An integrative circuit-host modelling framework for predicting synthetic gene network behaviours
An integrative circuit-host modelling framework for predicting synthetic gene network behaviours
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DOI：
10.1038/s41564-017-0022-5
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发表时间：
2017-12-01
影响因子：
28.3
通讯作者：
Lu, Ting
中科院分区：
文献类型：
--
作者：
Liao, Chen;Blanchard, Andrew E.;Lu, Ting
合成生物学的一个基本挑战是缺乏准确描述和预测工程基因电路行为的定量工具。这一挑战来自多个因素，其中电路及其主机之间复杂的相互依赖性是一个主要原因。在这里，我们提出了一个基因电路建模框架，明确集成电路行为与主机生理通过双向电路主机耦合。该框架包括一个粗粒度的，但机械的主机生理学的描述，涉及动态资源分区，多层电路主机耦合，包括通用和系统特定的相互作用，和一个详细的动力学模块的外源电路。我们发现，在训练之后，该框架能够捕获和预测关于宿主及其外源基因过表达的大量实验数据。为了证明它的实用性，我们应用该框架来研究一个生长调节反馈电路，其动态特性被电路-宿主相互作用定性地改变。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和空间生态学的尺度切换开关的行为。这一工作推进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。
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.