Quantitative Chemoproteomic Profiling with Data-Independent Acquisition-Based Mass Spectrometry

被引:46
|
作者
Yang, Fan [1 ]
Jia, Guogeng [1 ]
Guo, Jiuzhou [2 ]
Liu, Yuan [1 ]
Wang, Chu [1 ,2 ]
机构
[1] Peking Univ, Coll Chem & Mol Engn, Synthet & Funct Biomol Ctr,Minist Educ, Beijing Natl Lab Mol Sci,Key Lab Bioorgan Chem &, Beijing 100871, Peoples R China
[2] Peking Univ, Acad Adv Interdisciplinary Studies, Peking Tsinghua Ctr Life Sci, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
CIRCADIAN CLOCK; POSTTRANSLATIONAL MODIFICATIONS; PROTEIN; TRANSCRIPTION; LANDSCAPE; DISCOVERY; COMPLEX; PROBES; CYCLE;
D O I
10.1021/jacs.1c11053
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Activity-based protein profiling (ABPP) has emerged as a powerful and versatile tool to enable annotation of protein functions and discovery of targets of bioactive ligands in complex biological systems. It utilizes chemical probes to covalently label functional sites in proteins so that they can be enriched for mass spectrometry (MS)-based quantitative proteomics analysis. However, the semistochastic nature of data-dependent acquisition and high cost associated with isotopically encoded quantification reagents compromise the power of ABPP in multidimensional analysis and high-throughput screening, when a large number of samples need to be quantified in parallel. Here, we combine the data-independent acquisition (DIA) MS with ABPP to develop an efficient label-free quantitative chemical proteomic method, DIA-ABPP, with good reproducibility and high accuracy for high-throughput quantification. We demonstrated the power of DIA-ABPP for comprehensive profiling of functional cysteineome in three distinct applications, including dose-dependent quantification of cysteines' sensitivity toward a reactive metabolite, screening of ligandable cysteines with a covalent fragment library, and profiling of cysteinome fluctuation in circadian clock cycles. DIA-ABPP will open new opportunities for indepth and multidimensional profiling of functional proteomes and interactions with bioactive small molecules in complex biological systems.
引用
收藏
页码:901 / 911
页数:11
相关论文
共 50 条
  • [21] Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues
    Bruderer, Roland
    Bernhardt, Oliver M.
    Gandhi, Tejas
    Miladinovic, Sasa M.
    Cheng, Lin-Yang
    Messner, Simon
    Ehrenberger, Tobias
    Zanotelli, Vito
    Butscheid, Yulia
    Escher, Claudia
    Vitek, Olga
    Rinner, Oliver
    Reiter, Lukas
    MOLECULAR & CELLULAR PROTEOMICS, 2015, 14 (05) : 1400 - 1410
  • [22] Deep learning approaches for data-independent acquisition proteomics
    Yang, Yi
    Lin, Ling
    Qiao, Liang
    EXPERT REVIEW OF PROTEOMICS, 2021, 18 (12) : 1031 - 1043
  • [23] Comparative proteomics analysis of Tibetan hull-less barley under osmotic stress via data-independent acquisition mass spectrometry
    Wang, Yulin
    Sang, Zha
    Xu, Shaohang
    Xu, Qijun
    Zeng, Xingquan
    Jabu, Dunzhu
    Yuan, Hongjun
    GIGASCIENCE, 2020, 9 (03):
  • [24] Data-independent acquisition method for ubiquitinome analysis reveals regulation of circadian biology
    Hansen, Fynn M.
    Tanzer, Maria C.
    Bruening, Franziska
    Bludau, Isabell
    Stafford, Che
    Schulman, Brenda A.
    Robles, Maria S.
    Karayel, Ozge
    Mann, Matthias
    NATURE COMMUNICATIONS, 2021, 12 (01)
  • [25] MS-BioAP: A Pipeline for biomarker analysis based on data independent acquisition mass spectrometry
    Zhang, ZhenHua
    Chen, Dehua
    Wang, Mei
    Pan, Qiao
    Wang, Zhen
    2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN, 2023,
  • [26] Data-independent acquisition combined with liquid chromatography mass spectrometry technique to detect prognostic protein markers in type I gastric neuroendocrine neoplasm
    Zhang, Meng
    Zheng, Xiuli
    Wang, Chunyan
    Li, Shengmian
    RAPID COMMUNICATIONS IN MASS SPECTROMETRY, 2024, 38 (16)
  • [27] OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data
    Roest, Hannes L.
    Rosenberger, George
    Navarro, Pedro
    Gillet, Ludovic
    Miladinovic, Sasa M.
    Schubert, Olga T.
    Wolskit, Witold
    Collins, Ben C.
    Malmstrom, Johan
    Malmstroem, Lars
    Aebersold, Ruedi
    NATURE BIOTECHNOLOGY, 2014, 32 (03) : 219 - 223
  • [28] Hybrid QconCAT-Based Targeted Absolute and Data-Independent Acquisition-Based Label-Free Quantification Enables In-Depth Proteomic Characterization of Wheat Amylase/Trypsin Inhibitor Extracts
    Sielaff, Malte
    Curella, Valentina
    Neerukonda, Manjusha
    Afzal, Muhammad
    El Hassouni, Khaoula
    Distler, Ute
    Schuppan, Detlef
    Longin, C. Friedrich H.
    Tenzer, Stefan
    JOURNAL OF PROTEOME RESEARCH, 2021, 20 (03) : 1544 - 1557
  • [29] High-throughput, in-depth and estimated absolute quantification of plasma proteome using data-independent acquisition/mass spectrometry ("HIAP-DIA")
    Zhou, Yue
    Tan, Zengqi
    Xue, Peng
    Wang, Yi
    Li, Xiang
    Guan, Feng
    PROTEOMICS, 2021, 21 (05)
  • [30] Using data-independent, high-resolution mass spectrometry in protein biomarker research: Perspectives and clinical applications
    Sajic, Tatjana
    Liu, Yansheng
    Aebersold, Ruedi
    PROTEOMICS CLINICAL APPLICATIONS, 2015, 9 (3-4) : 307 - 321