pFind Studio: a computational solution for mass spectrometry-based proteomics
2016
Statistical Analysis in Proteomics2016. et al.
National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Zhongguancun East Road 55, Beijing, 100190, China
ABSTRACT:Mass spectrometry-based proteomics provides a powerful tool for large-scale analysis of protein modifications. Statistical and computational analysis of mass spectrometry data is a key step in protein modification identification. This chapter presents common and advanced data analysis strategies for modification identification, including variable modification search, unrestrictive approaches for modification discovery, false discovery rate estimation and control methods, and tools for modification site localization.
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Molecular & Cellular Proteomics2016. Han, YM et al.
Univ Penn, Perelman Sch Med, Dept Biochem & Biophys, Epigenet Program,Smilow Ctr Translat Res, 3400 Civ Ctr Blvd,Bldg 421, Philadelphia, PA 19104 USA.
ABSTRACT:Protein phosphorylation, one of the most common and important modifications of acute and reversible regulation of protein function, plays a dominant role in almost all cellular processes. These signaling events regulate cellular responses, including proliferation, differentiation, metabolism, survival, and apoptosis. Several studies have been successfully used to identify phosphorylated proteins and dynamic changes in phosphorylation status after stimulation. Nevertheless, it is still rather difficult to elucidate precise complex phosphorylation signaling pathways. In particular, how signal transduction pathways directly communicate from the outer cell surface through cytoplasmic space and then directly into chromatin networks to change the transcriptional and epigenetic landscape remains poorly understood. Here, we describe the optimization and comparison of methods based on thiophosphorylation affinity enrichment, which can be utilized to monitor phosphorylation signaling into chromatin by isolation of phosphoprotein containing nucleosomes, a method we term phosphorylation-specific chromatin affinity purification (PS-ChAP). We utilized this PS-ChAP(1) approach in combination with quantitative proteomics to identify changes in the phosphorylation status of chromatin-bound proteins on nucleosomes following perturbation of transcriptional processes. We also demonstrate that this method can be employed to map phosphoprotein signaling into chromatin containing nucleosomes through identifying the genes those phosphorylated proteins are found on via thiophosphate PS-ChAP-qPCR. Thus, our results showed that PS-ChAP offers a new strategy for studying cellular signaling and chromatin biology, allowing us to directly and comprehensively investigate phosphorylation signaling into chromatin to investigate if these pathways are involved in altering gene expression. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD002436.
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Analytical Chemistry2016. Xiong, Y et al.
Chinese Acad Sci, Tianjin Inst Ind Biotechnol, Key Lab Syst Microbial Biotechnol, Tianjin 300308, Peoples R China.
ABSTRACT:Detection of proteins containing single amino acid polymorphisms (SAPs) encoded by nonsynonymous SNPs (nsSNPs) can aid researchers in studying the functional significance of protein variants. Most proteogenomic approaches for large-scale SAPs mapping require construction of a sample specific database containing protein variants predicted from the next-generation sequencing (NGS) data. Searching shotgun proteomic data sets against these NGS-derived databases allowed for identification of SAP peptides, thus validating the proteome-level sequence variation. Contrary to the conventional approaches, our study presents a novel strategy for proteome-wide SAP detection without relying on sample-specific NGS data. By searching a deep-coverage proteomic data set from an industrial thermotolerant yeast strain using our strategy, we identified 337 putative SAPs compared to the reference genome. Among the SAP peptides identified with stringent criteria, 85.2% of SAP sites were validated using whole-genome sequencing data obtained for this organism, which indicates high accuracy of SAP identification with our strategy. More interestingly, for certain SAP peptides that cannot be predicted by genomic sequencing, we used synthetic peptide standards to verify expression of peptide variants in the proteome. Our study has provided a unique tool for proteogenomics to enable proteome-wide direct SAP identification and capture nongenetic protein variants not linked to nsSNPs.
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Biotechnology letters2016. Ning, Chanjuan et al.
