Synthetic Biology and Biosystems Control Lab, Institut d'Automàtica i Informàtica Industrial, Universitat Politècnica de València, Camí de Vera S/N, 46022 Valencia, Spain.
ACS Synth Biol. 2021 Dec 17;10(12):3290-3303. doi: 10.1021/acssynbio.1c00131. Epub 2021 Nov 12.
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 . This allows us to explain why endogenous genes have evolved different strategies in the expression space and also makes the model suitable for model-based design of exogenous synthetic gene expression systems with desired characteristics.
考虑宿主-回路相互作用的基因表达模型对于理解细胞内源性基因进化的策略和相关权衡以及异源蛋白表达系统和合成遗传回路的有效设计是相关的。在这里,我们考虑了一个考虑到由于细胞资源有限而导致的宿主-回路相互作用的细菌细胞中基因表达动力学的小型模型。我们将细胞资源募集强度定义为一个关键的功能系数,该系数解释了资源在宿主和感兴趣基因之间的分配以及资源利用与细胞生长之间的关系。该功能系数明确考虑了实验室可获得的基因表达特征,例如启动子和核糖体结合位点 (RBS) 的强度,捕捉了它们与可用游离细胞资源的生长依赖性通量之间的相互作用。尽管模型很简单,但它捕获了启动子和 RBS 强度在蛋白质质量分数分布中的差异作用,作为生长速率的函数,以及与文献中的实验数据非常吻合的最佳蛋白质合成速率。这使我们能够解释为什么内源性基因在表达空间中进化出了不同的策略,并且还使模型适合基于模型的设计具有所需特性的外源性合成基因表达系统。