Comparative genome analysis and secondary biosynthetic potential of the Streptomyces microflavus strains isolated...

The Streptomyces genus is known for producing distinct secondary metabolites with bioactive potential, and advances in sequencing technology have sparked genome-mining efforts to discover an extensive repertoire of biosynthetic pathways. This study delves into the comparative genome analysis and biosynthetic potential of four Streptomyces microflavus strains isolated from high-altitude soils. These bacterial strains (S. microflavus AM2, AM4, AM6, and AM7) were isolated from Amarnath, J&K, India, and showed antifungal activities against Candida spp., Saccharomyces cerevisiae, and Aspergillus fumigatus, but did not exhibit significant antibacterial activity. 16 S rRNA sequence, genome-based comparisons (including average nucleotide identity and DNA-DNA hybridization), and phylogenomic analysis confirmed that all strains belong to S. microflavus. Genome analysis revealed that these strains possess multiple DNA repair pathways, with slightly higher gene copy numbers, and also include genes such as dcm, mutT, and uvrD/pcrA, stress response genes, and a complete carotenoid biosynthesis pathway. Genome mining identified 140 biosynthetic gene clusters, including terpene, hybrid, NRPS, and PKS clusters. These strains also harbored 15-20 unknown gene clusters with less than 30% similarity to the identified clusters in the MIBiG database, suggesting novel BGCs, and some of these might produce unknown bioactive metabolites. The presence of strain-specific BGCs was highlighted through BGC analysis and sequence similarity network, suggesting the unique biosynthetic potential of individual strains. Putative antifungal clusters that could be responsible for antifungal activity in these strains were also identified. This work emphasizes the need to mine genomes of Streptomyces strains from high-altitude environments that exhibit bioactivity against fungal pathogens to identify BGCs encoding potent antimicrobial compounds. Comparative BGC analysis revealed diverse, strain-specific gene clusters with lower similarity to known clusters in the MIBiG database, suggesting they may be novel BGCs.