Journal of Natural ProductsMicrobiologyPeer-reviewed journal article
The Transcriptional Architecture of Bacterial Biosynthetic Gene Clusters
Silvia Ribeiro MonteiroiD, Yasmine KerdeliD, Julianne GathotiD, Sébastien RigaliiD
Abstract
Bacteria produce diverse bioactive metabolites with ecological and pharmaceutical importance. These compounds are synthesized by biosynthetic gene clusters (BGCs), whose expression is tightly regulated. While many studies have examined the factors influencing BGC expression, including transcription factors (TFs) and environmental signals, the regulatory architecture governing BGCs expression remains largely unexplored. In this meta-analysis, we collected experimental datasets of bacterial transcription factor binding sites (TFBSs) to unveil i) the functional gene categories preferentially targeted by TFs, ii) the regulatory coverage based on cluster organization, iii) the positional distribution of TFBSs, and iv) the binding strength of TFs. Our analysis reveals a regulatory strategy where global TFs primarily target pathway-specific TFs when present, aligning with a "one-for-all" strategy ensuring cluster-wide expression control. Additionally, examination of the organization of TFBS-associated genes identified distinct transcriptional strategies: regulatory genes are frequently monocistronic, while biosynthetic genes tend to be co-transcribed in operons to guarantee biosynthesis efficiency. The positional distribution of TFBSs highlights a strong enrichment in the upstream regions of genes optimizing their role in gene regulation. Finally, assessment of TF-TFBS interaction strength suggests that TFBSs within BGCs exhibit lower binding affinities compared to those associated with core regulon genes that reside outside BGCs, allowing greater regulatory flexibility in response to multiple environmental cues. These findings provide new insights into the regulatory principles shaping BGC expression and would help predict conditions for activating cryptic BGCs, facilitating the discovery of novel bioactive compounds through targeted culture and engineering strategies.
- organism: bacteria (other)
- assay: DNA methylation
- assay: ChIP-seq
- research focus: chromatin & epigenetic regulation
- approach: statistical model
- Citations
- 11
- FWCI
- 6.18
- Field percentile
- top 3%
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