A computational screen for type I polyketide synthases in metagenomics shotgun data

Konrad U. Foerstner*, Tobias Doerks, Christopher J. Creevey, Anja Doerks, Peer Bork

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Background: Polyketides are a diverse group of biotechnologically important secondary metabolites that are produced by multi domain enzymes called polyketide synthases (PKS). Methodology/Principal Findings: We have estimated frequencies of type I PKS (PKS I) - a PKS subgroup - in natural environments by using Hidden-Markov-Models of eight domains to screen predicted proteins from six metagenomic shotgun data sets. As the complex PKS I have similarities to other multi-domain enzymes (like those for the fatty acid biosynthesis) we increased the reliability and resolution of the dataset by maximum-likelihood trees. The combined information of these trees was then used to discriminate true PKS I domains from evolutionary related but functionally different ones. We were able to identify numerous novel PKS I proteins, the highest density of which was found in Minnesota farm soil with 136 proteins out of 183,536 predicted genes. We also applied the protocol to UniRef database to improve the annotation of proteins with so far unknown function and identified some new instances of horizontal gene transfer. Conclusions/Significance: The screening approach proved powerful in identifying PKS I sequences in large sequence data sets and is applicable to many other protein families.

Original languageEnglish
Article numbere3515
JournalPLoS ONE
Volume3
Issue number10
DOIs
Publication statusPublished - 27 Oct 2008
Externally publishedYes

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

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