| Literature DB >> 35835881 |
Jason Derks1, Andrew Leduc2, Georg Wallmann2, R Gray Huffman2, Matthew Willetts3, Saad Khan2, Harrison Specht2, Markus Ralser4,5, Vadim Demichev6, Nikolai Slavov7.
Abstract
Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completeness, reducing missing data more than twofold across samples. Applied to single human cells, plexDIA quantified ~1,000 proteins per cell and achieved 98% data completeness within a plexDIA set while using ~5 minutes of active chromatography per cell. These results establish a general framework for increasing the throughput of sensitive and quantitative protein analysis.Entities:
Year: 2022 PMID: 35835881 DOI: 10.1038/s41587-022-01389-w
Source DB: PubMed Journal: Nat Biotechnol ISSN: 1087-0156 Impact factor: 68.164