One fundamental challenge in synthetic biology is the lack of quantitative tools that accurately describe and predict the behaviours of engineered gene circuits. This challenge arises from multiple factors, among which the complex interdependence of circuits and their host is a leading cause. Here we present a gene circuit modelling framework that explicitly integrates circuit behaviours with host physiology through bidirectional circuit-host coupling. The framework consists of a coarse-grained but mechanistic description of host physiology that involves dynamic resource partitioning, multilayered circuit-host coupling including both generic and system-specific interactions, and a detailed kinetic module of exogenous circuits. We showed that, following training, the framework was able to capture and predict a large set of experimental data concerning the host and its foreign gene overexpression. To demonstrate its utility, we applied the framework to examine a growth-modulating feedback circuit whose dynamics is qualitatively altered by circuit-host interactions. Using an extended version of the framework, we further systematically revealed the behaviours of a toggle switch across scales from single-cell dynamics to population structure and to spatial ecology. This work advances our quantitative understanding of gene circuit behaviours and also benefits the rational design of synthetic gene networks.

中文翻译：

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用于预测合成基因网络行为的集成电路-主机建模框架。

合成生物学的一个基本挑战是缺乏准确描述和预测基因工程电路行为的定量工具。这一挑战来自多种因素，其中电路及其主机之间的复杂相互依赖性是主要原因。在这里，我们介绍了一个基因电路建模框架，该框架通过双向电路-主机耦合将电路行为与主机生理显式地集成在一起。该框架包括对主机生理的粗粒度但机械的描述，其中涉及动态资源分配，多层电路-主机耦合，包括通用和系统特定的相互作用，以及外源电路的详细动力学模块。我们证明，经过培训，该框架能够捕获和预测有关宿主及其外源基因过表达的大量实验数据。为了证明其实用性，我们将框架应用于检验生长调制反馈电路，该电路的动态性会因电路与主机之间的相互作用而发生质的变化。使用该框架的扩展版本，我们进一步系统地揭示了从单细胞动力学到种群结构再到空间生态的各种尺度上的拨动开关的行为。这项工作提高了我们对基因电路行为的定量理解，也有利于合成基因网络的合理设计。我们应用该框架来研究生长调制反馈电路，该电路的动态性会因电路与主机之间的相互作用而发生质的变化。使用该框架的扩展版本，我们进一步系统地揭示了从单细胞动力学到种群结构再到空间生态的各种尺度上的拨动开关的行为。这项工作提高了我们对基因电路行为的定量理解，也有利于合成基因网络的合理设计。我们应用该框架来研究生长调制反馈电路，该电路的动态性会因电路与主机之间的相互作用而发生质的变化。使用该框架的扩展版本，我们进一步系统地揭示了从单细胞动力学到种群结构再到空间生态的各种尺度上的拨动开关的行为。这项工作提高了我们对基因电路行为的定量理解，也有利于合成基因网络的合理设计。