Translational Genome Mining for Natural Products, Interfaculty Institute of Microbiology and Infection Medicine Tübingen (IMIT), Interfaculty Institute for Biomedical Informatics (IBMI), University of Tübingen, Auf der Morgenstelle 28, 72076, Tübingen, Germany.
University of Tübingen, Cluster of Excellence 'Controlling Microbes to Fight Infections', Auf der Morgenstelle 28, Tübingen 72076, Germany.
Nucleic Acids Res. 2023 Jul 5;51(W1):W191-W197. doi: 10.1093/nar/gkad386.
There is an urgent need to diversify the pipeline for discovering novel natural products due to the increase in multi-drug resistant infections. Like bacteria, fungi also produce secondary metabolites that have potent bioactivity and rich chemical diversity. To avoid self-toxicity, fungi encode resistance genes which are often present within the biosynthetic gene clusters (BGCs) of the corresponding bioactive compounds. Recent advances in genome mining tools have enabled the detection and prediction of BGCs responsible for the biosynthesis of secondary metabolites. The main challenge now is to prioritize the most promising BGCs that produce bioactive compounds with novel modes of action. With target-directed genome mining methods, it is possible to predict the mode of action of a compound encoded in an uncharacterized BGC based on the presence of resistant target genes. Here, we introduce the 'fungal bioactive compound resistant target seeker' (FunARTS) available at https://funarts.ziemertlab.com. This is a specific and efficient mining tool for the identification of fungal bioactive compounds with interesting and novel targets. FunARTS rapidly links housekeeping and known resistance genes to BGC proximity and duplication events, allowing for automated, target-directed mining of fungal genomes. Additionally, FunARTS generates gene cluster networking by comparing the similarity of BGCs from multi-genomes.
由于多药耐药性感染的增加，迫切需要多样化新型天然产物的发现途径。与细菌一样，真菌也会产生具有强大生物活性和丰富化学多样性的次生代谢产物。为了避免自身毒性，真菌会编码抗性基因，这些基因通常存在于相应生物活性化合物的生物合成基因簇（BGCs）中。基因组挖掘工具的最新进展使得检测和预测负责次生代谢产物生物合成的 BGCs 成为可能。目前的主要挑战是确定最有前途的 BGCs，这些 BGCs 产生具有新型作用模式的生物活性化合物。通过靶向基因组挖掘方法，可以根据未表征 BGC 中编码化合物的抗性靶基因的存在来预测该化合物的作用模式。在这里，我们介绍了可在 https://funarts.ziemertlab.com 上获取的“真菌生物活性化合物抗性靶标搜索器”（FunARTS）。这是一种用于鉴定具有有趣和新颖靶标的真菌生物活性化合物的特定且高效的挖掘工具。FunARTS 可快速将管家基因和已知的抗性基因与 BGC 接近度和重复事件联系起来，从而实现针对真菌基因组的自动化靶向挖掘。此外，FunARTS 通过比较多基因组中 BGC 的相似性来生成基因簇网络。
