PTMiner: Localization and Quality Control of Protein Modifications Detected in an Open Search and Its Application to Comprehensive Post-translational Modification Characterization in Human Proteome

PgxSAVy: A tool for comprehensive evaluation of variant peptide quality in proteogenomics - catching the (un)usual suspects

Variant peptides resulting from single nucleotide polymorphisms (SNPs) can lead to aberrant protein functions and have translational potential for disease diagnosis and personalized therapy. Variant peptides detected by proteogenomics are fraught with high number of false positives, but there is no uniform and comprehensive approach to assess variant quality across analysis pipelines. Despite class-specific FDR along with ad-hoc filters, the problem is far from solved. These protocols are typically manual and tedious, and thus not uniform across labs. We demonstrate that variant peptide rescoring, integrated with intensity, variant event information and search result features, allows better discrimination of correct variant peptides. Implemented into PgxSAVy - a tool for quality control of variant peptides, this method can tackle the high rate of false positives. PgxSAVy provides a rigorous framework for quality control and annotations of variant peptides on the basis of (i) variant quality, (ii) isobaric masses, and (iii) disease annotation. PgxSAVy demonstrated high accuracy by identifying true variants with 98.43% accuracy on simulated data. Large-scale proteogenomic reanalysis of ∼2.8 million spectra (PXD004010 and PXD001468) resulted in 12,705 variant peptide spectrum matches (PSMs), of which PgxSAVy evaluated 3028 (23.8%), 1409 (11.1%) and 8268 (65.1%) as confident, semi-confident and doubtful respectively. PgxSAVy also annotates the variants based on their pathogenicity and provides support for assisted manual validation. The analysis of proteins carrying variants can provide fine granularity in discovering important pathways. PgxSAVy will advance personalized medicine by providing a comprehensive framework for quality control and prioritization of proteogenomics variants. PgxSAVy is freely available at https://pgxsavy.igib.res.in/ as a webserver and https://github.com/anuragraj/PgxSAVy as a stand-alone tool.

Exploring the dynamic landscape of immunopeptidomics: Unravelling posttranslational modifications and navigating bioinformatics terrain

Immunopeptidomics is becoming an increasingly important field of study. The capability to identify immunopeptides with pivotal roles in the human immune system is essential to shift the current curative medicine towards personalized medicine. Throughout the years, the field has matured, giving insight into the current pitfalls. Nowadays, it is commonly accepted that generalizing shotgun proteomics workflows is malpractice because immunopeptidomics faces numerous challenges. While many of these difficulties have been addressed, the road towards the ideal workflow remains complicated. Although the presence of Posttranslational modifications (PTMs) in the immunopeptidome has been demonstrated, their identification remains highly challenging despite their significance for immunotherapies. The large number of unpredictable modifications in the immunopeptidome plays a pivotal role in the functionality and these challenges. This review provides a comprehensive overview of the current advancements in immunopeptidomics. We delve into the challenges associated with identifying PTMs within the immunopeptidome, aiming to address the current state of the field.

Computational approaches to identify sites of phosphorylation

Due to their oftentimes ambiguous nature, phosphopeptide positional isomers can present challenges in bottom-up mass spectrometry-based workflows as search engine scores alone are often not enough to confidently distinguish them. Additional scoring algorithms can remedy this by providing confidence metrics in addition to these search results, reducing ambiguity. Here we describe challenges to interpreting phosphoproteomics data and review several different approaches to determine sites of phosphorylation for both data-dependent and data-independent acquisition-based workflows. Finally, we discuss open questions regarding neutral losses, gas-phase rearrangement, and false localization rate estimation experienced by both types of acquisition workflows and best practices for managing ambiguity in phosphosite determination.

