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Curr Opin Biotechnol. 2014 Aug;28:103-10. doi: 10.1016/j.copbio.2014.01.007. Epub 2014 Feb 4.

Extracting data from the muck: deriving biological insight from complex microbial communities and non-model organisms with next generation sequencing.

Author information

1
Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA.
2
Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142, USA.
3
Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA. Electronic address: momalley@engineering.ucsb.edu.

Abstract

It is becoming increasingly clear that microbes within microbial communities, for which cultured isolates have not yet been obtained, have an immense, untapped reservoir of enzymes that could help address grand challenges in human health, energy, and sustainability. Despite the obstacles associated with culturing these microbes, recent advances in next-generation sequencing (NGS) have made it possible to explore complex microbial communities in their native context for the first time. Key to extracting meaning from rapidly growing NGS datasets are bioinformatics tools that assemble the sequence data, annotate homologous sequences and interrogate it to reveal regulatory patterns. Complementing this are advances in proteomics that can link NGS data to biological function. This combination of next generation sequencing, proteomics and bioinformatic analysis forms a powerful tool to study non-model microbes, which will transform what we know about these dynamic systems.

PMID:
24503479
DOI:
10.1016/j.copbio.2014.01.007
[Indexed for MEDLINE]

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