Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas

被引:10
|
作者
van Wijk, Klaas J. [3 ]
Leppert, Tami [1 ]
Sun, Zhi [1 ]
Kearly, Alyssa [2 ]
Li, Margaret [1 ]
Mendoza, Luis [1 ]
Guzchenko, Isabell [3 ]
Debley, Erica [3 ]
Sauermann, Georgia [3 ]
Routray, Pratyush [3 ]
Malhotra, Sagunya [1 ]
Nelson, Andrew [2 ]
Sun, Qi [4 ]
Deutsch, Eric W. [1 ]
机构
[1] Inst Syst Biol ISB, Seattle, WA 98109 USA
[2] Boyce Thompson Inst Plant Res, Ithaca, NY 14853 USA
[3] Cornell Univ, Sch Integrat Plant Sci SIPS, Sect Plant Biol, Ithaca, NY 14853 USA
[4] Cornell Univ, Computat Biol Serv Unit, Ithaca, NY 14853 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Arabidopsis; PeptideAtlas; post-translational modifications; ProteomeXchange; machine learning; signaling peptides; E3; ligases; SPECTROMETRY-BASED ANALYSIS; MASS-SPECTROMETRY; N-TERMINOME; THALIANA; PLANT; IDENTIFICATION; PROTEINS; PHOSPHORYLATION; DATABASE; REVEALS;
D O I
10.1021/acs.jproteome.3c00536
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying similar to 0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.
引用
收藏
页码:185 / 214
页数:30
相关论文
共 50 条
  • [31] Comprehensive data and workflow for mapping global proteome and post-translational modifications in Indian Major Carp, Labeo rohita
    Nissa, Mehar Un
    Banerjee, Anwesha
    Goswami, Mukunda
    Srivastava, Sanjeeva
    Data in Brief, 2022, 45
  • [32] The Arabidopsis thaliana 2-D gel mitochondrial proteome: Refining the value of reference maps for assessing protein abundance, contaminants and post-translational modifications
    Taylor, Nicolas L.
    Heazlewood, Joshua L.
    Millar, A. Harvey
    PROTEOMICS, 2011, 11 (09) : 1720 - 1733
  • [33] 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
    An, Zhiwu
    Zhai, Linhui
    Ying, Wantao
    Qian, Xiaohong
    Gong, Fuzhou
    Tan, Minjia
    Fu, Yan
    MOLECULAR & CELLULAR PROTEOMICS, 2019, 18 (02) : 391 - 405
  • [34] Mass Spectrometry of Formalin-Fixed Paraffin-Embedded Tissue: Proteome, Phosphoproteome and Histone Post-Translational Modifications
    Wojcik, John
    Sidoli, Simone
    Garcia, Benjamin A.
    Cooper, Kumarasen
    LABORATORY INVESTIGATION, 2016, 96 : 525A - 525A
  • [35] Analysis of proteome and post-translational modifications of 2-hydroxyisobutyrylation reveals the glycolysis pathway in oral adenoid cystic carcinoma
    Chen, Sining
    Li, Dandan
    Zeng, Zhipeng
    Zhang, Wei
    Xie, Hongliang
    Tang, Jianming
    Liao, Shengyou
    Cai, Wanxia
    Liu, Fanna
    Tang, Donge
    Dai, Yong
    WORLD JOURNAL OF SURGICAL ONCOLOGY, 2023, 21 (01)
  • [36] Proteomics of acute myeloid leukemia: Cytogenetic risk groups differ specifically in their proteome, interactome and post-translational protein modifications
    Balkhi, MY
    Geletu, M
    Christopeit, M
    Behre, HM
    Behre, G
    BLOOD, 2005, 106 (11) : 356A - 356A
  • [37] A De Novo Sequencing method for identifying novel amino acid mutations and post-translational modifications in human serum proteome
    Liu, Hongbin
    Nicol, Gordon
    Martosella, James
    Zolotarjova, Nina
    Boyes, Barry
    MOLECULAR & CELLULAR PROTEOMICS, 2004, 3 (10) : S292 - S292
  • [38] Proteomics of acute myeloid leukaemia: cytogenetic risk groups differ specifically in their proteome, interactome and post-translational protein modifications
    Balkhi, M. Y.
    Trivedi, A. K.
    Geletu, M.
    Christopeit, M.
    Bohlander, S. K.
    Behre, H. M.
    Behre, G.
    ONCOGENE, 2006, 25 (53) : 7041 - 7058
  • [39] Proteomics of acute myeloid leukaemia: cytogenetic risk groups differ specifically in their proteome, interactome and post-translational protein modifications
    M Y Balkhi
    A K Trivedi
    M Geletu
    M Christopeit
    S K Bohlander
    H M Behre
    G Behre
    Oncogene, 2006, 25 : 7041 - 7058
  • [40] Analysis of proteome and post-translational modifications of 2-hydroxyisobutyrylation reveals the glycolysis pathway in oral adenoid cystic carcinoma
    Sining Chen
    Dandan Li
    Zhipeng Zeng
    Wei Zhang
    Hongliang Xie
    Jianming Tang
    Shengyou Liao
    Wanxia Cai
    Fanna Liu
    Donge Tang
    Yong Dai
    World Journal of Surgical Oncology, 21