A global view of the human post-translational modification landscape

Post-translational modifications (PTMs) provide a rapid response to stimuli, finely tuning metabolism and gene expression and maintain homeostasis. Advances in mass spectrometry over the past two decades have significantly expanded the list of known PTMs in biology and as instrumentation continues to improve, this list will surely grow. While many PTMs have been studied in detail (e.g. phosphorylation, acetylation), the vast majority lack defined mechanisms for their regulation and impact on cell fate. In this review, we will highlight the field of PTM research as it currently stands, discussing the mechanisms that dictate site specificity, analytical methods for their detection and study, and the chemical tools that can be leveraged to define PTM regulation. In addition, we will highlight the approaches needed to discover and validate novel PTMs. Lastly, this review will provide a starting point for those interested in PTM biology, providing a comprehensive list of PTMs and what is known regarding their regulation and metabolic origins.

Comparative Analysis of Chemical Cross-Linking Mass Spectrometry Data Indicates That Protein STY Residues Rarely React with N-Hydroxysuccinimide Ester Cross-Linkers

When it comes to mass spectrometry data analysis for identification of peptide pairs linked by N-hydroxysuccinimide (NHS) ester cross-linkers, search engines bifurcate in their setting of cross-linkable sites. Some restrict NHS ester cross-linkable sites to lysine (K) and protein N-terminus, referred to as K only for short, whereas others additionally include serine (S), threonine (T), and tyrosine (Y) by default. Here, by setting amino acids with chemically inert side chains such as glycine (G), valine (V), and leucine (L) as cross-linkable sites, which serves as a negative control, we show that software-identified STY-cross-links are only as reliable as GVL-cross-links. This is true across different NHS ester cross-linkers including DSS, DSSO, and DSBU, and across different search engines including MeroX, xiSearch, and pLink. Using a published data set originated from synthetic peptides, we demonstrate that STY-cross-links indeed have a high false discovery rate. Further analysis revealed that depending on the data and the search engine used to analyze the data, up to 65% of the STY-cross-links identified are actually K-K cross-links of the same peptide pairs, up to 61% are actually K-mono-links, and the rest tend to contain short peptides at high risk of false identification.

The Immunopeptidome from a Genomic Perspective: Establishing the Noncanonical Landscape of MHC Class I-Associated Peptides

Tumor antigens can emerge through multiple mechanisms, including translation of noncoding genomic regions. This noncanonical category of tumor antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry (MS) to enable the discovery of noncanonical MHC class I-associated peptides (ncMAP) from noncoding regions. Considering that the emergence of tumor antigens can also involve posttranslational modifications (PTM), we included an open search component in our pipeline. Leveraging the wealth of MS-based immunopeptidomics, we analyzed data from 26 MHC class I immunopeptidomic studies across 11 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant PTMs, using spectral matching and controlled their FDR to 1%. The noncanonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 55%. The data reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive therapeutic targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targets for T-cell therapies or vaccine development.

Large-Scale Profiling of Unexpected Tryptic Cleaved Sites at Ubiquitinated Lysines

Trypsin specifically cleaves the C-terminus of lysine and arginine residues but often fails to cleave modified lysines, such as ubiquitination, therefore resulting in the uncleaved K-ε-GG peptides. Therefore, the cleaved ubiquitinated peptide identification was often regarded as false positives and discarded. Interestingly, unexpected cleavage at the K48-linked ubiquitin chain has been reported, suggesting the latent ability of trypsin to cleave ubiquitinated lysine residues. However, it remains unclear whether other trypsin-cleavable ubiquitinated sites are present. In this study, we verified the ability of trypsin in cleaving K6 and K63 besides K48 chains. The uncleaved K-ε-GG peptide was quickly and efficiently generated during trypsin digestion, whereas cleaved ones were produced with much lower efficiency. Then, the K-ε-GG antibody was proved to efficiently enrich the cleaved K-ε-GG peptides and several published large-scale ubiquitylation datasets were re-analyzed to interrogate the cleaved sequence features. In total, more than 2400 cleaved ubiquitinated peptides were identified in the K-ε-GG and UbiSite antibody-based datasets. The frequency of lysine upstream of the cleaved modified K was significantly enriched. The kinetic activity of trypsin in cleaving ubiquitinated peptides was further elucidated. We suggest that the cleaved K-ε-GG sites with high post-translational modification probability (≥0.75) should be considered as true positives in future ubiquitome analyses.

