Advances in tools, strategies, and applications of mining of microbial genomes for novel antimicrobials: a comprehensive review.

Amidst the escalating crisis of antimicrobial resistance globally, genome mining has emerged as a promising field for the discovery of newer antibiotics from microbial sources. Secondary metabolites like non-ribosomal peptides, polyketides, and ribosomally synthesized post-translationally modified peptides are synthesized by biosynthetic gene clusters and exhibit diverse pharmacological activities. Advanced sequencing technologies and informatics studies have made high-precision identification and prediction of cluster function possible. Computational tools like antiSMASH, BAGEL, PRISM, and RiPPMiner are the core of BGC classification and characterization of derived metabolites from microbial genomes. Heterologous expression, microbial co-culture, elicitor induction, and genetic regulation have been used in various strategies to induce cryptic or silent gene clusters, leading to improved production of novel compounds. The combination of bioinformatics and synthetic biology has yielded higher precision in prediction and understanding of biosynthesis. Therefore, genome mining is an economical and productive approach for the discovery of next-generation antimicrobials, offering a potential solution to the global healthcare catastrophe caused by multidrug-resistant pathogens.