A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics

194

118

The myriad of peptides presented at the cell surface by class I and class II major histocompatibility complex (MHC) molecules are referred to as the immunopeptidome and are of great importance for basic and translational science. For basic science, the immunopeptidome is a critical component for understanding the immune system; for translational science, exact knowledge of the immunopeptidome can directly fuel and guide the development of next-generation vaccines and immunotherapies against autoimmunity, infectious diseases, and cancers. In this mini-review, we summarize established isolation techniques as well as emerging mass spectrometry-based platforms (i.e. SWATH-MS) to identify and quantify MHC-associated peptides. We also highlight selected biological applications and discuss important current technical limitations that need to be solved to accelerate the development of this field. Molecular & Cellular

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confidence: 99%

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry*

Caron

Kowalewski

Koh

et al. 2015

194

118

“…There is a broad spectrum of mass spectrometry search engines that can be employed for data analysis (5), and from most of these programs a measure of reliability for individual peptide identifications is reported, commonly in the form of a probability or expectation value. These calculations determine how much better than random a particular assignment is.…”

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confidence: 99%

Modification Site Localization Scoring Integrated into a Search Engine

Baker

Trinidad

Chalkley

2011

111

122

Large proteomic data sets identifying hundreds or thousands of modified peptides are becoming increasingly common in the literature. Several methods for assessing the reliability of peptide identifications both at the individual peptide or data set level have become established. However, tools for measuring the confidence of modification site assignments are sparse and are not often employed. A few tools for estimating phosphorylation site assignment reliabilities have been developed, but these are not integral to a search engine, so require a particular search engine output for a second step of processing. They may also require use of a particular fragmentation method and are mostly only applicable for phosphorylation analysis, rather than post-translational modifications analysis in general. In this study, we present the performance of site assignment scoring that is directly integrated into the search engine Protein Prospector, which allows site assignment reliability to be automatically reported for all modifications present in an identified peptide. It clearly indicates when a site assignment is ambiguous (and if so, between which residues), and reports an assignment score that can be translated into a reliability measure for individual site assignments. Molecular & Cellular Proteomics 10: 10.1074/mcp.M111.008078, 1-9, 2011.Proteomic research is increasingly moving from simply cataloging proteins to trying to understand which components are most important for regulation and function (1, 2). Protein activity can be controlled over the long term by changes in expression levels, but for rapid and precise changes, the cell employs a range of post-translational modifications (PTMs)1 . Mass spectrometry is the enabling tool for PTM characterization, as it is the only approach that can study thousands of modification sites in a single experiment (3). Modern mass spectrometers are able to produce large amounts of data in relatively short periods of time, such that the bottleneck in most proteomic research is the data analysis (4).There is a broad spectrum of mass spectrometry search engines that can be employed for data analysis (5), and from most of these programs a measure of reliability for individual peptide identifications is reported, commonly in the form of a probability or expectation value. These calculations determine how much better than random a particular assignment is. As a modified peptide with an incorrect modification site assignment is highly homologous to the correct answer, assignments to the correct peptide sequence but with incorrect site assignment will generally give a confident identification score. Hence, although these tools can be applied for analyzing peptides bearing chemical or biological modifications they will report some incorrect modification site assignments and no search engine currently reports a measure of reliability for the assignment of a site of modification within a peptide.To address this issue, a range of tools has been written to try to assess phosphorylation site assi...

“…Peptide inference is more constrained than glycan inference, because the chain of MS/MS peaks corresponds to a linear peptide sequence; given an MS/MS spectrum, the linear peptide sequence can be inferred through brute force or dynamic programming via de novo methods (4 -6) as described in Ref. 7. Additionally, the possible search space of peptides can be dramatically lowered by using database searching (8 -21) as described in Ref.…”

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confidence: 99%

“…Additionally, the possible search space of peptides can be dramatically lowered by using database searching (8 -21) as described in Ref. 7, which compares the MS/MS spectrum to the predicted spectra from only those peptides resulting from a protein database or translated open reading frames (ORFs) of a genomic database.…”

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confidence: 99%

SweetSEQer, Simple de Novo Filtering and Annotation of Glycoconjugate Mass Spectra

Serang¹,

Froehlich

Muntel

et al. 2013

The past 15 years have seen significant progress in LC-MS/MS peptide sequencing, including the advent of successful de novo and database search methods; however, analysis of glycopeptide and, more generally, glycoconjugate spectra remains a much more open problem, and much annotation is still performed manually. This is partly because glycans, unlike peptides, need not be linear chains and are instead described by trees. In this study, we introduce SweetSEQer, an extremely simple open source tool for identifying potential glycopeptide MS/MS spectra. We evaluate SweetSEQer on manually curated glycoconjugate spectra and on negative controls, and we demonstrate high quality filtering that can be easily improved for specific applications. We also demonstrate a high overlap between peaks annotated by experts and peaks annotated by SweetSEQer, as well as demonstrate inferred glycan graphs consistent with canonical glycan tree motifs. This study presents a novel tool for annotating spectra and producing glycan graphs from LC-MS/MS spectra. The tool is evaluated and shown to perform similarly to an expert on manually curated data. Protein glycosylation is a common modification, affecting ϳ50% of all expressed proteins (1). Glycosylation affects critical biological functions, including cell-cell recognition, circulating half-life, substrate binding, immunogenicity, and others (2). Regrettably, determining the exact role glycosylation plays in different biological contexts is slowed by a dearth of analytical methods and of appropriate software. Such software is crucial for performing and aiding experts in data analysis complex glycosylation.Glycopeptides are highly heterogeneous in regard to glycan composition, glycan structure, and linkage stereochemistry in addition to the tens of thousands of possible peptides. The analysis of protein glycosylation is often segmented into three distinct types of mass spectrometry experiments, which together help to resolve this complexity. The first analyzes enzymatically or chemically released glycans (which may or may not be chemically modified), and the second determines glycosylation sites after release of glycans from peptides (the resulting mass spectra allow detection of glycosylation sites and the glycans on those sites simultaneously). The third determines the glycosylation sites and the glycans on those sites simultaneously, by MS of intact glycopeptides. Frequently, researchers will perform all three types of analysis, with the first two types providing information about possible combinations of glycan structures and peptides that could be found in the third experiment. Using this MS1 information, the problem is reduced to matching masses observed with a combinatorial pool of all possible glycans and all possible glycosylated peptides within a sample; however, this combinatorial approach alone is insufficient (3), and tandem mass spectrometry can provide copious additional information to help resolve the glycopeptide content from complex samples.The similar problem of inferr...