Advances in phosphoproteomics and its application to COPD

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) was the third leading cause of global death in 2019, causing a huge economic burden to society. Therefore, it is urgent to identify specific phenotypes of COPD patients through early detection, and to promptly treat exacerbations. The field of phosphoproteomics has been a massive advancement, compelled by the developments in mass spectrometry, enrichment strategies, algorithms, and tools. Modern mass spectrometry-based phosphoproteomics allows understanding of disease pathobiology, biomarker discovery, and predicting new therapeutic modalities.

AREAS COVERED

In this article, we present an overview of phosphoproteomic research and strategies for enrichment and fractionation of phosphopeptides, identification of phosphorylation sites, chromatographic separation and mass spectrometry detection strategies, and the potential application of phosphorylated proteomic analysis in the diagnosis, treatment, and prognosis of COPD disease.

EXPERT OPINION

The role of phosphoproteomics in COPD is critical for understanding disease pathobiology, identifying potential biomarkers, and predicting new therapeutic approaches. However, the complexity of COPD requires the more comprehensive understanding that can be achieved through integrated multi-omics studies. Phosphoproteomics, as a part of these multi-omics approaches, can provide valuable insights into the underlying mechanisms of COPD.

Many kinds of oxidized proteins are present more in the urine of the elderly

BACKGROUND

Many studies have shown an association between aging and oxidation. To our knowledge, there have been no studies exploring aging-related urine proteome modifications. The purpose of this study was to explore differences in global chemical modifications of urinary protein at different ages.

METHODS

Discovery (n=38) cohort MS data including children, young and old groups were downloaded from three published studies, and this data was analyzed using open-pFind for identifying modifications. Verification cohort human samples (n=28) including young, middle-aged, and old groups, rat samples (n=7) at three-time points after birth, adulthood, and old age were collected and processed in the laboratory simultaneously based on label-free quantification combined with pFind.

RESULTS

Discovery cohort: there were 28 kinds of differential oxidations in the old group that were higher than those in the young or children group in. Verification cohort: there were 17 kinds of differential oxidations of 49 oxidized proteins in the middle and old groups, which were significantly higher than those in the young group. Both oxidations and oxidized proteins distinguished different age groups well. There were also 15 kinds of differential oxidations in old age higher than others in the rat cohort. The results showed that the validation experiment was basically consistent with the results of the discovery experiment, showing that the level of oxidized proteins in urine increased significantly with age.

CONCLUSIONS

Our study is the first to show that oxidative proteins occur in urine and that oxidations are higher in older than younger ages. Perhaps improving the degree of excretion of oxidative protein in vivo through the kidney is helpful for maintaining the homeostasis of the body's internal environment, delaying aging and the occurrence of senile diseases.

SIMSI-Transfer: Software-assisted reduction of missing values in phosphoproteomic and proteomic isobaric labeling data using tandem mass spectrum clustering

Isobaric stable isotope labeling techniques such as tandem mass tags (TMTs) have become popular in proteomics because they enable the relative quantification of proteins with high precision from up to 18 samples in a single experiment. While missing values in peptide quantification are rare in a single TMT experiment, they rapidly increase when combining multiple TMT experiments. As the field moves toward analyzing ever higher numbers of samples, tools that reduce missing values also become more important for analyzing TMT datasets. To this end, we developed SIMSI-Transfer (Similarity-based Isobaric Mass Spectra 2 [MS2] Identification Transfer), a software tool that extends our previously developed software MaRaCluster (© Matthew The) by clustering similar tandem MS2 from multiple TMT experiments. SIMSI-Transfer is based on the assumption that similarity-clustered MS2 spectra represent the same peptide. Therefore, peptide identifications made by database searching in one TMT batch can be transferred to another TMT batch in which the same peptide was fragmented but not identified. To assess the validity of this approach, we tested SIMSI-Transfer on masked search engine identification results and recovered >80% of the masked identifications while controlling errors in the transfer procedure to below 1% false discovery rate. Applying SIMSI-Transfer to six published full proteome and phosphoproteome datasets from the Clinical Proteomic Tumor Analysis Consortium led to an increase of 26 to 45% of identified MS2 spectra with TMT quantifications. This significantly decreased the number of missing values across batches and, in turn, increased the number of peptides and proteins identified in all TMT batches by 43 to 56% and 13 to 16%, respectively.

