Potential natural product discovery from microbes through a diversity-guided computational framework

As the occurrence of natural compounds is related to the spatial distribution and evolution of microorganisms for biological and ecological relevance, the data integration of chemistry, geography, and phylogeny within an analytical framework is needed to make better decisions on sourcing the microbes for drug discovery. Such a framework should help researcher to decide on (a) which microorganisms are capable to produce the structurally diverse-bioactive compounds and (b) where those microbes could be found. Here, we present GIST (Geospatial Integrated Species, sites and bioactive compound relationships Tracking tool), a computational framework that could describe and compare how the chemical and genetic diversity varied among microbes in different areas. GIST mainly exploits the measures of bioactive diversity (BD) and phylogenetic diversity (PD), derived from the branch length of bioactive dendrogram and phylogenetic tree, respectively. Based on BD and PD, our framework could provide guidance and tools for measuring, monitoring, and evaluating of patterns and changes in biodiversity of microorganisms to improve the success rate of drug discovery.