| Literature DB >> 34319755 |
Andrea Fossati1,2,3, Alicia L Richards1,2,3, Kuei-Ho Chen1,2,3, Devan Jaganath4,5,6, Adithya Cattamanchi4,5,6, Joel D Ernst7, Danielle L Swaney1,2,3.
Abstract
Rapid and consistent protein identification across large clinical cohorts is an important goal for clinical proteomics. With the development of data-independent technologies (DIA/SWATH-MS), it is now possible to analyze hundreds of samples with great reproducibility and quantitative accuracy. However, this technology benefits from empirically derived spectral libraries that define the detectable set of peptides and proteins. Here, we apply a simple and accessible tip-based workflow for the generation of spectral libraries to provide a comprehensive overview on the plasma proteome in individuals with and without active tuberculosis (TB). To boost protein coverage, we utilized nonconventional proteases such as GluC and AspN together with the gold standard trypsin, identifying more than 30,000 peptides mapping to 3309 proteins. Application of this library to quantify plasma proteome differences in TB infection recovered more than 400 proteins in 50 min of MS acquisition, including diagnostic Mycobacterium tuberculosis (Mtb) proteins that have previously been detectable primarily by antibody-based assays and intracellular proteins not previously described to be in plasma.Entities:
Keywords: DIA-MS; clinical proteomics; label-free quantification; proteases
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Year: 2021 PMID: 34319755 PMCID: PMC8442619 DOI: 10.1021/acs.jproteome.1c00357
Source DB: PubMed Journal: J Proteome Res ISSN: 1535-3893 Impact factor: 5.370