DART-ID increases single-cell proteome coverage

• Published in: PLoS computational biology Vol. 15; no. 7; p. e1007082
• Main Authors: Chen, Albert Tian, Franks, Alexander, Slavov, Nikolai
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.07.2019; Public Library of Science (PLoS)
• Subjects: Alignment; Analytical chemistry; Artificial intelligence; Automation; Bayes Theorem; Bayesian analysis; Benchmarking; Benchmarks; Bioengineering; Bioinformatics; Biology and Life Sciences; Cells (Biology); Chromatography; Chromatography, Liquid - methods; Confidence; Data points; Estimates; Experiments; Identification; Liquid chromatography; Lymphocytes T; Machine learning; Mammalian cells; Mass spectrometry; Mass spectroscopy; Medicine and Health Sciences; Methods; Missing data; Monocytes; Peptides; Physical Sciences; Proteins; Proteome; Proteomes; Proteomics; Quantitative analysis; Research and Analysis Methods; Retention; Retention time; Scientific imaging; Search engines; Single-Cell Analysis; Software; Spectroscopy; Statistical methods; T cells; Tandem Mass Spectrometry - methods; China; United States > US; Massachusetts; California
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1007082

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. DART-ID can be applied to diverse experimental designs and is freely available at http://dart-id.slavovlab.net.