ArticleNucleic acids research2025
Unraveling the regulatory dynamics of bidirectional promoters for modulating gene co-expression and metabolic flux in Saccharomyces cerevisiae.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence.Comprehensive reviews in food science and food safety · 2026Review
- The shape of fitness functions and the distribution of mutational effect sizes jointly limit adaptation by regulatory mutations.Nature ecology & evolution · 2026Article
- Yeast species resource exploration and application in cell factories.Synthetic and systems biotechnology · 2026Review
- PrimerWeaver: an integrated web server for primer design in molecular biology workflows.Nucleic acids research · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
Bidirectional promoters (BDPs) hold great promise for applications in synthetic biology by enabling co-expression of multiple genes with minimized promoter size. However, the lack of well-characterized BDPs along with an incomplete understanding of their regulatory mechanisms limits broader applications. Here, we conducted genome-wide screening and characterization of 749 BDP candidates containing a single shared nucleosome-depleted region in yeast Saccharomyces cerevisiae. A pronounced asymmetry in BDP strength was observed using both transcriptomic and fluorescence reporter analyses. We demonstrated that these unbalanced BDP strengths could be utilized for fine-tuning metabolic flux in yeast, achieving yields comparable to or exceeding those of commonly used constitutive or inducible promoters for terpenoid production under the examined conditions. Using in silico mutagenesis guided by the DREAM-CNN yeast cis-regulatory AI prediction model, we identified conserved activator-binding hotspots within the central region of 63.8% of identified BDP candidates. Disruption of these hotspots in six selected BDPs significantly reduced promoter strength in both orientations, suggesting that these AI-predicted motifs are indeed critical for the functionality of BDPs. Overall, this study provides a comprehensive framework for BDP identification and engineering, leveraging AI-guided models to advance rational synthetic promoter design, thus paving the way for precise genetic control in synthetic biology.
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Registered trials
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