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Spectrum clustering enables peptide identification transfer between LC–MS/MS runs.

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The SIMSI pipeline supports processing full proteome and phosphoproteome data.

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SIMSI increases the number of quantifiable PSMs by 26 to 45%.

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SIMSI reduces missing values in multibatch TMT labeling experiments by up to 21%.

Systematic analysis of the lysine malonylome in Sanghuangporus sanghuang

Background

Sanghuangporus sanghuang is a well-known traditional medicinal mushroom associated with mulberry. Despite the properties of this mushroom being known for many years, the regulatory mechanisms of bioactive compound biosynthesis in this medicinal mushroom are still unclear. Lysine malonylation is a posttranslational modification that has many critical functions in various aspects of cell metabolism. However, at present we do not know its role in S. sanghuang. In this study, a global investigation of the lysine malonylome in S. sanghuang was therefore carried out.

Results

In total, 714 malonyl modification sites were matched to 255 different proteins. The analysis indicated that malonyl modifications were involved in a wide range of cellular functions and displayed a distinct subcellular localization. Bioinformatics analysis indicated that malonylated proteins were engaged in different metabolic pathways, including glyoxylate and dicarboxylate metabolism, glycolysis/gluconeogenesis, and the tricarboxylic acid (TCA) cycle. Notably, a total of 26 enzymes related to triterpene and polysaccharide biosynthesis were found to be malonylated, indicating an indispensable role of lysine malonylation in bioactive compound biosynthesis in S. sanghuang.

Conclusions

These findings suggest that malonylation is associated with many metabolic pathways, particularly the metabolism of the bioactive compounds triterpene and polysaccharide. This paper represents the first comprehensive survey of malonylation in S. sanghuang and provides important data for further study on the physiological function of lysine malonylation in S. sanghuang and other medicinal mushrooms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08120-0.

caAtlas: An immunopeptidome atlas of human cancer

Comprehensive characterization of tumor antigens is essential for the design of cancer immunotherapies, and mass spectrometry (MS)-based immunopeptidomics enables high-throughput identification of major histocompatibility complex (MHC)-bound peptide antigens in vivo. Here we construct an immunopeptidome atlas of human cancer through an extensive collection of 43 published immunopeptidomic datasets and standardized analysis of 81.6 million MS/MS spectra using an open search engine. Our analysis greatly expands the current knowledge of MHC-bound antigens, including an unprecedented characterization of post-translationally modified antigens and their cancer-association. We also perform systematic analysis of cancer-testis antigens, cancer-associated antigens, and neoantigens. We make all these data together with annotated MS/MS spectra supporting identification of each antigen in an easily browsable web portal named cancer antigen atlas (caAtlas). caAtlas provides a central resource for the selection and prioritization of MHC-bound peptides for in vitro HLA binding assay and immunogenicity testing, which will pave the way to eventual development of cancer immunotherapies.

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Extensive collection of 43 immunopeptidomic datasets with 1018 samples

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Standardized and rigorous identification of HLA-bound peptides, including PTM peptides

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Comprehensive annotation of CT antigens and cancer-associated antigens

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User-friendly data dissemination through the caAtlas web portal

AA_stat: Intelligent profiling of in vivo and in vitro modifications from open search results

