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FunARTS, the Fungal bioActive compound Resistant Target Seeker, an exploration engine for target-directed genome mining in fungi

  • Turgut Mesut Yllmaz
  • , Mehmet Direncoo Mungan
  • , Aileen Berasategui
  • , Nadine Ziemert

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

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.
Original languageEnglish
Pages (from-to)W191-W197
JournalNucleic acids research
Volume51
Issue number1 W
DOIs
Publication statusPublished - 5 Jul 2023
Externally publishedYes

Funding

The authors acknowledge the use of de.NBI cloud and the support by the High Performance and Cloud Computing Group at the Zentrum für Datenverarbeitung of the University of Tübingen and the Federal Ministry of Education and Research (BMBF) through grant no 031 A535A. We also acknowledge all FunARTS users for helpful comments and feedback. We especially thank Libera Lo Presti for her helpful comments on the manuscript. N.Z. and M.D.M. acknowledge the German Center for Infection Research [DZIF TTU09.716]; T.M.Y. is financially supported through a Study Abroad Program by the Ministry of National Education[Law: 1416], Republic of Turkey; A.B. thanks the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) for funding under Germany's Excellence Strategy [EXC 2124 – 390838134]. Funding for open access charge: BMBF [DZIF TTU09.716] (project 09.030 and project BE 6922/1-1).

FundersFunder number
Zentrum für Datenverarbeitung of the University of Tübingen
Deutsches Zentrum für InfektionsforschungDZIF TTU09.716
Deutsche ForschungsgemeinschaftEXC 2124 – 390838134
Bundesministerium für Bildung und Forschung031 A535A, 09.030, BE 6922/1-1
Kementerian Pendidikan Nasional1416

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