South China Normal Univ, Sch Life Sci, Key Lab Ecol & Environm Sci Guangdong Higher Educ, Guangzhou 510631, Guangdong, Peoples R China
ABSTRACT:To establish an in-house virtual protein database that can be employed in proteomic research on non-model plants.A total of 87,430 unigenes were obtained through transcriptome sequencing from onion roots. Of these, 24,305 unigenes were annotated and their nucleotide sequences of coding regions were translated into amino acid sequences. The corresponding 24,305 amino acid sequences were considered as an in-house virtual protein database. Thirty-two protein spots with significant differential abundance were selected. Their MS data were submitted to a restriction enzyme map which was converted from the in-house virtual protein database. A total of 27 proteins were finally matched.The in-house protein database is a feasible and innovative strategy for proteomic research on non-model plants.
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Journal of Genetics and Genomics2016. Wei, CQ et al.
Hebei Normal Univ, Hebei Key Lab Mol & Cellular Biol, Key Lab Mol & Cellular Biol,Coll Life Sci, Hebei Collaborat Innovat Ctr Cell Signaling,Minis, Shijiazhuang 050024, Peoples R China.
ABSTRACT:Plant growth is controlled by integration of hormonal and light-signaling pathways. BZS1 is a B-box zinc finger protein previously characterized as a negative regulator in the brassinosteroid (BR)-signaling pathway and a positive regulator in the light-signaling pathway. However, the mechanisms by which BZS1/BBX20 integrates light and hormonal pathways are not fully understood. Here, using a quantitative proteomic workflow, we identified several BZS1-associated proteins, including light-signaling components COP1 and HY5. Direct interactions of BZS1 with COP1 and HY5 were verified by yeast two-hybrid and co-immunoprecipitation assays. Overexpression of BZS1 causes a dwarf phenotype that is suppressed by the hy5 mutation, while overexpression of BZS1 fused with the SRDX transcription repressor domain (BZS1-SRDX) causes a long-hypocotyl phenotype similar to hy5, indicating that BZS1's function requires HY5. BZS1 positively regulates HY5 expression, whereas HY5 negatively regulates BZS1 protein level, forming a feedback loop that potentially contributes to signaling dynamics. In contrast to BR, strigolactone (SL) increases BZS1 level, whereas the SL responses of hypocotyl elongation, chlorophyll and HY5 accumulation are diminished in the BZS1-SRDX seedlings, indicating that BZS1 is involved in these SL responses. These results demonstrate that BZS1 interacts with HY5 and plays a central role in integrating light and multiple hormone signals for photomorphogenesis in Arabidopsis. Copyright (C) 2016, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Limited and Science Press. All rights reserved.
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Journal of Proteome Research2016. Choi, M et al.
Northeastern Univ, Boston, MA 02115 USA.
ABSTRACT:Detection of differentially abundant proteins in label-free quantitative shotgun liquid chromatography tandem mass spectrometry (LC-MS/MS) experiments requires a series of computational steps that identify and quantify LC-MS features. It also requires statistical analyses that distinguish systematic changes in abundance between conditions from artifacts of biological and technical variation. The 2015 study of the Proteome Informatics Research Group (iPRG) of the Association of Biomolecular Resource Facilities (ABRF) aimed to evaluate the effects of the statistical analysis on the accuracy of the results. The study used LC tandem mass spectra acquired from a controlled mixture, and made the data available to anonymous volunteer participants. The participants used methods of their choice to detect differentially abundant proteins, estimate the associated fold changes, and characterize the uncertainty of the results. The study found that multiple strategies (including the use of spectral counts versus peak intensities, and various software tools) could lead to accurate results, and that the performance was primarily determined by the analysts' expertise. This manuscript summarizes the outcome of the study, and provides representative examples of good computational and statistical practice. The data set generated as part of this study is publicly available.
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Current Protocols in Protein Science2016. Xing-Jun Cao1; Benjamin A. Garcia et al.