Characterization of post-translational modifications is among the most challenging tasks in tandem mass spectrometry-based proteomics which has yet to find an efficient solution. The ultra-tolerant (open) database search attempts to meet this challenge. However, interpretation of the mass shifts observed in open search still requires an effective and automated solution. We have previously introduced the AA_stat tool for analysis of amino acid frequencies at different mass shifts and generation of hypotheses on unaccounted in vitro modifications. Here, we report on the new version of AA_stat, which now complements amino acid frequency statistics with a number of new features: (1) MS/MS-based localization of mass shifts and localization scoring, including shifts which are the sum of modifications; (2) inferring fixed modifications to increase method sensitivity; (3) inferring monoisotopic peak assignment errors and variable modifications based on abundant mass shift localizations to increase the yield of closed search; (4) new mass calibration algorithm to account for partial systematic shifts; (5) interactive integration of all results and a rated list of possible mass shift interpretations. With these options, we improve interpretation of open search results and demonstrate the utility of AA_stat for profiling of abundant and rare amino acid modifications. AA_stat is implemented in Python as an open-source command-line tool available at https://github.com/SimpleNumber/aa_stat. SIGNIFICANCE: Mass spectrometry-based PTM characterization has a long history, yet most of the methods rely on a priori knowledge of modifications of interest and do not provide a whole proteome modification landscape in a blind manner. The open database search is an efficient attempt to address this challenge by identifying peptides with mass shifts corresponding to possible modifications. Then, interpreting these mass shifts is required. Therefore, development of bioinformatics software for post-processing of the open search results, which is capable of detection and accurate annotation of new or unexpected modifications, from characterization of sample preparation efficiency and quality control to discovery of rare post-translational modifications, is of high importance.

Proteomics in aging research: A roadmap to clinical, translational research

The identification of plasma proteins that systematically change with age and, independent of chronological age, predict accelerated decline of health is an expanding area of research. Circulating proteins are ideal translational "omics" since they are final effectors of physiological pathways and because physicians are accustomed to use information of plasma proteins as biomarkers for diagnosis, prognosis, and tracking the effectiveness of treatments. Recent technological advancements, including mass spectrometry (MS)-based proteomics, multiplexed proteomic assay using modified aptamers (SOMAscan), and Proximity Extension Assay (PEA, O-Link), have allowed for the assessment of thousands of proteins in plasma or other biological matrices, which are potentially translatable into new clinical biomarkers and provide new clues about the mechanisms by which aging is associated with health deterioration and functional decline. We carried out a detailed literature search for proteomic studies performed in different matrices (plasma, serum, urine, saliva, tissues) and species using multiple platforms. Herein, we identified 232 proteins that were age-associated across studies. Enrichment analysis of the 232 age-associated proteins revealed metabolic pathways previously connected with biological aging both in animal models and in humans, most remarkably insulin-like growth factor (IGF) signaling, mitogen-activated protein kinases (MAPK), hypoxia-inducible factor 1 (HIF1), cytokine signaling, Forkhead Box O (FOXO) metabolic pathways, folate metabolism, advance glycation end products (AGE), and receptor AGE (RAGE) metabolic pathway. Information on these age-relevant proteins, likely expanded and validated in longitudinal studies and examined in mechanistic studies, will be essential for patient stratification and the development of new treatments aimed at improving health expectancy.

Leveraging orthogonal mass spectrometry based strategies for comprehensive sequencing and characterization of ribosomal antimicrobial peptide natural products

Covering: Up to July 2020Ribosomal antimicrobial peptide (AMP) natural products, also known as ribosomally synthesized and post-translationally modified peptides (RiPPs) or host defense peptides, demonstrate potent bioactivities and impressive complexity that complicate molecular and biological characterization. Tandem mass spectrometry (MS) has rapidly accelerated bioactive peptide sequencing efforts, yet standard workflows insufficiently address intrinsic AMP diversity. Herein, orthogonal approaches to accelerate comprehensive and accurate molecular characterization without the need for prior isolation are reviewed. Chemical derivatization, proteolysis (enzymatic and chemical cleavage), multistage MS fragmentation, and separation (liquid chromatography and ion mobility) strategies can provide complementary amino acid composition and post-translational modification data to constrain sequence solutions. Examination of two complex case studies, gomesin and styelin D, highlights the practical implementation of the proposed approaches. Finally, we emphasize the importance of heterogeneous AMP peptidoforms that confer varying biological function, an area that warrants significant further development.

