DART-ID increases single-cell proteome coverage

被引:52
作者
Chen, Albert Tian [1 ,2 ]
Franks, Alexander [3 ]
Slavov, Nikolai [1 ,2 ,4 ]
机构
[1] Northeastern Univ, Dept Bioengn, Boston, MA 02115 USA
[2] Northeastern Univ, Barnett Inst, Boston, MA 02115 USA
[3] Univ Calif Santa Barbara, Dept Stat & Appl Probabil, Santa Barbara, CA 93106 USA
[4] Northeastern Univ, Dept Biol, Boston, MA 02115 USA
基金
美国国家卫生研究院;
关键词
DATA-INDEPENDENT ACQUISITION; RETENTION TIME PREDICTION; REVERSED-PHASE HPLC; PEPTIDE RETENTION; LIQUID-CHROMATOGRAPHY; ACCURATE MASS; STATISTICAL-MODEL; TARGETED ANALYSIS; IDENTIFICATION; INFORMATION;
D O I
10.1371/journal.pcbi.1007082
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Analysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. This process, however, remains challenging for smaller samples, such as the proteomes of single mammalian cells, because reduced protein levels reduce the number of confidently sequenced peptides. To alleviate this reduction, we developed Data-driven Alignment of Retention Times for IDentification (DART-ID). DART-ID implements principled Bayesian frameworks for global retention time (RT) alignment and for incorporating RT estimates towards improved confidence estimates of peptide-spectrum-matches. When applied to bulk or to single-cell samples, DART-ID increased the number of data points by 30-50% at 1% FDR, and thus decreased missing data. Benchmarks indicate excellent quantification of peptides upgraded by DART-ID and support their utility for quantitative analysis, such as identifying cell types and cell-type specific proteins. The additional datapoints provided by DART-ID boost the statistical power and double the number of proteins identified as differentially abundant in monocytes and T-cells.
引用
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页数:30
相关论文
共 64 条
[31]   Critical assessment of alignment procedures for LC- MS proteomics and metabolomics measurements [J].
Lange, Eva ;
Tautenhahn, Ralf ;
Neumann, Steffen ;
Groepl, Clemens .
BMC BIOINFORMATICS, 2008, 9 (1)
[32]   Single cell protein analysis for systems biology [J].
Levy, Ezra ;
Slavov, Nikolai .
SYSTEMS BIOLOGY, 2018, 62 (04) :595-605
[33]   Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures [J].
Li, Guo-Zhong ;
Vissers, Johannes P. C. ;
Silva, Jeffrey C. ;
Golick, Dan ;
Gorenstein, Marc V. ;
Geromanos, Scott J. .
PROTEOMICS, 2009, 9 (06) :1696-1719
[34]   Locus-specific Retention Predictor (LsRP): A Peptide Retention Time Predictor Developed for Precision Proteomics [J].
Lu, Wenyuan ;
Liu, Xiaohui ;
Liu, Shanshan ;
Cao, Weiqian ;
Zhang, Yang ;
Yang, Pengyuan .
SCIENTIFIC REPORTS, 2017, 7
[35]   Skyline: an open source document editor for creating and analyzing targeted proteomics experiments [J].
MacLean, Brendan ;
Tomazela, Daniela M. ;
Shulman, Nicholas ;
Chambers, Matthew ;
Finney, Gregory L. ;
Frewen, Barbara ;
Kern, Randall ;
Tabb, David L. ;
Liebler, Daniel C. ;
MacCoss, Michael J. .
BIOINFORMATICS, 2010, 26 (07) :966-968
[36]  
Malioutov D, 2014, PR MACH LEARN RES, V32, P109
[37]   Information-dependent LC-MS/MS acquisition with exclusion lists potentially generated on-the-fly: Case study using a whole cell digest of Clostridium thermocellum [J].
McQueen, Peter ;
Spicer, Vic ;
Rydzak, Thomas ;
Sparling, Richard ;
Levin, David ;
Wilkins, John A. ;
Krokhin, Oleg .
PROTEOMICS, 2012, 12 (08) :1160-1169
[38]   PREDICTION OF PEPTIDE RETENTION TIMES IN HIGH-PRESSURE LIQUID-CHROMATOGRAPHY ON THE BASIS OF AMINO-ACID-COMPOSITION [J].
MEEK, JL .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-BIOLOGICAL SCIENCES, 1980, 77 (03) :1632-1636
[39]   PEPTIDE RETENTION TIME PREDICTION [J].
Moruz, Luminita ;
Kall, Lukas .
MASS SPECTROMETRY REVIEWS, 2017, 36 (05) :615-623
[40]   Training, Selection, and Robust Calibration of Retention Time Models for Targeted Proteomics [J].
Moruz, Luminita ;
Tomazela, Daniela ;
Kall, Lukas .
JOURNAL OF PROTEOME RESEARCH, 2010, 9 (10) :5209-5216