Real-Time Coupling of Gene Networks in Single Cells

基因调控网络的复杂动力学是许多基本生物学问题的基础，包括细胞正常状态的维持、细胞对内部和外部信号的反应、生物系统固有噪声的处理以及生物体的进化轨迹。此外，含有相同基因集的细胞在表观遗传状态下几乎总是异质的，其中少数关键调控因子的随机波动（内在噪声）和生化机制的普遍波动（外在噪声）的影响严重影响网络动力学。处理这些过程的数学方法还没有完全发展起来。在这个提议中，利用了一种新的合成生物学方法，结合随机进化博弈论的相互作用建模。后者是噪声相互作用系统的理想建模框架，其中组件状态的概率分布相互影响。两个合成遗传网络将在两个独立的酵母细胞内设计和实施，这些细胞在其他方面的遗传相同（交配型位点除外）。这两个网络中的每一个都以一种共同的代谢物作为输入，并输出两种荧光蛋白中的一种，这两种荧光蛋白将通过实时成像技术在单个细胞中进行测量。这两个网络将通过配对细胞相互耦合，并对耦合动态进行监测。网络的设计使它们有机会相互合作，也有机会相互干扰。耦合系数是可调的。将设计一个随机进化博弈论模型来确定与实验结果的一致性。这里提出的理论和实验都是高风险的：1)单细胞中两个合成遗传电路耦合的实时动力学从未被研究过；2)本文提出的特定基因网络尚未被研究，因此不能保证观察到的动态将反映模拟的动态；3)对单细胞基因表达动态的交配细胞成像尚未尝试（据我们所知）；4)随机进化博弈论是数学科学中一个相对较新的研究领域，其在基因调控网络动力学中的适用性尚不确定。考虑到这些不确定性，考虑到如果项目成功，可能会推进一种关于生物网络动力学的新思维方式，该项目被认为适合提交给EAGER。从这些研究中获得的见解将有助于理解网络如何在嘈杂环境中通信，以及具有随机行为的模态理性实体如何在通信网络中合作或竞争。

PI: Animesh Ray Real-time coupling of gene networks in single cells SUMMARY The complex dynamics of gene regulatory networks underlie a host of fundamental biological questions including the maintenance of normal cellular states, response of cells to internal and external signals, handling of noise inherent in biological systems, and the evolutionary trajectory of organisms. Moreover, cells containing identical gene sets nearly always are heterogeneous in their epigenetic states, where the effects of stochastic fluctuation of a small number of key regulators (intrinsic noise) and general fluctuation in biochemical machinery (extrinsic noise) critically affect network dynamics. Mathematical methods for tackling these processes are not yet fully developed. In this proposal advantage is taken of a novel synthetic biology approach coupled with interaction modeling by stochastic evolutionary game theory. The latter is an ideal modeling framework for noisy interacting systems where the probability distribution of component states influence one another. Two synthetic genetic networks will be designed and implemented within two separate yeast cells that are otherwise genetically identical (except at the mating type locus). Each of these two networks takes as input a common metabolite and outputs one of two fluorescent proteins that will be measured in single cells by real time imaging techniques. The two networks will be coupled to each other by mating the cells and the coupled dynamics will be monitored. The networks are designed such that they have the opportunity to both cooperate and interfere with each other. The coupling coefficients are tunable. A stochastic evolutionary game theoretic model will be devised to determine agreement with experimental results. Both the theory and experiments proposed here are high-risk: 1) Real-time dynamics of coupling of two synthetic genetic circuits in single cells have never been studied before; 2) The particular gene networks proposed here have not been studied, so there is no guarantee that the observed dynamics will reflect simulated dynamics; 3) Imaging mating cells for single cell gene expression dynamics has not yet been attempted (to our knowledge); 4) Stochastic evolutionary game theory is a relatively new area of research in mathematical sciences and its applicability to gene regulatory network dynamics is uncertain. Given these uncertainties, and given the potential for advancing a new way of thinking about biological network dynamics if the project is successful, this project is deemed suitable for an EAGER submission. Insights learned from these studies will be valuable for understanding how networks communicate in a noisy environment and how modally rational entities with stochastic behavior cooperate or compete in communication networks.