Enhancing Open Modification Searches via a Combined Approach Facilitated by Ursgal

The identification of peptide sequences and their post-translational modifications (PTMs) is a crucial step in the analysis of bottom-up proteomics data. The recent development of open modification search (OMS) engines allows virtually all PTMs to be searched for. This not only increases the number of spectra that can be matched to peptides but also greatly advances the understanding of the biological roles of PTMs through the identification, and the thereby facilitated quantification, of peptidoforms (peptide sequences and their potential PTMs). Whereas the benefits of combining results from multiple protein database search engines have been previously established, similar approaches for OMS results have been missing so far. Here we compare and combine results from three different OMS engines, demonstrating an increase in peptide spectrum matches of 8-18%. The unification of search results furthermore allows for the combined downstream processing of search results, including the mapping to potential PTMs. Finally, we test for the ability of OMS engines to identify glycosylated peptides. The implementation of these engines in the Python framework Ursgal facilitates the straightforward application of the OMS with unified parameters and results files, thereby enabling yet unmatched high-throughput, large-scale data analysis.

Proteomic approaches to drive advances in helminth extracellular vesicle research

Helminths can interact with their hosts in many different ways, including through the secretion of soluble molecules (such as lipids, glycans and proteins) and extracellular vesicles (EVs). The field of helminth secreted EVs has significantly advanced in recent years, mainly due to the molecular characterisation of EV proteomes and research highlighting the potential of EVs and their constituent molecules in the diagnosis and control of parasitic infections. Despite these advancements, the lack of appropriate isolation and purification methods is impeding the discovery of suitable biomarkers for the differentiation of helminth EV populations. In the present review we offer our viewpoint on the different proteomic techniques and approaches that have been developed, as well as solutions to common pitfalls and challenges that could be applied to advance the study of helminth EVs.

PTM-Shepherd: Analysis and Summarization of Post-Translational and Chemical Modifications From Open Search Results

Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of post-translational modification profiles detected in open searches based on attributes, such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multiexperiment comparisons for studying changes in modification profiles, e.g., in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed and paraffin-embedded samples, detects extreme underalkylation of cysteine in some data sets, discovers an artifactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multicenter proteomics profiling study.

Fragment Mass Spectrum Prediction Facilitates Site Localization of Phosphorylation

Liquid chromatography tandem mass spectrometry (LC-MS/MS) has been the most widely used technology for phosphoproteomics studies. As an alternative to database searching and probability-based phosphorylation site localization approaches, spectral library searching has been proved to be effective in the identification of phosphopeptides. However, incompletion of experimental spectral libraries limits the identification capability. Herein, we utilize MS/MS spectrum prediction coupled with spectral matching for site localization of phosphopeptides. In silico MS/MS spectra are generated from peptide sequences by deep learning/machine learning models trained with nonphosphopeptides. Then, mass shift according to phosphorylation sites, phosphoric acid neutral loss, and a "budding" strategy are adopted to adjust the in silico mass spectra. In silico MS/MS spectra can also be generated in one step for phosphopeptides using models trained with phosphopeptides. The method is benchmarked on data sets of synthetic phosphopeptides and is used to process real biological samples. It is demonstrated to be a method requiring only computational resources that supplements the probability-based approaches for phosphorylation site localization of singly and multiply phosphorylated peptides.

Global chemical modifications comparison of human plasma proteome from two different age groups

In this study, two groups of human plasma proteome at different age groups (old and young) were used to perform a comparison of global chemical modifications, as determined by tandem mass spectrometry (MS/MS) combined with non-limiting modification identification algorithms. The sulfhydryl in the cysteine A total of 4 molecular modifications were found to have significant differences passing random grouping tests: the succinylation and phosphorylation modification of cysteine (Cys, C) and the modification of lysine (Lys, K) with threonine (Thr, T) were significantly higher in the old group than in the young group, while the carbamylation of lysine was lower in the young group. We speculate that there is an increase in certain modified proteins in the blood of the old people which, in turn, changes the function of those proteins. This change may be one of the reasons why old people are more likely than young people to be at risk for age-related diseases, such as metabolic diseases, cerebral and cardiovascular diseases, and cancer.

