Literature DB >> 30268435

ProteoStorm: An Ultrafast Metaproteomics Database Search Framework.

Doruk Beyter1, Miin S Lin2, Yanbao Yu3, Rembert Pieper3, Vineet Bafna4.   

Abstract

Shotgun metaproteomics has the potential to reveal the functional landscape of microbial communities but lacks appropriate methods for complex samples with unknown compositions. In the absence of prior taxonomic information, tandem mass spectra would be searched against large pan-microbial databases, which requires heavy computational workload and reduces sensitivity. We present ProteoStorm, an efficient database search framework for large-scale metaproteomics studies, which identifies high-confidence peptide-spectrum matches (PSMs) while achieving a two-to-three orders-of-magnitude speedup over popular tools. A reanalysis of a urinary tract infection (UTI) dataset of 110 individuals revealed a complex pattern of polymicrobial expression, including sub-types of UTIs, cases of bacterial vaginosis, and evidence of no underlying disease. Importantly, compared to the initial UTI study that restricted the search database to a manually curated list of 20 genera, ProteoStorm identified additional genera that were previously unreported, including a case of infection with the rare pathogen Propionimicrobium.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  LC-MS/MS; metaproteomics; microbial communities; microbiology; proteome informatics; proteomics

Mesh:

Year:  2018        PMID: 30268435      PMCID: PMC6231400          DOI: 10.1016/j.cels.2018.08.009

Source DB:  PubMed          Journal:  Cell Syst        ISSN: 2405-4712            Impact factor:   10.304


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