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. 2012;7(3):e34064.
doi: 10.1371/journal.pone.0034064. Epub 2012 Mar 29.

The natural product domain seeker NaPDoS: a phylogeny based bioinformatic tool to classify secondary metabolite gene diversity

Affiliations

The natural product domain seeker NaPDoS: a phylogeny based bioinformatic tool to classify secondary metabolite gene diversity

Nadine Ziemert et al. PLoS One. 2012.

Abstract

New bioinformatic tools are needed to analyze the growing volume of DNA sequence data. This is especially true in the case of secondary metabolite biosynthesis, where the highly repetitive nature of the associated genes creates major challenges for accurate sequence assembly and analysis. Here we introduce the web tool Natural Product Domain Seeker (NaPDoS), which provides an automated method to assess the secondary metabolite biosynthetic gene diversity and novelty of strains or environments. NaPDoS analyses are based on the phylogenetic relationships of sequence tags derived from polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) genes, respectively. The sequence tags correspond to PKS-derived ketosynthase domains and NRPS-derived condensation domains and are compared to an internal database of experimentally characterized biosynthetic genes. NaPDoS provides a rapid mechanism to extract and classify ketosynthase and condensation domains from PCR products, genomes, and metagenomic datasets. Close database matches provide a mechanism to infer the generalized structures of secondary metabolites while new phylogenetic lineages provide targets for the discovery of new enzyme architectures or mechanisms of secondary metabolite assembly. Here we outline the main features of NaPDoS and test it on four draft genome sequences and two metagenomic datasets. The results provide a rapid method to assess secondary metabolite biosynthetic gene diversity and richness in organisms or environments and a mechanism to identify genes that may be associated with uncharacterized biochemistry.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. NaPDoS bioinformatic pipeline.
The web interface to this pipeline is divided 3 consecutive steps. Nucleic acid sequences are translated into predicted amino acids and genomic sequences are screened using Hidden Markov Models (HMM). For protein and small nucleic acid sequences a BLAST search is performed against curated reference database examples to identify matches to known PKS/NRPS pathways. Selected candidate sequences plus the BLAST results are trimmed and inserted into a manually curated reference alignment, keeping the original reference alignment intact. This alignment is used to build a tree.
Figure 2
Figure 2. Screen shot of the NaPDoS webpage.
Figure 3
Figure 3. Phylogeny based domain classification.
A) KS domain phylogeny. Polyphyletic groups are distinguished by letters. B) C domain phylogeny.

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