Abstract

The present study aimed to investigate the intraspecific variation of biosynthetic gene clusters (BGCs) in different strains of Burkholderia thailandensis in order to guide natural products (NPs) discovery process. Species from the genus Burkholderia are emerging as promising species due to their biosynthetic potential. Through genome-mining strategies, it was able to identify that B. thailandensis strains present major genome variation between chromosomes I and II and the standard. The positioning of BGCs also differs when comparing each chromosome. Classical pathways as well as terpene and bacteriocins were commonly identified to all of them and BGCs related to the production of nonribosomal peptides and polyketides compounds are often noticed. In addition, hybrids BGCs were identified as using large amount of replicon information. Among all species studied, the strain MSMB121 showed greater potential for biosynthesizing novel natural products and after phylogenetic analysis, the likelihood of recognizing sites of novelties was assigned.

Highlights

  • Species of the genus Burkholderia have emerged as owing promising biosynthetic capability for diverse natural products (NPs)

  • Core structures identified from Chr[1] and Chr[2] of B. thailandensis seems to not be originated from high levels of nucleotide homology to cluster themselves with similar scores, implying that they are independent in how they work in order to biosynthesize NPs

  • Results of hierarchical analyses using Euclidean distance further investigating NRPs- and PKs-related structures showed that the largest group expressing higher levels of similarity to the production of NPs is composed by the strains E444, E264, and H0587

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Summary

Introduction

Species of the genus Burkholderia have emerged as owing promising biosynthetic capability for diverse natural products (NPs). BGCs predictions were made using antiSMASH 3.0.22 Investigations were made in order to search for, among other results, an overview in genomic information allowing detecting classes of compounds, level of genomic similarities to already known compounds, and their core structures, including the comparative gene cluster analysis.

Results
Conclusion
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