Real-Time Coupling of Gene Networks in Single Cells

主要研究者：Animesh Ray单细胞中基因网络的实时耦合概要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，包括正常细胞状态的维持、细胞对内部和外部信号的响应、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几乎总是在其表观遗传状态下是异质的，其中少数关键调节因子的随机波动（内在噪声）和生化机制的一般波动（外在噪声）的影响严重影响网络动态。处理这些过程的数学方法尚未完全发展。在这个建议的优势是采取了一种新的合成生物学的方法，再加上相互作用建模随机进化博弈论。后者是一个理想的建模框架，噪声相互作用系统的组件状态的概率分布相互影响。将在两个单独的酵母细胞内设计和实施两个合成遗传网络，所述两个单独的酵母细胞在其他方面是遗传上相同的（除了在交配型基因座处）。这两个网络中的每一个都将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真实的时间成像技术在单细胞中进行测量。这两个网络将通过配对电池相互耦合，并监测耦合的动态。网络的设计使它们有机会相互合作和干扰。耦合系数是可调的。将设计一个随机进化博弈模型，以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）以前从未研究过单细胞中两个合成基因电路耦合的实时动力学; 2）这里提出的特定基因网络尚未研究过，因此不能保证观察到的动力学将反映模拟动力学; 3）尚未尝试对交配细胞进行单细胞基因表达动力学成像（据我们所知）; 4）随机进化博弈理论是数学科学中一个相对较新的研究领域，其对基因调控网络动力学的适用性尚不确定。鉴于这些不确定性，并考虑到如果该项目成功，可能会推进一种新的思考生物网络动力学的方式，该项目被认为适合EAGER提交。从这些研究中获得的见解对于理解网络如何在嘈杂的环境中进行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进行合作或竞争具有重要价值。

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.