ProteomicsPub Date : 2024-08-10DOI: 10.1002/pmic.202300491
Miguel Cosenza-Contreras, Adrianna Seredynska, Daniel Vogele, Niko Pinter, Eva Brombacher, Ruth Fiestas Cueto, Thien-Ly Julia Dinh, Patrick Bernhard, Manuel Rogg, Junwei Liu, Patrick Willems, Simon Stael, Pitter F Huesgen, E Wolfgang Kuehn, Clemens Kreutz, Christoph Schell, Oliver Schilling
{"title":"TermineR: Extracting information on endogenous proteolytic processing from shotgun proteomics data.","authors":"Miguel Cosenza-Contreras, Adrianna Seredynska, Daniel Vogele, Niko Pinter, Eva Brombacher, Ruth Fiestas Cueto, Thien-Ly Julia Dinh, Patrick Bernhard, Manuel Rogg, Junwei Liu, Patrick Willems, Simon Stael, Pitter F Huesgen, E Wolfgang Kuehn, Clemens Kreutz, Christoph Schell, Oliver Schilling","doi":"10.1002/pmic.202300491","DOIUrl":"https://doi.org/10.1002/pmic.202300491","url":null,"abstract":"<p><p>State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modifications) being reliably identified from (tandem-) mass spectrometry data, often without the need for biochemical enrichment. Semi-specific proteome searches, that enforce a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify of native protein termini or those arising from endogenous proteolytic activity (also referred to as \"neo-N-termini\" analysis or \"N-terminomics\"). Nevertheless, deriving biological meaning from these search outputs can be challenging in terms of data mining and analysis. Thus, we introduce TermineR, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity and known protein processing features, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, and (3) visualization of neo-N-termini location. We illustrate the use of TermineR by applying it to tandem mass tag (TMT)-based proteomics data of a mouse model of polycystic kidney disease, and assess the semi-specific searches for biological interpretation of cleavage events and the variable contribution of proteolytic products to general protein abundance. The TermineR approach and example data are available as an R package at https://github.com/MiguelCos/TermineR.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141910947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2024-08-09DOI: 10.1002/pmic.202300591
Roxane L Degroote, Adrian Schmalen, Simone Renner, Eckhard Wolf, Stefanie M Hauck, Cornelia A Deeg
{"title":"Diabetic retinopathy from the vitreous proteome perspective: The INS<sup>C94Y</sup> transgenic pig model study.","authors":"Roxane L Degroote, Adrian Schmalen, Simone Renner, Eckhard Wolf, Stefanie M Hauck, Cornelia A Deeg","doi":"10.1002/pmic.202300591","DOIUrl":"https://doi.org/10.1002/pmic.202300591","url":null,"abstract":"<p><p>INS<sup>C94Y</sup> transgenic pigs represent a model for mutant insulin gene-induced diabetes of youth, with impaired insulin secretion and beta cell loss, leading to elevated fasting blood glucose levels. A key complication of diabetes mellitus is diabetic retinopathy (DR), characterized by hyperglycemia-induced abnormalities in the retina. Adjacent to the retina lies the vitreous, a gelatinous matrix vital for ocular function. It harbors proteins and signaling molecules, offering insights into vitreous biology and ocular health. Moreover, as a reservoir for secreted molecules, the vitreous illuminates molecular processes within intraocular structures, especially under pathological conditions. To uncover the proteomic profile of porcine vitreous and explore its relevance to DR, we employed discovery proteomics to compare vitreous samples from INS<sup>C94Y</sup> transgenic pigs and wild-type controls. Our analysis identified 1404 proteins, with 266 showing differential abundance in INS<sup>C94Y</sup> vitreous. Notably, the abundances of ITGB1, COX2, and GRIFIN were significantly elevated in INS<sup>C94Y</sup> vitreous. Gene Set Enrichment Analysis unveiled heightened MYC and mTORC1 signaling in INS<sup>C94Y</sup> vitreous, shedding light on its biological significance in diabetes-associated ocular pathophysiology. These findings deepen our understanding of vitreous involvement in DR and provide valuable insights into potential therapeutic targets. Raw data are accessible via ProteomeXchange (PXD038198).</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141910946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2024-08-01DOI: 10.1002/pmic.202400106
