Abstract
The scarcely investigated myxobacterium Corallococcus coralloides holds a large genome containing many uncharacterized biosynthetic gene clusters (BGCs) that potentially encode the synthesis of entirely new natural products. Despite its promising genomic potential, suitable cultivation conditions have not yet been found to activate the synthesis of new secondary metabolites (SMs). Finding the right cultivation conditions to activate BGCs in the genome remains a major bottleneck, and its full biosynthetic potential has so far not been determined. We therefore applied a bivariate "one strain many compounds" (OSMAC) approach, using a combination of two elicitor changes at once, for the activation of BGCs and concomitant SM production by C. coralloides. The screening was carried out in Duetz-System 24-well plates, applying univariate and bivariate OSMAC conditions. We combined biotic additives and organic solvents with a complex growth medium for univariate conditions and with minimal medium for bivariate conditions. The success in the activation of BGCs was evaluated by determining the number of new mass features detected in the respective extracts. We found synergistic effects in the bivariate OSMAC designs, evidenced by the detection of completely new mass features in the bivariate OSMAC experiments, which were not detected in the univariate OSMAC designs with only one elicitor. Overall, the bivariate OSMAC screening led to 55 new mass features, which were not detected in the univariate OSMAC design. Molecular networks revealed that these new mass features embody potential novel natural compounds and chemical derivatives like the N-acyl fatty amine N-pentyloctadecanamide and possibly sulfur-containing natural products. Hence, the presence of multiple elicitors in the bivariate OSMAC designs successfully activated the biosynthetic potential in C. coralloides. We propose bivariate OSMAC designs with a complex combination of elicitors as a straightforward strategy to robustly expand the SM space of microorganisms with large genomes.