A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data

Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughput protein identification using mass spectrometry (MS). Current methodologies depend predominantly on the use of derived m/z values of fragment ions, and, the knowledge provided by the intensity information present in MS/MS spectra has not been fully exploited. Indeed spectrum intensity information is very rarely utilized in the algorithms currently in use for high-throughput protein identification. Results: In this work, a Bayesian neural network approach is employed to analyze ion intensity information present in 13878 different MS/MS spectra. The influence of a library of 35 features on peptide fragmentation is examined under different proton mobility conditions. Useful rules involved in peptide fragmentation are found and subsets of features which have significant influence on fragmentation pathway of peptides are characterised. An intensity model is built based on the selected features and the model can make an accurate prediction of the intensity patterns for given MS/MS spectra. The predictions include not only the mean values of spectra intensity but also the variances that can be used to tolerate noises and system biases within experimental MS/MS spectra. Conclusion: The intensity patterns of fragmentation spectra are informative and can be used to analyze the influence of various characteristics of fragmented peptides on their fragmentation pathway. The features with significant influence can be used in turn to predict spectra intensities. Such information can help develop more reliable algorithms for peptide and protein identification

Mass Spectrometry in the Elucidation of the Glycoproteome of Bacterial Pathogens

Presently some three hundred post-translational modifications are known to occur in bacteria in vivo. Many of these modifications play critical roles in the regulation of proteins and control key biological processes. One of the most predominant modifications, N- and O-glycosylations are now known to be present in bacteria (and archaea) although they were long believed to be limited to eukaryotes. In a number of human pathogens these glycans have been found attached to the surfaces of pilin, flagellin and other surface and secreted proteins where it has been demonstrated that they play a role in the virulence of these bacteria. Mass spectrometry characterization of these glycosylation events has been the enabling key technology for these findings. This review will look at the use of mass spectrometry as a key technology for the detection and mapping of these modifications within microorganisms, with particular reference to the human pathogens, Campylobacter jejuni and Mycobacterium tuberculosis. The overall aim of this review will be to give a basic understanding of the current ‘state-of-the-art’ of the key techniques, principles and technologies, including bioinformatics tools, involved in the analysis of the glycosylation modifications

Deamidation at Asparagine and Glutamine As a Major Modification upon Deterioration/Aging of Proteinaceous Binders in MuralPaintings

Proteomic strategies are herein proved to be a complementary approach to the well established amino acid composition analysis for the characterization of the aging and deterioration phenomena occurring to proteinaceous materials in works-of-art. Amino acid analyses on several samples demonstrated that proteins in the frescoes from the Camposanto Monumentale in Pisa are deteriorated as revealed by the decrease in Met, Lys, and Tyr content and by the presence in all the samples of amino malonic acid as a result of Ser, Phe, and Cys oxidation. Proteomic analysis identified deamidation at Asn and Gln as a further major event occurred. This work paves the way to the exploitation of proteomic strategies for the investigation of the molecular effects of aging and deterioration in historical objects. Results show that proteomic searches for deamidation by liquid chromatography-tandem mass spectrometry (LC-MS/MS) could constitute a routine analysis for paintings or any artistic and historic objects where proteins are present. Peptides that can be used as molecular markers when casein is present were identified

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Characterization of Cell Glycocalyx with Mass Spectrometry Methods.

The cell membrane plays an important role in protecting the cell from its extracellular environment. As such, extensive work has been devoted to studying its structure and function. Crucial intercellular processes, such as signal transduction and immune protection, are mediated by cell surface glycosylation, which is comprised of large biomolecules, including glycoproteins and glycosphingolipids. Because perturbations in glycosylation could result in dysfunction of cells and are related to diseases, the analysis of surface glycosylation is critical for understanding pathogenic mechanisms and can further lead to biomarker discovery. Different mass spectrometry-based techniques have been developed for glycan analysis, ranging from highly specific, targeted approaches to more comprehensive profiling studies. In this review, we summarized the work conducted for extensive analysis of cell membrane glycosylation, particularly those employing liquid chromatography with mass spectrometry (LC-MS) in combination with various sample preparation techniques

