [James et al., 1993; Mann et al., 1993]. These data are then searched against a database containing the sequences of known proteins digested with the same enzyme in silico. This strategy is versatile and powerful and has also been employed successfully to identify proteins that have been post-translationally modified, e.g., N-terminal acetylation, glycosylation, or phosphorylation [Mills et al., 2001; Sickmann et al., 2001]. 113 Although 2DE remains the preferred approach for the global representation of a proteome, it has shortcomings. These include the inability to adequately resolve low molecular weight and basic proteins, the limited solubility of hydrophobic and high mass proteins, co-migration of proteins, and inadequate sensitivity for low abundant proteins [Patton, 1999]. To overcome these problems alternative strategies have been adopted such as the separation of tryptic peptides by multidimensional liquid chromatography and identification by tandem mass spectrometry [McCormack et al., 1997; Yates et al., 1997; Link et al., 1999; Yates et al., 2000; Davis et al., 2001; Washburn et al., 2001]. Although these approaches are able to identify multiple proteins rapidly, even in complex mixtures, they are not able to easily detect post-translational modifications or to differentiate between multiple forms of the same protein present in vivo. To fully characterise the peptide and protein constituents of biological tissues or fluids requires a comprehensive strategy involving several separation, detection and identification techniques. In this study a combined approach involving gel electrophoresis, MALDI-TOFMS and ESI-LC/MS/MS was used to characterise the peptide and protein constituents of human seminal fluid. Proteins were separated by either 1D or 2D gel electrophoresis prior to identification by ESI-LC/MS/MS and MALDI-TOFMS respectively. The peptide components were also investigated by direct analysis ofunfractionated seminal fluid by MALDI-TOFMS. This approach enables the accurate mass of peptides to be determined, and ESI-LC/MS/MS was employed thereafter to obtain amino acid sequence information for each peptide. 114 4.2. Methods Toe methods employed for this study can be found in Chapter 2 (pages 41 -44). 4.3. Results 4.3.1. Detection and identification of proteins by two dimensional gel electrophoresis Separation of proteins in normal human seminal fluid by 2DE followed by visualisation with silver staining indicated the presence of over 300 discrete protein spots. Figures 4.1 and 4.2 show examples of two annotated silver stained gels of seminal fluid proteins focused over two different pH ranges (pi range 4 - 7 and 6 - 11 respectively). Of the 300 discrete protein spots that were excised and digested, 169 were positively identified by peptide mass fingerprinting and database searching. Of these 169 proteins, only 32 unique proteins were identified. The other proteins were identified as post translational variants of these. Additionally, some proteins were found to co-migrate so that two or more proteins could be identified under a single spot. Some of the proteins identified include serum proteins (e.g., serum albumin, Zn-cx-2-glycoprotein, fibronectin), enzymes and proteins believed to be specific to seminal fluid (e.g., prostate specific antigen, prostate secreted seminal plasma, semenogelin I, semenogelin II}. Listed in Tables 4.1 - 4.4 are the proteins that were identified in each gel, including proteins that were found to co-migrate. 115 Figure 4.1. An annotated silver-stained two dimensional gel of semjnal fluid proteins separated over the pl range 4 - 7. Indicated are the protein spots that were excised, digested with trypsin, and identified by peptide mass fingerprinting. Increasing pi I ? 0 () 5 i 4 e 6 10 12 0 9 0 0 bi 3 0 13 4 15 ~ . 0 0 0 18 19 16 17 0 0 200 bi 8 2:\ 24 25 26 29 3S 31 32 ::::J tJ 68 0 u 0 035 Cl) 3p 3~ 36 36 31b 3% 4(\) 0 0 42 o41 E 't) CJ 96 8 ~8 49 0 0 43 Cl 53 C: 500 ~1°s2 . '54 ·c:;; l'0 55 65 ~ 56 S7 u o o 58 C: sf 6z 0 0 61 82 ~ 0 66 6J 68 64 72 0 78 77 0 0 79 6 88 ~ 0 94 0 104 116 Figure 4.2. An annotated silver-stained two dimensional gels of seminal fl uid proteins separated over the pI range 6 - 11. Indicated are the protein spots that were excised, digested with trypsin, and identified by peptide mass fingerprinting. Increasing pi ') 0 o- 3 0 d ... 5 6. ~ 0 7 10 en , ~ 0 "ai ~- ...== .!2 8 17 :::, = I S (J 0 .S! 01 9 0 ') E en C: 1'i ')6 "iii c::, C'O 28 (I)... 27 (J C: 3 32 :n 35 0 0 36 39 040 38 0 37 c::::> JI. 0 44 4 .'i 42 -g 0 0 47 48 0 11 7 Table 4.1. Proteins in seminal fluid that were identified by 2DE (pi range 4 - 7). Listed below are the identified proteins with their corresponding experimentally determined molecular weight and isoelectric point derived from the gel. EXPT. EXPT. SPOT PROTEIN MOLECULAR ISOELECTRIC # WEIGHT (kDa) POINT cx-1-antitrypsin Accession number: 1703025 19 45 5.7 Theoretical molecular weight: 46.7 kDa Theoretical isoelectric point: 5.3 cx-enolase Accession number: 119339 32 45 7.0 Theoretical molecular weight: 4 7.1 kDa Theoretical isoelectric point: 7 .0 Antioxidant protein 2 74 20 6.4 Accession number: 1718024 Theoretical molecular weight: 24.9 kDa Theoretical isoelectric point: 6.0 75 20 6.5 Carboxypeptidase B Accession number: 115892 94 15 4.0 Theoretical molecular weight: 53.1 kDa Theoretical isoelectric point: 5.0 Cathe~sinB Accession number: 115711 41 40 6.3 Theoretical molecular weight: 37.8 kDa Theoretical isoelectric point: 5.9 34 45 6.4 CathepsinD 37 43 5.2 Accession number: 115717 Theoretical molecular weight: 44.5 kDa 38 43 5.4 Theoretical isoelectric point: 6.1 39 43 5.6 118 EXPT. EXPT. SPOT MOLECULAR ISOELECTRIC PROTEIN # WEIGHT (kDa) POINT 53 40 6.0 Clusterin Accession number: 116533 55 37 5.2 Theoretical molecular weight: 52.5 kDa Theoretical isoelectric point: 5.9 65 35 6.0 Cystatin S 107 10 4.5 Accession number: 399336 Theoretical molecular weight: 16.2 kDa 108 10 4.7 Theoretical isoelectric point: 4.9 8 65 5.7 Fibronectin 13 65 6.2 Accession number: 2506872 Theoretical molecular weight: 262.6 kDa 14 65 6.3 Theoretical isoelectric point: 5.4 15 65 6.4 Glycodelin Accession number: 130701 78 20 5.5 Theoretical molecular weight: 20.6 kDa Theoretical isoelectric point: 5.3 Heat shock 27 kDa protein number: 123571 Accession 72 20 6.2 Theoretical molecular weight: 22.3 kDa Theoretical isoelectric point: 7 .8 Heat shock 70 kDa, protein 1B 4885431 Accession number: 7 65 5.5 Theoretical molecular weight: 70.0 kDa Theoretical isoelectric point: 5.5 1 70 6.5 4 70 6.7 Lactotransferrin Accession number: 6175096 5 70 7.0 Theoretical molecular weight: 78.3 kDa Theoretical isoelectric point: 8.5 33 43 6.3 35 43 6.5 119 EXPT. EXPT. SPOT MOLECULAR ISOELECTRIC PROTEIN # WEIGHT (kDa) POINT Isocitrate dehydrogenase (NADP+ - dependant) Accession number: 1352423 36 43 6.7 Theoretical molecular weight: 46.6 kDa Theoretical isoelectric point: 6.3 Proapolipoprotein A-I Accession number: 113992 77 20 5.3 Theoretical molecular weight: 30.7 kDa Theoretical isoelectric point: 5.5 96 13 5.1 104 13 4.5 105 13 4.6 Prolactin-inducible protein 106 13 4.6 Accession number: 134170 109 10 4.9 Theoretical molecular weight: 16.5 kDa 110 13 5.0 Theoretical isoelectric point: 8.2 111 13 5.1 113 13 5.4 115 13 5.5 Prostate secreted seminal plasma protein Accession number: 131436 116 10 5.5 Theoretical molecular weight: 12.8 kDa Theoretical isoelectric point: 5.3 54 35 6.4 67 25 6.4 68 25 6.7 71 23 6.8 Prostate specific antigen 74 20 6.4 Accession number: 130989 79 17 6.0 Theoretical molecular weight: 28.7 kDa 80 17 6.2 Theoretical isoelectric point: 7 .6 81 17 6.4 87 17 5.8 91 15 6.7 99 13 6.2 120 EXPT. EXPT. SPOT PROTEIN MOLECULAR ISOELECTRIC # WEIGHT (kDa) POINT Prostate transglutaminase Accession number: 3915892 83 17 6.4 Theoretical molecular weight: 77 .1 kDa Theoretical isoelectric point: 6.3 18 45 5.6 20 45 5.0 21 45 5.1 22 45 5.2 23 45 5.3 24 45 5.4 25 45 5.5 26 45 5.6 27 45 5.7 Prostatic acid phosphatase Accession number: 130730 28 45 5.8 Theoretical molecular weight: 44.5 kDa 29 45 6.0 Theoretical isoelectric point: 5.8 56 35 5.1 57 33 5.2 58 30 5.3 59 35 5.0 60 33 5.1 61 30 5.2 62 30 5.5 101 13 6.7 102 13 6.7 Protein tyrosine phosphatase, receptor type, cr Accession number: 14765223 Theoretical molecular weight: 217 .1 kDa 76 20 6.3 Theoretical isoelectric point: 6.0 121 EXPT. EXPT. SPOT PROTEIN MOLECULAR ISOELECTRIC # WEIGHT (kDa) POINT 84 17 6.7 85 17 6.7 88 17 5.8 89 15 6.6 90 15 6.6 92 15 6.8 Semenogelin I 93 15 6.9 Accession number: 134426 Theoretical molecular weight: 52.1 kDa 100 13 6.3 Theoretical isoelectric point: 9 .3 114 13 5.4 117 10 5.6 118 10 5.6 119 10 5.6 120 13 5.8 121 10 5.9 95 13 5.0 Semenogelin II 97 13 5.5 Accession number: 401079 98 13 5.8 Theoretical molecular weight: 65.5 kDa 112 13 5.2 Theoretical isoelectric point: 9.0 114 13 5.4 Serotransferrin 2 70 6.6 Accession number: 136191 Theoretical molecular weight: 77 .0 kDa 6.7 Theoretical isoelectric point: 6.8 3 70 44 40 5.0 Zn-a-2-glycoprotein 45 40 5.1 Accession number: 141596 46 40 5.2 Theoretical molecular weight: 33.9 kDa 50 40 5.2 Theoretical isoelectric point: 5.6 55 37 5.2 122 EXPT. EXPT. SPOT PROTEIN MOLECULAR ISOELECTRIC # WEIGHT (kDaJ POINT 9 65 5.8 10 65 5.8 11 65 5.9 12 65 6.0 16 60 6.1 17 60 6.3 30 45 6.3 31 45 6.4 40 43 5.8 42 40 5.6 43 40 5.7 47 40 5.3 Serum albumin Accession number: 113576 48 40 5.4 Theoretical molecular weight: 69.3 kDa 49 40 5.5 Theoretical isoelectric point: 5.9 51 37 5.3 52 37 5.4 53 40 6.0 62 30 5.5 63 25 5.6 64 25 5.6 66 25 6.0 69 23 6.4 70 23 6.6 73 20 6.3 86 15 5.4 103 10 7.0 123 Table 4.2. Proteins in seminal fluid that were identified by 2DE (pi range 4 - 7). These proteins were found to comigrate. EXPT. EXPT. SPOT PROTEIN MOLECULAR ISO ELECTRIC # WEIGHT (kDa) POINT Serum albumin Accession number: 113576 Theoretical molecular weight: 69 .3 kDa Theoretical isoelectric point: 5.9 53 40 6.0 Clusterin Accession number: 116533 Theoretical molecular weight: 52.5 kDa Theoretical isoelectric point: 5.9 Clusterin Accession number: 116533 Theoretical molecular weight: 52.5 kDa Theoretical isoelectric point: 5.9 55 37 5.2 Zn-Cl-2-glycoprotein Accession number: 141596 Theoretical molecular weight: 33.9 kDa Theoretical isoelectric point: 5.6 Prostatic acid phosphatase Accession number: 130730 Theoretical molecular weight: 44.5 kDa Theoretical isoelectric point: 5.8 62 30 5.5 Serum albumin Accession number: 113576 Theoretical molecular weight: 69.3 kDa Theoretical isoelectric point: 5.9 124 EXP'f. EXP'f. SPOT MOLECULAR ISO ELECTRIC PROTEIN # WEIGHT (kDa) POINT Antioxidant protein 2 Accession number: 1718024 Theoretical molecular weight: 24.9 kDa Theoretical isoelectric point: 6.0 74 20 6.4 Prostate specific antigen Accession number: 130989 Theoretical molecular weight: 28.7 kDa Theoretical isoelectric point: 7 .6 Semenogelin I Accession number: 134426 Theoretical molecular weight: 52.1 kDa Theoretical isoelectric point: 9 .3 114 13 5.4 Semenogelin II Accession number: 401079 Theoretical molecular weight: 65.5 kDa Theoretical isoelectric point: 9.0 125 Table 4.3. Proteins in seminal fluid that were identified by 2DE (pi range 6 - 11 ). Listed below are the identified proteins with their corresponding experimentally determined molecular weight and isoelectric point derived from the gel. EXYr. EXYr. SPOT PROTEIN MOLECULAR ISOELECTRIC # WEIGHT (kDa) POINT a-1-antichymotrypsin Accession number: 112874 42 18 6.0 Theoretical molecular weight: 47.6 kDa Theoretical isoelectric point: 5.3 a-1-antitrypsin 10 45 9.0 Accession number: 1703025 Theoretical molecular weight: 46.7 kDa 48 Theoretical isoelectric point: 5.3 10 7.5 Clusterin Accession number: 116533 12 36 6.4 Theoretical molecular weight: 52.5 kDa Theoretical isoelectric point: 5.9 Fibronectin 18 35 9.3 Accession number: 2506872 Theoretical molecular weight: 262.6 kDa 19 35 9.5 Theoretical isoelectric point: 5.4 Glyceraldehyde 3-phosphate dehydrogenase Accession number: 14761208 17 36 8.8 Theoretical molecular weight: 36.0 kDa Theoretical isoelectric point: 8.5 1 78 7.4 2 70 7.4 Lactotransferrin 3 60 7.0 Accession number: 6175096 4 55 7.7 Theoretical molecular weight: 78.3 kDa Theoretical isoelectric point: 8.5 8 41 6.4 15 36 7.7 16 36 8.5 126 EXPT. EXPT. SPOT MOLECULAR ISOELECTRIC PROTEIN # WEIGHT (kDa) POINT Isocitrate dehydrogenase (NADP+ -dependant) 5 45 6.5 Accession number: 1352423 Theoretical molecular weight: 46.6 kDa Theoretical isoelectric point: 6.3 6 45 7.0 Phosphoglycerate kinase Accession number: 129904 7 45 8.5 Theoretical molecular weight: 44.8 kDa Theoretical isoelectric point: 8.8 11 36 6.3 Prostatic acid phosphatase 13 36 6.4 Accession number: 130730 Theoretical molecular weight: 44.5 kDa 14 36 6.5 Theoretical isoelectric point: 5.8 41 20 6.0 20 30 7.0 21 29 6.4 22 29 6.5 23 29 7.5 Prostate specific antigen Accession number: 130989 24 27 6.5 Theoretical molecular weight: 28.7 kDa 29 25 6.4 Theoretical isoelectric point: 7.6 30 25 6.4 31 25 6.3 32 23 6.5 39 20 6.7 37 20 10.5 Semenogelin I 38 20 11.0 Accession number: 134426 Theoretical molecular weight: 52.1 kDa 45 18 8.3 Theoretical isoelectric point: 9.3 47 15 8.5 127 EXPT. EXPT. SPOT PROTEIN MOLECULAR ISOELECTRIC # WEIGHT (kDa) POINT 33 23 7.8 34 23 8.5 35 23 10.5 36 20 10.5 Semenogelin II 7.5 Accession number: 401079 40 20 Theoretical molecular weight: 65.5 kDa 43 17 6.4 Theoretical isoelectric point: 9.0 44 17 7.8 46 15 10.5 47 15 8.5 48 10 7.5 Serum albumin 25 27 7.0 Accession number: 113576 26 27 7.3 Theoretical molecular weight: 69 .3 kDa Theoretical isoelectric'point: 5.9 28 27 7.3 Sorbitol dehydrogenase Accession number: 4033691 9 38 8.5 Theoretical molecular weight: 38.3 kDa Theoretical isoelectric point: 8.2 Triosephosphate isomerase Accession number: 136060 27 27 7.0 Theoretical molecular weight: 26. 7 kDa Theoretical isoelectric point: 6.5 128 Table 4.4. Proteins in seminal fluid that were identified by 2DE (pi range 6 - 11 ). These proteins were found to comigrate. EXPT. EXPT. SPOT PROTEIN MOLECULAR ISO ELECTRIC # WEIGHT (kDa) POINT Phosphoglycerate kinase Accession number: 129904 Theoretical molecular weight: 44.8 kDa Theoretical isoelectric point: 8.8 7 45 8.5 Plasma serine protease inhibitor Accession number: 400068 Theoretical molecular weight: 45.7 kDa Theoretical isoelectric point: 9.3 Semenogelin I Accession number: 134426 Theoretical molecular weight: 52.1 kDa Theoretical isoelectric point: 9 .3 47 15 8.5 Semenogelin II Accession number: 401079 Theoretical molecular weight: 65.5 kDa Theoretical isoelectric point: 9.0 a.-1-antitrypsin Accession number: 1703025 Theoretical molecular weight: 46.7 kDa Theoretical isoelectric point: 5.3 48 10 7.5 Semenogelin II Accession number: 401079 Theoretical molecular weight: 65.5 kDa Theoretical isoelectric point: 9.0 129 4.3.2. Detection and identification of proteins by one dimensional gel electrophoresis To identify proteins not detected by the 2DE approach, such as high molecular weight and hydrophobic proteins, seminal fluid proteins were also separated by one dimensional gel electrophoresis according to their molecular weight. Specific regions of the gel were excised and digested in-gel with trypsin. The resulting tryptic peptides were analysed by ESI-LC/MS/MS and identified by database searching. Figure 4.3 shows the base peak chromatogram for peptides derived from proteins in four different molecular weight regions of the ID gel (i.e., regions corresponding to the molecular weight ranges of 20, 40, 50 and 60 kDa). Peptides derived from multiple proteins (10- 15) were identified in each gel region. In comparison to 2DE, many more proteins (95) were identified by this approach. Proteins found included plasma proteins, enzymes, and proteins believed to be specific to either the seminal vesicle or prostate gland. The majority of the proteins previously detected and identified by 2DE and peptide mass fingerprinting were also identified. Some of the proteins identified, such as serum albumin, fibronectin, semenogelin I and semenogelin II were identified in more than one molecular weight region of the gel indicating that these proteins are present in at least two distinct forms. These proteins were also identified in multiple forms by 2DE. Table 4.5 (p 132) lists those proteins identified by this technique and includes their theoretical and experimentally determined molecular weight. 130 131 kDa 20 - kDa 40 - kDa 07 _ 93 50 1,.,,..,,_\.-, .. .._ . kDa _,_ - 24 ...... 97 ~ 94 - 60 83 proteins. · "' ,,,. - ._ -_.., . . .I\. 39 95 . .... 002 l fluid 81 92 . 09 . ,,, 0 ,1 100 I a 1 73 . ·t I I ·I\ ,11 11 . 1 min I · _ ij I I 42 se 5 _ 8 74 06 90 . 8 of 81 ~ . ' 83 l I ' I 62.31 71 ge -!l~Qey 1 70 67 43 " 80 55 95 89 ~··" . , , 15 , 73 •. 52 .- ' ) .. 62 . 51 ,,,.,.," 85 ,1,1 ... 5640 73 'L1,}j1li.1~1,1-~.,."'<·I· k ,. II 1 1 , 42 ,, . · 70 , SDS-PAGE I 08 J j u I I s922 56 .. 42.25 ! 1 o1 iii 63 1 ,,11,~j\ · j\/~,l.\ 1D \ 84 1 I \ ~a 44 57 55r1 . ll 41 3830 ! I ~ t 42 438t 62 . the i, 50 60 I ,i 48 I \ • 33 of 95 :,,,.1.l\ 84 '" , I : , 91 4122 59 1, :. 11 l 5 , 21 28 ' r .I I ,. ll 36 " 44 77 L (min) 50 M ~ [ 25 42 ~ ,. regions : __ 34 34 98 95 .J. 53 11\i)ll,,, Time . 32 nt 23 _ 80 ...... _..,,~ 22 lli~-•,.,. : · 38 35 38 i· 40 1 ffere 98 04 . · 59 14 1 37 32 di ½ 34 j 29 IIL;,;;.: 1 l 34 82 15~3 1 4 im 8 98 26.89 30 for 65 7 31 30 35 93 25.97 6 25 .,_l!.,,1,,, 11 02 ,'. 31 ·-,. "1 97 _... , 5.80 15 ,., 20 ,L ...... .. ~ . 1487 • chromatogram ~077 I 95 ll 11(\ii~l_i;) 1 .,, 13 10 ak 10 e p 07 ase j ., 0 B 0 9 10 90 30 80 70 60 40 50 20 100 a, ~ > C ni 3 ~ "C ~ cc 4.3. Figure Table 4.5. Proteins found in seminal fluid following separation by ID gel electrophoresis, in gel digestion and ESI-LC/MS/MS analysis. Also listed are the theoretical and experimentally determined molecular weights for each protein. THEORETICAL EXPT. PROTEIN MOLECULAR MOLECULAR WEIGHT (kDa) WEIGHT (kDa) Acidic epididymal glycoprotein-like 1 28.4 85 Accession number: 4501983 cx.-enolase 47.1 50 Accession number: 119339 cx.-1-acid glycoprotein 1 23.4 50 Accession number: 9257232 46.6 43 I -antitrypsin ex.