Single-Cell Proteomics (SCP) can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. In addition to achieving in-depth proteome coverage from single cells, higher throughput measurements enable large-scale and statistically significant features within single cell populations. This dissertation focuses on method development to improve the sensitivity and throughput of SCP based on the nanoPOTS (nanodroplet Processing in One pot for Trace Samples) platform. The methods discussed here include miniaturization of bottom-up proteome sample preparation and liquid chromatography (LC) separations, implementation of an ultrasensitive latest-generation mass spectrometer, development of automated sample handling workflow, and combination of isotopic and isobaric labeling for higher order multiplexing. The miniaturization of sample preparation largely reduced protein loss during sample preparation and enabled in-depth single-cell proteomics. The sensitivity was further improved using a 20-μm-i.d. in-house-packed nanoLC column and the latest generation Orbitrap Eclipse Tribrid mass spectrometer. A >70% increase in proteome coverage was observed for single cells relative to previous efforts using a 30-μm-i.d. LC columns coupled to a previous-generation Orbitrap Fusion Lumos mass spectrometer. To make SCP and low-input proteome profiling accessible to more proteomics laboratories, a fully automated platform termed autoPOTS (automated Preparation in One pot for Trace Samples) was developed using only commercially available instrumentation for sample processing and analysis. AutoPOTS can be used to analyze 1–500 cells with a modest reduction in peptide coverage for 150 cells and a 24% reduction in coverage for single cells compared to the nanoliter preparation. To improve the throughput of SCP, a hyperplexing sample preparation and analysis method for Single-Cell Proteomics (hyperSCP) was developed using a combination of isotopic and isobaric labeling. This method can improve the throughput by at least 28 times with the same gradient compared to the label-free proteomics and can double or triple the throughput of standard tandem mass tag multiplexing.

The utility of 193 nm ultraviolet photodissociation (UVPD) and negative electron transfer dissociation (NETD) for the characterization of peptide anions was systematically evaluated. UVPD outperformed NETD in nearly all metrics; however, both methods provided complementary information to traditional collision induced dissociation (CID) of peptide cations in high throughput analyses. In order to enhance the performance of NETD, activated ion negative electron transfer dissociation (AI-NETD) methods were developed and characterized. The use of low-level infrared photoactivation or collisional activation during the NETD reaction period significantly improved peptide anion sequencing capabilities compared to NETD alone. Tyrosine deprotonation was shown to yield preferential electron detachment upon NETD or UVPD, resulting in N - C[alpha] bond cleavage N-terminal to the tyrosine residue. LC-MS/MS analysis of a tryptic digest of BSA demonstrated that these cleavages were regularly observed under high pH conditions. Transmission mode desorption electrospray ionization (TM-DESI) was coupled with 193 nm UVPD and CID for the rapid analysis and identification of protein digests. Comparative results are presented for TM-DESI-MS/CID and TM-DESI-MS/UVPD analyses of five proteolyzed model proteins. In some cases TM-DESI/UVPD outperformed TM-DESI-MS/CID due to the production of an extensive array of sequence ions and the ability to detect low m/z product ions. 193 nm UVPD was implemented in an Orbitrap mass spectrometer for characterization of intact proteins. Near-complete fragmentation of proteins up to 29 kDa was achieved. The high-energy activation afforded by UVPD exhibited far less precursor ion charge state dependence than conventional methods, and the viability of 193 nm UVPD for high throughput top-down proteomics analyses was demonstrated for the less 30 kDa protein from a fractionated yeast cell lysate. The use of helium instead of nitrogen as the C-trap and HCD cell bath gas and trapping ions in the HCD cell prior to high resolution mass analysis significantly reduced the signal decay rate for large protein ions. As a result, monoclonal IgG1 antibody was isotopically resolved and mass accurately determined. A new high mass record for which accurate mass and isotopic resolution has been achieved (148,706.3391 Da ± 3.1 ppm) was established. / text

