Microbial Bioactives
Microbial Bioactives | Online ISSN 2209-2161
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Volume 8 Number 1 2025
REVIEWS (Open Access)
Deep Mining the Microbial Biosphere: Genomics-Driven Discovery of Natural Products in the Era of Antimicrobial Resistance
Dhiraj Kumar Chaudhary 1*, Ram Hari Dahal 2, Ramesh Prasad Pandey 3
Microbial Bioactives 8 (1) 1-8 https://doi.org/10.25163/microbbioacts.8110649
Submitted: 20 November 2024 Revised: 13 January 2025 Accepted: 22 January 2025 Published: 24 January 2025
Abstract
The accelerating crisis of antimicrobial resistance (AMR) has exposed the limitations of conventional natural product discovery pipelines and renewed interest in microbial secondary metabolites as a foundation for future therapeutics. Historically, bioactivity-guided screening of cultivable microorganisms yielded many of today’s frontline antibiotics; however, this approach now suffers from diminishing returns due to frequent rediscovery of known compounds and a narrow exploration of microbial diversity. Advances in genome sequencing and systems-level analytics have fundamentally reshaped this landscape. This systematic review and meta-analytical synthesis examines how genomics-driven “deep mining” of the microbial biosphere has transformed natural product discovery, shifting the field from serendipity toward predictive, data-informed strategies. Evidence across diverse studies demonstrates that microbial genomes harbor a vast reservoir of cryptic biosynthetic gene clusters (BGCs), most of which remain silent under standard laboratory conditions. Genome mining, resistance-guided prioritization, metagenomics, and integrative metabolomics have collectively expanded access to this hidden biosynthetic potential. The review further highlights how marine and rare biosphere microbes contribute disproportionately to chemical novelty, reinforcing the value of underexplored environments. Recent incorporation of artificial intelligence and machine learning has improved BGC detection, dereplication, and gene–metabolite linking, increasing discovery efficiency and reducing redundancy. Meta-analytical trends indicate that integrative, genomics-centered workflows consistently outperform traditional screening in novelty yield and mechanistic insight. Despite remaining challenges in pathway activation, compound expression, and scalable production, deep mining strategies represent a robust and necessary response to the AMR crisis. Harnessing microbial genomic diversity is therefore not only a scientific opportunity but a strategic imperative for sustaining the antibiotic pipeline.
Keywords: Antimicrobial resistance; microbial natural products; genome mining; biosynthetic gene clusters; metagenomics; deep mining; artificial intelligence
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