Optimization-Based Peptide Mass Fingerprinting for Protein Mixture Identification

*Motivation:* In current proteome research, peptide sequencing is probably the most widely used method for protein mixture identification. However, this peptide-centric method has its own disadvantages such as the immense volume of tandem Mass Spectrometry (MS) data for sequencing peptides. With the fast development of technology, it is possible to investigate other alternative techniques. Peptide Mass Fingerprinting (PMF) has been widely used to identify single purified proteins for more than 15 years. Unfortunately, this technique is less accurate than peptide sequencing method and cannot handle protein mixtures, which hampers the widespread use of PMF technique. If we can remove these limitations, PMF will become a useful tool in protein mixture identification. 
*Results:* We first formulate the problem of PMF protein mixture identification as an optimization problem. Then, we show that the use of some simple heuristics enables us to find good solutions. As a result, we obtain much better identification results than previous methods. Moreover, the result on real MS data can be comparable with that of the peptide sequencing method. Through a comprehensive simulation study, we identify a set of limiting factors that hinder the performance of PMF method in protein mixtures. We argue that it is feasible to remove these limitations and PMF can be a powerful tool in the analysis of protein mixtures

NBPMF: Novel Network-Based Inference Methods for Peptide Mass Fingerprinting

Proteins are large, complex molecules that perform a vast array of functions in every living cell. A proteome is a set of proteins produced in an organism, and proteomics is the large-scale study of proteomes. Several high-throughput technologies have been developed in proteomics, where the most commonly applied are mass spectrometry (MS) based approaches. MS is an analytical technique for determining the composition of a sample. Recently it has become a primary tool for protein identification, quantification, and post translational modification (PTM) characterization in proteomics research. There are usually two different ways to identify proteins: top-down and bottom-up. Top-down approaches are based on subjecting intact protein ions and large fragment ions to tandem MS directly, while bottom-up methods are based on mass spectrometric analysis of peptides derived from proteolytic digestion, usually with trypsin. In bottom-up techniques, peptide mass fingerprinting (PMF) is widely used to identify proteins from MS dataset. Conventional PMF representatives such as probabilistic MOWSE algorithm, is based on mass distribution of tryptic peptides. In this thesis, we developed a novel network-based inference software termed NBPMF. By analyzing peptide-protein bipartite network, we designed new peptide protein matching score functions. We present two methods: the static one, ProbS, is based on an independent probability framework; and the dynamic one, HeatS, depicts input dataset as dependent peptides. Moreover, we use linear regression to adjust the matching score according to the masses of proteins. In addition, we consider the order of retention time to further correct the score function. In the post processing, we design two algorithms: assignment of peaks, and protein filtration. The former restricts that a peak can only be assigned to one peptide in order to reduce random matches; and the latter assumes each peak can only be assigned to one protein. In the result validation, we propose two new target-decoy search strategies to estimate the false discovery rate (FDR). The experiments on simulated, authentic, and simulated authentic dataset demonstrate that our NBPMF approaches lead to significantly improved performance compared to several state-of-the-art methods

Fully denaturing two-dimensional electrophoresis of membrane proteins: a critical update

The quality and ease of proteomics analysis depends on the performance of the analytical tools used, and thus of the performances of the protein separation tools used to deconvolute complex protein samples. Among protein samples, membrane proteins are one of the most difficult sample classes, because of their hydrophobicity and embedment in the lipid bilayers. This review deals with the recent progresses and advances made in the separation of membrane proteins by 2-DE separating only denatured proteins. Traditional 2-D methods, i.e., methods using IEF in the first dimension are compared to methods using only zone electrophoresis in both dimensions, i.e., electrophoresis in the presence of cationic or anionic detergents. The overall performances and fields of application of both types of method is critically examined, as are future prospects for this field

Power and limitations of electrophoretic separations in proteomics strategies

Proteomics can be defined as the large-scale analysis of proteins. Due to the complexity of biological systems, it is required to concatenate various separation techniques prior to mass spectrometry. These techniques, dealing with proteins or peptides, can rely on chromatography or electrophoresis. In this review, the electrophoretic techniques are under scrutiny. Their principles are recalled, and their applications for peptide and protein separations are presented and critically discussed. In addition, the features that are specific to gel electrophoresis and that interplay with mass spectrometry (i.e., protein detection after electrophoresis, and the process leading from a gel piece to a solution of peptides) are also discussed

