A major challenge in synthetic genetic circuit development is the inter-dependency between heterologous gene expressions by circuits and host's growth rate. Increasing heterologous gene expression increases burden to the host, resulting in host growth reduction; which reduces overall heterologous protein abundance. Hence, it is difficult to design predictable genetic circuits. Here, we develop two biophysical models; one for promoter, another for RBS; to correlate heterologous gene expression and growth reduction. We model cellular resource allocation in E. coli to describe the burden, as growth reduction, caused by genetic circuits. To facilitate their uses in genetic circuit design, inputs to the model are common characteristics of biological parts [e.g. relative promoter strength (RPU) and relative ribosome binding sites strength (RRU)]. The models suggest that E. coli's growth rate reduces linearly with increasing RPU / RRU of the genetic circuits; thus, providing 2 handy models taking parts characteristics as input to estimate growth rate reduction for fine tuning genetic circuit design in silico prior to construction. Our promoter model correlates well with experiments using various genetic circuits, both single and double expression cassettes, up to a relative promoter unit of 3.7 with a 60% growth rate reduction (average R2 ~ 0.9).
翻译:合成基因电路开发方面的一个主要挑战是,通过电路和宿主的生长率等异血基因表达方式之间的相互依存性。增加异血基因表达方式增加了宿主的负担,导致宿主增长减少;从而降低了整体异血蛋白丰度。因此,很难设计可预测的遗传电路。在这里,我们开发了两种生物物理模型;一种是推广者模型,另一种是RBS;联系异血基因表达方式和生长减少;我们用E.coli模型模拟蜂窝资源的分配方式来描述基因电路的生长减少所造成的负担。为了便利基因电路设计中的应用,对模型的投入是生物部分的共同特征[例如相对促动强度(RPU)和相对脊椎结合地点的强度(RRRU)]。这些模型表明,E. coli的增长率随着基因电路路的不断增长(RPU/RRU)增加而线下降;因此,我们以E. coli 提供2 部分特性作为估计增长率降低因基因电路路的精确调整而导致的生长速度下降。为了在建造Silico的基因电路路路段设计中,对模型的投入投入,对模型的投入是生物部分进行生物部分的共60的双重的模型,我们促进率的模型,同时进行一种推式的模型,同时进行一种精化的推导式的推导率的推导式的推压。