Multi-Scale Engineering of Heterogeneity in the Host-Aware Synthetic Gene Circuits

点击翻译按钮获取中文摘要

Project Summary Current approaches to designing and constructing synthetic gene circuits have reached a dilemma due to the substantial heterogeneity driven by circuit-host interactions, especially for large-scale gene circuits. The conventional trial-and-error iteration approach on synthetic gene circuit development is regarded as inefficient since the assembled gene circuits often are susceptible to experimental conditions. One fundamental reason is that the heterogeneity driven by circuit-host interactions become significant with the increase of the number of components in gene circuits but are often neglected. Moreover, the lack of quantitative frameworks for quantifying, characterizing, and controlling heterogeneity in the host-aware synthetic gene circuits impedes the progress in the field. My laboratory has been focusing on dissecting the mechanisms of how the circuit-host mutual interactions affect the gene circuit functions and developing control strategies targeting circuit-host interactions to optimize engineered synthetic gene circuits. Recently we found a topology-dependent interference of synthetic gene circuit function by growth feedback, which was published in Nature Chemical Biology. We also found winner-takes-all resource competition that redirected cascading cell fate transitions, which is in revision to Nature Communication. In the proposed projects, we will establish experimental and computational frameworks to quantify, characterize, and control the gene expression heterogeneity in the host- aware synthetic gene circuits. The heterogeneity can result from stochastic cellular resource allocation, stochastic biochemical reactions in gene circuits, and stochastic cell divisions. These heterogeneities are intertwined due to the complex interactions between the gene circuits and the host organisms, creating another layer of challenge and complexity to engineering robust gene circuits. We will integrate a microfluidics system for time-lapse live-cell analysis, a Turbidostat platform with Python-based easy-to-use web interface for accurate growth rate control and automatic yet remotely-controllable in-situ fluorescence measurement, and hybrid agent-based modeling algorithms for stochastic simulation of all the single cells in the bacterial community to characterize the heterogeneity from various noise sources in the host-aware synthetic gene circuits. I have built up my research group with all the necessary expertise and capabilities to complete the proposed projects. This work will provide a systematic in-depth mechanical understanding of the heterogeneity driven by circuit-host interactions, and will greatly help us to rationally design and control the synthetic gene circuits for sophisticated clinical applications in a real-world environment, such as bacterial infection and tumor microenvironments.