Dataset Information

BioCAT: Search for biosynthetic gene clusters producing nonribosomal peptides with known structure.

ABSTRACT: Nonribosomal peptides are a class of secondary metabolites synthesized by multimodular enzymes named nonribosomal peptide synthetases and mainly produced by bacteria and fungi. NMR, LC-MS/MS and other analytical methods allow to determine a peptide structure precisely, but it is often not a trivial task to find natural producers of them. There are cases when potential producers should be found among hundreds of strains, for instance, when analyzing metagenomic data. We have developed BioCAT, a tool designed for finding biosynthetic gene clusters which may produce a given nonribosomal peptide when the structure of an interesting nonribosomal peptide has already been found. BioCAT unites the antiSMASH software and the rBAN retrosynthesis tool but some improvements were added to both gene cluster and peptide structure analysis. The main feature of the method is an implementation of a position-specific score matrix to store specificities of nonribosomal peptide synthetase modules, which has increased the alignment sensitivity in comparison with more strict approaches developed earlier. We tested the method on a manually curated nonribosomal peptide producers database and compared it with competing tools GARLIC and Nerpa. Finally, we showed the method's applicability on several external examples.

SUBMITTER: Konanov DN

PROVIDER: S-EPMC8914306 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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BioCAT: Search for biosynthetic gene clusters producing nonribosomal peptides with known structure.

Konanov Dmitry N DN Krivonos Danil V DV Ilina Elena N EN Babenko Vladislav V VV

Computational and structural biotechnology journal 20220304

Nonribosomal peptides are a class of secondary metabolites synthesized by multimodular enzymes named nonribosomal peptide synthetases and mainly produced by bacteria and fungi. NMR, LC-MS/MS and other analytical methods allow to determine a peptide structure precisely, but it is often not a trivial task to find natural producers of them. There are cases when potential producers should be found among hundreds of strains, for instance, when analyzing metagenomic data. We have developed BioCAT, a t ...[more]

PMID: 35317229

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Project description:Gene clusters are groups of genes that are co-locally conserved across various genomes, not necessarily in the same order. Their discovery and analysis is valuable in tasks such as gene annotation and prediction of gene interactions, and in the study of genome organization and evolution. The discovery of conserved gene clusters in a given set of genomes is a well studied problem, but with the rapid sequencing of prokaryotic genomes a new problem is inspired. Namely, given an already known gene cluster that was discovered and studied in one genomic dataset, to identify all the instances of the gene cluster in a given new genomic sequence. Thus, we define a new problem in comparative genomics, denoted PQ-TREE SEARCH that takes as input a PQ-tree T representing the known gene orders of a gene cluster of interest, a gene-to-gene substitution scoring function h, integer arguments [Formula: see text] and [Formula: see text], and a new sequence of genes S. The objective is to identify in S approximate new instances of the gene cluster; These instances could vary from the known gene orders by genome rearrangements that are constrained by T, by gene substitutions that are governed by h, and by gene deletions and insertions that are bounded from above by [Formula: see text] and [Formula: see text], respectively. We prove that PQ-TREE SEARCH is NP-hard and propose a parameterized algorithm that solves the optimization variant of PQ-TREE SEARCH in [Formula: see text] time, where [Formula: see text] is the maximum degree of a node in T and [Formula: see text] is used to hide factors polynomial in the input size. The algorithm is implemented as a search tool, denoted PQFinder, and applied to search for instances of chromosomal gene clusters in plasmids, within a dataset of 1,487 prokaryotic genomes. We report on 29 chromosomal gene clusters that are rearranged in plasmids, where the rearrangements are guided by the corresponding PQ-trees. One of these results, coding for a heavy metal efflux pump, is further analysed to exemplify how PQFinder can be harnessed to reveal interesting new structural variants of known gene clusters.

Project description:Polyketides (PKs) and nonribosomal peptides (NRPs) are two microbial secondary metabolite (SM) families known for their variety of functions, including antimicrobials, siderophores, and others. Despite their involvement in bacterium-bacterium and bacterium-plant interactions, root-associated SMs are largely unexplored due to the limited cultivability of bacteria. Here, we analyzed the diversity and expression of SM-encoding biosynthetic gene clusters (BGCs) in root microbiomes by culture-independent amplicon sequencing, shotgun metagenomics, and metatranscriptomics. Roots (tomato and lettuce) harbored distinct compositions of nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs) relative to the adjacent bulk soil, and specific BGC markers were both enriched and highly expressed in the root microbiomes. While several of the highly abundant and expressed sequences were remotely associated with known BGCs, the low similarity to characterized genes suggests their potential novelty. Low-similarity genes were screened against a large set of soil-derived cosmid libraries, from which five whole BGCs of unknown function were retrieved. Three clusters were taxonomically affiliated with Actinobacteria, while the remaining were not associated with known bacteria. One Streptomyces-derived BGC was predicted to encode a polyene with potential antifungal activity, while the others were too novel to predict chemical structure. Screening against a suite of metagenomic data sets revealed higher abundances of retrieved clusters in roots and soil samples. In contrast, they were almost completely absent in aquatic and gut environments, supporting the notion that they might play an important role in root ecosystems. Overall, our results indicate that root microbiomes harbor a specific assemblage of undiscovered SMs.IMPORTANCE We identified distinct secondary-metabolite-encoding genes that are enriched (relative to adjacent bulk soil) and expressed in root ecosystems yet almost completely absent in human gut and aquatic environments. Several of the genes were distantly related to genes encoding antimicrobials and siderophores, and their high sequence variability relative to known sequences suggests that they may encode novel metabolites and may have unique ecological functions. This study demonstrates that plant roots harbor a diverse array of unique secondary-metabolite-encoding genes that are highly enriched and expressed in the root ecosystem. The secondary metabolites encoded by these genes might assist the bacteria that produce them in colonization and persistence in the root environment. To explore this hypothesis, future investigations should assess their potential role in interbacterial and bacterium-plant interactions.

Dataset Information

BioCAT: Search for biosynthetic gene clusters producing nonribosomal peptides with known structure.

Publications

BioCAT: Search for biosynthetic gene clusters producing nonribosomal peptides with known structure.

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