An alignment-free "metapeptide" strategy for metaproteomic characterization of microbiome samples using shotgun metagenomic sequencing

Damon H. May, Emma Timmins-Schiffman, Molly P. Mikan, H. Rodger Harvey, Elhanan Borenstein, Brook L. Nunn, William S. Noble*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

In principle, tandem mass spectrometry can be used to detect and quantify the peptides present in a microbiome sample, enabling functional and taxonomic insight into microbiome metabolic activity. However, the phylogenetic diversity constituting a particular microbiome is often unknown, and many of the organisms present may not have assembled genomes. In ocean microbiome samples, with particularly diverse and uncultured bacterial communities, it is difficult to construct protein databases that contain the bulk of the peptides in the sample without losing detection sensitivity due to the overwhelming number of candidate peptides for each tandem mass spectrum. We describe a method for deriving "metapeptides" (short amino acid sequences that may be represented in multiple organisms) from shotgun metagenomic sequencing of microbiome samples. In two ocean microbiome samples, we constructed site-specific metapeptide databases to detect more than one and a half times as many peptides as by searching against predicted genes from an assembled metagenome and roughly three times as many peptides as by searching against the NCBI environmental proteome database. The increased peptide yield has the potential to enrich the taxonomic and functional characterization of sample metaproteomes.

Original languageEnglish
Pages (from-to)2697-2705
Number of pages9
JournalJournal of Proteome Research
Volume15
Issue number8
DOIs
StatePublished - 5 Aug 2016
Externally publishedYes

Funding

FundersFunder number
National Science Foundation1633939, 1233014, 1233589
National Institute of General Medical SciencesP41GM103533

    Keywords

    • mass spectrometry
    • metagenomics
    • metaproteomics
    • microbial communities
    • microbial ecology

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