- 46.6 60 Accession number: 1703025 46.6 50 Arachidonate 12-lipoxygenase, 12R type 80.3 < 10 Accession number: 12230234 ~-2-microglobulin 13.7 60 Accession number: 114773 Bactericidal permeability increasing protein 19.3 20 Accession number: 2822120 Calcineurin binding protein I 246.3 < 10 Accession number: 6912458 Carbonic anhydrase 39.4 50 Accession number: 4502515 Carboxypeptidase D 152.4 < 10 Accession number: 4503007 Cathepsin C 51.8 20 Accession number: 4503141 Cathepsin F 53.3 20 Accession number: 6042196 132 THEORETICAL EXPT. PROTEIN MOLECULAR MOLECULAR WEIGHT (kDa) WEIGHT (kDa) Cathepsin G 28.8 40 Accession number: 4503149 Ceruloplasmin 122.2 60 Accession number: 4557485 52.5 85 Clusterin Accession number: 4502905 52.5 50 52.5 40 192.4 85 Complement C4A Accessionnumber: 14577919 192.4 20 Complement component C5 188.2 60 Accession number: 4502507 Complement component C9 63.1 20 Accession number: 4502511 Complement factor B 85.4 220 Accession number: 4502397 Corticotropin releasing factor-binding protein 36.1 10 Accession number: 544099 CYR61 protein 42.0 20 Accession number: 13638596 Epididymal secretory protein E3 alpha 14.9 85 Accession number: 7227896 262.6 220 Fibronectin Accession number: 2506872 262.6 85 Fibroblast growth factor receptor 2 92.0 60 Accession number: 4503709 Galectin 3 binding protein 65.3 60 Accession number: 5031863 yEnolase 47.3 50 Accession number: 5803011 133 THEORETICAL EXPT. PROTEIN MOLECULAR MOLECULAR WEIGHT (kDa) WEIGHT (kDa) Gastricin (pepsinogen C) 42.4 40 Accession number: 4505757 Gastrin-releasing peptide 16.1 20 Accession number: 4504159 Glucose phosphate isomerase 63.2 50 Accession number: 4504087 Glutathione S-transferase A2 25.7 20 Accession number: 121733 Glutathione S-transferase mu 1 25.7 20 Accession number: 11428198 Glutathione S-transferase p 1-1 25.7 < 10 Accession number: 2981694 Glyceraldehyde 3-phosphate dehydrogenase 36.0 40 Accession number: 7669492 Glycerol kinase, testes specific 60.5 85 Accession number: 12230075 Glycodelin 20.6 50 Accession number: 13639329 Growth/differentiation factor 15 34.1 20 Accessionnumber: 13124261 Heat shock 20 kDa like protein 22.4 20 Accession number: 6016272 Heat shock 60 kDa protein, mitochondrial 61.1 85 Accession number: 129379 Heat shock 70 kDa protein-like-I 70.4 85 Accession number: 5031769 Heat shock protein (HSPl 10 family) 94.5 85 Accession number: 7656894 Heat shock protein 105 kDa 96.8 50 Accession number: 2495344 HistoneHlA 22.1 20 Acccession number: 121916 134 THEORETICAL EXP'f. PROTEIN MOLECULAR MOLECULAR WEIGHT (kDa) WEIGHT (kDa) Histone HIB 21.8 60 Accession number: 121919 HistoneHID 21.3 50 Accession number: 417101 Histone H2A family 14.0 40 Accession number: 121968 Accession number: 121959 Accession number: 12585257 14.0 50 Accession number: 12585251 Accession number: 12643341 Accession number: 121986 14.0 60 Accession number: 121971 Accession number: 121970 Histone H2B family 14.0 25 Accession number: 122055 Accession number: 7387743 14.0 40 Accession number: 7387741 Accession number: 7387742 Accession number: 462236 14.0 50 Accession number: 7387739 Accession number: 7387740 14.0 60 Accession number: 122026 Accession number: 7387736 Accession number: 7404367 14.0 85 Accession number: 9973351 hSMP-1 (sperm membrane protein) 55.1 85 Accession number: 1836035 lg alpha-I chain C region 37.6 60 Accession number: 113584 Inhibin alpha chain 39.7 25 Accession number: 4504697 Inhibin beta A chain 47.4 60 Accession number: 4504699 Inhibin beta B chain 45.1 40 Accession number: 1708437 Insulin-like growth factor binding protein 2 35.1 60 Accession number: 124058 Interleukin 4 17.5 20 Accession number: 4504669 135 THEORETICAL EXPT. PROTEIN MOLECULAR MOLECULAR WEIGHT (kDa) WEIGHT (kDa) 1-plastin 70.3 10 Accession number: 4505897 Isocitrate dehydrogenase 1 (NADP+) soluble 46.7 25 Accession number: 51744 71 Kallikrein 14 27.4 < 10 Accession number: 11545747 Kallistatin 48.6 25 Accession number: 5453888 Keratinocyte growth factor (FGF-7) 22.4 < 10 Accession number: 4503705 Kinesin heavy chain 109.7 220 Accession number: 4758648 76.3 25 Lactotransferrin Accession number: 6175096 76.3 85 Major sperm fibrous sheath protein 93.5 50 Accession number: 3777541 Malate dehydrogenase, mitochondrial 35.5 85 Accession number: 5174541 Myeloperoxidase 83.8 85 Accession number: 4557759 Neutrophil cytosol factor 4 39.0 20 Accession number: 4505345 Nitric oxide synthase, inducible 131.1 25 Accession number: 1352513 Nucleobindin 2 50.2 50 Accession number: 4826870 Peroxiredoxin 2 21.9 85 Accession number: 5902726 Phosphatidylserine-specific phospholipase Al-a. 49.7 50 Accession number: 7706661 136 THEORETICAL EXPT. PROTEIN MOLECULAR MOLECULAR WEIGHT (kDa) WEIGHT (kDa) Phosphoglycerate kinase, testes specific 44.8 < 10 Accession number: 129904 Plasma serine protease inhibitor 45.6 50 Accession number: 400068 Plasminogen activator, tissue type 62.9 220 Accession number: Proactivator polypeptide (prosaposin) 58.1 60 Accession number: 11386147 Prolactin-inducible protein 16.6 10 Accession number: 4505821 16.6 25 68.7 85 Prostagladin G/H synthase 1 68.7 60 Accession number: 11386141 68.7 20 Prostate secreted seminal plasma protein 12.8 20 Accession number: 45570623 Prostate specific antigen 28.6 60 Accession number: 4758398 Prostatic acid phosphatase 44.6 70 Accession number: 6382064 44.6 50 Protein-glutamine gamma-glutamyltransferase 77.2 60 Accession number: 4759228 Putative peroxisomal antioxidant enzyme 16.9 85 Accession number: 3915613 52.1 220 52.1 60 52.1 50 Semenogelin I 52.1 40 Accession number: 4506883 52.1 < 10 52.1 10 52.1 25 52.1 20 137 THEORETICAL EXPT. PROTEIN MOLECULAR MOLECULAR WEIGHT (kDa) WEIGHT (kDa) 65.4 220 65.4 60 65.4 50 Semenogelin II 65.4 40 Accession number: 4506885 65.4 10 65.4 20 65.4 < 10 65.4 25 Serine hydroxymethyltransferase, mitochondrial 56.0 220 Accession number: 6226865 76.9 10 Serotransferrin Accession number: 4557871 76.9 85 69.4 10 69.4 < 10 Serum albumin 69.4 220 Accession number: 4557519 69.4 60 69.4 85 13.1 85 Sperm histone P2 (protamine) Accession number: 123700 13.1 40 Sperm membrane protein BS-63 198.7 220 Accession number: 5809678 Tektin 2 49.7 60 Accession number: 7657643 Testis-specific bromodomain protein 107.8 220 Accession number: 4502453 50.7 20 Thymopoietin, isoforms beta/gamma Accession number: 1174690 50.7 < 10 138 THEORETICAL EXP'f. PROTEIN MOLECULAR MOLECULAR WEIGHT (kDa) WEIGHT (kDa) 46.3 40 Thyroxine-binding globulin ( clade A) Accession number: 11422666 46.3 60 Transforming growth factor-~ induced protein IG-H3 74.7 50 Accession number: 4507467 Triosephosphate isomerase 26.7 20 Accession number: 4507645 Ubiquitin 8.6 220 Accession number: 4507761 Uromodulin 69.7 50 Accession number: 137116 Vascular endothelial growth factor 46.8 85 Accession number: 4558049 Vitamin K-dependant protein S 75.1 60 Accession number: 131086 Zn-a.-2-glycoprotein 33.9 40 Accession number: 141596 139 This technique also identified the presence of histones in seminal fluid, in particular the histone 2A and 2B family of proteins. Multiple peptides from each of these proteins were detected, corresponding to 44% and 26% sequence coverage of the proteins in the histone 2A and 2B families respectively. Because proteins in each of these families share greater than 95% sequence homology, analysis by ESI-LC/MS/MS was not able to distinguish between the different histone proteins present, i.e., a unique tryptic peptide fragment for each of these proteins was not detected by ESI-LC/MS/MS. The amino acid sequence for the proteins in the histone 2A and histone 2B families, and the tryptic peptides from each that were detected and identified, are shown in Figures 4.4 and 4.5 respectively.· 140 Figure 4.4. The amino acid sequences of the histone 2A family of proteins and the tryptic peptides that were detected (underlined) by ESI-LC/MS/MS. Each protein in the histone 2A family consists of 130 amino acids, with the exception of H2A.E and H2A.X (128 and 143 amino acids respectively). Highlighted are the unique sequences within each protein. The tryptic peptides detected are underlined. 141 Figure 4.4. The amino acid sequences of proteins in the histone 2A family. The tryptic peptides detected by ESI-LC/MS/MS are indicated (underlined). HISTONE PROTEIN SEQUENCE H2A.A MSGRGKQGGKARAKAKTRSSRAGLQFPVGRVHRLLRKGNYSERVGAGAPV H2A.C / D/I/N/P MSGRGKQGGKARAKAKTRSSRAGLQFPVGRVHRLLRKGNYAERVGAGAPV H2A .E MSGRGKQGGKARAKAKTRSSRAGLQFPVGRVHRLLRKGNYAERVGAGAPV H2A.G MSGRGKQGGKARAKAKTRSSRAGLQFPVGRVHRLLRKGNYSERVGAGAPV H2A.L MSGRGKQGGKARAKAKSRSSRAGLQFPVGRVHRLLRKGNYAERVGAGAPV H2A . M MSGRGKQGGKARAKAKTRSSRAGLQFPVGRVHRLLRKAHYSERVGAGAPV H2A.0 MSGRGKQGGKARAKAKSRSSRAGLQFPVGRVHRLLRKGNYAERVGAGAPV H2A.X MSGRGKTGGKARAKAKSRSSRAGLQFPVGRVHRLLRKGHYAERVGAGAPV H2A.A YLAAVLEYLTAEILELAGNAARDNKKTRIIPRHLQLAIRNDEELNKLLGR H2A.C / D/I/N/P YLAAVLEYLTAEILELAGNAARDNKKTRIIPRHLQLAIRNDEELNKLLGK H2A.E YLAAVLEYLTAEI LELAGNAARDNKKTRIIPRHLQLAIRNDEELNKLLGK H2A . G YLAAVLEYLTAEILELAGNAARDNKKTRIIPRHLQLAIRNDEELNKLLGK H2A.L YLAAVLEYLTAEILELAGNAARDNKKTRII PRHLQLAIRNDEELNKLLGK H2A.M YLAAVLEYLTAEILELAGNAARDNKKTRIIPRHLQLAI RNDEELNKLLGR H2A.0 YMAAVLEYLTAEILELAGNAARDNKKTRIIPRHLQLAIRNDEELNKLLGK H2A.X YLAAVLEYLTAEILELAGNAARDNKKTRIIPRHLQLAIRNDEELNKLLGG H2A.A VTIAQGGVLPNIQAVLLPKKTESHHKAKGK H2A.C / D/I/N/P VTIAQGGVLPNIQAVLLPKKTESHHKAKGK H2A . E VTIAQGGVLPNIQAVLLPKKTESHHKTK H2A.G VTIAQGGVLPNIQAVLLPKKTESHHKAKGK H2A.L VTIAQGGVLPNIQAVLLPKKTESHHKAKGK H2A.M VTIAQGGVLPNIQAVLLPKKTESHHKAKGK H2A. 0 VTIAQGGVLPNIQAVLLPKKTESHHKAKGK H2A. X VTIAQGGVLPNIQAVLLPKKTSATVGPKAPSGGKKATQASQEY 142 Figure 4.5. The amino acid sequences of the histone 2B family of proteins and the tryptic peptides that were detected (underlined) by ESI-LC/MS/MS. Each protein in the histone 2B family consists of 126 amino acids and shares greater than 95% sequence homology. Highlighted are the unique sequences within each protein. The tryptic peptides that were detected are underlined. 143 Figure 4.5. The amino acid sequences of the histone 2B family of proteins and the tryptic peptides that were detected (underlined) by ESI-LC/MS/MS. HISTONE PROTEIN SEQUENCE H2B.A/G/K MPEPAKSAPAPKKGSKKAVTKAQKKDGKKRKRSRKESYSVYVYKVLKQVH H2B.C MPELAKSAPAPKKGSKKAVTKAQKKDGKKRKRSRKESYSVYVYKVLKQVH B2B.D MPEPSKSAPAPKKGSKKAVTKAQKKDGKJCRKRSRKESYSVYVYKVLKQVH B2B.B MPEPVKSAPVPKKGSKKAINKAQKKDGKKRKRSRKESYSVYVYKVLKQVH B2B.P MPEPSKSAPAPKKGSKKAITKAQKKDGKKRKRSRKESYSZYVYKVLKQVH B2B.J MPDPAKSAPAPKKGSKKAVTKAQKKDGKKRKRSRKESYSVYVYKVLKQVH H2B.L MPBPSKSAPAPKKGSKKAVTKAQKKDGKKRKRTRKESYSVYVYKVLKQVH B2B.N MPDPAKSAPAPKKGSKKAVTKAQKKDGKERKRSRKESYSZYVYKVLKQVH B2B.Q MPEPAKSAPAPKKGSKKAVTKAQKKDGKKRKRSRKESYSZYVYKVLKQVH B2B.R MPEPAKSAPAPKKGSKKAVTKAQKKDGKKRKRSRKESYSZYVYKVLKQVH B2B.S MPEPAKSAPAPKKGSKKAVTKAQKKDGRKRKRSRKESYSVYVYKVLKQVH B2B.A/G/K PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR H2B.C PDTGISSKAMGIMNSFVNDIFERIASEASRLAHYNKRSTITSREIQTAVR B2B.D PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR H2B.B PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR H2B.P PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR B2B.J PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR H2B.L PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR H2B.N PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR H2B.Q PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR H2B.R PDTGISSKAMGIMNSFVNDIFERIAGEASRLAHYNKRSTITSREIQTAVR H2B.S PDTGISSKAMGIMNSFVNDIFERIAGEASRLPHYNKRSTITSREIQTAVR B2B.A/G/K LLLPGELAKHAVSEGTKAVTKYTSSK H2B.C LLLPGELAKHAVSEGTKAVTKYTSSK B2B.D LLLPGELAKHAVSEGTKAVTKYTSSK B2B.B LLLPGELAKHAVSEGTKAVTKYTSSK H2B.P LLLPGELAKHAVSEGTKAVTKYTSSK B2B.J LLLPGELAKHAVSEGTKAVTKYTSSK B2B.L LLLPGELAKHAVSEGTKAVTKYTSSK B2B.N LLLPGELAKHAVSEGTKAVTKYTSSK H2B.Q LLLPGELAKHAVSEGTKAVTKYTSSK B2B.R LLLPGELAKHAVSEGTKAVTKYTSAK H2B.S LLLPGELAKHAVSEGTKAVTKYTSAK 144 4.3.3. Direct analysis of seminal fluid by MALDI-TOFMS and ESI-MS Direct analysis ofunfractionated seminal fluid by MALDI-TOFMS revealed the presence of numerous components in the mass range 500 - 10,000 Da. Due to the signal suppression effects of the MALDI ionisation process, components greater than 10,000 Da were not detected. Because MALDI-TOFMS only provides the accurate molecular weight of molecules, capillary ESI-LC/MS/MS was employed to identify these peptides. Shown in Figure 4.6 is the MALDI mass spectrum (linear mode) of the peptide components of seminal fluid. The majority of the peptides detected by MALDI-TOFMS and subsequently identified by ESI-LC/MS/MS are proteolytic peptides derived from either semenogelin I or semenogelin II. (These peptides are listed in Table 4.6, p 148.) Seminal basic protein ([M+Ht 5,757.65 Da), an endogenous bioactive peptide derived from semenogelin I, was also detected [Robert and Gagnon, 1999]. Analysis of the peptides in seminal fluid by ESI-LC/MS/MS and database searching identified 50 peptides. Of these, 35 peptides were derived from either semenogelin I or semenogelin II. Figures 4. 7 (p 149) and 4.8 (p 150) show the amino acid sequence of semenogelin I and II respectively, and the peptides that were identified and that are derived from each protein. Also detected were peptides derived from seminal fluid proteins that had previously been identified following separation by either 1D- or 2D- gel electrophoresis. The peptides that were identified by ESI-LC/MS/MS and database searching are listed in Table 4.7 (pl51). 145 Figure 4.6. A MALDI mass spectrum ofunfractionated seminal fluid. An aliquot (0.2 µL) of diluted human seminal fluid (1:10) was analysed by MALDI TOFMS (with a.-cyano-4-hydroxycinnamic acid as the MALDI matrix). When analysed in the linear mode, numerous peptides below 10,000 Da were detected. Indicated are those peptides that were identified by ESI-LC/MS/MS as proteolytic peptides derived from either semenogelin I or semenogelin II. (See Table 4.6, p 148.) 146 147 147 3000 3000 7300 7300 S1E,S2D S1E,S2D 7000.60 7000.60 2769.39 2769.39 2560 2560 6440 6440 6271.36 6271.36 i i 5809.64 5809.64 ! ! Da Da protein protein 2120 2120 \ \ 5560 5560 5754.65 5754.65 basic basic 928.88 928.88 [M+Ht [M+Ht Seminal Seminal Mass(m/z) Mass(m/z) fluid. fluid. 692.74 692.74 , , 1680 1680 4m 4m 1 s seminal seminal S1B S1B ~~~~~~""'"~,M~..,._,Jt,JWJ,lw,,i).~~,.,!Jl,;.l,~~.Ji.J...... ,-~~ ~~~~~~""'"~,M~..,._,Jt,JWJ,lw,,i).~~,.,!Jl,;.l,~~.Ji.J...... ,-~~ 1 1460.74 1460.74 S1H S1H 37 37 . 4140 I I 1 S1A S1A 129910 129910 I I ofunfractionated ofunfractionated 3890.94 3890.94 . . 5.51 5.51 ,1226,65 ,1226,65 3810.46 3810.46 ~o ~o 118•. 118•. 1240 1240 tl7!4 tl7!4 ~••llllt.l""'-' spectrum spectrum S1G S1G 1010.55 1010.55 mass mass r r 32!0.78 32!0.78 j 310< 310< ,~.w~u~u-~ ,~.w~u~u-~ S1F,S2E S1F,S2E MALDI MALDI A A ~ ~ oJ""""'""''·J.~- 0 100 100 100 100 4.6. 4.6. ~ ~ ~ ~ ~ ~ a: a: "ii "ii i i e... e... ! ! - Figure Figure Table 4.6. Peptides that were detected by MALDI-TOFMS in unfractionated seminal fluid (see Figure 4.6, p 147) and subsequently identified by ESI-LC/MS/MS. EXPT.MASS PEPTIDE PROTEIN [M+Ht FRAGMENT SIA Semenogelin I 1,404.38 361-373 SIB Semenogelin I 1,640.40 222-235 SIC Semenogelin I 2,446.54 80-107 SID Semenogelin I 2,481.87 195 -215 SlE Semenogelin I 2,893.95 428-453 SlF Semenogelin I 3,083.53 81-107 SlG Semenogelin I 3,211.02 195 -221 SlH Semenogelin I 4,309.32 390-427 Sll Semenogelin I 4,623.85 68-107 S2A Semenogelin II 1,591.71 86-99 S2B Semenogelin II 2,307.80 68 - 85 S2C Semenogelin II 2,509.96 195 -215 S2D Semenogelin II 2,893.95 481-507 S2E Semenogelin II 3,083.53 248-273 S2F Semenogelin II 4,469.78 236-273 148 Figure 4.7. The amino acid sequence of semenogelin I showing those peptides identified by ESI-LC/MS/MS. Highlighted in red is the portion of the protein that corresponds to seminal basic protein (residues 108 - 159). MKPNIIFVLSLLLILEKQAAVMGQKGGSKGRLPSEFSQFPHGQKGQHYSGQKGKQQTESK GSFSIQYTYHVDANDHDQSRKSQQYDLNALHKTTKSORHLGGS OOLLHNKQEGRDHDKSK 68 ______107 81 07 86~------,07 GHFHRVVIHHKGGKAHRGTQNPSQDQGNSPSGKGISSQY160.,__SNTEERLWVHGLSKEQTSVSG______160------160 ------161 f&.KGRKQGGSQSSYVLQTEELVAN-KQQRETKNSHQNKGHYQNVVEVREEHSSKVOTSLCP 182 192 215 222 235 --183 193 215 185 - 182 AHQDKLQHGSKDIFSTODELLVYNKNQHQTKNLNQDQQHGRKANKISYQSSSTEERRLHY 248 ______273 253 273 GENGVQKDVSQSSIYSQTEEKAQGKSQKQITIPSQEQEHSQKANKISYQSSSTEERRLHY GENGVOKDVSORSIYSOTEKLVAGKSOI OAPNPKOEPWHGENAKGESGOSTNREQDLLSH 361 ---- 373 376 409 362 368 376 410 376 381 390 EQKGRHQHGSHGGLDIVIIEOEDDSDRHLAOHLNNDRNPLFT 428 453 428 462 427 ----427 427 149 Figure 4.8. The amino acid sequence of sernenogelin II showing those peptides identified by ESI-LC/MS/MS. MKSIILFVLSLLLILEKQAAVMGQKGGSKGQLPSGSSQFPHGQKGQHYFGQKDQQHTKSK GSFSIQHTYHVDINDHDWTRKSOOYDLNALHKATKSKQHLGGSQQLLNYKQEGRDHDKSK . ~ • w 70 86______99 GHFHMIVIHHKGGQAHHGTQNPSQDQGNSPSGKGLSSQCSNTEKRLWVHGLSKEQASASG AQKGRTQGGSQSSYVLOTEELVVNKOORETKNSHONKGHYQNVVDVREEHSSKLQTSLHP 192 215 22 229 23 194 215 AHODRLOHGPKDIFTTODELLVYNKNOHOTKNLSQDQEHGRKAHKISYPSSRTEERQLHH 273 253 273 GEKSVQKDVSKGSISIQTEEKIHGKSQNQVTIHSQDQEHGHKENKISYQSSSTEERHLNC GEKGIQKGVSKGSISIQTEEQIHGKSQNQVRIPSQAQEYGHKENKISYQSSSTEERRLNS GEKDVQKGVSKGS ISIQTEEKIHGKSQNQVTIPSQDQEHGHKENKMSYQSSSTEERRLNY GGKSTOKDVSOSSISFOIEKLVEGKS~IQTPNPNQDQWSGQNAKGKSGQSADSKQDLLSH m Ot 481 509 488,------5·09 EQKGRYK~ESSESHNIVITEHEVAODDHLTOOYNEDRNPIST ~ ~ ~9 582 150 Table 4.7. Peptides in unfractionated seminal fluid that were identified by ESI-LC/MS/MS and database searching. These peptides were not evident by direct MALDI-TOFMS analysis of the unfractionated seminal fluid. PROTEIN PEYfIDE FRAGMENT(S) Antibacterial protein F ALL-39 72-96 Accession number: 1706745 cl+-independent phospholipase A2 short form 383-399 Accession number: 7670058 Coagulation factor V 1397-1418 Accession number: 462045 Complement component C4A 863-880 Accession number: 116602 Complement component C 1R component 109-151 Accession number: 115204 Fibronectin 2280-2304 Accession number: 2506872 Glycoprotein hormones alpha chain 77-102 Accession number: 121312 Heat shock protein 70 testes variant 612-639 Accession number: 3461866 Histone Hl' 24-47 Accession number: 121897 Histone HlB 98-151 Accession number: 121919 Platelet-activating factor acetylhydrolase 187-209 Accession number: 2497687 Prolactin-inducible protein 34-47 Accession number: 134170 Prostasin 78-98 Accession number: 2833277 Sperm membrane protein BS-63 510-519 Accession number: 5809678 151 PROTEIN PEPTIDE FRAGMENT(S) 68-107, 81-107, 86-107, 160-182, 160-183, 160-185, 161-182, 192-215, Semenogelin I 193-215, 222-235, 248-273, 253-273, Accession number: 4506883 361-373, 362-368, 376-409, 376-410, 376-427, 381-427, 390-427, 428-453, 428-462 68-85, 68-99, 70-99, 86-99, 192-215, Semenogelin II 194-215, 225-229, 236-273, 253-273, Accession number: 4506885 481-507, 481-509, 488-509, 548-573, 549-582 Testis-specific protein TEX28 177-192 Accession number: 6136075 152 4.4. Discussion A comprehensive analysis of the peptide and protein constituents of human seminal fluid was performed by combining gel electrophoresis (1D and 2D) with MALDI TOFMS, ESI-LC/MS/MS and database searching. Proteins in seminal fluid were separated by 2DE and identified by peptide mass fingerprinting. Additionally, proteins were also separated by ID gel electrophoresis and identified by ESI-LC/MS/MS. Peptides in seminal fluid were also detected following direct analysis by MALDI TOFMS and identified by ESI-LC/MS/MS. Over 100 unique peptides and proteins were identified in seminal fluid by this combined approach. Separation of seminal fluid proteins by 2DE allowed visualisation of over 300 protein spots and enabled the approximate molecular weight and isoelectric point of each protein to be determined. This technique also enabled proteins that had been post translationally modified, for example, phosphorylated, glycosylated or truncated proteins, to be separated and subsequently identified. Some of the modifications are not evident by other protein separation and identification techniques, such as the direct multidimensional liquid chromatography tandem mass spectrometry approach. In total, only 32 unique proteins were identified by peptide mass fingerprinting and database searching. These included prolactin-inducible protein, prostate secreted seminal plasma protein, serum albumin, fibronectin, and lactotransferrin. Multiple isoforms of proteins such as prostatic acid phosphatase and prostate specific antigen are known to be present in human seminal plasma [Taga et al., 1983; Zhang et al., 1995; Wang et al., 1999], and some of these isoforms, as well as their degradation products, were resolved and detected by 2DE in this study. In addition, multiple truncated forms 153 of semenogelin I and II were detected, consistent with proteolytic activity in seminal fluid. Semenogelin I and II and fibronectin are believed to be the main constituents of seminal coagulum and are rapidly degraded upon ejaculation by serine proteases such as prostate specific antigen [Malm et al., 1996; Peter et al., 1998; Robert and Gagnon, 1999]. This process of semen liquefaction plays an important role in sperm motility (Robert and Gagnon, 1999]. Separation by 1D gel electrophoresis enabled 95 unique proteins to be identified, including some that are not amenable to separation by 2DE, such as high molecular weight proteins and basic proteins. Additionally, many of the proteins were identified in multiple molecular weight regions of the gel, indicating that they are present in several modified forms in seminal fluid. For example, proteins detected in a region lower than their theoretical mass have likely undergone proteolysis; other proteins found to migrate at a higher mass than predicted may be present as glycosylated forms or as covalent complexes with other proteins. For instance, prostate specific antigen has been reported to form complexes in seminal fluid with protein C inhibitor, as well as with antiproteases in serum such as a.