Epigenetics Program, Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
ABSTRACT:Lysinemethylationis a commonproteinpost-translational modification dynamically mediated byproteinlysinemethyltransferases (PKMTs) andproteinlysinedemethylases (PKDMs). Beyond histone proteins,lysinemethylationon non-histone proteins plays a substantial role in a varietyoffunctions in cells and is closely associated with diseases such as cancer. A large bodyofevidence indicates that the dysregulationofsome PKMTs leads to tumorigenesis via their non-histone substrates. However, most studies on other PKMTs have made slow progress owing to the lackofapproaches for extensive screeningoflysinemethylationsites. However, recently, there has been a seriesofpublications to perform large-scaleanalysisofproteinlysinemethylation. In this unit, we introduce a protocol for theglobalanalysisofproteinlysinemethylationin cells by meansofimmunoaffinity enrichment and mass spectrometry. 2016 by John Wiley & Sons, Inc.
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Molecular Plant2016. Shuo-Lei Bu; Chao Liu; Ning Liu et al.
Hebei Key Laboratory of Molecular and Cellular Biology, Hebei Collaboration Innovation Center for Cell Signaling, College of Life Science, Hebei Normal University, Hebei 050024, China | Department of Plant Biology, Carnegie Institution for Science, Stanford, CA 94305, USA
ABSTRACT:
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Analytical and Bioanalytical Chemistry2016. Zhu, H et al.
Georgia State Univ, Dept Chem, Atlanta, GA 30303 USA.
ABSTRACT:N-Glycosylation is one of the most prevalent protein post-translational modifications and is involved in many biological processes, such as protein folding, cellular communications, and signaling. Alteration of N-glycosylation is closely related to the pathogenesis of diseases. Thus, the investigation of protein N-glycosylation is crucial for the diagnosis and treatment of disease. In this research, we applied diethylaminoethanol (DEAE) Sepharose solid-phase extraction microcolumns for N-glycopeptide enrichment. This method integrated the advantages of Click Maltose and zwitterionic HILIC (ZIC-HILIC) and showed a relatively higher specificity for N-glycosylated peptides. This strategy was then applied to tryptic digests of normal human serum, followed by deglycosylation using peptide-N-glycosidase F (PNGase F) in H-2 O-18. Subsequent LC-MS/MS analysis allowed for the assignment of 219 N-glycosylation sites from 115 serum N-glycoproteins. This study provides an alternative approach for N-glycopeptide enrichment and the method employed is effective for large-scale N-glycosylation site identification.
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Molecular Cancer Therapeutics2016. Yi, JM et al.
Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Div Antitumor Pharmacol, Shanghai, Peoples R China.
ABSTRACT:Multidrug resistance (MDR) is a major cause of tumor treatment failure; therefore, drugs that can avoid this outcome are urgently needed. We studied triptolide, which directly kills MDR tumor cells with a high potency and a broad spectrum of cell death. Triptolide did not inhibit P-glycoprotein (P-gp) drug efflux and reduced P-gp and MDR1 mRNA resulting from transcription inhibition. Transcription factors including c-MYC, SOX-2, OCT-4, and NANOG were not correlated with triptolide-induced cell killing, but RPB1, the largest subunit of RNA polymerase II, was critical in mediating triptolide's inhibition of MDR cells. Triptolide elicited antitumor and anti-MDR activity through a universal mechanism: by activating CDK7 by phosphorylating Thr170 in both parental and MDR cell lines and in SK-OV-3 cells. The CDK7-selective inhibitor BS-181 partially rescued cell killing induced by 72-hour treatment of triptolide, which may be due to partial rescue of RPB1 degradation. We suggest that a precise phosphorylation site on RPB1 (Ser1878) was phosphorylated by CDK7 in response to triptolide. In addition, XPB and p44, two transcription factor TFIIH subunits, did not contribute to tripto-lide-driven RPB1 degradation and cell killing, although XPB was reported to covalently bind to triptolide. Several clinical trials are underway to test triptolide and its analogues for treating cancer and other diseases, so our data may help expand potential clinical uses of triptolide, as well as offer a compound that overcomes tumor MDR. Future investigations into the primary molecular target(s) of triptolide responsible for RPB1 degradation may suggest novel anti-MDR target(s) for therapeutic development. (C) 2016 AACR.
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