Volume 7 Issue 3
Jun.  2021
Turn off MathJax
Article Contents
Shao Guangcan, Cao Yong, Chen Zhenlin, Liu Chao, Li Shangtong, Chi Hao, Dong Meng-Qiu. How to use open-pFind in deep proteomics data analysis?— A protocol for rigorous identification and quantitation of peptides and proteins from mass spectrometry data[J]. Biophysics Reports, 2021, 7(3): 207-226. doi: 10.52601/bpr.2021.210004
Citation: Shao Guangcan, Cao Yong, Chen Zhenlin, Liu Chao, Li Shangtong, Chi Hao, Dong Meng-Qiu. How to use open-pFind in deep proteomics data analysis?— A protocol for rigorous identification and quantitation of peptides and proteins from mass spectrometry data[J]. Biophysics Reports, 2021, 7(3): 207-226. doi: 10.52601/bpr.2021.210004

How to use open-pFind in deep proteomics data analysis?— A protocol for rigorous identification and quantitation of peptides and proteins from mass spectrometry data

doi: 10.52601/bpr.2021.210004
Funds:  The authors would like to thank Yong-Hong Yan, Dr. Li Tao, and Yue Zhao of NIBS, Beijing and Dr. Ming Ding of China Pharmaceutical University for providing sample datasets to this protocol. The authors also thank the National Natural Science Foundation of China (grant 21675153), the Beijing Municipal Science and Technology Commission, and the Ministry of Science and Technology of China for research funding.
More Information
  • High-throughput proteomics based on mass spectrometry (MS) analysis has permeated biomedical science and propelled numerous research projects. pFind 3 is a database search engine for high-speed and in-depth proteomics data analysis. pFind 3 features a swift open search workflow that is adept at uncovering less obvious information such as unexpected modifications or mutations that would have gone unnoticed using a conventional data analysis pipeline. In this protocol, we provide step-by-step instructions to help users mastering various types of data analysis using pFind 3 in conjunction with pParse for data pre-processing and if needed, pQuant for quantitation. This streamlined pParse-pFind-pQuant workflow offers exceptional sensitivity, precision, and speed. It can be easily implemented in any laboratory in need of identifying peptides, proteins, or post-translational modifications, or of quantitation based on 15N-labeling, SILAC-labeling, or TMT/iTRAQ labeling.
  • loading
  • [1]
    Aebersold R, Mann M (2016) Mass-spectrometric exploration of proteome structure and function. Nature 537: 347−355 doi: 10.1038/nature19949
    [2]
    Chen C, Hou J, TannerJJ, Cheng J (2020) Bioinformatics methods for mass spectrometry-based proteomics data analysis. Int J Mol Sci 21: 2873. https://doi.org/10.3390/ijms21082873 doi: 10.3390/ijms21082873
    [3]
    Chi H, Liu C, Yang H, Zeng WF, Wu L, Zhou WJ, Wang RM, Niu XN, Ding YH, Zhang Y, Wang ZW, Chen ZL, Sun RX, Liu T, Tan GM, Dong MQ, Xu P, Zhang PH, He SM (2018) Comprehensive identification of peptides in tandem mass spectra using an efficient open search engine. Nat Biotechnol 36: 1059−1061 doi: 10.1038/nbt.4236
    [4]
    Cong Y, Motamedchaboki K, Misal SA, Liang Y, Guise AJ, Truong T, Huguet R, Plowey ED, Zhu Y, Lopez-Ferrer D, Kelly RT (2021) Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell. Chem Sci 12: 1001−1006 doi: 10.1039/D0SC03636F
    [5]
    Conrads TP, Alving K, Veenstra TD, Belov ME, Anderson GA, Anderson DJ, Lipton MS, Pasa-Tolic L, Udseth HR, Chrisler WB, Thrall BD, Smith RD (2001) Quantitative analysis of bacterial and mammalian proteomes using a combination of cysteine affinity tags and 15N-metabolic labeling. Anal Chem 73: 2132−2139 doi: 10.1021/ac001487x
    [6]
    Creasy DM, Cottrell JS (2004) Unimod: protein modifications for mass spectrometry. Proteomics 4: 1534−1536 doi: 10.1002/pmic.200300744
    [7]
    Hoopmann MR, Moritz RL (2013) Current algorithmic solutions for peptide-based proteomics data generation and identification. Curr Opin Biotechnol 24: 31−38 doi: 10.1016/j.copbio.2012.10.013
    [8]
    Huesgen PF, Lange PF, Rogers LD, Solis N, Eckhard U, Kleifeld O, Goulas T, Gomis-Ruth FX, Overall CM (2015) LysargiNase mirrors trypsin for protein C-terminal and methylation-site identification. Nat methods 12: 55−58 doi: 10.1038/nmeth.3177
    [9]
    Ma J, Chen T, Wu S, Yang C, Bai M, Shu K, Li K, Zhang G, Jin Z, He F (2019) iProX: an integrated proteome resource. Nucleic Acids Res 47: D1211−D1217 doi: 10.1093/nar/gky869
    [10]
    Meier F, Brunner AD, Frank M, Ha A, Bludau I, Voytik E, Kaspar-Schoenefeld S, Lubeck M, Raether O, Bache N, Aebersold R, Collins BC, Röst HL, Mann M (2020) diaPASEF: parallel accumulation-serial fragmentation combined with data-independent acquisition. Nature methods 17: 1229−1236 doi: 10.1038/s41592-020-00998-0
    [11]
    Milo R (2013) What is the total number of protein molecules per cell volume? A call to rethink some published values. BioEssays 35: 1050−1055 doi: 10.1002/bies.201300066
    [12]
    Muller JB, Geyer PE, Colaco AR, Treit PV, Strauss MT, Oroshi M, Doll S, Virreira Winter S, Bader JM, Kohler N, Theis F, Santos A, Mann M (2020) The proteome landscape of the kingdoms of life. Nature 582: 592−596 doi: 10.1038/s41586-020-2402-x
    [13]
    Ong SE, Blagoev B, Kratchmarova I, Kristensen DB, Steen H, Pandey A, Mann M (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1: 376−386 doi: 10.1074/mcp.M200025-MCP200
    [14]
    Thompson A, Schafer J, Kuhn K, Kienle S, Schwarz J, Schmidt G, Neumann T, Johnstone R, Mohammed AK, Hamon C (2003) Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal Chem 75: 1895−1904 doi: 10.1021/ac0262560
    [15]
    Valikangas T, Suomi T, Elo LL (2018) A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation. Brief Bioinform 19: 1344−1355
  • Supplementary Materials.pdf
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(22)  / Tables(1)

    Article Metrics

    Article views (2097) PDF downloads(171) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return