Computational methods and tools for protein phosphorylation analysis

Signaling pathways represent a central regulatory mechanism of biological systems where a key event in their correct functioning is the reversible phosphorylation of proteins. Protein phosphorylation affects at least one-third of all proteins and is the most widely studied posttranslational modification. Phosphorylation analysis is still perceived, in general, as difficult or cumbersome and not readily attempted by many, despite the high value of such information. Specifically, determining the exact location of a phosphorylation site is currently considered a major hurdle, thus reliable approaches are necessary for the detection and localization of protein phosphorylation. The goal of this PhD thesis was to develop computation methods and tools for mass spectrometry-based protein phosphorylation analysis, particularly validation of phosphorylation sites. In the first two studies, we developed methods for improved identification of phosphorylation sites in MALDI-MS. In the first study it was achieved through the automatic combination of spectra from multiple matrices, while in the second study, an optimized protocol for sample loading and washing conditions was suggested. In the third study, we proposed and evaluated the hypothesis that in ESI-MS, tandem CID and HCD spectra of phosphopeptides can be accurately predicted and used in spectral library searching. This novel strategy for phosphosite validation and identification offered accuracy that outperformed the other currently existing popular methods and proved applicable to complex biological samples. And finally, we significantly improved the performance of our command-line prototype tool, added graphical user interface, and options for customizable simulation parameters and filtering of selected spectra, peptides or proteins. The new software, SimPhospho, is open-source and can be easily integrated in a phosphoproteomics data analysis workflow. Together, these bioinformatics methods and tools enable confident phosphosite assignment and improve reliable phosphoproteome identification and reportin

Matrix assisted laser desorption/ionization time-of-flight mass spectrometry as a novel assay for the detection of Clostridium difficile toxins A and B

Clostridium difficile infection is a major cause of nosocomial diarrhoea, and can culminate in the life-threatening conditions pseudomembranous colitis and toxic megacolon. Disease is produced in C. difficile infection through the release of toxin A and toxin B. Current diagnostics rely on a combination of immunoassays, histopathological findings, and PCR. Immunoassays, though fast, lack sensitivity compared to more expensive and time-consuming histopathology methods. PCR, though sensitive, only indicates the presence of toxin genes and not whether they are being expressed. Matrix Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry (MALDI-TOF) has been gaining popularity in medical laboratories as a means of identifying bacterial isolates due to high sensitivity and fast turnaround time. The purpose of this study is to investigate MALDI-TOF as a means of detecting the presence of C. difficile toxins A and B. The method developed was based on the proposed cellular processing mechanism of toxin A and B – both are large toxins (approximately 300 kDa) that are endocytosed and undergo a pH-induced conformation change in the early endosome. This causes the active domain and protease domain of the toxin to be translocated into the cytoplasm. Inositol hexakisphosphate, an abundant cystosolic signaling molecule, then binds to the protease domain of the toxin and induces the release of the 63 kDa active toxin. The active component of both toxin A and B glucosylates cellular Rho GTPases, which results in cytoskeleton derangement and cell death. The method developed required fecal material to be prepared as a 1:10 dilution in deionized water followed by filter sterilization. The filtrate volume was then divided into two equal volumes, and each volume was subjected to an acetonitrile precipitation. One pellet was resuspended in deionized water, and the other in sodium acetate buffer (100mM, pH 4.7) to mimic the conditions of the early endosome. The spectra produced from each condition were overlaid, which demonstrated the presence of a high-intensity peak at approximately 60 kDa in known toxin positive specimens. If this peak can be shown to be correlated to the presence of toxin in a larger sample set, this method may hold promise as a means of detecting C. difficile toxins A and B. This protocol avoids the extensive time and labour associated with a mass-fingerprinting approach, while maintaining higher degree of specificity than simple intact protein detection due to the comparison of spectra between acid and neutral conditions

In-Capillary Reduction and Digestion of Proteins at Nano-Liter Volume Using Capillary Electrophoresis

To analyze the proteins present in biological samples several major steps are involved. One of the crucial steps in proteomics has been sample preparation. Prior to mass spectral analysis proteins containing disulfide bonds must be reduced which is followed by digestion. In this work, a novel way of performing protein reduction and digestion at nano-liter volume using capillary electrophoresis is presented. In this work, zone passing CE technique was utilized to analyze the reduction products in CE. After the successful in-capillary reduction, digestion of protein was also performed. A pH mediated stacking was used to bring the reduced protein and trypsin together for digestion. For performing in-capillary reactions, very low amount of sample is needed resulting in the miniaturization of the reaction. MALDI MS was used for detection considering the ease of coupling to the instrument and only nano-liter sample volume was needed for MS analysis

Analysis of peroxynitrite-mediated post-translational modifications of caveolin-1

