New solutions for antibiotic discovery: Prioritizing microbial biosynthetic space using ecology and machine learning

Antibiotics have significantly extended human life spans, but antimicrobial resistance (AMR) is making them ineffective. The lack of new antibiotic classes and limited commercial incentives hinder antibiotic research and development. The “silent pandemic” is a potential crisis, with 10 million deaths annually by 2050. To discover new antibiotic classes, researchers need to explore new methods. Whole genome sequencing has revealed Actinobacteria’s genomes contain dozens of biosynthetic gene clusters (BGCs) that encode the synthesis of natural products. Bioinformatic tools like antiSMASH allow automated identification of BGCs and prediction of their molecules. However, only 3% of the natural product structural classes have been experimentally characterized. Prioritizing unknown BGCs and their cognate metabolites is a major question. Understanding the underlying mechanisms of BGC control may open up new biology and chemical diversity. DNA affinity purification sequencing (DAP-seq) can generate genome-wide DNA binding profiles, accelerating the predictive power of BGC control and enabling the characterization of their cognate metabolites. Cloning can also avoid regulatory constraints on BGCs.