-1-antichymotrypsin and a.-1-macroglobulin [Lilja et al., 1991; Christensson and Lilja, 1994; Kise et al., 1996; Leinonen et al., 1996; Seregni et al., 1996; Charrier et al., 1999; Zhang et al., 2000]. The nature of the complex between prostate specific antigen and these proteins has not been completely defined. Although gel electrophoresis can be successfully applied to separate and detect proteins, it is not able to adequately resolve low molecular weight polypeptides(< 10,000 Da) or endogenous peptide components. In this study, the direct analysis ofunfractionated seminal fluid by MALDI-TOFMS revealed the presence of over 50 peptide components. 154 The identity of some of these constituents, and of other peptides not evident by MALDI-TOFMS, was subsequently established by ESI-LC/MS/MS. The majority of the peptides detected were identified as fragments of either semenogelin I or semenogelin II, providing further evidence that these proteins undergo extensive proteolysis. These peptides are primarily generated by cleavage C-terminal to glutamine residues, tyrosine and leucine residues, indicating the presence of enzymes with chymotryptic activity, e.g., prostate specific antigen [Malm et al., 1996; Peter et al., 1998]. Analysis by MALDI-TOFMS also detected the presence of seminal basic protein, a bioactive peptide derived from semenogelin I that is believed to inhibit sperm motility [Robert and Gagnon, 1999]. Although seminal fluid reportedly contains other bioactive peptides such as oxytocin [Goverde et al., 1998], angiotensin II [O'Mahony et al., 2000], calcitonin [Slavakis and Papadimas, 2000], somatostatin-64 [Odum and Johnsen, 1994] and thyrotropin-releasing hormone [Khan and Smyth, 1993; Cockle et al., 1994; Gkonos et al., 1994], as well as antimicrobial peptides such as human cationic antimicrobial peptide-18 {hCAP-18) [Malm et al., 2000], these were not detected by the techniques used here. The inability to detect these peptides by either MALDI-TOFMS or ESI-LC/MS/MS may be due to the high abundance of semenogelin peptides, or be due to degradation of the peptides by the proteases present in seminal fluid. Although numerous peptides in seminal fluid were identified, some of the abundant constituents detected by MALDI-TOFMS remain unknown. The inability to identify some of these peptides may be due to post-translational modifications such as C- or N terminal modifications (e.g., amidation, acetylation), amino acid side chain 155 modifications, and/or the presence of intramolecular disulfide bridges (e.g., oxytocin). Because the available protein sequences are direct translations from DNA sequences, these potential modifications are not considered in the available protein databases. 156 CHAPTERS QUANTIFICATION OF BIOMOLECULES BY MALDI-TOF MASS SPECTROMETRY 157 5.1. Introduction Since its inception and commercial availability, the versatility of MALDI-TOFMS has been demonstrated convincingly by its extensive use for qualitative analysis of many different biomolecules. For example, MALDI-TOFMS has been employed for the characterisation of synthetic polymers [Wu and Odom, 1998; Marie et al., 2000], peptide and protein analysis [Nguyen et al., 1995; Zaluzec et al., 1995; Roepstorff, 2000], DNA and oligonucleotide sequencing [Bentzley et al., 1996; Faulstich et al., 1997; Miketova and Schram, 1997], and the characterisation of recombinant proteins [Kanazawa et al., 1999; Villanueva et al., 2001]. Recently, applications ofMALDI TOFMS have extended to include the direct analysis of biological tissues and single cell organisms with the aim of characterising endogenous peptide and protein constituents [Caprioli et al., 1997; Chaurand et al., 1999; Jespersen et al., 1999; Li et al., 1999; Lynn et al., 1999; Stoeckli et al., 1999; Li et al., 2000; Stoeckli et al., 2001]. The properties that make MALDI-TOFMS a popular qualitative tool - its ability to analyse molecules across an extensive mass range, high sensitivity, minimal sample preparation and rapid analysis times - also make it a potentially useful quantitative tool. MALDI-TOFMS also enables non-volatile and thermally labile molecules to be analysed with relative ease. These factors make it worthwhile to explore the potential of MALDI-TOFMS for quantitative analysis in clinical settings, for toxicological screenings, as well as for environmental analysis. In addition, the application of MALDI-TOFMS to the quantification of peptides and proteins is particularly relevant. The ability to quantify intact proteins in biological tissue and fluids presents a particular challenge in the expanding area of proteomics. Investigators urgently require methods to accurately measure the absolute quantity of proteins. 158 While there have been reports of quantitative MALDI-TOFMS applications, there are many problems inherent to the MALDI ionisation process that have restricted its use [Duncan et al., 1993; Gusev et al., 1993; Harvey, 1993; Tang et al., 1993; Muddiman et al., 1994; Nelson et al., 1994; Jespersen et al., 1995; Muddiman et al., 1995; Nicola et al., 1995; Abell and Spoms, 1996; Bruenner et al., 1996; Gusev et al., 1996; Muddiman et al., 1996; Tang et al., 1996; Wu et al., 1997; Kazmaier et al., 1998; Ling et al., 1998; Desiderio et al., 2000; Gobom et al., 2000; Wang and Spoms, 2000; Horak et al., 2001]. These limitations primarily stem from factors such as the sample/matrix heterogeneity that is believed to contribute to the large variability seen in the observed signal intensity for analytes, the limited dynamic range due to detector saturation, and difficulties associated with coupling MALDI-TOFMS to on-line separation techniques such as liquid chromatography. Combined, these factors are thought to compromise the accuracy, precision and utility with which quantitative determinations can be made. Because of these difficulties, examples of quantitative applications ofMALDI-TOFMS have been limited. Most of the studies to date have focused on the quantification oflow mass analytes, in particular, alkaloids or active ingredients in agricultural or food products [Wang and Spoms, 1999; Wang et al., 1999; Jiang and V asanthan, 2000; Wang et al., 2000; Yang and Chien, 2000; Wittmann and Heinzle, 2001]; other studies have demonstrated the potential ofMALDI-TOFMS for the quantification of biologically relevant analytes such as neuropeptides, proteins, antibiotics, or various metabolites in biological tissue or fluid [Duncan et al., 1993; Muddiman et al., 1994; Nelson et al., 1994; Muddiman et al., 1995; Muddiman et al., 1996; Wu et al., 1997; Gobom et al., 2000; Mirgorodskaya et al., 2000]. 159 This study explores the utility ofMALDI-TOFMS for the quantification of five different biomolecules in biological tissue or fluid: homovanillic acid in human urine; catecholamines (epinephrine and norepinephrine) in human adrenal tissue; insulin in human pancreatic tissue; LVV-hemorphin- 7 in human adrenal gland; and growth hormone in the rat pituitary gland. These samples cover a wide mass range and represent practical examples of quantification in complex real world biological matrices. 5.2. Methods The methods employed for this study can be found in Chapter 2 (pages 45 - 49). 160 5.3. Results 5.3.1. Quantification of proteins in biological tissue Growth hormone in rat pituitary tissue (n = 2) was successfully quantified using ~ lactoglobulin as the internal standard. Figure 5.1 shows a MALDI mass spectrum of rat pituitary extract spiked with ~-lactoglobulin (15 nmol) using caffeic acid as the matrix. Also evident were the doubly charged species for these proteins, as well as other minor protein components from the pituitary gland. Figure 5.2 shows the standard curve obtained for rat methionyl growth hormone when the internal standard was not employed. This standard curve was constructed by plotting the average signal intensity for 10 determinations (y-axis) against the amount of methionyl growth hormone applied to the MALDI target (x-axis). Figure 5.3 shows the standard curve obtained for rat methionyl growth hormone with ~-lactoglobulin incorporated as the internal standard. In this case, peak height ratios of analyte to internal standard were used to construct the standard curve. Greater precision was achieved when an internal standard was employed. The standard curve is linear (R2 = 0.997, slope= 1.17) over the chosen concentration range (1-21 µmol/g tissue, 0- 200 pmol met-GH), but has a non-zero intercept. Growth hormone was measured in two different rat pituitary glands and values were determined to be 2.40 ± 0.40 and 2.49 ± 0.25 µmol/g tissue. The values obtained in this study are in agreement with published values for growth hormone in rat pituitary tissue 161 (2.3 - 3.2 µmol/g tissue) [Dickerman et al., 1971]. Coefficients of variation for these measurements were approximately 20% (n = 10). 162 Figure 5.1. A representative MALDI mass spectrum for growth hormone ([M+Ht 21,808 Da) in a rat pituitary extract. ~-Lactoglobulin ([M+Ht 18,364 Da) was added as an internal standard and caffeic acid was used as the MALDI matrix. ~-Lactoglobulin ([M+Ht 18364.0 Da) 100 Rat growth hormone G> fl ([M+Hr 21808.9 Da) > ; 'I "i '1 a: 11 ! I I~ 16155.9 I \ 1\ I \ 1! I ' i~ I~ 17600 19200 20800 22400 24000 Mass (m/z) 163 Figure S.2. A representative standard curve obtained for methionyl rat growth hormone (met-rGH, 0 - 200 pmol) without an internal standard. The plot is the average peak height ratios for met-rGH (y-axis) plotted against amount (x-axis) applied to the MALDI target. Error bars represent standard deviations. 25000 ,------~ y = 65. 77x + 755.07 20000 R2 = 0.687 ~ 15000 ,n i .5 ~ D.= 10000 5000 0 50 100 150 200 250 Concentration rat met-GH (pmol) 164 Figure 5.3. A representative standard curve obtained for methionyl rat growth hormone (met-rGH, 0 - 200 pmol) using ~-lactoglobulin (100 pmol) as the internal standard. The plot is the average peak height ratios for met-rGH to ~-lactoglobulin (n = 10) plotted against molar concentration ratio. Error bars represent standard deviation. 3.5 ~------~ 3.0 y = 1.17x - 0.14 R2 = 0.997 .5 2.5 0 :i ·-!.2.Cl ~ g> 2.0 ·-I!.!!u .! c:o.. .5~ -::C 1.5 1B \? a. .:. EID 1.0 0.5 0.0 0.5 1.0 1.5 2.0 2.5 Concentration ratio met-rGH / ~-lactoglobulin 165 5.3.2. Quantification of peptides in biological samples 5.3.2.1. Insulin in human pancreatic tissue Insulin was quantified in human pancreatic tissue (n = 2) by incorporating porcine insulin as the internal standard. Shown in Figure 5.4 are the MALDI-TOF mass spectra of a pancreatic tissue extract obtained in both linear and reflector modes. Samples were analysed using sinapinic acid as the MALDI matrix. Complete resolution of human insulin and the internal standard (porcine insulin) was achieved in both modes of analysis. The amino acid sequences for porcine and human insulin are shown in Figure 5.5 (p 169). These polypeptides differ by one amino acid and the corresponding mass difference for this amino acid substitution is 30 Da. (Human insulin has a threonine residue at position 109 whereas porcine insulin has an alanine residue at this.position.) Figure 5.6 (p 170) shows the standard curve obtained for insulin in both linear (R2 = 0.999, slope= 1.08) and reflector modes (R2 = 0.999, slope= 0.98) using peak height ratios of analyte to internal standard. For samples analysed in reflector mode, the peak heights of each isotopic form in each respective insulin isotope cluster were summed to calculate the peak height ratios. The values obtained for insulin in each of the pancreatic tissue samples are shown in Table 5.1 (p 172) and are the average often separate determinations. 166 Figure 5.4. Representative MALDI-TOF mass spectra for the analysis of a mixture of human insulin ([M+Ht 5,809 Da) and porcine insulin ([M+Ht 5,778 Da). A. Human and porcine insulin detected in linear mode with sinapinic acid as the MALDI matrix. Porcine insulin ([M+Ht Da) 6000 sns.s 5000 ,4000 Cl) E :::, Human insulin 0 (.) 3000 ([M+Ht 5809.0 Da) 2000 1000 0 5720 5740 5760 5780 5800 5820 58,40 5860 Mass (m/Z) 167 Figure S.4. Representative MALDI-TOF mass spectra for the analysis of a mixture of human insulin ([M+Ht 5,809 Da) and porcine insulin ([M+Ht 5,778 Da). B. Detection of human and porcine insulin in reflector mode using sinapinic acid as the MALDI matrix. 2500 Porcine insulin 2000 1500 ~:::, Human insulin ..... 0 (.) •n~ r-- 1000 CD r-- . . a::i en to C !ii CD~ fB Lli Cil m 500 § 0 5775 5780 5785 5790 5795 5800 5805 5810 5815 Mass (mfz) 168 Figure 5.5. The amino acid sequence for human and porcine insulin. Insulin is composed of two subunits joined by 2 intramolecular disulfide bonds. Insulin A chain consists of 21 amino acids and insulin B chain consists of 30 amino acids. Shown are the amino acid sequences for porcine and human insulin A and B chains. The sequence for these polypeptides differ by one amino acid (highlighted). Amino acid sequence HUMAN INSULIN A CHAIN GIVEQCCTSICSLYQLENYCN PORCINE INSULIN A CHAIN GIVEQCCTSICSLYQLENYCN HUMAN INSULIN B CHAIN FVNQHLCGSHLVEALYLVCGERGFFYTPKT PORCINE INSULIN B CHAIN FVNQHL CGSHLVEAL Y LVCGERGFFY TPKA 169 Figure 5.6. Representative standard curves obtained for human insulin (0 - 600 pmol) using porcine insulin (200 pmol) as the internal standard. These are plots of average peak intensity ratios for human insulin to porcine insulin (n = 10). Error bars represent standard deviation. A. Standard curve for human insulin obtained in linear mode. as-.------ 3 y = 1.08x: + 0.04 .5 R2:0.999 ]25 0 .5 .::e l!.5 ~I:! 2 -o c_• 0. ,! C c=1.5 -::::, .:.=1n I .5 a. i 1 E ::::, ::c 0.5 0-----1------t------t-----+----+----+----' 0 0.5 1.5 2 25 3 Concemalion ratio HLmat Insulin/ porcine insulin 170 Figure 5.6. Representative standard curves obtained for human insulin (0 - 600 pmol) using porcine insulin (200 pmol) as the internal standard. These are plots of average peak intensity ratios for human insulin to porcine insulin (n = 10). Error bars represent standard deviation. B. Standard curve for human insulin obtained in reflector mode. 3.5 ~------~ 3 y = 0.98x + 0.04 C R2 =0.999 ·-::::,o= 1ij IO .. c2.5 ~-; e-10 C a, 2 .. e0 .5 Q. ~as C !_ =§ 1.5 "0 ~ Cl) ·- E c E as 1 ::::, E ,,, ::::, ::c 0.5 o~----+-----+-----+------1------+------1--...J 0 0.5 1.5 2 2.5 3 Concentration ratio Human insulin/ porcine Insulin 171 Table 5.1. Insulin concentrations measured in human pancreatic tissue obtained from two cadavers. Each pancreatic tissue was divided into three sections and analysed in both linear and reflector modes. The concentration of insulin is the average of ten determinations from each tissue sample. LINEARMODE REFLECTOR MODE HUMANINSULIN HUMAN INSULIN CV(%) CV(%) (nmol/g tissue) (nmol/g tissue) A 20.9 1.6 19.7 6.1 Pancreas 1 B 18.7 1.4 18.2 7.1 C 16.8 2.9 16.l 6.8 A 12.6 3.3 12.1 6.4 Pancreas 2 B 15.2 2.3 13.6 11.2 C 12.9 3.0 10.7 6.6 172 5.3.2.2. L VV-hemorphin-7 in human adrenal gland LW-hemorphin- 7 was quantified in whole human adrenal tissue (n = 10), adrenal cortex (n = 10), adrenal medulla (n = 9), and in pheochromocytoma tissue (n = 3). All analyses were performed in linear mode using cx.-cyano-4-hydroxycinnamic acid as the MALDI matrix. To determine the concentration of LW-hemorphin- 7 in pancreatic tissue, a standard addition curve was constructed using a pancreatic tissue extract as the matrix. Linear standard curves (R2 = 0.999) were routinely obtained over the concentration range 7 to 500 nmol/g tissue (0-600 nmol/g tissue of human LW-hemorphin-7 added). The structural homologue, rat LW-hemorphin-7 (300 nmol/g tissue), was used as the internal standard. Figure 5.7 shows the results obtained by MALDI-TOFMS analysis when compared to electrospray analysis of the same extracts [Cerpa-Poljak et al., 1997]. To determine the concentration of LW-hemorphin- 7 by MALDI-TOFMS, each tissue sample was analysed 10 times and the average concentration calculated. The values obtained by MALDI-TOFMS for LW-hemorphin-7 were found to correlate well with the electrospray data generated from the same samples [Cerpa-Poljak et al., 1997]. 173 Figure 5. 7. A comparison of L W-hemorphin-7 concentrations in human adrenal gland determined by MALDI-TOFMS and ESI-MS. The values obtained by MALDI-TOFMS are the average of 10 separate determinations. Co-efficients of variation (CV) for each measurement were less than 10%. 