MS1 ion current-based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts

被引:36
作者
Wang, Xue [1 ]
Shen, Shichen [2 ]
Rasam, Sailee Suryakant [3 ]
Qu, Jun [1 ,2 ,3 ]
机构
[1] Roswell Park Canc Inst, Dept Cell Stress Biol, Buffalo, NY 14263 USA
[2] SUNY Buffalo, Dept Pharmaceut Sci, New York, NY USA
[3] SUNY Buffalo, Dept Biochem, New York, NY USA
关键词
MS1; quantification; ion current-based proteomics; LC-MS; reproducible protein measurement; large cohorts; DATA-INDEPENDENT ACQUISITION; FALSE DISCOVERY RATES; SAMPLE PREPARATION METHOD; LIQUID CHROMATOGRAPHY/MASS SPECTROMETRY; REVEALS CANDIDATE MARKERS; LABEL-FREE QUANTIFICATION; COMPLEX PROTEIN MIXTURES; DECOY SEARCH STRATEGY; MASS-SPECTROMETRY; LC-MS;
D O I
10.1002/mas.21595
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
The rapidly-advancing field of pharmaceutical and clinical research calls for systematic, molecular-level characterization of complex biological systems. To this end, quantitative proteomics represents a powerful tool but an optimal solution for reliable large-cohort proteomics analysis, as frequently involved in pharmaceutical/clinical investigations, is urgently needed. Large-cohort analysis remains challenging owing to the deteriorating quantitative quality and snowballing missing data and false-positive discovery of altered proteins when sample size increases. MS1 ion current-based methods, which have become an important class of label-free quantification techniques during the past decade, show considerable potential to achieve reproducible protein measurements in large cohorts with high quantitative accuracy/precision. Nonetheless, in order to fully unleash this potential, several critical prerequisites should be met. Here we provide an overview of the rationale of MS1-based strategies and then important considerations for experimental and data processing techniques, with the emphasis on (i) efficient and reproducible sample preparation and LC separation; (ii) sensitive, selective and high-resolution MS detection; iii)accurate chromatographic alignment; (iv) sensitive and selective generation of quantitative features; and (v) optimal post-feature-generation data quality control. Prominent technical developments in these aspects are discussed. Finally, we reviewed applications of MS1-based strategy in disease mechanism studies, biomarker discovery, and pharmaceutical investigations.
引用
收藏
页码:461 / 482
页数:22
相关论文
共 233 条
[1]   A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease [J].
Addona, Terri A. ;
Shi, Xu ;
Keshishian, Hasmik ;
Mani, D. R. ;
Burgess, Michael ;
Gillette, Michael A. ;
Clauser, Karl R. ;
Shen, Dongxiao ;
Lewis, Gregory D. ;
Farrell, Laurie A. ;
Fifer, Michael A. ;
Sabatine, Marc S. ;
Gerszten, Robert E. ;
Carr, Steven A. .
NATURE BIOTECHNOLOGY, 2011, 29 (07) :635-U119
[2]   In vitro and in silico processes to identify differentially expressed proteins [J].
Allet, N ;
Barrillat, N ;
Baussant, T ;
Boiteau, C ;
Botti, P ;
Bougueleret, L ;
Budin, N ;
Canet, D ;
Carraud, S ;
Chiappe, D ;
Christmann, N ;
Colinge, J ;
Cusin, I ;
Dafflon, N ;
Depresle, B ;
Fasso, I ;
Frauchiger, P ;
Gaertner, H ;
Gleizes, A ;
Gonzalez-Couto, E ;
Jeandenans, C ;
Karmime, A ;
Kowall, T ;
Lagache, S ;
Mahé, E ;
Masselot, A ;
Mattou, H ;
Moniatte, M ;
Niknejad, A ;
Paolini, M ;
Perret, F ;
Pinaud, N ;
Ranno, F ;
Raimondi, S ;
Reffas, S ;
Regamey, PO ;
Rey, PA ;
Rodriguez-Tomé, P ;
Rose, K ;
Rossellat, G ;
Saudrais, C ;
Schmidt, C ;
Villain, M ;
Zwahlen, C .
PROTEOMICS, 2004, 4 (08) :2333-2351
[3]   Surfactant-Aided Precipitation/on-Pellet-Digestion (SOD) Procedure Provides Robust and Rapid Sample Preparation for Reproducible, Accurate and Sensitive LC/MS Quantification of Therapeutic Protein in Plasma and Tissues [J].
An, Bo ;
Zhang, Ming ;
Johnson, Robert W. ;
Qu, Jun .
ANALYTICAL CHEMISTRY, 2015, 87 (07) :4023-4029
[4]   A universal denoising and peak picking algorithm for LC-MS based on matched filtration in the chromatographic time domain [J].
Andreev, VP ;
Rejtar, T ;
Chen, HS ;
Moskovets, EV ;
Ivanov, AR ;
Karger, BL .
ANALYTICAL CHEMISTRY, 2003, 75 (22) :6314-6326
[5]   MassUntangler: A novel alignment tool for label-free liquid chromatography-mass spectrometry proteomic data [J].
Ballardini, R. ;
Benevento, M. ;
Arrigoni, G. ;
Pattini, L. ;
Roda, A. .
JOURNAL OF CHROMATOGRAPHY A, 2011, 1218 (49) :8859-8868
[6]   A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS [J].
Bellew, Matthew ;
Coram, Marc ;
Fitzgibbon, Matthew ;
Igra, Mark ;
Randolph, Tim ;
Wang, Pei ;
May, Damon ;
Eng, Jimmy ;
Fang, Ruihua ;
Lin, ChenWei ;
Chen, Jinzhi ;
Goodlett, David ;
Whiteaker, Jeffrey ;
Paulovich, Amanda ;
McIntosh, Martin .
BIOINFORMATICS, 2006, 22 (15) :1902-1909
[7]   Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach [J].
Beretov, Julia ;
Wasinger, Valerie C. ;
Millar, Ewan K. A. ;
Schwartz, Peter ;
Graham, Peter H. ;
Li, Yong .
PLOS ONE, 2015, 10 (11)
[8]   A better understanding of molecular mechanisms underlying human disease [J].
Bermudez-Crespo, Jose ;
Lopez, Jose Luis .
PROTEOMICS CLINICAL APPLICATIONS, 2007, 1 (09) :983-1003
[9]  
Bessant C, 2016, PROTEOME INFORM
[10]   Comparison of Novel Decoy Database Designs for Optimizing Protein Identification Searches Using ABRF sPRG2006 Standard MS/MS Data Sets [J].
Bianco, Luca ;
Mead, Jennifer A. ;
Bessant, Conrad .
JOURNAL OF PROTEOME RESEARCH, 2009, 8 (04) :1782-1791