High-Throughput DNA Assembly Pipeline for Natural Product Discovery in Streptomycetes

Disease suppressive soil has the ability to inhibit disease development even in the presence of pathogens and susceptible plant hosts. Studies suggest that the interaction of soil microbiota, especially their secondary metabolites production, is one of the primary factors of disease suppressiveness. Research approaches combining culture-based assessments and DNA-based techniques have expanded physiological and molecular knowledge about the operative mechanisms of soil microbial communities. However, these procedures could produce biased representation of the microbial community due to extraction difficulties, differential culturing requirements and relative differences of amplification of target sequences among different organisms. Here, we report a high-throughput genomic approach to identify putative biosynthetic gene clusters and their corresponding secondary metabolites from microbes isolated from suppressive soil.As a proof-of-concept, three new soil Streptomycetes strains from disease suppressive soil were isolated and sequenced. The de novo assembly by PacBio® SMRT sequencing pipeline produced three high-quality draft genomes and were able to capture large read, extreme GC content and highly repetitive regions which the second-generation sequencing was incapable of. Using draft genome as an input, bioinformatics analysis by antiSMASH for prediction of novel natural products identifies corresponding putative gene clusters to be cloned and characterized. To simplify the design of targeted multigene constructs for high-throughput cloning, we developed a DNA fabrication pipeline which includes primer design automation algorithm and a standardized, modular vector system based on Type IIS restriction enzymes. In light of the sequence data and an alternative modular assembly method, we hope to use this genome-guided method to elucidate the biochemical properties of novel secondary metabolites found in the microbiota of disease suppressive soil. In addition, we provide a tool to rapidly convert sequence data to diverse secondary metabolite information.