800-.------~ 700 R2 = 0.796 C 0 • i 600 'E Cl) U) g 'ii' "i 500 0:::, > u • 'ii .!! C ":" ;, as 400 C :::. (I) :c I:& Q. C I ...... ci5 300 ~ w .! 200 ~ 100 0 50 100 150 200 250 300 350 400 LVV-hemorphin-7 concentration (nrnoVg tissue) MALDI-TOFMS analysis 174 5.3.3. Quantification of low mass analytes in biological samples 5.3.3.1. Catecholamines in human adrenal gland The catecholamines, epinephrine and norepinephrine, were quantified in normal human adrenal gland (n = 3) and pheochromocytoma tissues (n = 3) using ferulic acid as the MALDI matrix. Standard addition curves (concentration range 0- 18 µmol/g tissue) for both epinephrine and norepinephrine were constructed using an extract of adrenal cortex as the matrix. Linear standard curves were obtained for both epinephrine (R2 = 0.999) and norepinephrine (R2 = 0.998) when the respective stable isotopomers were used as the internal standard. For epinephrine, [2H3]-epinephrine (4 µmol/g tissue) was used as the internal standard; [2H3]-norepinephrine (6 µmol/g tissue) was used as the internal standard for norepinephrine. Figure 5.8 shows an example of epinephrine, norepinephrine and their internal standards in an adrenal tissue extract. All spectra were acquired in reflector mode. Table 5.2 shows the results for the quantification of epinephrine and norepinephrine in normal adrenal tissue and pheochromocytoma tissue. 175 Figure S.8. A representative MALDI-TOF mass spectrum for norepinephrine, epinephrine and their respective internal standards in human adrenal extracts. Samples were analysed in reflector mode and ferulic acid was used as the MALDI matrix. Epinephrine [2H3]-Epinephrine ([M+H( 184.0972 Da) ([M+H( 187.1161 Da) 100 ~ I -0~ Norepinephrine ([M+H( 170.0823 Da) [2H3]-N~repinephrine ([M-,H] 173.1005 Da) /' I 172 176 181 185 190 Mass (m/z) 176 Table 5.2. Concentrations ofnorepinephrine and epinephrine in hwnan adrenal tissue (n = 3) and pheochromocytoma tissue (n = 3). Values are the average of 10 separate determinations. NOREPINEPHRINE EPINEPHRINE MEANVALUE MEAN VALUE CV(%) CV(%) (nmol/g tissue) (nmol/g tissue) 233 16 279 6 Adrenal gland A Adrenal gland B 510 13 582 10 Adrenal gland C 499 17 690 19 Pheochromocytoma 1 3,989 7 184 16 Pheochromocytoma 2 6,708 8 2,854 8 Pheochromocytoma 3 59,940 5 5,735 4 177 5.3.3.2. Homovanillic acid in human urine Homovanillic acid was quantified in urine obtained from healthy volunteers (n = 19). An example of a MALDI-TOF mass spectrum showing the molecular ion of homovanillic acid and its internal standard ([2H5]-homovanillic acid, 100 pmol) in a urine sample is shown in Figure 5.9. All spectra were acquired in reflector mode using 2,5-dihydroxybenzoic acid as the MALDI matrix. Because the molecular ion for both molecules was the most abundant species in the mass spectrum, the peak height and peak area for these ions were used for all calculations. Linear standard curves (concentration range 0- 1,000 pmol) were obtained when either peak height (R2 = 0.999, slope= 0.97) or peak area (R2 = 0.999, slope= 1.05) ratios_were calculated. Standards and samples were analysed 10 times to obtain an average value. The co efficient of variation was less than 10% for each sample analysed. The same 19 urine samples were also independently analysed for homovanillic acid content at a clinical laboratory by high performance liquid chromatography (HPLC). These values correlated well with those obtained by MALDI-TOFMS when either peak height or peak area ratios were used. Figure 5 .10 shows the results for both peak height and peak area ratio values. 178 Figure S.9. A representative MALDI mass spectrum for homovanillic acid detected in human urine. The internal standard [2H5]-homovanillic acid (I 00 pmol) was added prior to analysis. Samples were analysed in reflector mode using 2,5-dihydroxybenzoic acid as the MALDI matrix. [2H5]-Homovanilllc acid (M+. 187.0896 Da) Homovanillic acid 100 (M+. 182.0577 Da) ~ ui C f 5 Cl) ;> 'i a: 179 Figure S.10. Homovanillic acid concentrations in human urine (n = 19) determined by MALDI-TOFMS vs homovanillic acid values determined by a commercial clinical laboratory (HPLC method). The values obtained by MALDI-TOFMS analysis are the average of 10 measurements for each sample. A. Homovanillic acid concentrations obtained using peak height ratios. 12000 R2 = 0.915 C 0 10000 =! a, C 'i -Cl) u f 8000 C C o ::::r as u E u, :5! ::& 6000 u tE u. as C 0 .!:! - '7 ~ 9 4000 as CC • g ::& • E 0 2000 ::c 0+-----'.___-~-~--~--~------0 1000 2000 3000 4000 5000 6000 7000 8000 Homovanillic acid concentration (nmoVml} 180 Figure 5.10. Homovanillic acid concentrations in human urine (n = 19) determined by MALDI-TOFMS vs homovanillic acid values determined by a commercial clinical laboratory (HPLC method). The values obtained by MALDI-TOFMS analysis are the average of 10 measurements for each sample. B. Homovanillic acid concentrations obtained using peak area ratios. 7000 R2 = 0.942 6000 C 0 • .:; l! .!5000,n ..C >- pj 'ii C C 0 :::r as 4000 u E u, "Cl ::::, ::E 0 LL. uas ! e3000 ~ cI ·cas ..I > ;2000 0 E 0 ::c 1000 0 0 1000 2000 3000 401)0 5000 6000 7000 8000 Homovanilllc acid concentration (nmol/ml) 181 5.4. Discussion MALDI-TOFMS has been applied successfully to the quantitative analysis of several biologically relevant molecules ranging in molecular weight from 170 - 22 kDa. Linear calibration curves (R2 > 0.99) were routinely obtained for each analyte over the chosen concentration range. Each analyte was detected and quantified in a biological matrix with minimal sample preparation. The accuracy of the approach was demonstrated by comparison of these results with literature values, or by independent analysis. In each case, the values obtained by MALDI-TOFMS were in good agreement with those reported or obtained by other techniques [Dickerman et al., 1971; Cerpa-Poljak et al., 1997]. This study has also shown the potential ofMALDI-TOFMS for the quantification of low mass analytes, especially in a clinical diagnostic setting. Factors such as the speed of analysis(< 1 min per sample) and minimal sample preparation make MALDI TOFMS appropriate for these types of analyses. Additionally, the accurate mass capability of MALDI-TOFMS offers an additional level of specificity when quantifying low mass analytes because mass assignments within 5 ppm can be achieved routinely. In this mode, elemental composition can confirm assignment (using internal calibration in reflector mode). In this study, levels ofhomovanillic acid measured by MALDI TOFMS were found to correlate well with those obtained by HPLC analysis in a commercial laboratory setting. Both peak height ratios and peak area ratios were used for the quantification of homovanillic acid and similar results were obtained when either was employed. This indicates that for the quantification of low mass analytes, either one can be used to obtain accurate and precise measurements. Additionally, elevated levels of epinephrine and/or norepinephrine were measured in pheochromocytoma tissue when 182 compared to normal adrenal glands, with the exception of epinephrine in one of the pheochromocytoma samples analysed. This may occur because cortisol, produced by the adrenal cortex, is a necessary factor for the conversion of norepinephrine to epinephrine via phenylethanolamine N-methyltransferase. A large medullary tumour grows at the expense of the adrenal cortex reducing the availability of this co-factor, thereby reducing the synthesis of epinephrine by the adrenal gland. The utility ofMALDI-TOFMS for the absolute quantification of peptides and proteins in biological tissue has also been demonstrated. Growth hormone in rat pituitary tissue was quantified employing ~-lactoglobulin as the internal standard and caffeic acid as the MALDI matrix. Although broadening of the signal obtained for both growth hormone and ~-lactoglobulin was observed (see Figure 5.1, p 163), possibly due to protein heterogeneity and the formation of protein/matrix adducts [Beavis and Chait, 1989], the amount of growth hormone in rat pituitary gland could still be accurately determined. Human insulin and LVV-hemorphin- 7 were also quantified in pancreatic tissue and adrenal gland extract respectively. In both cases, structural homologues were employed as internal standards. Insulin in pancreatic tissue was quantified using both linear and reflector modes and similar results were obtained when either mode was employed. Although an improved level of precision was achieved in linear mode, either mode of analysis can still be used for peptide quantification. Peptide quantification by MALDI TOFMS was also demonstrated with L VV-hemorphin-7. The results obtained by MALDI-TOFMS were found to compare well with those obtained by ESI-MS analysis of the same extracts [Cerpa-Poljak et al., 1997]. However, the values measured in this 183 present study were found to be slightly lower than those previously obtained, possibly due to degradation of the adrenal extract during storage (2 years). In this study, internal standards were employed to reduce variations that arise from heterogeneity in the sample/matrix co-crystallisation process. For the low mass analytes, isotopomers were employed as the internal standard, and structural analogues were used for the analysis of LVV-hemophin- 7 and insulin. In the case of growth hormone, homologous proteins, such as human growth hormone, were initially investigated as potential internal standards, but the two species could not be adequately resolved by MALDI-TOFMS. Therefore, a structurally unrelated protein of similar mass (i.e., ~-lactoglobulin) was employed as the internal standard. Here the precision was significantly lower than those observed when structural analogues and isotopomers were employed. These differences are likely due to the different physical and chemical properties between the two proteins, notably the differences in ionisation efficiencies of the two proteins, as well as differences in solubility of the proteins in the chosen matrix solvent (80 % CH3CN) [Cohen and Chait, 1996]. Although acceptable mass accuracy was obtained in this instance, the ideal internal standard for quantitative analyses is an isotopomer, thereafter a close structural analogue. Based on these results, and as might be expected, compounds with little chemical or physical similarity are less than ideal when employed as internal standards; however, they do allow for greater precision than when peak intensity alone is plotted against concentration (see Figures 5.2 and 5.3, p 164- 165). The incorporation of an internal standard also serves to increase the precision with which a value can be measured. Precision may be improved further by employing 184 alternative methods of sample/matrix deposition, such as electrospray deposition of sample and matrix [Hensel et al., 1997], the addition of additives such as nitrocellulose [Preston et al., 1993; Gusev et al., 1995], or the application of sample and matrix using the fast-evaporation technique [Vorm et al., 1994; Nicola et al., 1995]. These techniques result in the formation of smaller crystals uniformally distributed, and therefore this minimises observable variations in signal intensity between successive laser shots, as well the variations observed from sample to sample. Although proteins can be accurately quantified using this technique, there are limitations: a restricted dynamic range and limited sensitivity. Due to the signal suppression effects of the MALDI process, the limit of detection of a protein is dependant on the complexity of the sample matrix. A highly purified protein sample containing only the protein of interest and the internal standard yields lower limits of detection and improve sensitivity. This issue is important when attempting to measure circulating biomarkers that are often present in low abundance with respect to other serum proteins (e.g., serum albumin and hemoglobin). It has been shown that by combining MALDI-TOFMS with immunoaffinity or other sample purification steps, the dynamic range and sensitivity can be improved [Nelson et al., 1995; Tubbs et al., 2001]. The potential quantitative applications ofMALDI-TOFMS are unlimited. On-going technical advances will likely provide solutions to some of the current obstacles, and these will allow MALDI-TOFMS to be used routinely in quantitative settings. MALDI TOFMS can offer high sensitivity and specificity, and this study has shown that it can also be used for diagnostic purposes where the presence of a particular analyte has either markedly increased or decreased in a pathological state. Also, proteins such as 185 circulating growth hormone and insulin are currently measured using immunochemical techniques, and these techniques alone may not provide sufficient specificity for a confident diagnosis [Strasburger and Dattani, 1997; Strasburger, 1998; Chevenne et al., 1999]. By utilising MALDI-TOFMS, these and other biomarkers can be accurately quantified. 186 CHAPTER6 ALTERNATIVE APPROACHES TO PROTEIN QUANTIFICATION 187 6.1. Introduction Different approaches to protein characterisation have been described, but among the most commonly adopted today is detection by mass spectrometry, followed by identification through database searching. Strategies include separation of proteins by gel electrophoresis, or chromatographic separation of proteolytic peptides generated from complex protein mixtures. By employing two dimensional gel electrophoresis (2DE), protein post-translational modifications, such as phosphorylation, glycosylation and truncation can be visualised [Larsen and Roepstorff, 2000; Sarioglu et al., 2000] and information concerning changes in protein expression between samples of similar biological origin can be obtained [Gros et al., 2001]. Although 2DE is the most widely accepted technique for global protein separation, the ability to obtain an accurate measurement of absolute amounts of protein, or to determine relative levels with acceptable precision, remain a considerable challenge. Various approaches have been employed to determine the relative concentrations of proteins in biological samples. The majority of these involve isolation and purification of the protein(s) of interest prior to quantification. Standard biochemical approaches for protein quantification include immunochemical techniques such as ELISA, radioimmunnoassays, or derivatisation with specific reagents to promote detection by fluorescence following protein isolation [Krull et al., 1997; Weller, 2000]. Even though these techniques can offer high sensitivity, they must be targeted toward particular proteins and therefore lack versatility. In contrast, recent advances in proteomic technologies now enable proteins to be quantified on a global scale. Because proteomic approaches allow many hundreds of proteins to be separated and identified in a few steps, the ability to quantify these with precision and accuracy is an important objective. 188 2DE and densitometry have been employed to estimate the relative abundances of proteins in tissue obtained from normal and disease states, or between wild type and treated cells [Newsholme et al., 2000; Poirier et al., 2001; Yoo et al., 2001]. Because many proteins can be simultaneously detected, this approach also enables the presence of protein isoforms and modified proteins to be monitored. Many detailed studies investigating methods to improve the precision of quantitative measurements made by 2DE have been reported. These have been focused on the development of computer algorithms to improve protein spot detection and matching [Pleissner et al., 1999; Kriegel et al., 2000], as well as investigations into compatible protein stains that offer high sensitivity, linearity and a wide dynamic range [Yan et al., 1999; Berggren et al., 2000; Lopez et al., 2000; Yan et al., 2000]. Although this approach is widely applicable for both in vivo and in vitro studies, many limitations exist. For instance, it is widely recognised that a two dimensional gel does not provide a complete representation of the entire proteome of a chosen organism [Gygi et al., 2000]. Further, hydrophobic proteins, basic proteins, high mass and low mass proteins are not readily amenable to 2DE separations, and at times, co-migration of proteins may lead to inaccurate estimates of protein expression levels. Alternatively, methods to quantify proteolytic peptides by mass spectrometry following differential isotope labeling have also been developed. For example, the relative quantities of gel separated proteins obtained from matched biological samples have been determined by isotopic labeling of either the N- or C- terminal residue of proteolytically derived peptides [Munchbach et al., 2000; Yao et al., 2001]. MALDI TOFMS and peptide mass fingerprinting is then used to identify the protein and to 189 determine the relative amounts of each. In addition to enabling proteins to be identified and quantified, this approach also facilitates interpretation of tandem mass spectral data and protein identification by de novo sequencing [Munchbach et al., 2000]. Additionally, proteins have been quantified by combining proteins obtained from cells cultured in normal medium with those obtained by metabolic labeling of proteins in cell cultures maintained in an isotopically enriched medium [Oda et al., 1999; Conrads et al., 2001; Smith et al., 2001]. Here the proteins are electrophoretically separated, proteolytically digested, and the relative abundance of each protein (i.e., labeled and unlabeled) is quantified by ESI-LC/MS. Although demonstrated to offer precise and accurate quantification of proteins, and has the potential for quantification of modified proteins, [Oda et al., 1999], the utility of this approach is limited to monitoring protein expression in in vitro studies. Other techniques that provide a global approach to protein quantification, such as isotope-coded affinity tagging (ICAT), have also been developed. These allow the relative amounts of many proteins to be determined simultaneously when two samples containing an identical set of proteins are compared [Gygi et al., 1999]. Proteins in each sample are proteolytically digested and the resulting peptides are reacted with mass tags that are chemically identical, but differ in mass. Peptides containing the mass tags are then purified, combined and analysed. In contrast to techniques involving metabolic labeling of proteins, this approach is more universally applicable; however, it involves the incorporation of a mass tag that is highly specific for one amino acid residue (i.e., cysteine) and therefore only those proteins containing cysteine residues can be quantified. More recently, a similar