Mini review: Genome mining approaches for the identification of secondary metabolite biosynthetic gene clusters in Streptomyces

Streptomyces are a large and valuable resource of bioactive and complex secondary metabolites, many of which have important clinical applications. With the advances in high throughput genome sequencing methods, various in silico genome mining strategies have been developed and applied to the mapping of the Streptomyces genome. These studies have revealed that Streptomyces possess an even more significant number of uncharacterized silent secondary metabolite biosynthetic gene clusters (smBGCs) than previously estimated. Linking smBGCs to their encoded products has played a critical role in the discovery of novel secondary metabolites, as well as, knowledge-based engineering of smBGCs to produce altered products. In this mini review, we discuss recent progress in Streptomyces genome sequencing and the application of genome mining approaches to identify and characterize smBGCs. Furthermore, we discuss several challenges that need to be overcome to accelerate the genome mining process and ultimately support the discovery of novel bioactive compounds. (C) 2020 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.