Aurora Callahan, Xien Yu Chua, Alijah A Griffith, Tobias Hildebrandt, Guoping Fu, Mengzhou Hu, Renren Wen, Arthur R Salomon
{"title":"Deep phosphotyrosine characterisation of primary murine T cells using broad spectrum optimisation of selective triggering.","authors":"Aurora Callahan, Xien Yu Chua, Alijah A Griffith, Tobias Hildebrandt, Guoping Fu, Mengzhou Hu, Renren Wen, Arthur R Salomon","doi":"10.1002/pmic.202400106","DOIUrl":"https://doi.org/10.1002/pmic.202400106","url":null,"abstract":"<p><p>Sequencing the tyrosine phosphoproteome using MS-based proteomics is challenging due to the low abundance of tyrosine phosphorylation in cells, a challenge compounded in scarce samples like primary cells or clinical samples. The broad-spectrum optimisation of selective triggering (BOOST) method was recently developed to increase phosphotyrosine sequencing in low protein input samples by leveraging tandem mass tags (TMT), phosphotyrosine enrichment, and a phosphotyrosine-loaded carrier channel. Here, we demonstrate the viability of BOOST in T cell receptor (TCR)-stimulated primary murine T cells by benchmarking the accuracy and precision of the BOOST method and discerning significant alterations in the phosphoproteome associated with receptor stimulation. Using 1 mg of protein input (about 20 million cells) and BOOST, we identify and precisely quantify more than 2000 unique pY sites compared to about 300 unique pY sites in non-BOOST control samples. We show that although replicate variation increases when using the BOOST method, BOOST does not jeopardise quantitative precision or the ability to determine statistical significance for peptides measured in triplicate. Many pY previously uncharacterised sites on important T cell signalling proteins are quantified using BOOST, and we identify new TCR responsive pY sites observable only with BOOST. Finally, we determine that the phase-spectrum deconvolution method on Orbitrap instruments can impair pY quantitation in BOOST experiments.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141873751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2024-08-01DOI: 10.1002/pmic.202400022
Gautam Ghosh, Ariana E Shannon, Brian C Searle
{"title":"Data acquisition approaches for single cell proteomics.","authors":"Gautam Ghosh, Ariana E Shannon, Brian C Searle","doi":"10.1002/pmic.202400022","DOIUrl":"https://doi.org/10.1002/pmic.202400022","url":null,"abstract":"<p><p>Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141873750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2024-07-23DOI: 10.1002/pmic.202400002
Hongkai Xu, Jiangguo Zhang, Fang Wang, Yiyang Chen, Hao Chen, Yang Feng, Guixue Hou, Jin Zi, Meiping Zhang, Jinfeng Zhou, Le Deng, Liang Lin, Xiaoyin Zhang, Siqi Liu
{"title":"Integration of metagenomics and metaproteomics in the intestinal lavage fluids benefits construction of discriminative model and discovery of biomarkers for HBV liver diseases.","authors":"Hongkai Xu, Jiangguo Zhang, Fang Wang, Yiyang Chen, Hao Chen, Yang Feng, Guixue Hou, Jin Zi, Meiping Zhang, Jinfeng Zhou, Le Deng, Liang Lin, Xiaoyin Zhang, Siqi Liu","doi":"10.1002/pmic.202400002","DOIUrl":"https://doi.org/10.1002/pmic.202400002","url":null,"abstract":"<p><p>Intestinal lavage fluid (IVF) containing the mucosa-associated microbiota instead of fecal samples was used to study the gut microbiota using different omics approaches. Focusing on the 63 IVF samples collected from healthy and hepatitis B virus-liver disease (HBV-LD), a question is prompted whether omics features could be extracted to distinguish these samples. The IVF-related microbiota derived from the omics data was classified into two enterotype sets, whereas the genomics-based enterotypes were poorly overlapped with the proteomics-based one in either distribution of microbiota or of IVFs. There is lack of molecular features in these enterotypes to specifically recognize healthy or HBV-LD. Running machine learning against the omics data sought the appropriate models to discriminate the healthy and HBV-LD IVFs based on selected genes or proteins. Although a single omics dataset is basically workable in such discrimination, integration of the two datasets enhances discrimination efficiency. The protein features with higher frequencies in the models are further compared between healthy and HBV-LD based on their abundance, bringing about three potential protein biomarkers. This study highlights that integration of metaomics data is beneficial for a molecular discriminator of healthy and HBV-LD, and reveals the IVF samples are valuable for microbiome in a small cohort.