technique has been described which is more general 190 in nature [Goodlett et al., 2001]. Instead of a single specific amino acid being derivatised, here all C-tenninal residues, and the acidic side chains of aspartic acid and glutamic acid residues, are converted to methyl esters prior to analysis and quantification. These procedures do not require individual proteins to be separated prior to analysis, and in contrast to approaches involving quantification of electrophoretically separated proteins, rely solely on the separation of peptides by liquid chromatography. Even though many of these methods have been successfully applied to the determination of relative amounts of proteins in model systems, they have not been readily adopted. This is due to the level of precision that can be achieved, limitations relating to the proteins that can be quantified, less than ideal yields following the derivatisation or mass tagging procedure, and the complexity of the overall process. For example, incorporation of chemical derivatives may confound analysis due to unexpected side reactions or incomplete derivatisation [Krull et al., 1997]. Quantification strategies that overcome these difficulties, offer accurate and precise measurements of changes in protein expression, and that are widely applicable to many different biological systems are therefore required. This study describes a procedure to determine the relative abundances of proteins: here applied to human tear fluid obtained under two different biological conditions. Because tear is believed to perform different biological functions under different conditions, human tear fluid derived from the open eye and closed eye state reportedly contain the same protein components but at different concentrations [Sack et al., 2000]. During the open eye state, the tear film primarily serves to protect the external ocular surface from potential pathogens, provide nourishment for the corneal surface, and to remove waste 191 products resulting from cellular respiration [Coyle et al., 1989; Wollensak et al., 1990]; during eye closure, tear flow is static, and both the nourishment of the corneal and conjunctiva! surfaces and removal of potentially toxic waste products are less efficient. Therefore, the primary function of tear fluid proteins during prolonged eye closure is to maintain the viability of the ocular surface [Sack et al., 2000]. The analytical process described here involves the esterification of proteolytically derived peptides with butanol, either native or deuterated butanol (d10-butanol), and subsequent analysis by ESI-LC/MS to measure the relative amounts of each protein. Carboxylic acid groups of glutamic acid and aspartic acid residues are specifically targeted, as well as the C-terminal residue of each peptide. In contrast to ICAT, this approach is not selective for a specific amino acid residue and as a result, potentially all proteins in a sample can be quantified. In addition, this approach offers multiple determinations of relative levels for each protein because multiple derivatised peptides are formed and can be measured. Proteins in open and closed eye tear fluid were chosen as the model system to demonstrate the potential of this approach for determining the relative quantities of proteins in a complex biological sample. 6.2. Methods Details of the methods employed for this study can be found in Chapter 2 (pages 38 -40). 192 6.3. Results 6.3.1. Demonstration of the approach To demonstrate the feasibility of the approach, horse apomyoglobin was chosen as a model protein. An aliquot of protein was digested using trypsin and the resulting peptides divided into two portions (ratio of 1: 1) prior to derivatisation with either acidified butanol (do) or acidified deuterated butanol (d10-butanol). This resulted in the esterification of the C-terminus of all peptides, as well as all acidic amino acid residues, i.e., glutamic acid and aspartic acid (Figure 6.1). The addition of each butyl ester resulted in an increase in the peptide mass of 56 Da for do-butanol, and 65 Da for d10- butanol. Following derivatisation, samples were combined and analysed by MALDI TOFMS and ESI-LC/MS. One of the difficulties associated with this study was to ensure complete derivatisation of the peptide mixture. Therefore, analysis by MALDI-TOFMS was performed to assess the conversion of the free acids of the tryptic peptides to the butyl ester under the conditions employed (i.e., 3hrs, 70°C). Figure 6.2A (p 196) shows a representative MALDI mass spectrum of an apomyoglobin tryptic digest prior to esterification. Tryptic peptides derived from the predicted sequence of apomyoglobin are indicated. The remaining peptides are the result of non-specific enzymatic cleavage of apomyoglobin, or arise from impurities in the protein sample. (Analysis of the tryptic peptides by ESI LC/MS/MS identified contaminant proteins such as tropomyosin, hemoglobin and phosphatidylethanolamine binding protein.) Figure 6.2B (p 197) shows a MALDI mass spectrum of the same digest following derivatisation with acidified do-butanol. Complete derivatisation of all tryptic peptides was achieved under the conditions 193 employed. Peptides derived from apomyoglobin that were detected at multiples of 56 Da higher in mass due to butyl esterification are highlighted. 194 195 195 and and acid acid glutamic glutamic 3 3 D D as as C C D2 such such C D2 oH oH C) C) ESI-LC/MS ESI-LC/MS ° C ,o ,o ' 70 D2 BY BY residues residues , , C C - OC hrs X X ~ ~ 3 3 - Acidic Acidic -butanol/HCI -butanol/HCI M, M, X X 10 d (1 (1 - IDENTIFY IDENTIFY X X peptide. peptide. - l l X X -x-~c, -x-~c, - X - tryptic tryptic a a X X H2N H2N - of of s s u H2N H2N ANALYSE ANALYSE C-termin e e and and h t ESI-LC/MS ESI-LC/MS to to BY BY 70°C) 70°C) oH oH ester ester l l ,o ,o ' COMBINE COMBINE OCH2CH2CH2CH3 OCH2CH2CH2CH3 hrs, hrs, C C buty 3 3 ~ ~ - a a X X C' C' -butanol/HCI -butanol/HCI M, M, of of 0 - d (1 (1 X- X X - - l l X X X addition addition - - residue residue X X X X the the - acid acid X X N - N 2 - H mino mino N N ESI-LC/MS ESI-LC/MS showing showing 2 a esterified. esterified. H ny ny BY BY a also also are are notes notes Schematic Schematic e d acid acid DENTIFY DENTIFY 6.1. 6.1. 'X' 'X' I rtic rtic a p as Figure Figure 196 in 3000 analysed were indicated. are 2602.32 Samples 97-108 2500 trypsin. apomyoglobin with from digestion derived 1983.01 79-96 2000 1885.98 103-118 following peptides - I.I (m/z) •. 1854.92 tryptic Mass 80-96 1606.85 17-31 apomyoglobin matrix. 1500 119-133 predicted the horse as The of 1271.67 1502.67 I 32-42 acid l~\111> ' 1158.59 I 33-42 " spectrum esterification. to mass 1000 941.49 I 146-153 prior MALDI 748.43 '! 134-139 digest I I a-cyano-4-hydroxycinnamic I tryptic F 500 0 using 1 representative i i '#. ~ a: - - "i :; A mode 6.2. Apomyoglobin Figure reflector A. in 197 in increased that analysed 2500 were apomyoglobin Samples 2166.23 32-47 from trypsin. 2100 derived with 1889.08 32-45 1832.05 peptides 17-31 digestion Those 1700 following 1434.91 64-n (m/z) do-butanol. Mass apomyoglobin acidified matrix. 1300 the highlighted. with horse as are 1174.82 43-50 of acid spectrum derivatisation esterification mass 900 860.55 134-139 -1139 butyl 789.51 following to 135 MALDI due digest Da 676.41 56 a-cyano-4-hydroxycinnamic 136-139 tryptic of 0500 using 1 representative C ~ fl) ~ ~ 0 ·;;; - a: - i :; A mode multiples 6.2. by Apomyoglobin Figure reflector B. mass Following derivatisation, the esterified peptides were combined (ratio of 1: 1). To determine the relative quantity of each peptide, an aliquot of the combined apomyoglobin tryptic digest was analysed by ESI-LC/MS. The deuterated peptides were found to have a slightly earlier retention time than the corresponding unlabeled peptide. Co-eluting peptide pairs showing an appropriate mass difference were detected (SIN > 3), with the observed mass difference being dependant on the number of incorporated butyl esters and the charge state of each peptide. The relative amount of each co-eluting peptide pair was determined by integrating the area under the extracted ion chromatograms for the do- and d10- butylated peptides. Analysis by ESI-LC/MS detected many co-eluting tryptic peptide pairs that were derived from apomyoglobin following digestion and derivatisation with do-butanol or d10-butanol. Some of these peptides were a result of non-specific enzymatic cleavage of apomyoglobin, or were peptides derived from contaminant proteins in the sample. Some of the esterified tryptic peptides derived from apomyoglobin, as well as their measured peak area ratios, are listed in Table 6.1. The average observed ratio (do-/ d10- butyl peptide esters) was determined to be 1.03 ± 0.19 (CV 18 %). This indicates that this technique can be used to precisely and accurately determine the relative amount of proteins in a complex sample. 198 Table 6.1. The relative abundance oftryptic peptides derived from apomyoglobin. Following derivatisation with either do- or d10- butanol, equal aliquots were combined and analysed by ESI-LC/MS. The observed ratio for do-/ d10- butylated peptides was determined to be 1.03 ± 0.19 (CV 18 %). TRYPTIC CHARGE OBSERVED RATIO PEPTIDE STATE (do-butanol / d10-butanol) 17-31 +2 0.97 32-42 +2 0.89 43-45 +l 1.29 48-50 +l 1.13 51-56 +l 1.11 57-63 +l 0.74 97-102 +l 1.32 99-102 +l 0.79 134-139 +l 1.14 140-145 +l 0.97 148-153 +l 0.91 199 6.3.2. Identification of esterified peptides in open and closed eye tear Aliquots (10 µg of total protein) from open and closed eye tear fluid obtained from healthy individuals were digested using trypsin and the resulting peptides derivatised with either acidified do- or d10- butanol respectively. To ensure complete derivatisation of the peptides an aliquot of each was analysed by MALDI-TOFMS prior to quantification by ESI-LC/MS. Figure 6.3 shows a MALDI mass spectrum of a combined aliquot of open and closed eye tear following tryptic digestion and butanol esterification. Some of the peptide pairs, identified by a mass difference of 9 Da ( or multiple of), are highlighted. Esterified peptides derived from both open and closed eye tear were analysed separately by ESI-LC/MS/MS and identified by database searching prior to quantification. This ensured that the same proteins could be detected and identified in both types of tear fluid. Figure 6.4 (p 202) shows an example of a fragment ion spectrum of an esterified peptide derived from open eye tear. Database searching using SEQUEST identified this as the tryptic peptide 107 - 120 of lacrimal proline-rich protein containing two butyl esters. Some of the other proteins detected include growth factors, immunoglobulins, lactotransferrin, lysozyme, tear lipocalin, and many serum proteins. Due to the complex nature of human tear, and the limited solubility of some peptides in butanol, only a subset of the proteins previously identified by ESI-LC/MS/MS were detected and identified (see Chapter 3). In this case, only the most abundant proteins (ea. 50 proteins) in tear fluid were identified in open or closed eye tear fluid following butanol esterification (cf. with the 400 identified previously). 200 201 201 in in ,.;l'/f. ,.;l'/f. ' 2200 2200 ,14 ,14 . present present l'/ 15 15 . ...... 14 14 . 2052.24 2052.24 987 987 l l ,It:" ,It:" 1 I I proteins proteins i i 2034 the the ' ' i j j from from ~/ ~/ 1 0 0 1 1880 1880 . derived derived 08 08 " 1976 13.96 13.96 pairs pairs 1732 1 1 peptide peptide tryptic tryptic 531.99 531.99 1560 1560 1513.86 1513.86 ) ) m/z ( d10-butylated d10-butylated nd nd Mass Mass a ~~---i~~/~~1'~1 ~~---i~~/~~1'~1 1315.99 1315.99 ~ ~ ~ \ \ 1297.88 1297.88 91 91 75 75 . . . 79 79 1240 1240 . ~ ~ 51 do-butylated do-butylated 1160 1111 1111 1 1 . . I I . . i i \ \ 1093.63 1093.63 l~j l~j showing showing . . 936.71 936.71 spectrum spectrum 927.65 927.65 920 920 mass mass .~-~ .~-~ 58 58 56 56 . . respectively 815.66 815.66 744.64 744.64 790 797 180870 180870 tear tear / / eye eye MALDI-TOF MALDI-TOF 5\ 5\ . A A closed closed 726 6.3. 6.3. ,------,------,------,------,-----~------,------~-----,-----~-----~ ,------,------,------,------,-----~------,------~-----,-----~-----~ 600 600 and and 0 n n 100 100 e >, >, ea ea > > Q) Q) C: C: Q) Q) Ill Ill C: C: - Q) Q) a: a: ~ ~ 0 0 :;: :;: ~ ~ - p o Figure Figure 202 protein. glutamic Da). 1 ' ' esterified proline-rich 1,713.0 Y12 contains an oflacrimal ([M+Ht also 1 120) Y11 tear - and . eye _ (107 Y10 . open esterified I in _ yg peptide 11, I detected tryptic a Ya I C-terminally as 11 I is peptide 1ll,1 I I mlz 1 I peptide Y1 tryptic identified I ,I 11 The I esterified peptide was peptide an 800 1.Ul I Ys for This ill.1.111 R* Ys 1i111,I spectrum FPSVSLQEASSFFR. detected. I, is ion was A S S F F E* ions peptide Q fragment the a ofy- of of series sequence F PS V S L example An acid complete 6.4. residue. amino almost • 100 C ea g C ::, G> i -;ft. c( .a - 'g i - a: Figure An acid The 6.3.3. Relative quantification of proteins in open and closed eye tear fluid Following esterification and identification, combined aliquots of the do- and d10- butylated peptides were analysed by capillary ESI-LC/MS. Co-eluting peptides exhibiting an expected mass shift were identified and their relative amounts determined by comparing their respective peak areas obtained from each extracted ion chromatogram. The observed mass difference between each corresponding peptide pair is dependant on the number ofbutanol esters incorporated, as well as the charge state of the peptides. Over 100 co-eluting peptide pairs were detected (SIN> 3) representing more than 20 different proteins in the combined tear fluid. This enabled multiple peptide pairs derived from the same protein in tear fluid to be used for quantification. Figure 6.5 shows an example of an averaged mass spectrum showing at least three different co-eluting peptide pairs (retention time of 60 - 62 minutes). The corresponding extracted ion chromatogram for one of these peptide pairs is shown in Figure 6.6 (p 206). By comparing the area under each peak, this peptide (identified as tryptic peptide 120- 125 from lysozyme) was estimated to be five times more abundant in open eye tear. 203 Figure 6.5. An example of a mass spectrum (m/z 600 - 1,300) of esterified open and closed eye tear showing at least three different co-eluting tryptic peptide pairs. These peptides eluted over a retention time window of 60 - 62 minutes and were derived from lysozyme (m/z 797.5 and 815.6, residues 120-125; mlz 790.5 and 808.6, residues 19-23) and lactotransferrin (m/z 1,206.5 and 1,215.6, residues 110- 119). The extracted ion chromatograms for one of these peptide pairs are shown in Figure 6.6 (p 206). 204 Figure 6.5. An example of a mass spectrum (m/z 600 - 1,300) of esterified tear samples (open and closed eye) showing at least three different co-eluting tryptic peptide pairs. 797.5 ~ -0 Cl) 7~0.5 0 C: ea 'O C: :::J .0 < Cl) .:> 808.6 ea 'ii a: '815.6 1206.5 1215.6 600 700 800 900 1000 1100 1200 m/z 205 206 butyl tes. u two s min in ta 62 * n - R* co 60 130 G I R of Q peptide P P Q G I dow is n 120 h D* D* T wi . e m ti n tio DPQGIR n e t ce e n r 100 110 e a t qu se s a e ir 90 a th p e as h ptid 80 nd e p e a g m (min) lutin 70 ysozy m/z815.6 co-e m/z797.5 Time m l e h t 60 fro of 25 e 1 n o - 50 20 for 1 m e d 40 atogra pepti m ro h 30 c tryptic n e io h t l tear as 20 tota tear eye eye 10 identified Closed extracted Open B. A. was The 0 6.6. 10 10 peptide ::::l C1I C: ::: 0 C: C1I Ill Ill ~ - "O <( .D ~ Qi a: . - Figure This esters(*). Multiple peptides{> 3) derived from the same protein in each sample were used to determine the variation in the measured changes in the relative abundance for each protein. Table 6.2 shows an example of the peak area ratios obtained from multiple tryptic peptides of tear lipocalin. Listed are the tryptic peptides derived from this protein and the relative peak area ratio for each of these. Some of the proteins found to be equally abundant in open and closed eye tear fluid include lactotransferrin, lacrimal proline-rich protein and various complement proteins (e.g., C2, C4, C7). Table 6.3 (p 209) lists those proteins that were determined to be more abundant in open eye tear. Listed in Table 6.4 (p 210) are those proteins that were found to be more abundant in closed eye tear. These proteins were primarily serum based proteins. 207 Table 6.2. The relative abundances of tryptic peptides derived from tear lipocalin. This protein was found to be 1.7 (± 0.4, CV 22 %) times more abundant in open eye tear. TRYYfIC -,r OBSERVED m/z ¥ OBSERVED mlz CHARGE * OBSERVED RATIO PEPTIDE Open eye tear Closed eye tear STATE (open eye: closed eye) 95 - 101 823.4 841.5 +1 1.5: 1 84- 88 671.5 689.5 +1 1.9 : 1 89-94 814.5 832.6 +1 1.7: 1 102-108 927.6 936.6 +1 2.4: 1 156 - 166 649.4 658.3 +2 1.4: 1 1 Observed mlz for do-butyl ester. ¥ Observed mlz for d10-butyl ester. • Average observed ratio of do- I d10- butyl esters. 208 Table 6.3. Proteins that were found to be more abundant in open eye tear in comparison to closed eye tear. * OBSERVED RATIO PROTEIN (open eye: closed eye) Lysozyme 5: 1 Tear lipocalin 1.7: 1 Transforming growth factor ~-2 1.5:1 Transcobalamin 1 2: 1 Fibroblast growth factor 1 1.5 : 1 Hepatocyte growth factor 1.5:1 Catalase 5:1 Prolactin inducible protein 1.5:1 • Average observed ratio of do-/ d1 0- butyl esters. 209 Table 6.4. Proteins that were found to be more abundant in closed eye tear in comparison to open eye tear. * OBSERVED RATIO PROTEIN (open eye: closed eye) Plasminogen 1 : 10 Serotransferrin 1 : 3 von Willebrand factor 1 : 10 Serum albumin 1 : 3 Apolipoprotein A 1: 2 Immunoglobulin A 1 : 3 Lymphotoxin a 1: 2 Interferon fi 1 : 3 • Average observed ratio of do-/ dw- butyl esters. 