COMMBAT: a web platform for exploring expression control of biosynthetic gene clusters

Nucleic Acids Research, vol. 54, pp. W359–W366

Abstract

Bacterial genomes contain thousands of biosynthetic gene clusters (BGCs) responsible for the production of structurally diverse natural products with applications in medicine, agriculture, and biotechnology. Expression of these BGCs is tightly regulated by transcription factors (TFs) responding to environmental cues, yet predicting which TFs regulate specific BGCs remains challenging. In particular, TF binding sites (TFBSs) within BGCs often diverge from canonical motifs, limiting the effectiveness of standard motif-scanning approaches and hindering systematic exploration of BGC regulation. Here, we present COMMBAT (COnditions for Microbial Metabolite Biosynthesis Activated Transcription), a framework for large-scale prediction of TF-BGC regulatory interactions across bacterial genomes. COMMBAT integrates motif matching with genomic context and gene function information to predict functional TFBSs. The COMMBAT web platform (https://www.commbat.uliege.be) enables users to (i) identify BGCs potentially regulated by a given TF, and (ii) predict candidate TFs that control a specific BGC. With over 4000 TF position weight matrices from four public repositories and more than 400 000 BGCs from MIBiG and antiSMASH DB, COMMBAT provides a scalable resource to predict regulatory inputs and guide/prioritize culture conditions and genetic engineering strategies for natural product discovery.

Authors 10

1. Silvia Ribeiro Monteiro

   University of Liège

   Affiliation as printed

   InBioS—Center for Protein Engineering, University of Liège, Institut de Chimie , Liège B-4000 ,

2. Augustin Rigolet Aachen Molecular Biotechnology Institute of Biology, Leiden University

   Leiden University

   Affiliation as printed

   Molecular Biotechnology, Institute of Biology, Leiden University , Sylviusweg 72, 2333 BE Leiden ,

3. Clément Jeunehomme

   University of Liège

   Affiliation as printed

   InBioS—Center for Protein Engineering, University of Liège, Institut de Chimie , Liège B-4000 ,

4. Julianne Gathot

   University of Liège

   Affiliation as printed

   InBioS—Center for Protein Engineering, University of Liège, Institut de Chimie , Liège B-4000 ,

5. Yasmine Kerdel

   University of Liège

   Affiliation as printed

   InBioS—Center for Protein Engineering, University of Liège, Institut de Chimie , Liège B-4000 ,

6. Matthias Henry

   University of Liège

   Affiliation as printed

   InBioS—Center for Protein Engineering, University of Liège, Institut de Chimie , Liège B-4000 ,

7. Hannah E. Augustijn Aachen Molecular Biotechnology Institute of Biology, Leiden University

   Leiden University · Wageningen University & Research

   Affiliation as printed

   Bioinformatics Group, Wageningen University & Research , Droevendaalsesteeg 1, 6708 PB Wageningen ,

   Molecular Biotechnology, Institute of Biology, Leiden University , Sylviusweg 72, 2333 BE Leiden ,

8. Marnix H. Medema

   Wageningen University & Research

   Affiliation as printed

   Bioinformatics Group, Wageningen University & Research , Droevendaalsesteeg 1, 6708 PB Wageningen ,

9. Gilles P. van Wezel Aachen Molecular Biotechnology Institute of Biology, Leiden University

   Leiden University

   Affiliation as printed

   Molecular Biotechnology, Institute of Biology, Leiden University , Sylviusweg 72, 2333 BE Leiden ,

10. Sébastien Rigali corresponding

    University of Liège

    Affiliation as printed

    InBioS—Center for Protein Engineering, University of Liège, Institut de Chimie , Liège B-4000 ,