MMS2plot: An R Package for Visualizing Multiple MS/MS Spectra for Groups of Modified and Non-Modified Peptides

A large number of post-translational modifications (PTMs) in proteins are buried in the unassigned mass spectrometric (MS) spectra in shot-gun proteomics datasets. Because the modified peptide fragments are low in abundance relative to the corresponding non-modified versions, it is critical to develop tools that allow facile evaluation of assignment of PTMs based on the MS/MS spectra. Such tools will preferably have the ability to allow comparison of fragment ion spectra and retention time between the modified and unmodified peptide pairs or group. Herein, MMS2plot, an R package for visualizing peptide-spectrum matches (PSMs) for multiple peptides, is described. MMS2plot features a batch mode and generates the output images in vector graphics file format that facilitate evaluation and publication of the PSM assignment. MMS2plot is expected to play an important role in PTM discovery from large-scale proteomics datasets generated by liquid chromatography-MS/MS. The MMS2plot package is freely available at https://github.com/lileir/MMS2plot under the GPL-3 license.

Unambiguous Phosphosite Localization through the Combination of Trypsin and LysargiNase Mirror Spectra in a Large-Scale Phosphoproteome Study

Understanding of the kinase-guided signaling pathways requires the identification and analysis of phosphosites. Mass spectrometry (MS)-based phosphoproteomics is a rapid and highly sensitive approach for high-throughput identification of phosphosites. However, phosphosite determination from MS data with a single protease is more likely to be ambiguous, regardless of the strategy used for phosphopeptide detection. Here, we explored the application of LysargiNase, which was recently reported to mirror trypsin in specificity to cleave arginine and lysine residues exclusively at the N-terminal side. We found that the combination of trypsin and LysargiNase mirror spectra resulted in higher ion coverage in MS₂ spectra. The median ion coverage values of b ions in tryptic spectra, LysargiNase spectra, and combined spectra are 8.3, 20.5, and 25.0%, respectively. As for the median ion coverage of y ions, these values are 27.8, 10.0, and 32.3%. Higher ion coverage was helpful to pinpoint the precise phosphosites. Compared to trypsin alone, the combined use of trypsin and LysargiNase mirror spectra enabled 67.1% of mirror spectra with unreliable scores (confidence score <0.75) to become reliable (confidence score ≥ 0.75). Meanwhile, all of the mirror peptide-spectrum matches (PSMs) with multiple potential phosphosites from trypsin and LysargiNase digests could be assigned one precise phosphosite after applying the combination strategy. Besides, the combination strategy could identify more novel phosphosites than the union strategy did. We synthesized three phosphopeptides corresponding to the three novel phosphosites and validated the reliability of the identification. Taken together, our data demonstrated the distinctive potential of the combination strategy presented here for unambiguous phosphosite localization (Project accession PXD011178).

Transfer posterior error probability estimation for peptide identification

BACKGROUND

In shotgun proteomics, database searching of tandem mass spectra results in a great number of peptide-spectrum matches (PSMs), many of which are false positives. Quality control of PSMs is a multiple hypothesis testing problem, and the false discovery rate (FDR) or the posterior error probability (PEP) is the commonly used statistical confidence measure. PEP, also called local FDR, can evaluate the confidence of individual PSMs and thus is more desirable than FDR, which evaluates the global confidence of a collection of PSMs. Estimation of PEP can be achieved by decomposing the null and alternative distributions of PSM scores as long as the given data is sufficient. However, in many proteomic studies, only a group (subset) of PSMs, e.g. those with specific post-translational modifications, are of interest. The group can be very small, making the direct PEP estimation by the group data inaccurate, especially for the high-score area where the score threshold is taken. Using the whole set of PSMs to estimate the group PEP is inappropriate either, because the null and/or alternative distributions of the group can be very different from those of combined scores.