210 6.4. Discussion Proteins in open and closed eye tear were identified and the relative abundances of some of these were determined following proteolytic digestion and esterification with either butanol or deuterium labeled butanol. Esterification results in an increase in mass of multiples of either 56 Da ( do-butanol) or 65 Da ( d 10-butanol) due to modification of the C-terminus of each peptide, as well as aspartic acid and glutamic acid residues. The observed mass difference between each peptide pair is dependant on the charge state of the peptides, as well as the number of butyl groups incorporated in each peptide. The use ofbutanol and its deuterated isotopomer ensures a measurable mass difference between higher order charge states of the same peptide and controls for variations in physiochemical properties and ionisation efficiencies for each co-eluting peptide pair. Current methods of protein quantification include the use of appropriate antibodies, autoradiography or densitometry and require complete separation of the proteins of interest, usually by chromatographic approaches or gel electrophoresis [Krull et al., 1997; Weller, 2000]. The technique described here enables multiple proteins to be quantified in a single analysis and does not require prior separation of proteins. Additionally, multiple peptides derived from the same protein can be used to measure independently the relative abundance of each protein, and therefore improve the accuracy and precision of the quantitative determinations. In this study the accuracy and precision of the approach was determined using horse apomyoglobin as the model protein. Following digestion and derivatisation with either do- or d10- butanol, equal aliquots of each were combined. Analysis of the combined sample by ESI-LC/MS revealed that the observed ratio (1.03) for this analysis was not 211 significantly different from the expected ratio (1.00). Furthermore, the co-efficient of variation for these determinations was found to be 18%. This indicates that this technique can be used to accurately measure changes in protein expression and enables modest changes (i.e., - 2 fold increase or decrease) in protein abundances to be assessed. Although the deuterium labeled peptides co-eluted at a slightly earlier retention time than the corresponding unlabeled peptide [Masters et al., 1988; Gygi et al., 1999; Goodlett et al., 2001], this did not affect the accuracy of the quantitative determination. This technique was employed to measure the relative abundance of over 20 different proteins in tear fluid obtained from the open and closed eye states. At least three different peptides derived from the same parent protein were employed for each measurement. Several serum-based proteins were found to be elevated in closed eye tear, and in comparison, various growth factors and lacrimal gland derived proteins were found to be more abundant in open eye tear. These findings are supported by other studies, where serum proteins such as albumin, vitronectin and fibronectin, have been found to increase in abundance in closed eye tear [Sack et al., 1994; Fukuda et al., 1996; Sack et al., 1997]. Other proteins such as lactotransferrin and lacrimal proline rich protein were equally abundant in both open and closed eye tear [Sack et al., 1992]. In contrast to other techniques, such as ICAT, that have been developed for the global quantification of peptides and proteins, the approach described here is not selective for a particular amino acid residue (i.e., cysteine) [Gygi et al., 1999]. Instead, this technique involves a simple chemical reaction that is directed toward acidic functional groups (i.e., C-terminus of all peptides). As a result, all proteins present in a sample can be 212 quantified and multiple peptides derived from each can then be used to determine the relative changes in protein expression. However, because the ICAT reagent incorporates a biotin affinity tag, labeled peptides can be selectively isolated using avidin affinity chromatography. By reducing the complexity of the sample, quantification of proteins present at low abundance can be facilitated. For instance, in this study only a limited number of proteins in tear fluid could be detected and their relative quantities determined. Also of consideration is the dynamic range of this quantification technique. This is dependant on the complexity of the sample as well as the instrument employed. Although an ion trap mass spectrometer offers limited dynamic range and precision in comparison with other mass spectrometers, the dynamic range can be improved by reducing sample complexity. Protein quantification techniques that are based on relative levels of proteolytic peptides, such as quantification using butyl esterification, are not able to distinguish between different in vivo forms of the intact protein, and therefore can be misleading. However, the technique described here can be applied to quantify any pair of separated proteins, for example, in comparative or functional proteomic studies where protein isoforms and modified proteins can be separated by 2DE. This technique is highly versatile and can be employed to measure the relative amounts of proteins in a variety of biological systems. 213 CHAPTER 7 DISCUSSION 214 7 .1. Discussion Over the last decade, mass spectrometry has emerged as a powerful tool for protein and peptide analysis. Both MALDI-TOFMS and ESI-MS have matured to the point where they offer the sensitivity and specificity required to detect peptides and proteins in complex biological samples and these complementary approaches are now considered the primary tools for peptide and protein characterisation. The ability to obtain data such as peptide mass fingerprints and/or partial amino acid sequence on trace quantities of a protein has proved invaluable in the area of protein analysis. Further, extensive protein databases and database search algorithms that utilise the mass spectrometric data can now unambiguously identify proteins on a global scale. This allows the discovery of potentially important protein candidates that may be relevant to a particular biological process or disease. These developments, coupled with the ready availability of commercial mass spectrometers, have enabled protein identification to become routine in many laboratory settings. However, the dynamic nature of the protein complement of a cell still poses significant challenges. The techniques to detect, characterise and quantify biologically relevant proteins that are differentially expressed or post-translationally modified are not readily available, and biochemical methods remain essential to determine the significance of a particular protein in a biological or disease process, or its potential impact on therapeutic strategies. Proteomics has emerged as an important technology for protein characterisation and involves the use of integrated protein separation and identification strategies. The comer stones are gel electrophoresis and mass spectrometry, but there are continual 215 refinements and concurrent development of alternative approaches. For instance, comparative proteomics, which involves the analysis of protein expression between two (or more) different states of a biological system, shows considerable promise for the identification of biomarkers of disease, and to determine potentially important proteins involved in specific cellular functions. This approach requires complete resolution of protein isoforms, unambiguous identification of each protein and its modification, as well as an accurate measurement of the changes in the expression of each protein. Before studies such as these become routine, the limitations of the current strategies must be addressed, or alternative technologies considered. 7 .2. Protein identification strategie~ To completely describe a proteome, practical integrated strategies to separate, detect and identify peptide and protein constituents are required. Unambiguous identification of multiple proteins represents the initial step in elucidating their potential biological role, and there have been many different strategies described to undertake this process [Shevchenko et al., 1996; Yates et al., 1997; Link et al., 1999; Patton, 1999]. Although these strategies employ a variety of separation procedures, such as electrophoretic or chromatographic techniques, mass spectrometry is now common to the protein identification process. Prior to mass spectrometry, proteins were identified using Edman degradation or by amino acid analysis but these techniques neccesitated high sample purity and homogeneity to be successful. Mass spectrometry, in particular MALDI and ESI mass spectrometry, provides the sensitivity and certainty necessary to unequivocally identify a protein in biological samples without these restrictions. Proteins can be identified following enzymatic or chemical degradation to generate 216 unique peptides that can then be mass measured by MALDI-TOFMS (i.e., a peptide mass fingerprint or peptide mass map) [Henzel et al., 1993; J atnes et al., 1993; Mann et al., 1993; Pappin et al., 1993; Yates et al., 1993; Cottrell, 1994], or the atnino acid sequence of one or more of the proteolytic peptides can be obtained using tandem mass spectrometry [Mann and Wilm, 1994; Yates et al., 1995]. Protein identifications are then achieved by searching these data directly against the publicly available protein or genomic databases. Although many protein detection and identification strategies have been described, most of these are not suitable for the analysis of endogenous levels of free peptides. These peptides are often not retained by gel electrophoresis, or ifESI-LC/MS/MS is employed, these endogenous peptides are not able to be distinguished from those that were generated by the initial proteolytic step. Peptides, such as neuropeptides and growth factors are usually secreted into the general circulation and interact with receptors, usually in an endocrine or paracrine manner, to regulate many physiological processes [Verhaert et al., 2001]. As a result, strategies that enable facile analysis of peptides are important in monitoring the function of biological systems. By directly analysing biological tissues or fluids by MALDI-TOFMS, the accurate mass of endogenous peptides can be determined, and mnino acid sequence information can be obtained by MALDI-PSD, by another form of tandem mass spectrometry or by de novo sequencing. 217 7.2.1. Two dimensional gel electrophoresis and peptide mass f"mgerprinting The current accepted approach for protein identification involves separation by gel electrophoresis, in particular two dimensional gel electrophoresis (2DE), followed by peptide mass fingerprinting and database searching. This strategy, first described in 1993 [Henzel et al., 1993; James et al., 1993; Mann et al., 1993; Pappin et al., 1993; Yates et al., 1993 ], involves generating a set of peptide masses by proteolytic digestion and MALDI-TOFMS, then matching these experimentally derived peptide masses with those calculated from in silico digestion of all the proteins in the database. For a positive identification, it has been suggested that a minimum of 4 peptides accurate to within 10 ppm of their theoretically calculated mass is required [Clauser et al., 1999]. This criterion is easily achieved with current MALDI-TOFMS technology. In addition to this, sequence tags derived from tandem mass spectrometry can also be used to confirm an identity [Mann and Wilm, 1994; Wilkins et al., 1998]. Importantly, as it stands, no single strategy is capable of delivering all the data that is necessary to determine the relevant information in a proteomics study. As a part of this study, two dimensional gel electrophoresis combined with peptide mass fingerprinting was employed as a first step to detect and unambiguously identify proteins in human seminal fluid. Separation by 2DE allowed detection of more than 300 discrete protein spots, however, subsequent analysis by MALDI-TOFMS identified only 32 unique proteins. The remainder of the proteins detected were found to be post translationally modified forms of these 32 proteins, e.g., multiple forms of prostate specific antigen and prostatic acid phosphatase were detected. Additionally, numerous truncated forms of serum albumin, semenogelin I and semenogelin II were identified. These :findings indicate that there is extensive proteolytic activity in seminal fluid, and 218 this is supported by the numerous enzymes that were also identified. The detection of multiple forms of any single protein would not be possible using any of the current alternative protein identification strategies, such as ESI-LC/MS/MS analysis of proteolytically derived peptides. Although one dimensional gel electrophoresis in combination with capillary ESI LC/MS/MS identified over 100 different proteins in seminal fluid, some modified proteins could not be detected or identified in this way. By contrast, high mass proteins and basic proteins that are not amenable to 2DE separations, such as fibronectin and histone proteins, were identified by this technique. This approach also identified many more proteins than 2DE and these data highlight some of the problems associated with the 2DE process. For example, some protein classes are known to stain poorly with Coomassie or silver staining techniques and this reduces their ability to be detected [Rabilloud, 2000]. Additionally, some proteins are present at low abundance and are not readily detectable by 2DE; identification of other protein spots is confounded by the presence of comigrating proteins. For instance, at least 7 excised spots were found to contain more than one protein when seminal fluid was separated by 2DE (see Tables 4.2 and 4.4, p 124 and 129 respectively). Consistent with this finding, the presence of at least 6 unique proteins has been reported within one discrete protein spot [Gygi et al., 2000]. Therefore, improvements in current 2DE technology are required to address issues such as difficulties in detecting low abundant proteins, the co-migration of proteins, and the inability to adequately resolve high mass proteins, hydrophobic proteins and basic proteins. Solutions are being continuously described in the literature, including sample 219 pre-fractionation strategies and the application of narrow range immobilised pH gradient strips that improve protein separation and enable detection of low abundant proteins [Zuo and Speicher, 2000; Zuo et al., 2001]. Also, sensitive fluorescent protein stains, such as Sypro Red and Sypro Orange, capable of detecting low femtomoles of a protein, have also been described [Steinberg et al., 1996a; Steinberg et al., 1996b; Harvey et al., 1998; Berggren et al., 2000; Guttman et al., 2000; Lopez et al., 2000; Patton, 2000; Steinberg et al., 2000a; Steinberg et al., 2000b; Valdes et al., 2000; Yan et al., 2000; Lauber et al., 2001; Tonge et al., 2001]. Although the exact nature of the interaction between proteins and these stains has not been defined, these fluorescent stains are believed to bind noncovalently with proteins. In contrast to conventional silver and Coomassie blue staining, the staining properties of fluorescent dyes are not dependant on any specific chemical interaction with amino acid residues [Rabilloud, 2000; Yan et al., 2000]. As a result, protein detection using fluorescent stains is less dependant on amino acid sequence. These stains also have the added advantage of being able to detect proteins over a wide linear dynamic range, thereby facilitating quantitative protein analysis [Lopez et al., 2000; Yan et al., 2000]. 7.2.2. Direct analysis of proteins by ESI-LC/MS/MS To overcome the problems associated with 2DE some investigators have adopted an approach involving direct analysis of proteolytically derived peptides following chromatographic separation [McCormack et al., 1997; Yates et al., 1997; Link et al., 1999; Yates et al., 2000; Davis et al., 2001; Washburn et al., 2001]. In contrast to 2DE and peptide mass fingerprinting, separation of proteins prior to analysis is not required and amino acid sequence data for each peptide can be obtained by ESI tandem mass 220 spectrometry. These data are then compared with the available protein and genomic databases. This technique involves minimal sample preparation and because of the increased information content of sequence data, the probability of detecting and identifying proteins present at low abundance is enhanced. Also, by combining different chromatographic separations in series, such as ion exchange chromatography followed by reverse phase chromatography, a greater number of peptides can be detected than with a single stage of chromatography. This two dimensional chromatography mass spectrometric approach for protein identification has been termed MuDPIT [Yates et al., 1997; Link et al., 1999]. This technique enables proteins that are not amenable to electrophoretic separation, such as hydrophobic proteins or high mass proteins, to be identified. However, because this technique only requires the sequence ofup to 6 amino acids for a positive protein identification [Wilkins et al., 1998], it does not routinely deliver high sequence coverage of the protein, nor are post-translational modifications usually identified. In the work detailed in this thesis, LC/MS/MS of proteolytically generated peptides was employed to identify proteins in the human tear film. An aliquot of tear fluid was digested with trypsin and the proteins identified by capillary ESI-LC/MS/MS and database searching. This approach enabled more than 400 different proteins to be unambiguously identified, including known constituents of human tear such as tear lipocalin, lactotransferrin, lysozyme and secretory lgA. Proteins that have not been previously detected in tear fluid were also detected and identified. The tear fluid is also reported to contain a large number of modified proteins, such as glycoproteins, truncated proteins and N-terminally processed proteins as well as isoforms of proteins such as lactotransferrin and Zn-a-2-glycoprotein [Coyle et al., 1989; Fullard and 221 Kissner, 1991; Kuizenga et al., 1991; Molloy et al., 1997; Jumblatt et al., 1999; McKenzie et al., 2000]. Although numerous proteins were identified, modified proteins and protein isoforms could not be distinguished. This study has also demonstrated that LC/MS/MS is a rapid approach for the identification of proteins in complex biological samples where tandem mass spectra only are obtained on one or two peptide(s) derived from the precursor protein. Additionally, this approach may be superior to 2DE in some respects, especially because peptide mass fingerprinting does not always yield a positive protein identification due to the presence of contaminants or peptides derived from more than one protein. 