Metaproteomic data analysis at a glance: advances in computational microbial community proteomics. (2nd August 2016)

• Record Type: Journal Article
• Authors: Muth, Thilo; Renard, Bernhard Y.; Martens, Lennart
• Is Part Of: Expert review of proteomics. Volume 13:Number 8(2016)
• Page Start: 757
• Page End: 769
• Publication Date: 2016-08-02
• Subjects: Metaproteomics -- MS/MS -- bioinformatics -- microbial community samples -- computational proteomics -- data analysis -- protein identification; Proteins -- Biotechnology -- Periodicals; Proteomics -- Periodicals; 572.6
• DOI: 10.1080/14789450.2016.1209418
• Languages: English
• ISSNs: 1478-9450

Abstract

ABSTRACT: Introduction : Within the last decade, the study of microbial communities has gained increasing research interest also driven by the recognition of the important role of these consortia in human health and disease. Metaproteomics, the analysis of the entire set of proteins from all microorganisms present in one ecosystem, has become a prominent technique for studying the relation between taxonomic diversity and functional profile of microbial communities. Areas covered : The aim of this review is to address opportunities and challenges of metaproteomics from a computational perspective. Appealing to an audience of microbial ecologists and proteomic researchers alike, we provide an overview on state-of-the-art software and databases by which metaproteome data can be readily analyzed. Expert commentary : While tailored protein databases, combined search algorithms and iterative workflows are means to improve the identification yield, software tools for taxonomic and functional analysis are challenged by the vast amount of unannotated sequences in metaproteomics.