Structure analysis of biologically important prokaryotic glycopolymers

Of the many post-translational modifications organisms can undertake, glycosylation is the most prevalent and the most diverse. The research in this thesis focuses on the structural characterisation of glycosylation in two classes of glycopolymer (lipopolysaccharide (LPS) and glycoprotein) in two domains of life (bacteria and archaea). The common theme linking these subprojects is the development and application of high sensitivity analytical techniques, primarily mass spectrometry (MS), for studying prokaryotic glycosylation. Many prokaryotes produce glycan arrangements with extraordinary variety in composition and structure. A further challenge is posed by additional functionalities such as lipids whose characterisation is not always straightforward. Glycosylation in prokaryotes has a variety of different biological functions, including their important roles in the mediation of interactions between pathogens and hosts. Thus enhanced knowledge of bacterial glycosylation may be of therapeutic value, whilst a better understanding of archaeal protein glycosylation will provide further targets for industrial applications, as well as insight into this post- translational modification across evolution and protein processing under extreme conditions. The first sub-project focused on the S-layer glycoprotein of the halophilic archeaon Haloferax volcanii, which has been reported to be modified by both glycans and lipids. Glycoproteomic and associated MS technologies were employed to characterise the N- and O-linked glycosylation and to explore putative lipid modifications. Approximately 90% of the S-layer was mapped and N-glycans were identified at all the mapped consensus sites, decorated with a pentasaccharide consisting of two hexoses, two hexuronic acids and a methylated hexuronic acid. The O-glycans are homogeneously identified as a disaccharide consisting of galactose and glucose. Unexpectedly it was found that membrane-derived lipids were present in the S- layer samples despite extensive purification, calling into question the predicted presence of covalently linked lipid. The H. volcanii N-glycosylation is mediated by the products of the agl gene cluster and the functional characterisation of members of the agl gene cluster was investigated by MS analysis of agl-mutant strains of the S-layer. Burkholderia pseudomallei is the causative agent of melioidosis, a serious and often fatal disease in humans which is endemic in South-East Asia and other equatorial regions. Its LPS is vital for serum resistance and the O-antigen repeat structures are of interest as vaccine targets. B. pseudomallei is reported to produce several polysaccharides, amongst which the already characterised ‘typical’ O-antigen of K96243 represents 97% of the strains. The serologically distinct ‘atypical’ strain 576 produces a different LPS, whose characterisation is the subject of this research project. MS strategies coupled with various hydrolytic and chemical derivatisation methodologies were employed to define the composition and potential sequences of the O-antigen repeat unit. These MS strategies were complemented by a novel NMR technique involving embedding of the LPS into micelles. Taken together the MS and NMR data have revealed a highly unusual O-antigen structure for atypical LPS which is remarkably different from the typical O-antigen. The development of structural analysis tools in MS and NMR applicable to the illustrated types of glycosylation in these prokaryotes will give a more consistent approach to sugar characterisation and their modifications thus providing more informative results for pathogenicity and immunological studies as well as pathway comparisons.Open Acces

PI: An open-source software package for validation of the SEQUEST result and visualization of mass spectrum

<p>Abstract</p> <p>Background</p> <p>Tandem mass spectrometry (MS/MS) has emerged as the leading method for high- throughput protein identification in proteomics. Recent technological breakthroughs have dramatically increased the efficiency of MS/MS data generation. Meanwhile, sophisticated algorithms have been developed for identifying proteins from peptide MS/MS data by searching available protein sequence databases for the peptide that is most likely to have produced the observed spectrum. The popular SEQUEST algorithm relies on the cross-correlation between the experimental mass spectrum and the theoretical spectrum of a peptide. It utilizes a simplified fragmentation model that assigns a fixed and identical intensity for all major ions and fixed and lower intensity for their neutral losses. In this way, the common issues involved in predicting theoretical spectra are circumvented. In practice, however, an experimental spectrum is usually not similar to its SEQUEST -predicted theoretical one, and as a result, incorrect identifications are often generated.</p> <p>Results</p> <p>Better understanding of peptide fragmentation is required to produce more accurate and sensitive peptide sequencing algorithms. Here, we designed the software PI of novel and exquisite algorithms that make a good use of intensity property of a spectrum.</p> <p>Conclusions</p> <p>We designed the software PI with the novel and effective algorithms which made a good use of intensity property of the spectrum. Experiments have shown that PI was able to validate and improve the results of SEQUEST to a more satisfactory degree.</p

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

Probing the mechanism of electron capture and electron transfer dissociation using tags with variable electron affinity

Electron capture dissociation (ECD) and electron transfer dissociation (ETD) of doubly protonated electron affinity (EA)-tuned peptides were studied to further illuminate the mechanism of these processes. The model peptide FQpSEEQQQTEDELQDK, containing a phosphoserine residue, was converted to EA-tuned peptides via β-elimination and Michael addition of various thiol compounds. These include propanyl, benzyl, 4-cyanobenzyl, perfluorobenzyl, 3,5-dicyanobenzyl, 3-nitrobenzyl, and 3,5-dinitrobenzyl structural moieties, having a range of EA from −1.15 to +1.65 eV, excluding the propanyl group. Typical ECD or ETD backbone fragmentations are completely inhibited in peptides with substituent tags having EA over 1.00 eV, which are referred to as electron predators in this work. Nearly identical rates of electron capture by the dications substituted by the benzyl (EA = −1.15 eV) and 3-nitrobenzyl (EA = 1.00 eV) moieties are observed, which indicates the similarity of electron capture cross sections for the two derivatized peptides. This observation leads to the inference that electron capture kinetics are governed by the long-range electron−dication interaction and are not affected by side chain derivatives with positive EA. Once an electron is captured to high-n Rydberg states, however, through-space or through-bond electron transfer to the EA-tuning tags or low-n Rydberg states via potential curve crossing occurs in competition with transfer to the amide π* orbital. The energetics of these processes are evaluated using time-dependent density functional theory with a series of reduced model systems. The intramolecular electron transfer process is modulated by structure-dependent hydrogen bonds and is heavily affected by the presence and type of electron-withdrawing groups in the EA-tuning tag. The anion radicals formed by electron predators have high proton affinities (approximately 1400 kJ/mol for the 3-nitrobenzyl anion radical) in comparison to other basic sites in the model peptide dication, facilitating exothermic proton transfer from one of the two sites of protonation. This interrupts the normal sequence of events in ECD or ETD, leading to backbone fragmentation by forming a stable radical intermediate. The implications which these results have for previously proposed ECD and ETD mechanisms are discussed