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A computational screen for type I polyketide synthases in metagenomics shotgun data
Konrad U Foerstner1, Tobias Doerks, Christopher J Creevey
1European Molecular Biology Laboratory, Heidelberg, Germany.
Plos One
|October 28, 2008
Summary
Researchers identified novel polyketide synthase I (PKS I) proteins in natural environments using computational methods. This approach enhances the discovery of these important biotechnological compounds.
Area of Science:
- Biotechnology
- Genomics
- Enzymology
Background:
- Polyketides are vital secondary metabolites with significant biotechnological applications.
- Polyketide synthases (PKS) are large, multi-domain enzymes responsible for polyketide biosynthesis.
- Type I PKS (PKS I) represents a key subgroup within the PKS enzyme family.
Purpose of the Study:
- To estimate the frequency of PKS I in natural environments.
- To develop and apply a robust computational method for identifying PKS I sequences.
- To improve the annotation of proteins with unknown functions and detect horizontal gene transfer.
Main Methods:
- Utilized Hidden-Markov-Models (HMMs) to screen predicted proteins from metagenomic shotgun data.
- Employed maximum-likelihood trees to enhance the reliability and resolution of PKS I domain identification.
- Combined HMM and phylogenetic analyses to accurately discriminate true PKS I domains from related enzymes.
Main Results:
- Identified numerous novel PKS I proteins across diverse natural environments.
- Discovered the highest density of PKS I proteins in Minnesota farm soil (136 proteins per 183,536 genes).
- Applied the protocol to the UniRef database, identifying new instances of horizontal gene transfer and aiding protein annotation.
Conclusions:
- The developed screening approach is highly effective for identifying PKS I sequences in large datasets.
- This methodology is adaptable for the identification of other protein families.
- The findings expand our understanding of PKS I diversity and distribution in nature.
