Data-Independent Acquisition Mass Spectrometry in Metaproteomics of Gut Microbiota-Implementation and Computational Analysis

J Proteome Res. 2020 Jan 3;19(1):432-436. doi: 10.1021/acs.jproteome.9b00606. Epub 2019 Dec 4.


Metagenomic approaches focus on taxonomy or gene annotation but lack power in defining functionality of gut microbiota. Therefore, metaproteomics approaches have been introduced to overcome this limitation. However, the common metaproteomics approach uses data-dependent acquisition mass spectrometry, which is known to have limited reproducibility when analyzing samples with complex microbial composition. In this work, we provide a proof of concept for data-independent acquisition (DIA) metaproteomics. To this end, we analyze metaproteomes using DIA mass spectrometry and introduce an open-source data analysis software package, diatools, which enables accurate and consistent quantification of DIA metaproteomics data. We demonstrate the feasibility of our approach in gut microbiota metaproteomics using laboratory-assembled microbial mixtures as well as human fecal samples.

Keywords: bioinformatics; data analysis; data-independent acquisition; human gut microbiota; mass spectrometry; metaproteomics; microbiota functionality; proteomics; software.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods
  • Feces / microbiology
  • Gastrointestinal Microbiome / physiology*
  • Humans
  • Mass Spectrometry / methods*
  • Proteomics / methods*
  • Software