ArticleACS synthetic biology2021
RBS and Promoter Strengths Determine the Cell-Growth-Dependent Protein Mass Fractions and Their Optimal Synthesis Rates.
Article in ACS synthetic biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism.Trends in microbiology · 2026Review
- Host-aware Identification of Intrinsic Gene Expression Biopart Parameters using Combinatorial Libraries.Nature communications · 2026Article
- Programming Next-Generation Synthetic Biosensors by Genetic Circuit Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Controlling 3-hydroxyhexanoate mole fraction in poly (3-hydroxybutyrate-co-3-hydroxyhexanoate) by altering enoyl-CoA hydratase (phaJ) ribosome-binding site in Cupriavidus necator H16.Bioprocess and biosystems engineering · 2026Article
- Codon usage modulates the relationship between the burden and yield of protein overexpression.Journal of biological engineering · 2025Article
- Multiscale modelling of bioprocess dynamics and cellular growth.Microbial cell factories · 2024Article
- A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits.Nature communications · 2024Article
- Multi-level metabolic engineering of Escherichia coli for high-titer biosynthesis of 2'-fucosyllactose and 3-fucosyllactose.Microbial biotechnology · 2022Article
- Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback.Nature communications · 2022Article
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4 authors.
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Abstract
Models of gene expression considering host-circuit interactions are relevant for understanding both the strategies and associated trade-offs that cell endogenous genes have evolved and for the efficient design of heterologous protein expression systems and synthetic genetic circuits. Here, we consider a small-size model of gene expression dynamics in bacterial cells accounting for host-circuit interactions due to limited cellular resources. We define the cellular resources recruitment strength as a key functional coefficient that explains the distribution of resources among the host and the genes of interest and the relationship between the usage of resources and cell growth. This functional coefficient explicitly takes into account lab-accessible gene expression characteristics, such as promoter and ribosome binding site (RBS) strengths, capturing their interplay with the growth-dependent flux of available free cell resources. Despite its simplicity, the model captures the differential role of promoter and RBS strengths in the distribution of protein mass fractions as a function of growth rate and the optimal protein synthesis rate with remarkable fit to the experimental data from the literature for
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