The Integration of Genome Mining, Comparative Genomics, and Functional Genetics for Biosynthetic Gene Cluster Identification.

Antimicrobial resistance is a worldwide health crisis for which new antibiotics are needed. One strategy for antibiotic discovery is identifying unique antibiotic biosynthetic gene clusters that may produce novel compounds. The aim of this study was to demonstrate how an integrated approach that combines genome mining, comparative genomics, and functional genetics can be used to successfully identify novel biosynthetic gene clusters that produce antimicrobial natural products.

A broad-spectrum antibacterial natural product from the cystic fibrosis isolate, Pantoea agglomerans Tx10.

The prevalence of antibiotic-resistant Gram-positive and Gram-negative pathogens has prompted considerable efforts to identify new antibacterials. Here we show that Pantoea agglomerans Tx10-an isolate from the sputum sample of a cystic fibrosis patient-is a strong competitor that inhibits the growth of a wide range of Gram-positive and Gram-negative bacteria through the production of a secreted compound. A genetic screen to identify the genes involved in the production of this compound resulted in the delineation of a 6-gene biosynthetic cluster.