Shotgun metagenomics, from sampling to analysis

Christopher Quince, Alan W. Walker, Jared T. Simpson, Nicholas J. Loman, Nicola Segata*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

445 Citations (Scopus)

Abstract

Diverse microbial communities of bacteria, archaea, viruses and single-celled eukaryotes have crucial roles in the environment and in human health. However, microbes are frequently difficult to culture in the laboratory, which can confound cataloging of members and understanding of how communities function. High-throughput sequencing technologies and a suite of computational pipelines have been combined into shotgun metagenomics methods that have transformed microbiology. Still, computational approaches to overcome the challenges that affect both assembly-based and mapping-based metagenomic profiling, particularly of high-complexity samples or environments containing organisms with limited similarity to sequenced genomes, are needed. Understanding the functions and characterizing specific strains of these communities offers biotechnological promise in therapeutic discovery and innovative ways to synthesize products using microbial factories and can pinpoint the contributions of microorganisms to planetary, animal and human health.

Original languageEnglish
Pages (from-to)833-844
Number of pages12
JournalNature Biotechnology
Volume35
Issue number9
DOIs
Publication statusPublished - 12 Sep 2017
Externally publishedYes

Bibliographical note

Funding Information:
A.W.W. and the Rowett Institute receive core funding support from the Scottish Government’s Rural and Environmental Science and Analysis Service (RESAS). N.S. is supported by the European Research Council (ERC-STG project MetaPG), a European Union Framework Program 7 Marie-Curie grant (PCIG13-618833), a MIUR grant (FIR RBFR13EWWI), a Fondazione Caritro grant (Rif.Int.2013.0239) and a Terme di Comano grant. C.Q. and N.J.L. are funded through a MRC bioinformatics fellowship (MR/M50161X/1) as part of the MRC Cloud Infrastructure for Microbial Bioinformatics (CLIMB) consortium (MR/L015080/1). J.T.S. is supported by the Ontario Institute for Cancer Research through funding provided by the Government of Ontario.

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