Two Cellular Resource Based Models Linking Growth and Parts Characteristics Aids the Study and Optimization of Synthetic Gene Circuits

TL;DR

This paper introduces two biophysical models linking gene expression parts to host growth rate in E. coli, enabling better design and optimization of synthetic gene circuits by predicting growth burden based on part characteristics.

Contribution

The study develops novel promoter and RBS models that predict growth reduction from gene expression levels, aiding in circuit design optimization.

Findings

Models accurately predict growth reduction up to 60%.

Growth rate decreases linearly with promoter and RBS strength.

High correlation (R2 ~ 0.9) with experimental data.

Abstract

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).