Genome mining of Neowestiellopsis persica NC-DW uncovers cryptic antimicrobial gene clusters with potential against drug-resistant pathogens.

The emerging crisis of antibiotic resistance is becoming a worldwide health emergency that is worsened by the decrease in drug development. To address this, innovative approach like genome mining offers a promising strategy by combining next-generation sequencing with bioinformatics to rapidly identify biosynthetic gene clusters for novel drug candidates. In this study, the cyanobacterium Neowestiellopsis persica NC-DW was isolated from the West Khasi Hills district of Meghalaya, and phytochemical analysis revealed the presence of diverse bioactive compounds, while antioxidant assays confirmed its radical-scavenging properties. Antimicrobial assays of the methanolic extract demonstrated inhibitory activity against Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumoniae. To further investigate its antagonistic potential, degenerate primers (MTF/MTR and DKF/DKR) were used to screen for non-ribosomal peptide synthase and polyketide synthase gene clusters. Using blue-white screening, the ketosynthase domain of a PKS gene cluster was retrieved, and subsequent NaPDoS analysis identified four biosynthetic gene clusters. Whole-genome sequencing confirmed 31 cryptic secondary metabolite clusters, of which antiSMASH predicted five to encode antimicrobial compounds, including a bicornutin cluster with 100% homology. Real-time PCR was further utilized to investigate the expression patterns of these biosynthetic clusters under iron and phosphorus nutrient-limiting conditions. The findings indicate a significant upregulation in the expression of these biosynthetic gene clusters during the exponential phase when phosphorus was limited. This study underscores the immense potential of genome mining for uncovering novel, cryptic antimicrobial biosynthetic gene clusters, thereby fuelling new avenues for drug discovery.