Self-resistance-gene-guided, high-throughput automated genome mining of bioactive natural products from Streptomyces.

利用自身抗性基因引导的高通量自动化基因组挖掘技术,从链霉菌中筛选生物活性天然产物

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作者:Yuan Yujie, Huang Chunshuai, Singh Nilmani, Xun Guanhua, Zhao Huimin
Natural products (NPs) from bacteria, fungi, and plants are a vital source of drug leads, with Streptomyces species being particularly significant due to their capability of producing diverse bioactive compounds. Here, we present a fully automated, scalable, high-throughput platform for discovering bioactive NPs in Streptomyces (FAST-NPS). This platform integrates computational biosynthetic gene cluster (BGC) prediction and prioritization guided by self-resistance genes, automated cloning and heterologous expression, high-throughput fermentation, and product extraction. As a proof of concept, we cloned 105 BGCs (10-100 kb) from 11 Streptomyces strains with a 95% success rate. Heterologous expression in Streptomyces lividans TK24 led to the detection of 23 NPs, including 8 with antibacterial or antitumor bioactivities from 5 BGCs. This work highlights the potential of FAST-NPS to accelerate bioactive NP discovery for biomedical and biotechnological applications. A record of this paper's transparent peer review process is included in the supplemental information.

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