Diversity Analysis and Genome Mining of Microbial 16S rRNA Gene and Metagenomic Data for the Discovery of Novel Antibiotics

There is an urgent need for new antimicrobials due to constantly advancing antimicrobial resistance. Here, we worked with environmental samples from diverse habitats including different savannah and forest soils, volcanic caves, and termite mounds and assessed their microbial communities for the potential of biosynthesis of secondary metabolites. We analysed and compared microbial composition by applying the QIIME2 pipeline to 16S rRNA gene data. We focused on the abundance of Actinobacteria and Streptomyces as they are important producers of antimicrobials. Out of the samples analysed, the highest abundance of Actinobacteria was found in termite mound and volcanic cave samples. Moreover, the termite mound samples also had the highest abundance of Streptomyces. When comparing microbial composition, soil samples and termite mound samples each formed their own clusters, but volcanic cave samples appeared more dispersed. We assessed the antimicrobial potential of a subset of samples by analysing metagenomic data to predict biosynthetic gene clusters (BGCs) using antiSMASH5.2.0, which resulted in over 800 hits per sample. This number was narrowed down by evaluating identified BGCs based on antimicrobial potential, completeness, size, presence/absence of regulatory and transport-related genes, and dissimilarity with known BGCs. This resulted in an average of 20 BGCs per sample. These BGCs will be subjected to further sequence-based analyses before attempting heterologous expression. Following successful expression, antimicrobial potential will be assessed by screening for growth inhibition of multidrug resistant E.coli strains and the ESKAPE pathogens.