Microbial BiotechnologyGenomicsPeer-reviewed journal article
Bursts in biosynthetic gene cluster transcription are accompanied by surges of natural compound production in the myxobacterium Sorangium sp.
Judith BoldtiD, Laima Lukoševičiūtė, Chengzhang FuiD, Matthias SteglichiD, Boyke BunkiD, Vera Junker, Aileen Gollasch, Birte Trunkwalter, Kathrin I. Mohr, Michael BeckstetteiD, Joachim M. WinkiD, Jörg OvermanniD, Rolf MülleriD, Ulrich NübeliD
Abstract
We have investigated the time course of genome-wide transcription in the myxobacterium Sorangium sp. So ce836 in relation to its production of natural compounds. Time-resolved RNA sequencing revealed that core biosynthesis genes from 48 biosynthetic gene clusters (BGCs; 92% of all BGCs encoded in the genome) were actively transcribed at specific time points in a batch culture. The majority (80%) of polyketide synthase and non-ribosomal peptide synthetase genes displayed distinct peaks of transcription during exponential bacterial growth. Strikingly, these bursts in BGC transcriptional activity were associated with surges in the production of known natural compounds, indicating that their biosynthesis was critially regulated at the transcriptional level. In contrast, BGC read counts from single time points had limited predictive value about biosynthetic activity, since transcription levels varied >100-fold among BGCs with detected natural products. Taken together, our time-course data provide unique insights into the dynamics of natural compound biosynthesis and its regulation in a wild-type myxobacterium, challenging the commonly cited notion of preferential BGC expression under nutrient-limited conditions. The close association observed between BGC transcription and compound production warrants additional efforts to develop genetic engineering tools for myxobacterial producer strains, to boost compound yields by manipulating transcriptional activity.
- organism: bacteria (other)
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 11
- FWCI
- 1.71
- Field percentile
- top 17%
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