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

Area of Science:

• Microbiology
• Genomics
• Bioinformatics

Background:

• Bacterial genomes harbor numerous biosynthetic gene clusters (BGCs) producing valuable natural products.
• Transcription factors (TFs) regulate BGC expression in response to environmental signals.
• Predicting TF-BGC regulatory interactions is difficult due to divergent TF binding sites (TFBSs).

Purpose of the Study:

• To develop a framework for large-scale prediction of TF-BGC regulatory interactions.
• To create a web platform for identifying TF-BGC regulatory relationships.
• To facilitate natural product discovery by predicting regulatory inputs.

Main Methods:

• Developed COMMBAT (COnditions for Microbial Metabolite Biosynthesis Activated Transcription) framework.
• Integrated motif matching with genomic context and gene function data.
• Utilized over 4000 TF position weight matrices and 400,000+ BGCs.

Main Results:

• COMMBAT predicts functional TFBSs by integrating diverse data.
• The COMMBAT web platform allows users to predict TF-BGC interactions.
• Provides a scalable resource for understanding BGC regulation.

Conclusions:

• COMMBAT offers a novel approach to predict TF-BGC regulatory interactions.
• Enables systematic exploration of BGC regulation across bacterial genomes.
• Guides strategies for natural product discovery and optimization.