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141750689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2024-07-23DOI: 10.1002/pmic.202400031
Jiří Pospíšil, Alice Sax, Martin Hubálek, Libor Krásný, Jiří Vohradský
{"title":"Whole proteome analysis of germinating and outgrowing Bacillus subtilis 168","authors":"Jiří Pospíšil, Alice Sax, Martin Hubálek, Libor Krásný, Jiří Vohradský","doi":"10.1002/pmic.202400031","DOIUrl":"10.1002/pmic.202400031","url":null,"abstract":"<p>In this study, we present a high-resolution dataset and bioinformatic analysis of the proteome of <i>Bacillus subtilis</i> 168 trp+ (BSB1) during germination and spore outgrowth. Samples were collected at 14 different time points (ranging from 0 to 130 min) in three biological replicates after spore inoculation into germination medium. A total of 2191 proteins were identified and categorized based on their expression kinetics. We observed four distinct clusters that were analyzed for functional categories and KEGG pathways annotations. The examination of newly synthesized proteins between successive time points revealed significant changes, particularly within the first 50 min. The dataset provides an information base that can be used for modeling purposes and inspire the design of new experiments.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202400031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141750690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2024-07-17DOI: 10.1002/pmic.202300650
Fei Fang, Guangyao Gao, Qianyi Wang, Qianjie Wang, Liangliang Sun
{"title":"Combining SDS-PAGE to capillary zone electrophoresis-tandem mass spectrometry for high-resolution top-down proteomics analysis of intact histone proteoforms","authors":"Fei Fang, Guangyao Gao, Qianyi Wang, Qianjie Wang, Liangliang Sun","doi":"10.1002/pmic.202300650","DOIUrl":"10.1002/pmic.202300650","url":null,"abstract":"<p>Mass spectrometry (MS)-based top-down proteomics (TDP) analysis of histone proteoforms provides critical information about combinatorial post-translational modifications (PTMs), which is vital for pursuing a better understanding of epigenetic regulation of gene expression. It requires high-resolution separations of histone proteoforms before MS and tandem MS (MS/MS) analysis. In this work, for the first time, we combined SDS-PAGE-based protein fractionation (passively eluting proteins from polyacrylamide gels as intact species for mass spectrometry, PEPPI-MS) with capillary zone electrophoresis (CZE)-MS/MS for high-resolution characterization of histone proteoforms. We systematically studied the histone proteoform extraction from SDS-PAGE gel and follow-up cleanup as well as CZE-MS/MS, to determine an optimal procedure. The optimal procedure showed reproducible and high-resolution separation and characterization of histone proteoforms. SDS-PAGE separated histone proteins (H1, H2, H3, and H4) based on their molecular weight and CZE provided additional separations of proteoforms of each histone protein based on their electrophoretic mobility, which was affected by PTMs, for example, acetylation and phosphorylation. Using the technique, we identified over 200 histone proteoforms from a commercial calf thymus histone sample with good reproducibility. The orthogonal and high-resolution separations of SDS-PAGE and CZE made our technique attractive for the delineation of histone proteoforms extracted from complex biological systems.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":null,"pages":null},"PeriodicalIF":3.4,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202300650","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141632126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}