7.2.3. Detection and identification of endogenous peptides in biological samples The techniques described above are able to identify proteins with high confidence; however, they are not compatible for the analysis of endogenous peptide components. Peptide components in biological fluids or tissues can only be detected by direct analysis of the sample employing either MALDI-TOFMS or ESI-MS. This allows the accurate masses of the endogenous peptide components to be determined, and post source decay (PSD) or tandem mass spectrometry can also be employed to obtain information pertaining to the amino acid sequence of each individual peptide [Jespersen et al., 1999; V erhaert et al., 2001]. In this thesis, the direct analysis of human tear fluid by MALDI-TOFMS enabled the intact mass of numerous abundant peptide and protein components to be accurately 222 determined. In addition, PSD analysis allowed the sequence of five of the more abundant peptides to be elucidated. Further investigations revealed that these peptides were derived from the C-terminus of a lacrimal proline-rich protein that had not previously been detected in human tear fluid [Dickinson and Thiesse, 1995]. Subsequent studies employing size exclusion chromatography and MALDI-TOFMS analysis confirmed the presence and identity of a truncated form of this protein in tear fluid. This demonstrates the potential ofMALDI-TOFMS in identifying the circulating form of peptides and proteins in biological fluids, especially because peptides and low mass proteins are often not detected by standard gel electrophoretic techniques. A combination ofMALDI-TOFMS and capillary ESI-LC/MS/MS was also employed to detect and identify the endogenous peptide constituents in human seminal fluid. MALDI-TOFMS enabled the accurate intact mass of peptides to be determined and ESI-LC/MS/MS enabled the identity of these peptides to be ascertained. Multiple peptide fragments of semenogelin I and semenogelin II were detected, including seminal basic protein, a bioactive peptide derived from semenogelin I [Robert and Gagnon, 1999]. Human seminal fluid is known to contain many proteolytic enzymes, and the presence of these peptides is indicative of the high level of enzymatic activity. In this case, the ability to detect peptide components may prove valuable in deciphering the biological role of many of the protein constituents. For instance, semenogelin I and II are known to be the major components of the seminal coagulum which is rapidly degraded by proteases upon ejaculation [Malm et al., 1996; Peter et al., 1998; Robert and Gagnon, 1999]. The presence of these peptide fragments, and the observation that the terminal amino acid residues of these peptides were consistent with cleavage by 223 prostate specific antigen supports their putative role in sperm motility [Robert and Gagnon, 1999]. 7.3. Characterising protein post-translational modifications Although the human genome has been reported to encode for approximately 30,000 unique proteins, it is widely believed that many more proteins exist in vivo [Kellner, 2000]. This discrepancy is due to protein modifications, and the synthesis of protein variants and isoforms as a result of gene splicing and frameshift mutations. Modifications such as these can not be predicted from DNA sequences and can only be determined using proteomic strategies. There are many documented protein modifications that may occur in the cell. These include oxidation, amino acid substitution, acetylation, acylation, amidation, phosphorylation and glycosylation. Proteins often require specific modifications to prolong their stability or halflife, to determine their subcellular localisation or to effect specific biological function (e.g., cleavage of a prepro-protein precursor to its bioactive form). In addition, some of these modifications, such as the phosphorylation of proteins involved in signal transduction pathways, are often reversible. Hence, the ability to isolate and detect the modified protein(s) of interest, as well as to identify the type and site of modification, will aid our understanding of many biological processes. 224 7.3.1. Detection and isolation of modified proteins The separation of seminal fluid proteins by 2DE identified multiple forms of many proteins. For example, multiple forms of serum albumin, prostate specific antigen, lactotransferrin and prostatic acid phosphatase were detected and these modified proteins were found to migrate at a different isoelectric point and/or molecular weight when compared to their native form, i.e., when compared to their theoretical isoelectric point and mass (Chapter 4, Figures 4.1 - 4.2 and Tables 4.1 - 4.4, p 116 - 129). Although 2DE remains the most effective biochemical method for the separation of complex protein mixtures and enables visualisation of modified proteins, it only provides the approximate molecular weight for each protein [Klose and Kobalz, 1995; Lopez, 1999]. Characterisation of post-translational modifications can be aided by obtaining the accurate molecular weight of the intact protein prior to proteolysis. Mass spectrometry is a sensitive technique for accurately determining the molecular weights of proteins. For instance, MALDI and ESI enable large non volatile molecules to be ionised and mass analysers, such as the time-of-flight mass analyser, offer superior resolution and mass accuracy than gel electrophoresis. The interfacing ofMALDI or ESI with the appropriate mass analyser allows modified proteins to be identified by the distinct mass shift from its predicted mass. For example, phosphorylation would result in a mass increase of 80 Da, and acetylation results in a mass increase of 42 Da. However, small mass differences, such as those that occur as result of amidation (increase in 1 Da) or amino acid substitutions (e.g., a substitution of glutamine for glutamic acid results in a mass increase of 1 Da) are not easily measurable by mass spectrometric analysis of intact proteins. However, these modifications often result in pi changes allowing detection and identification by 2DE [Larsen and Roepstorff, 2000]. 225 Despite the popularity and widespread use of 2DE, there are many difficulties associated with improving the compatibility of electrophoretically separated proteins with direct analysis by mass spectrometry. The efficiency with which intact proteins can be extracted from gel pieces, whether by electroelution or by chemical means, is low [Eckerskom et al., 1997; Mirza et al., 2000], and direct MALDI analysis of gel pieces often does not yield the sensitivity or mass resolution required to confidently assign a mass and hence identify a particular type of modification [Ogorzalek Loo et al., 1997]. To overcome these problems, alternative methods for protein separation and isolation that are more compatible with mass spectrometric analyses are therefore required. Alternative methods for protein purification and isolation include various chromatographic techniques (e.g., reverse phase, affinity chromatography, ion exchange chromatography). There have been several reports of coupling on-line chromatographic separation, in particular reverse phase chromatography, to mass spectrometry for the analysis of whole proteins. For instance, Opiteck et al. (1997) have developed a technique that utilises on-line chromatographic separation interfaced to a quadrupole mass spectrometer for the direct analysis of complex protein mixtures. Alternatively, there have been reports of successful direct deposition of chromatographic eluent on to a MALDI target for subsequent analysis, thereby eliminating the need for fraction collection [Zhang and Caprioli, 1996; Miliotis et al., 2000]. Although this has only been demonstrated for low mass molecules such as peptides, it can potentially be adapted for the separation of complex protein mixtures. In addition to chromatographic analysis, other investigators have attempted to directly analyse intact proteins by MALDI- 226 TOFMS following separation by solution phase isoelectric focusing although this approach still requires manual :fraction collection [Loo et al., 1999; Walker et al., 2001]. 7.3.2. Identifying post-translational modifications Although the identity of modified proteins can be achieved using standard proteomic techniques, these do not adequately address the difficulties associated with the characterisation of extensively modified proteins. For example, peptide mass fingerprinting (or mapping) involves the matching of a set of proteolytically derived peptide masses to those derived from known proteins entered into a specific database. The available protein databases contain the primary amino acid sequence of genetically encoded proteins and do not include information concerning potential modifications. Therefore, if a protein is extensively modified, the resulting set of proteolytic peptide(s) containing the modification(s) will not match the theoretically calculated peptide mass(es ), thereby hindering identification of the protein [Larsen and Roepstorff, 2000]. High sequence coverage of a protein is also required before a modification can be confidently assigned, and although this is best achieved by peptide mass fingerprinting, it is often hindered by the reduced ionisation efficiencies of some proteolytic peptides and signal suppression effects that occur during the MALDI ionisation process. As a result, modifications can often only be localised to a small segment of the protein. However, modifications can still be identified by comparing the experimentally determined peptide masses with those predicted from the database, and the modification predicted from the shift in mass from its theoretical value. 227 Alternatively, the nature and site of modification can be established with peptide sequence information derived from either MALDI-PSD or ESI tandem mass spectrometry. This strategy has been most successfully employed to identify sites of protein phosphorylation and glycosylation [Larsen and Roepstorff, 2000; Yanagida et al., 2000; Oda et al., 2001]. Nevertheless, the specific site of modification can be difficult to determine, especially because tandem mass spectrometry rarely yields the full sequence of a peptide. Both computer search algorithms and de novo sequencing methods are usually required for accurate interpretation of the mass spectral data and confirmation of the specific site of modification. In some instances, the site of modification can be localised to a particular amino acid residue (e.g., glycosylation at threonine, serine or asparagine residues, amidation at acidic residues, or N-terminal acetylation) simplifying interpretation of the product ion spectrum. Both MALDI-TOFMS and ESI-MS are valuable for the detection and identification of modified proteins. For example, in this thesis, MALDI-TOFMS was used to detect and identify a truncated form oflacrimal proline-rich protein in human tear fluid following its isolation by size exclusion chromatography. The intact mass of the protein was determined by MALDI-TOFMS and then ESI-LC/MS/MS was employed to confirm the identity of the protein following digestion with multiple enzymes (trypsin and Asp-N). This strategy established that the mass of the secreted form of this protein (11,733 Da) was consistent with residues 18- 121 of the predicted protein (from the DNA sequence) and that the 13 C-terminal residues were cleaved in vivo to form a series of homologous peptides. Proteolysis of the isolated protein with multiple enzymes confirmed the identity of the protein and enabled more than 50% sequence coverage of the protein (See Figure 3.5, p 79). The truncated form of the lacrimal proline-rich protein could not 228 be detected when tear fluid was proteolytically digested and directly analysed by ESI LC/MS/MS. Only two peptides corresponding to residues 82-97 and 127-134 of the full length protein were detected by this approach. The trend toward lower flow liquid chromatography (flow rates of30 nL/min have been reported [Wilm and Mann, 1996]) is rapidly establishing ESI-MS as the tool of choice, especially when this ionisation technique is coupled with hybrid mass analysers such as the quadrupole time-of-flight: low flow liquid chromatography allows both separation of individual peptides and high sensitivity. Further, high mass accuracy can be obtained with a quadrupole time-of-flight mass analyser [Morris et al., 1997; Borchers et al., 2000; Kristensen et al., 2000; Ma et al., 2001; Macek et al., 2001; Steen et al., 2001]. The ability to obtain the sensitivity and mass accuracy that these instruments can provide is essential in the area of functional or comparative proteomics where modified proteins may be important determinants of cellular function. 7.4. Protein quantification Another important requirement of a protein analysis strategy is the ability to accurately quantify the protein(s) of interest; or at least to be able to measure changes in protein expression in response to various stimuli. Quantification by mass spectrometry is capable of offering a level of sensitivity and specificity not available by other commonly employed protein quantification methods such as chromatographic, immunoaffinity or immunochemical techniques, but this area is not well developed at this time. Because there is a poor correlation between measured mRNA levels and protein expression in the cell [Anderson and Seilhamer, 1997; Gygi et al., 1999b], 229 protein quantification is particularly important. In addition, quantification is essential in areas where proteomics is applied to the search for biomarkers or indices of therapeutic efficacy, or when alterations in the level of expression of modified proteins may result in perturbations in cellular function. 7 .4.1. Relative quantification of proteins There are examples describing the measurement of the relative expression levels of individual proteins by densitometry following 2DE separation [Newsholme et al., 2000; Poirier et al., 2001; Yoo et al., 2001]. Although it maybe possible to estimate the relative abundance of a protein in this manner, the reproducibility, dynamic range, accuracy and precision with which this determination can be made is less than ideal [Tonge et al., 2001]. These studies are highly dependant on gel to gel reproducibility and the accuracy of gel comparison and matching software algorithms available. These methods also assume efficient staining of all proteins present in the sample, i.e., that all proteins have the same chemical response to the chosen stain [Pleissner et al., 1999; Kriegel et al., 2000; Voss and Haberl, 2000]. A recent study has highlighted the limitations of gel to gel reproducibility with respect to protein spot pattern and spot density and the consequences for protein quantification [Voss and Haberl, 2000]. Mass spectrometric techniques that measure the relative abundance of proteins by differential mass tagging of proteolytically derived peptides have been described [Schnolzer et al., 1996; Gygi et al., 1999a; Ji et al., 2000; Munchbach et al., 2000; Goodlett et al., 2001; Wang et al., 2001; Yang et al., 2001; Wang et al., 2002]. These strategies can be employed to determine the differences in the relative expression of 230 proteins on a global scale, or they can be applied to specific proteins following their separation by 2DE. These methods, however, are only capable of measuring modest changes in protein expression and require efficient labeling of all peptides. The quantification of modified proteins presents additional analytical challenges because these proteins are often present at low abundances and modifications may be transient in nature. One study described in this thesis involved the development of a technique that allows the relative abundance of multiple proteins in a sample to be determined. Proteins in open and closed eye tear fluid were reacted with either do-butanol or d10-butanol resulting in esterification of the C-terminal residues of each peptide as well as aspartic acid and glutamic acid residues. The relative amounts of more than 20 proteins in open and closed eye tear fluid were measured using this approach, and multiple peptides from each protein were employed in the analysis. In contrast to the ICAT approach, this technique allows all peptides in the mixture to be quantified because it does not target a single amino acid residue, e.g., cysteine. Because all peptides can be used for quantification, this approach has the potential to improve the accuracy with which changes in protein expression can be measured. Although this approach is able to accurately measure changes in protein expression, subtle changes are not able to be precisely determined (i.e., less than 2 fold differences). Approaches such as this, however, presents an alternative for the quantification of biologically important proteins that have been previously isolated using standard chromatographic or electrophoretic approaches. 231 7 .4.2. Quantification of intact proteins Most of the approaches available for determining the relative level of proteins in a sample involve derivatisation of proteolytic peptides and subsequent detection by ESI or MALDI mass spectrometry [Schnolzer et al., 1996; Gygi et al., 1999a; Oda et al., 1999; Ji et al., 2000; Munchbach et al., 2000; Conrads et al., 2001; Goodlett et al., 2001; Smith et al., 2001; Wang et al., 2001; Yao et al., 2001; Wang et al., 2002]. There is currently no established inass spectrometric technique available to measure the relative or absolute levels of intact proteins. MALDI-TOFMS has been well established as a sensitive approach for qualitative analysis of peptides and proteins. In addition to rapid analysis times and high mass accuracy, analysis of peptides and proteins by MALDI-TOFMS primarily yields the singly protonated molecule simplifying interpretation of the data. In this thesis the absolute quantification of proteins and peptides has been examined by MALDI-TOFMS following their extraction from an appropriate biological matrix (i.e., rat growth hormone in pituitary gland, insulin in human pancreatic tissue and L VV-hemorphin-7 in adrenal gland extract). Linear calibration curves were obtained for all analyses and the values obtained by MALDI-TOFMS for each analyte were consistent with those reported by others [Dickerman et al., 1971; Cerpa-Poljak et al., 1997]. Because MALDI-TOFMS is able to measure the intact mass of proteins, it can also be employed to determine the degree of modification of a chosen protein provided that the two species, i.e., the modified and unmodified form, can be adequately resolved. However, problems may arise due to the heterogeneity of the modification; for example, a protein may contain multiple potential sites for phosphorylation and care must be 232 taken to ensure that only one modified species is being detected and quantified. To overcome these types of difficulties, adequate separation of the protein of interest is required. Selection of the appropriate internal standard is also an important factor for the accurate quantification of proteins by MALDI-TOFMS. The optimum standard is a homologous protein, e.g., obtained from another species, or from the same protein family. Alternatively, the protein of interest can be purified following its expression in cell culture maintained in isotopically enriched media. Internal standards such as these will minimise problems associated with different ionisation efficiencies and other physical and chemical properties important in the isolation and purification steps. Although it has been demonstrated that proteins can be accurately quantified by this approach, this application ofMALDI-TOFMS requires additional development. As it stands, it is limited by the dynamic range and the poor sensitivity for high mass molecules. Issues relating to dynamic range and protein solubility can be overcome by selecting the appropriate matrix molecule and solvents [Cohen and Chait, 1996], especially because the number of potential organic molecules that can be employed as suitable MALDI matrices is continuously expanding [Fitzgerald et al., 1993; Bai et al., 1996; Krause et al., 1996; Zhu et al., 1996; Nonami et al., 1998; Ayorinde et al., 1999; Vandell and Limbach, 1999]. MALDI-TOFMS offers many advantages for the quantitative analysis of proteins, such as minimal sample preparation and fast analysis times, but it is not amenable to on-line separation techniques. Therefore, proteins must still be purified and isolated off-line to 233 yield the most accurate and precise results. This relies on traditional protein purification techniques such as various chromatographic separations and/or immunoaffinity separations. For example, glycoproteins can be purified using lectin chromatography or affinity-based methods and phosphorylated peptides and proteins can be isolated by employing immobilised metal affinity chromatography [Kobata, 1994; Hage, 1999; Li and Dass, 1999; Posewitz and Tempst, 1999]. The use of microscale sample preparation methods such as on-target immunoaffinity capture of both analyte and internal standard has been described [Nelson et al., 1995; Tubbs et al., 2001]. This approach involves modification of a MALO I target, e.g., by the incorporation of antibodies that are targeted toward the protein of interest. This requires low sample volume and potentially offers fast and specific analysis because extensive purification and concentration of the analyte is unnecessary. In addition, the mass accuracy offered by MALDI-TOFMS can be employed to increase selectivity. The ability ofMALDI-TOFMS to discriminate proteins based on mass becomes important when quantifying potential biomarkers, especially since antibodies are capable of recognising multiple epitopes and are not able to distinguish between multiple forms of the same protein that are present in vivo. By employing MALDI-TOFMS, only the protein of interest is quantified. 