Dataset Information

Chromosomal organization of biosynthetic gene clusters, including those of nine novel species, suggests plasticity of myxobacterial specialized metabolism.

ABSTRACT:

Introduction

Natural products discovered from bacteria provide critically needed therapeutic leads for drug discovery, and myxobacteria are an established source for metabolites with unique chemical scaffolds and biological activities. Myxobacterial genomes accommodate an exceptional number and variety of biosynthetic gene clusters (BGCs) which encode for features involved in specialized metabolism.

Methods

In this study, we describe the collection, sequencing, and genome mining of 20 myxobacteria isolated from rhizospheric soil samples collected in North America.

Results

Nine isolates were determined to be novel species of myxobacteria including representatives from the genera Archangium, Myxococcus, Nannocystis, Polyangium, Pyxidicoccus, Sorangium, and Stigmatella. Growth profiles, biochemical assays, and descriptions were provided for all proposed novel species. We assess the BGC content of all isolates and observe differences between Myxococcia and Polyangiia clusters.

Discussion

Continued discovery and sequencing of novel myxobacteria from the environment provide BGCs for the genome mining pipeline. Utilizing complete or near-complete genome sequences, we compare the chromosomal organization of BGCs of related myxobacteria from various genera and suggest that the spatial proximity of hybrid, modular clusters contributes to the metabolic adaptability of myxobacteria.

SUBMITTER: Ahearne A

PROVIDER: S-EPMC10435759 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Chromosomal organization of biosynthetic gene clusters, including those of nine novel species, suggests plasticity of myxobacterial specialized metabolism.

Ahearne Andrew A Phillips Kayleigh E KE Knehans Thomas T Hoing Miranda M Dowd Scot E SE Stevens David Cole DC

Frontiers in microbiology 20230803

<h4>Introduction</h4>Natural products discovered from bacteria provide critically needed therapeutic leads for drug discovery, and myxobacteria are an established source for metabolites with unique chemical scaffolds and biological activities. Myxobacterial genomes accommodate an exceptional number and variety of biosynthetic gene clusters (BGCs) which encode for features involved in specialized metabolism.<h4>Methods</h4>In this study, we describe the collection, sequencing, and genome mining o ...[more]

PMID: 37601375

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Project description:While specialized metabolites are thought to mediate ecological interactions, the evolutionary processes driving chemical diversification, particularly among closely related lineages, remain poorly understood. Here, we examine the evolutionary dynamics governing the distribution of natural product biosynthetic gene clusters (BGCs) among 118 strains representing all nine currently named species of the marine actinobacterial genus Salinispora. While much attention has been given to the role of horizontal gene transfer (HGT) in structuring BGC distributions, we find that vertical descent facilitates interspecies BGC diversification over evolutionary timescales. Moreover, we identified a distinct phylogenetic signal among Salinispora species at both the BGC and metabolite level, indicating that specialized metabolism represents a conserved phylogenetic trait. Using a combination of genomic analyses and liquid chromatography-high-resolution tandem mass spectrometry (LC-MS/MS) targeting nine experimentally characterized BGCs and their small molecule products, we identified gene gain/loss events, constrained interspecies recombination, and other evolutionary processes associated with vertical inheritance as major contributors to BGC diversification. These evolutionary dynamics had direct consequences for the compounds produced, as exemplified by species-level differences in salinosporamide production. Together, our results support the concept that specialized metabolites, and their cognate BGCs, can represent phylogenetically conserved functional traits with chemical diversification proceeding in species-specific patterns over evolutionary time frames. IMPORTANCE Microbial natural products are traditionally exploited for their pharmaceutical potential, yet our understanding of the evolutionary processes driving BGC evolution and compound diversification remain poorly developed. While HGT is recognized as an integral driver of BGC distributions, we find that the effects of vertical inheritance on BGC diversification had direct implications for species-level specialized metabolite production. As such, understanding the degree of genetic variation that corresponds to species delineations can enhance natural product discovery efforts. Resolving the evolutionary relationships between closely related strains and specialized metabolism can also facilitate our understanding of the ecological roles of small molecules in structuring the environmental distribution of microbes.

