Genomic and metabolomic exploration of antimicrobials of beehive-associated actinobacteria

Abstract

Actinobacteria, particularly the Streptomyces genus, are well-known for producing an extensive array of bioactive compounds, with over 10,000 identified, many of which harbor therapeutic potential. Numerous animal species benefit from Streptomyces’s natural predisposition to produce antibiotics as growing number of studies showed that insects, such as ants, termites, beewolf, and bees, host antimicrobial-producing bacteria to preserve their environment from their natural pathogens. This study focuses on characterizing a collection of beehive-associated actinobacteria, resulting in approximately 200 isolates across 55 phylotypes, sampled from five elements of an Apis mellifera beehive: pollen, propolis, wax, honey and a bee. By combining bioactivity assays, genome mining, and metabolomic approaches, this research aims to unveil the cocktail of antibiotics produced by this actinobacteria collection and explore its role in maintaining a pathogen-free environment, particularly against beehive pathogens Paenibacillus larvae and Ascosphaera apis, as well as human pathogens (ESKAPE pathogens, Bacillus subtilis, and Kocuria rhizophila). Additionally, this study seeks to discover novel antimicrobial compounds by expressing cryptic biosynthetic gene clusters (BGCs). Remarkably, all Streptomyces strains in the collection displayed strong inhibitory activity against all tested pathogens. In total, 54 of the 55 phylotypes displayed antimicrobial activities against at least one pathogen. Genome mining revealed 40 BGCs involved in the production of known antimicrobial molecules, with 50 out of 55 phylotypes possessing BGCs linked to known antimicrobials. Antimicrobial compound extraction was successfully achieved for 14 phylotypes, and initial MS analyses identified valinomycin and surugamides antimicrobials produced by strains DT165 and DT197, respectively, as predicted by genome mining. Interestingly, none of the ions identified in the active extract of strain DT73 corresponded to known antimicrobials, and the predicted antimicrobials from strain DT73’s genome mining were not identified in the bioactive extract, suggesting that strain DT73 would produce at least one novel antimicrobial compound. In conclusion, the combination of bioactivity assays, genome mining, and mass spectrometry analyses supports the hypothesis that the strains isolated from the beehive have been selected to protect this environment from pathogens.