Bacterial Transcription: Automated model-predictive design of synthetic promoters with Dr. Salis

In this episode, we are joined by Dr. Howard Salis, who has been pioneering research on the complex mechanisms governing transcription rates in bacteria. The focus of our discussion is his team's recent breakthrough in predicting site-specific transcription initiation rates for any σ70 promoter sequence in bacteria.A critical challenge in the field has been understanding how non-canonical sequence motifs collectively control transcription rates. Dr. Salis' team ingeniously used a combination of massively parallel assays, biophysics, and machine learning to develop a 346-parameter model. This model, validated across 22,132 bacterial promoters with diverse sequences, holds the potential to unravel the intricate processes of gene regulation in natural genetic systems. The model's application extends to predicting genetic context effects, designing σ70 promoters with specific transcription rates, and identifying undesired promoters within engineered genetic systems. This breakthrough provides a new level of precision in transcriptional control, which is crucial for the engineering of synthetic genetic systems.Join us as Dr. Salis illuminates the world of bacterial transcription and the role it plays in both nature and the realm of synthetic biology.Keywords: Bacterial Transcription, Gene Regulation, Synthetic Biology, Machine Learning, Biophysics, σ70 Promoter, Genetic Systems, Dr. Howard Salis.Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria. Nat Commun 13, 5159 (2022). https://doi.org/10.1038/s41467-022-32829-5