Abstract
Diverse microbial communities of bacteria, archaea, viruses and single-celled eukaryotes have crucial roles in the environment and human health. However, microbes are frequently difficult to culture in the laboratory, which can confound cataloging members and understanding how communities function.
Cheap, high-throughput sequencing technologies and a suite of computational pipelines have been combined into shotgun metagenomics methodsthat have transformed microbiology. Still, computational approaches to overcome 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 offer biotechnological promise in therapeutic discovery, or innovative ways to synthesize products using microbial factories, but can also pinpoint the contributions of microorganisms to planetary, animal and human health.
Cheap, high-throughput sequencing technologies and a suite of computational pipelines have been combined into shotgun metagenomics methodsthat have transformed microbiology. Still, computational approaches to overcome 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 offer biotechnological promise in therapeutic discovery, or innovative ways to synthesize products using microbial factories, but can also pinpoint the contributions of microorganisms to planetary, animal and human health.
| Original language | English |
|---|---|
| Pages (from-to) | 833-844 |
| Number of pages | 12 |
| Journal | Nature Biotechnology |
| Volume | 35 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 12 Sept 2017 |
Bibliographical note
AWW and The Rowett Institute, University of Aberdeen, receive core funding support from the Scottish Government's Rural and Environmental Science and Analysis Service (RESAS). NS is supported by the European Research Council (ERC-STG project MetaPG), European Union FP7 Marie-Curie grant (PCIG13-618833), MIUR grant FIR RBFR13EWWI, Fondazione Caritro grant Rif.Int.2013.0239, and Terme di Comano grant. CQ and NL 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). JTS is supported by the Ontario Institute for Cancer Research through funding provided by the Government of Ontario