RESULTS

The transfer PEP algorithm is proposed to more accurately estimate the PEPs of peptide identifications in small groups. Transfer PEP derives the group null distribution through its empirical relationship with the combined null distribution, and estimates the group alternative distribution, as well as the null proportion, using an iterative semi-parametric method. Validated on both simulated data and real proteomic data, transfer PEP showed remarkably higher accuracy than the direct combined and separate PEP estimation methods.

CONCLUSIONS

We presented a novel approach to group PEP estimation for small groups and implemented it for the peptide identification problem in proteomics. The methodology of the approach is in principle applicable to the small-group PEP estimation problems in other fields.

Large-scale Identification of N-linked Intact Glycopeptides in Human Serum using HILIC Enrichment and Spectral Library Search

Large-scale identification of N-linked intact glycopeptides by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) in human serum is challenging because of the wide dynamic range of serum protein abundances, the lack of a complete serum N-glycan database and the existence of proteoforms. In this regard, a spectral library search method was presented for the identification of N-linked intact glycopeptides from N-linked glycoproteins in human serum with target-decoy and motif-specific false discovery rate (FDR) control. Serum proteins were firstly separated into low-abundance and high-abundance proteins by acetonitrile (ACN) precipitation. After digestion, the N-linked intact glycopeptides were enriched by hydrophilic interaction liquid chromatography (HILIC) and a portion of the enriched N-linked intact glycopeptides were processed by Peptide-N-Glycosidase F (PNGase F) to generate N-linked deglycopeptides. Both N-linked intact glycopeptides and deglycopeptides were analyzed by LC-MS/MS. From N-linked deglycopeptides data sets, 764 N-linked glycoproteins, 1699 N-linked glycosites and 3328 unique N-linked deglycopeptides were identified. Four types of N-linked glycosylation motifs (NXS/T/C/V, X≠P) were used to recognize the N-linked deglycopeptides. The spectra of these N-linked deglycopeptides were utilized for N-linked deglycopeptides library construction and identification of N-linked intact glycopeptides. A database containing 739 N-glycan masses was constructed and utilized during spectral library search for the identification of N-linked intact glycopeptides. In total, 526 N-linked glycoproteins, 1036 N-linked glycosites, 22,677 N-linked intact glycopeptides and 738 N-glycan masses were identified under 1% FDR, representing the most in-depth serum N-glycoproteome identified by LC-MS/MS at N-linked intact glycopeptide level.

PTMProphet: Fast and Accurate Mass Modification Localization for the Trans-Proteomic Pipeline

Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms, and demonstrate its performance on ground-truth synthetic peptide reference data sets, one previously published small data set, one new larger data set, and also on a previously published phosphoenriched data set where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210.

Using the tools of proteomics to understand the pathogenesis of idiopathic inflammatory myopathies

PURPOSE OF REVIEW

One of the most important advances in medical research over the past 20 years has been the emergence of technologies to assess complex biological processes on a global scale. Although a great deal of attention has been given to genome-scale genetics and genomics technologies, the utility of studying the proteome in a comprehensive way is sometimes under-appreciated. In this review, we discuss recent advances in proteomics as applied to dermatomyositis/polymyositis as well as findings from other inflammatory diseases that may enlighten our understanding of dermatomyositis/polymyositis.

RECENT FINDINGS

Proteomic approaches have been used to investigate basic mechanisms contributing to lung and skin disease in dermatomyositis/polymyositis as well as to the muscle disease itself. In addition, proteomic approaches have been used to identify autoantibodies targeting the endothelium in juvenile dermatomyositis. Studies from other inflammatory diseases have shown the promise of using proteomics to characterize the composition of immune complexes and the protein cargoes of exosomes.

SUMMARY

There are many relevant scientific and clinical questions in dermatomyositis/polymyositis that can be addressed using proteomics approaches. Careful attention to both methodology and analytic approaches are required to obtain useful and reproducible data.