Project description:IntroductionThe antibiotic crisis is a major human health problem. Bioprospecting screenings suggest that proteobacteria and other extremophile microorganisms have biosynthetic potential for the production novel antimicrobial compounds. An Antarctic Sphingomonas strain (So64.6b) previously showed interesting antibiotic activity and elicitation response, then a relationship between environmental adaptations and its biosynthetic potential was hypothesized. We aimed to determine the genomic characteristics in So64.6b strain related to evolutive traits for the adaptation to the Antarctic environment that could lead to its diversity of potentially novel antibiotic metabolites.MethodsThe complete genome sequence of the Antarctic strain was obtained and mined for Biosynthetic Gene Clusters (BGCs) and other unique genes related to adaptation to extreme environments. Comparative genome analysis based on multi-locus phylogenomics, BGC phylogeny, and pangenomics were conducted within the closest genus, aiming to determine the taxonomic affiliation and differential characteristics of the Antarctic strain.Results and discussionThe Antarctic strain So64.6b showed a closest identity with Sphingomonas alpina, however containing a significant genomic difference of ortholog cluster related to degradation multiple pollutants. Strain So64.6b had a total of six BGC, which were predicted with low to no similarity with other reported clusters; three were associated with potential novel antibiotic compounds using ARTS tool. Phylogenetic and synteny analysis of a common BGC showed great diversity between Sphingomonas genus but grouping in clades according to similar isolation environments, suggesting an evolution of BGCs that could be linked to the specific ecosystems. Comparative genomic analysis also showed that Sphingomonas species isolated from extreme environments had the greatest number of predicted BGCs and a higher percentage of genetic content devoted to BGCs than the isolates from mesophilic environments. In addition, some extreme-exclusive clusters were found related to oxidative and thermal stress adaptations, while pangenome analysis showed unique resistance genes on the Antarctic strain included in genetic islands. Altogether, our results showed the unique genetic content on Antarctic strain Sphingomonas sp. So64.6, -a probable new species of this genetically divergent genus-, which could have potentially novel antibiotic compounds acquired to cope with Antarctic poly-extreme conditions.

Project description:BackgroundBiosynthetic gene clusters produce a wide range of metabolites with activities that are of interest to the pharmaceutical industry. Specific interest is shown towards those metabolites that exhibit antimicrobial activities against multidrug-resistant bacteria that have become a global health threat. Genera of the phylum Firmicutes are frequently identified as sources of such metabolites, but the biosynthetic potential of its Virgibacillus genus is not known. Here, we used comparative genomic analysis to determine whether Virgibacillus strains isolated from the Red Sea mangrove mud in Rabigh Harbor Lagoon, Saudi Arabia, may be an attractive source of such novel antimicrobial agents.ResultsA comparative genomics analysis based on Virgibacillus dokdonensis Bac330, Virgibacillus sp. Bac332 and Virgibacillus halodenitrificans Bac324 (isolated from the Red Sea) and six other previously reported Virgibacillus strains was performed. Orthology analysis was used to determine the core genomes as well as the accessory genome of the nine Virgibacillus strains. The analysis shows that the Red Sea strain Virgibacillus sp. Bac332 has the highest number of unique genes and genomic islands compared to other genomes included in this study. Focusing on biosynthetic gene clusters, we show how marine isolates, including those from the Red Sea, are more enriched with nonribosomal peptides compared to the other Virgibacillus species. We also found that most nonribosomal peptide synthases identified in the Virgibacillus strains are part of genomic regions that are potentially horizontally transferred.ConclusionsThe Red Sea Virgibacillus strains have a large number of biosynthetic genes in clusters that are not assigned to known products, indicating significant potential for the discovery of novel bioactive compounds. Also, having more modular synthetase units suggests that these strains are good candidates for experimental characterization of previously identified bioactive compounds as well. Future efforts will be directed towards establishing the properties of the potentially novel compounds encoded by the Red Sea specific trans-AT PKS/NRPS cluster and the type III PKS/NRPS cluster.

Dataset Information

Chromosomal organization of biosynthetic gene clusters, including those of nine novel species, suggests plasticity of myxobacterial specialized metabolism.

Introduction

Methods

Results

Discussion

Publications

Chromosomal organization of biosynthetic gene clusters, including those of nine novel species, suggests plasticity of myxobacterial specialized metabolism.

Similar Datasets

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