Metaproteomic analysis using the Galaxy framework

Pratik D. Jagtap, Alan Blakely, Kevin Murray, Shaun Stewart, Joel Kooren, James E. Johnson, Nelson L. Rhodus, Joel Rudney, Timothy J. Griffin

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Metaproteomics characterizes proteins expressed by microorganism communities (microbiome) present in environmental samples or a host organism (e.g. human), revealing insights into the molecular functions conferred by these communities. Compared to conventional proteomics, metaproteomics presents unique data analysis challenges, including the use of large protein databases derived from hundreds or thousands of organisms, as well as numerous processing steps to ensure high data quality. These challenges limit the use of metaproteomics for many researchers. In response, we have developed an accessible and flexible metaproteomics workflow within the Galaxy bioinformatics framework. Via analysis of human oral tissue exudate samples, we have established a modular Galaxy-based workflow that automates a reduction method for searching large sequence databases, enabling comprehensive identification of host proteins (human) as well as "meta-proteins" from the nonhost organisms. Downstream, automated processing steps enable basic local alignment search tool analysis and evaluation/visualization of peptide sequence match quality, maximizing confidence in results. Outputted results are compatible with tools for taxonomic and functional characterization (e.g. Unipept, MEGAN5). Galaxy also allows for the sharing of complete workflows with others, promoting reproducibility and also providing a template for further modification and enhancement. Our results provide a blueprint for establishing Galaxy as a solution for metaproteomic data analysis. All MS data have been deposited in the ProteomeXchange with identifier PXD001655 (http://proteomecentral.proteomexchange.org/dataset/PXD001655).

Original languageEnglish (US)
Pages (from-to)3553-3565
Number of pages13
JournalProteomics
Volume15
Issue number20
DOIs
StatePublished - Oct 2015

Keywords

  • Bioinformatics
  • Customized database generation
  • Mass spectrometry
  • Metaproteomics
  • Peptide sequence match
  • Sequence database search

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