Caveolin-1 is an important protein in caveolae, which plays a role in cholesterol transport, signal transduction, and transcytosis and tumor suppression. Caveolin-1 is found in endothelial cells, smooth muscle cells and adipocytes. The main focus of this study is to investigate the peroxynitrite-mediated in vitro post-translational modifications (PTMs) of caveolin-1. Bovine brain was used to isolate caveolin-1 as an initial step for isolation method development. Density gradient centrifugation was used to isolate caveolin-1 from bovine brain. From the isolate, caveolin-1α, caveolin-1β isomers and caveolin dimer were identified by western blotting with anti-caveolin monoclonal antibody. Glutathione S-transferase (GST)-caveolin fusion protein was used to isolate caveolin-1 and used for in vitro experiments in this study. During normal and pathological conditions, endothelial cells are subjected to locally generated reactive oxygen species such as peroxynitrite. Peroxynitrite is capable of modifying amino acids such as tyrosine, cysteine, tryptophan and methionine. Peroxynitrite mediated tyrosine nitration of caveolin-1 was detected by SDS-PAGE followed by western blotting with anti-nitrotyrosine monoclonal antibody. The approach used to identify potentially modified peptide sequences of caveolin-1 was ESI-MS/MS. Fluorometry was used to detect formation of dityrosine. Caveolin-1 was treated with different concentrations of peroxynitrite in caveolin- under the physiological conditions and found that caveolin-1 form dimer and oligomer under the physiological conditions. The stability of caveolin-1 dimer and oligomer suggests that the coupling mechanism could most likely be occurred via a covalent bond. Western blotting with anti-nitrotyrosine monoclonal antibody revealed the formation of nitrotyrosine upon the exposure to peroxynitrite. In this study, we report the nitration of specific tyrosine residues of caveolin-1 for the first time. ESI-MS/MS analysis revealed that peroxynitrite can selectively nitrate Tyr6 and Tyr14 located in the tryptic peptide YVDSEGHLYTVPIR under physiological conditions. Caveolin-1 can form dityrosine upon exposure to peroxynitrite as shown by fluorometry. Oxidative and nitrative modifications due to the reaction of peroxynitrite with caveolin-1 may lead to several pathological conditions. Our study can provide authentic standards of modified proteins, which will be used to determine post-translational modifications of caveolin-1 in vivo

Proteome Profiling of Breast Tumors by Gel Electrophoresis and Nanoscale Electrospray Ionization Mass Spectrometry

We have conducted proteome-wide analysis of fresh surgery specimens derived from breast cancer patients, using an approach that integrates size-based intact protein fractionation, nanoscale liquid separation of peptides, electrospray ion trap mass spectrometry, and bioinformatics. Through this approach, we have acquired a large amount of peptide fragmentation spectra from size-resolved fractions of the proteomes of several breast tumors, tissue peripheral to the tumor, and samples from patients undergoing noncancer surgery. Label-free quantitation was used to generate protein abundance maps for each proteome and perform comparative analyses. The mass spectrometry data revealed distinct qualitative and quantitative patterns distinguishing the tumors from healthy tissue as well as differences between metastatic and non-metastatic human breast cancers including many established and potential novel candidate protein biomarkers. Selected proteins were evaluated by Western blotting using tumors grouped according to histological grade, size, and receptor expression but differing in nodal status. Immunohistochemical analysis of a wide panel of breast tumors was conducted to assess expression in different types of breast cancers and the cellular distribution of the candidate proteins. These experiments provided further insights and an independent validation of the data obtained by mass spectrometry and revealed the potential of this approach for establishing multimodal markers for early metastasis, therapy outcomes, prognosis, and diagnosis in the future. © 2008 American Chemical Society

Liquid MALDI MS analysis of complex peptide and proteome samples

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) is well-known to be a powerful technique for the analysis of biological samples. By using glycerol-based liquid support matrices (LSMs) instead of conventional MALDI matrices the power of this technique can be extended further. In this study, we exploited LSMs for the identification of complex samples, i.e. the Lactobacillus proteome and a bovine serum albumin (BSA) digest. Liquid and solid MALDI samples were manually and robotically prepared by coupling a nanoflow high performance liquid chromatography (nanoHPLC) system to an automated MALDI sample spotting device. MS and MS/MS data were successfully acquired at the femtomole level using TOF/TOF as well as Q-TOF instrumentation and used for protein identification searching sequence databases. For the BSA digest analysis, liquid MALDI samples resulted in peptide mass fingerprints which led to a higher confidence in protein identification compared to solid (crystalline) MALDI samples. However, post-source decay (PSD) MS/MS analysis of both the proteome of Lactobacillus plantarum WCFS1 cells and BSA digest showed that further optimization of the formation and detection of peptide fragment ions is still needed for liquid MALDI samples as the MS/MS ion search score was lower than for the solid MALDI samples, reflecting the poorer quality of the liquid MALDI-PSD spectra, which can be attributed to the differences in PSD parameters and their optimization that is currently achievable