Despite tremendous advances in mass spectrometry instrumentation and mass spectrometry-based methodologies, global protein profiling of organellar, cellular, tissue and body fluid proteomes in different organisms remains a challenging task due to the complexity of the samples and the wide dynamic range of protein concentrations. In addition, large amounts of produced data make result exploitation difficult. To overcome these issues, further advances in sample preparation, mass spectrometry instrumentation as well as data processing and data analysis are required. The presented study focuses as first on the improvement of the proteolytic digestion of proteins in in-gel based proteomic approach (Gel-LCMS). To this end commonly used bovine trypsin (BT) was modified with oligosaccharides in order to overcome its main disadvantages, such as weak thermostability and fast autolysis at basic pH. Glycosylated trypsin derivates maintained their cleavage specifity and showed better thermostability, autolysis resistance and less autolytic background than unmodified BT. In line with the “accelerated digestion protocol” (ADP) previously established in our laboratory modified enzymes were tested in in-gel digestion of proteins. Kinetics of in-gel digestion was studied by MALDI TOF mass spectrometry using 18O-labeled peptides as internal standards as well as by label-free quantification approach, which utilizes intensities of peptide ions detected by nanoLC-MS/MS. In the performed kinetic study the effect of temperature, enzyme concentration and digestion time on the yield of digestion products was characterized. The obtained results showed that in-gel digestion of proteins by glycosylated trypsin conjugates was less efficient compared to the conventional digestion (CD) and achieved maximal 50 to 70% of CD yield, suggesting that the attached sugar molecules limit free diffusion of the modified trypsins into the polyacrylamide gel pores. Nevertheless, these thermostable and autolysis resistant enzymes can be regarded as promising candidates for gel-free shotgun approach. To address the reliability issue of proteomic data I further focused on protein identifications with borderline statistical confidence produced by database searching. These hits are typically produced by matching a few marginal quality MS/MS spectra to database peptide sequences and represent a significant bottleneck in proteomics. A method was developed for rapid validation of borderline hits, which takes advantage of the independent interpretation of the acquired tandem mass spectra by de novo sequencing software PepNovo followed by mass-spectrometry driven BLAST (MS BLAST) sequence similarity searching that utilize all partially accurate, degenerate and redundant proposed peptide sequences. It was demonstrated that a combination of MASCOT software, de novo sequencing software PepNovo and MS BLAST, bundled by a simple scripted interface, enabled rapid and efficient validation of a large number of borderline hits, produced by matching of one or two MS/MS spectra with marginal statistical significance.

Despite tremendous advances in mass spectrometry instrumentation and mass spectrometry-based methodologies, global protein profiling of organellar, cellular, tissue and body fluid proteomes in different organisms remains a challenging task due to the complexity of the samples and the wide dynamic range of protein concentrations. In addition, large amounts of produced data make result exploitation difficult. To overcome these issues, further advances in sample preparation, mass spectrometry instrumentation as well as data processing and data analysis are required. The presented study focuses as first on the improvement of the proteolytic digestion of proteins in in-gel based proteomic approach (Gel-LCMS). To this end commonly used bovine trypsin (BT) was modified with oligosaccharides in order to overcome its main disadvantages, such as weak thermostability and fast autolysis at basic pH. Glycosylated trypsin derivates maintained their cleavage specifity and showed better thermostability, autolysis resistance and less autolytic background than unmodified BT. In line with the “accelerated digestion protocol” (ADP) previously established in our laboratory modified enzymes were tested in in-gel digestion of proteins. Kinetics of in-gel digestion was studied by MALDI TOF mass spectrometry using 18O-labeled peptides as internal standards as well as by label-free quantification approach, which utilizes intensities of peptide ions detected by nanoLC-MS/MS. In the performed kinetic study the effect of temperature, enzyme concentration and digestion time on the yield of digestion products was characterized. The obtained results showed that in-gel digestion of proteins by glycosylated trypsin conjugates was less efficient compared to the conventional digestion (CD) and achieved maximal 50 to 70% of CD yield, suggesting that the attached sugar molecules limit free diffusion of the modified trypsins into the polyacrylamide gel pores. Nevertheless, these thermostable and autolysis resistant enzymes can be regarded as promising candidates for gel-free shotgun approach. To address the reliability issue of proteomic data I further focused on protein identifications with borderline statistical confidence produced by database searching. These hits are typically produced by matching a few marginal quality MS/MS spectra to database peptide sequences and represent a significant bottleneck in proteomics. A method was developed for rapid validation of borderline hits, which takes advantage of the independent interpretation of the acquired tandem mass spectra by de novo sequencing software PepNovo followed by mass-spectrometry driven BLAST (MS BLAST) sequence similarity searching that utilize all partially accurate, degenerate and redundant proposed peptide sequences. It was demonstrated that a combination of MASCOT software, de novo sequencing software PepNovo and MS BLAST, bundled by a simple scripted interface, enabled rapid and efficient validation of a large number of borderline hits, produced by matching of one or two MS/MS spectra with marginal statistical significance.

