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Cell. 2014 Jul 17;158(2):412-421. doi: 10.1016/j.cell.2014.06.034.

Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters.

Author information

1
Department of Bioengineering and Therapeutic Sciences and the California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA.
2
Department of Microbial Physiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, 9747AG Groningen, The Netherlands; Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, 9747AG Groningen, The Netherlands.
3
Department of Chemistry and Biochemistry, University of California, Santa Cruz, Santa Cruz, CA 95064, USA.
4
Department of Chemistry, Indiana University, Bloomington, IN 47405, USA.
5
US Department of Energy, Joint Genome Institute, Walnut Creek, CA 94598, USA.
6
The Broad Institute, Cambridge, MA 02142, USA.
7
Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA.
8
Department of Microbial Physiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, 9747AG Groningen, The Netherlands.
9
Department of Bioengineering and Therapeutic Sciences and the California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158, USA.
10
Department of Bioengineering and Therapeutic Sciences and the California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA. Electronic address: fischbach@fischbachgroup.org.

Abstract

Although biosynthetic gene clusters (BGCs) have been discovered for hundreds of bacterial metabolites, our knowledge of their diversity remains limited. Here, we used a novel algorithm to systematically identify BGCs in the extensive extant microbial sequencing data. Network analysis of the predicted BGCs revealed large gene cluster families, the vast majority uncharacterized. We experimentally characterized the most prominent family, consisting of two subfamilies of hundreds of BGCs distributed throughout the Proteobacteria; their products are aryl polyenes, lipids with an aryl head group conjugated to a polyene tail. We identified a distant relationship to a third subfamily of aryl polyene BGCs, and together the three subfamilies represent the largest known family of biosynthetic gene clusters, with more than 1,000 members. Although these clusters are widely divergent in sequence, their small molecule products are remarkably conserved, indicating for the first time the important roles these compounds play in Gram-negative cell biology.

PMID:
25036635
PMCID:
PMC4123684
DOI:
10.1016/j.cell.2014.06.034
[Indexed for MEDLINE]
Free PMC Article

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