7 .5. Alternative technologies for proteomic studies Current interest in proteomics is primarily concerned with the identification of proteins, differential expression of proteins in tissues or fluids obtained from normal and disease states, and in cell culture systems maintained under different conditions. Although mass 234 spectrometry has been established as the tool of choice for the detection and identification of peptides and proteins, it is well recognised that current separation techniques, such as 2DE or HPLC, are biased toward abundant proteins. As a result, approaches to enrich for particular classes of proteins are being investigated and are proposed to facilitate the detection of biologically important proteins that may provide an insight into cellular function or disease mechanism. For example, tissue samples are composed of many different cell types. Isolation and enrichment of specific cell populations from tissue samples by laser capture microdissection is valuable in comparative proteomic studies where abnormal cells can be selectively separated from surrounding non-affected cells. This enables potential biomarkers to be established and may also provide an insight into the possible role of proteins in the disease mechanism [Banks et al., 1999; Simone et al., 2000; Bichsel et al., 2001; Paweletz et al., 2001]. Proteins from the isolated cell population can then be extracted and analysed by common proteomic techniques. Similarly, direct analysis of intact biological tissue by MALDI-TOFMS allows regional mapping of the protein components of a tissue or cell. Proteins can be isolated to a specific cellular compartment or to a particular tissue region and this technique also enables the in vivo form of peptides and proteins to be determined [Caprioli et al., 1997; Chaurand et al., 1999; Jespersen et al., 1999; Li et al., 1999; Stoeckli et al., 1999; Stoeckli et al., 2001]. This approach also shows immense potential for detecting and establishing possible biomarkers for the diagnosis of disease, for example, following biopsy. 235 The development and integration of other technologies, such as microfluidics and micro fabrication technology, will overcome some of the limitations of current sample preparation techniques and may lead to improvements in the capabilities of mass spectrometry for protein analysis. At present, there is much interest in coupling microfluidic devices or protein chip arrays to mass spectrometry, primarily to MALDI and/or ESI [Figeys and Aebersold, 1997; Figeys et al., 1998a; Figeys et al., 1998b; Figeys and Aebersold, 1999; Ekstrom et al., 2000; Pinto et al., 2000; Zhang et al., 2000; Ekstrom et al., 2001; Figeys and Pinto, 2001]. These techniques are being developed to address issues in protein analysis relating to the automation of some aspects of the protein identification process such as sample preparation (e.g., sample purification and enrichment), enzymatic digestion of proteins, and peptide and/or protein separation prior to mass spectrometric analysis. Although the implementation of these devices is proposed to increase sample throughput and improve sensitivity [Figeys et al., 1998a; Ekstrom et al., 2001], current concerns are focused on the practical aspects of sample preparation that will be needed to successfully utilise these devices, i.e., the amount of sample required and the final volume necessary for analysis. 236 7 .6. Conclusions The ability to confidently identify proteins represents the initial stage in elucidating the biological function(s) of a protein, and hence its potential importance, in a chosen biological system. The primary structure of a protein is determined by the genetic code of an organism; however, additional information pertaining to secondary or tertiary structure, post-translational modifications, or interactions with other biological molecules must be investigated to understand the underlying mechanisms of a biological process or disease. The major obstacles that exist in the field of proteomics pertain to protein quantification and establishing the nature and extent of protein modification. Currently, MALDI TOFMS and ESI-MS are central components in the development of strategies to overcome these difficulties. The integration of mass spectrometric techniques into established strategies will ensure progress in the ability to relate gene function to protein expression, to direct therapeutic strategies, and to provide an insight into the mechanisms associated with normal biological function or dysfunction. Even though there are many difficulties associated with the analysis of a dynamic biological system where protein expression is constantly changing in response to multiple stimuli, the application of mass spectrometry will be pivotal in deciphering the interactions that exist between these and other biomolecules. 237 7.7. Summary Over the last decade, mass spectrometry has developed to enable the analysis of a wide range of biomolecules over an extensive mass range. In large part this is due to developments in instrumentation and ionization techniques such as electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI) that have enabled the analysis of high mass molecules such as peptides and proteins. Because of these advances, and coupled with the completion of the human genome project, interest in protein and peptide analysis has escalated as investigators attempt to identify potential new protein drug targets and to gain additional insight into disease mechanisms. As a result, there has been considerable interest in the development of methods to detect, identify and quantify peptides and proteins in biological samples. This thesis focuses on the development of mass spectrometric-based proteomic methods and their potential application in the biological sciences. A variety of strategies were examined and compared, including gel electrophoresis, ESI-LCMSMS, MALDI TOFMS and peptide mass fingerprinting. Proteins in human prostatic fluid were characterized using two dimensional gel electrophoresis (2DE) and peptide mass fingerprinting. Proteins were first separated by their isoelectric point (1 st dimension, pi), and are then by their molecular weight using SOS-PAGE (2nd dimension). Two dimensional separation was performed over two different pi ranges (pi 4-7 and 6-11 ), enabling better resolution of proteins, and allowing more proteins to be detected and identified. Over 100 proteins were visualized using this technique. Of these, 73 were positively identified by peptide mass fingerprinting, and these represented 20 unique proteins. For example, multiple forms of prostate specific antigen, prostatic acid phosphatase, clusterin and prolactin-induced 238 protein were all identified. These results highlight the primary strength of 2DE where protein isoforms and modified proteins can be readily detected. Due to some of the limitations of 2DE, such as co-migrating proteins and the inability to resolve basic proteins or high mass proteins, proteins in prostatic fluid were also separated by 1D gel electrophoresis, digested with trypsin and analysed by ESI-LCMSMS. This approach enabled more than 100 proteins to be identified, including proteins that had also been identified by 2DE. Multiple proteins were identified in each band that was excised. Although high molecular weight proteins and basic proteins could be detected and identified, in contrast to 2DE, modified forms of proteins could not be detected by this approach. In addition to gel electrophoresis, an unfractionated sample was also analysed directly by MALDI-TOFMS and ESI-LCMSMS to identify the peptide components in seminal fluid. These peptides and small proteins, which included seminal basic peptide and peptide fragments of semenogelins I and II, were not detected or identified by either of the electrophoretic approaches. In another study, the protein constituents of human tear were characterised by ESI LCMSMS and database searching following complete proteolysis of the sample with trypsin. Analysis of proteolytic peptides by ESI-LCMSMS overcomes some of the shortcomings inherent to 2DE, such as protein solubility and losses due to sample handling, and as a result may allow less abundant proteins to be detected and identified. This approach enabled more than 100 proteins to be identified in less than 10 µL of tear fluid, including many novel proteins that have not been identified in human tear before. Some of the proteins identified include lysozyme, prolactin-induced protein, slgA, tear lipocalin, lactoferrin, complement proteins, serum albumin and various growth factors such as EGF and bFGF. Multiple peptides derived from the same protein were required 239 to identify each protein. Although this technique is able to identify many proteins in a single analysis, it is not able to detect or identify proteins that have been modified. This technique also results in low sequence coverage when compared to the 2DE approach. In addition, human tear was analysed directly by MALDI-TOFMS. As a consequence, the 5 most abundant peptides in tear, which had not previously been described, were sequenced by post-source decay (PSD). These peptides were identified as a homologous family corresponding to the C-terminal portion of a novel lacrimal proline-rich protein. Further fractionation and purification of tear enabled detection of the remaining N terminal portion of the lacrimal proline-rich protein. The intact mass of the in vivo form of this protein was accurately determined to be 11,731 Da (in comparison to the predicted 13,478 Da), consistent with cleavage of the 13 C-terminal residues to form the peptides found in tear. Although this protein displays some homology with a salivary proline-rich protein, the biological function and significance of these proteins is not known. This particular study demonstrated that although ESI-LCMSMS is able to identify many proteins in a small volume of sample, it is riot able to accurately identify the circulating in vivo form(s) of proteins. The study of human tear was extended further to explore a method to determine the relative quantities of proteins in biological samples on a global scale. This method involved the esterification of acidic functional groups with either do- or d10-butanol under anhydrous conditions following complete proteolysis of the sample. In contrast to other protein quantification techniques that utilize differential mass tags ( e.g., ICAT), the method described here is not selective for any specific amino acid residue and therefore allows all peptides to be used for quantification. This method, however, also 240 assumes both complete proteolysis and derivatisation of proteins in the sample. The accuracy and precision of the technique was determined by combining equal amounts of a standard protein, horse apomyoglobin, following proteolysis and esterification (1.03 ± 0.19, CV 20%). By adopting this method, protein expression in normal open eye tear fluid was compared to proteins in tear collected following extended eye closure. Although the protein constituents of open and closed eye tear are the same, it is believed that during prolonged periods of eye closure ( e.g., during sleep) the protein constituents of tear fluid change to reflect an induced state of inflammation resulting from the static nature of the tear fluid during this time. Tear fluid functions to lubricate and supply nutrients to the corneal surface, and to remove cellular debris and waste products. During periods of eye closure, the blink action no longer serves to encourage the continuous flow of tear fluid over the anterior eye surface. In this study, proteins in open eye tear fluid were esterifed with do-butanol and the proteins for closed eye tear esterified with isotopically labeled d10-butanol. This resulted in a mass difference of 9 Da between corresponding peptides derived from each sample. Following esterification, the samples were combined and analysed by ESI-LCMSMS to determine the relative abundance of each protein in the sample. The peak area ratios of multiple peptide pairs derived the same protein were used to determine the relative abundance of each protein in each sample. Proteins that were found to be equally abundant in open and closed eye tear include various complement proteins, lactoferrin and lacrimal proline-rich protein. Proteins found to increase in abundance in open eye tear fluid include tear lipocalin and lysozyme. In contrast, proteins such as plasminogen, 241 von Willebrand factor and slgA were found to be up to 10 times more abundant in closed eye tear. Co-efficients of variation for all determinations were less than 20%. This thesis also explores the potential of MALDI-TOFMS for the absolute quantification of biomolecules, including urinary metabolites, peptides and proteins. MALDI-TOFMS is used extensively for qualitative analysis, such as DNA analysis and peptide and protein identification; however, its use for quantitative analysis is limited, especially in a biological setting. Although this thesis demonstrated that MALDI TOFMS can be used successfully for the absolute quantification of a variety of molecules in a biological setting, some limitations still exist, especially for the quantification oflarge biomolecules such as proteins. For instance, low sensitivity for high molecular weight proteins, a limited dynamic range and low precision need to be overcome before it becomes a routine procedure. Despite these limitations, MALDI TOFMS can be used to accurately quantify biomolecules over an extensive mass range. Homovanillic acid was quantified in human urine, and epinephrine and norepinephrine quantified in adrenal tissue by employing stable isotope labeled internal standards. The peptides LVV-hemorphin- 7 and insulin were quantified in human adrenal gland extract and human pancreatic tissue respectively by employing structural homologues as internal standards (i.e., rat LVV-hemorphin- 7 and porcine insulin respectively). In addition, growth hormone was quantified in rat pituitary gland by incorporating P lactoglobulin as the internal standard. This study revealed that MALDI-TOFMS is a good quantitative tool provided that the appropriate internal standard is used. For instance, correlation coefficients (r2) greater than 0.99 were routinely achieved with each chosen analyte and coefficients of variation (CV) were less than 10%, with the 242 exception of growth hormone where the CV was approximately 20%. The accuracy of the overall technique was determined by independent analysis of the same samples by a commercial laboratory ( e.g., in the case with homovanillic acid), by comparison with a different technique (LVV-hemorphin- 7) or by comparison with literature values (insulin, epinephrine, norepinephrine and growth hormone). This thesis assesses the most common methods for protein identification and highlights the strengths and weaknesses of each. Overall, it was determined that more than one strategy is required to comprehensively identify all proteins in a complex biological sample. 2DE is best utilized to visualize proteins in a sample, including those that have been post-translationally modified, because this often results in a change in pi and/or molecular weight of the protein, and hence changes in gel mobility. However, shortcomings include its inability to separate basic proteins, acidic proteins, high molecular weight proteins, small proteins and peptides and hydrophobic proteins. Alternative strategies such as direct analysis by ESI-LCMSMS following proteolytic digestion are therefore also required. Neither of these techniques, however, is able to detect peptides and/or small proteins(< 10000 Da) in a sample. For the characterization of small proteins and peptides, direct analysis by MALDI-TOFMS is suitable. Peptides can be further sequence by PSD or ESI-LCMSMS and identified by de novo sequencing and/or database searching. In addition, protein and peptide quantification using mass spectrometry was explored using two different approaches: relative quantification of proteins was explored by esterification of tryptic peptides using differential mass tags, and absolute quantification of peptides and proteins was explored using MALDI TOFMS. 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