Sample preparation is the most critical step in proteomics as it directly affects the subset of proteins and peptides that can be reliably identified and quantified. Although a variety of efficient and reproducible sample preparation strategies have been developed, their applicability and efficacy depends much on the biological sample. Here, three approaches were evaluated for the human milk and plasma proteomes. Protein extracts were digested either in an ultrafiltration unit (filter-aided sample preparation, FASP) or in-solution (ISD). ISD samples were desalted by solid-phase extraction prior to nRPC-ESI-MS/MS. Additionally, milk and plasma samples were directly digested by FASP without prior protein precipitation. Each strategy provided inherent advantages and disadvantages for milk and plasma. FASP appeared to be the most time efficient procedure with a low miscleavage rate when used for a biological sample aliquot, but quantitation was less reproducible. A prior protein precipitation step improved the quantitation by FASP due to significantly higher peak areas for plasma and a much better reproducibility for milk. Moreover, the miscleavage rate for milk, the identification rate for plasma, and the carbamidomethylation efficiency were improved. In contrast, ISD of both milk and plasma resulted in higher miscleavage rates and is therefore less suitable for targeted proteomics.

Proteins and their intricate network of interactions are fundamental to many molecular processes that govern life. Mass spectrometry-based structural proteomics represents a powerful set of techniques for characterizing protein structures and interactions. The last decade has witnessed a large-scale adoption in the application of these techniques toward solving a variety of biological questions. Addressing these questions has often been coincident with the further development of these techniques. Insight into the structures of individual proteins and their interactions with other proteins in a proteome-wide context has been made possible by recent developments in the relatively new field of chemical crosslinking combined with mass spectrometry. In these experiments crosslinking reagents are used to capture protein-protein interactions by forming covalent linkages between proximal amino acid residues. The crosslinked proteins are then enzymatically digested into peptides, and the covalently-coupled crosslinked peptides are identified by mass spectrometry. These identified crosslinked peptides thus provide evidence of interacting regions within or between proteins. In this dissertation the development of tools and methods that facilitate this powerful technique are described. The primary arc of this work follows the development and application of mass spectrometry-based approaches for the identification of protein crosslinks ranging from those which exist endogenously to those which are introduced synthetically. Firstly, the development of a novel strategy for comprehensive determination of naturally occurring protein crosslinks in the form of disulfide bonds is described. Secondly, the application of crosslinking reagents to create synthetic crosslinks in proteins coupled with molecular dynamics simulations is explored in order to structurally characterize the intrinsically disordered tau protein. Thirdly, improvements to a crosslinking-mass spectrometry method for defining a protein-protein interactome in a complex sample is developed. Altogether, these described approaches represent a toolset to allow researchers to access information about protein structure and interactions. / Graduate