DMS/NIGMS 1: Multi-timescale stochastic modeling to investigate epigenetic memory in bacteria

当一个细胞分裂时，每个子细胞都包含一个相同的DNA拷贝。DNA为细胞制造分子提供了蓝图，因此构成了一种遗传“记忆”。然而，细胞也将一种非遗传或“表观遗传”的记忆传递给它的子细胞。表观遗传记忆包括细胞已经产生的分子，以及DNA的化学和构象状态，这些由子细胞直接遗传。即使在像细菌这样的简单生物中，表观遗传记忆仍然知之甚少。在这个项目中，研究人员将使用一种新的实验设备和新的数学模型来解决有关表观遗传记忆的基本问题，比如它能持续几代。这项研究将与为匹兹堡地区的高中教师开发一门跨学科科学课程相结合。由于表观遗传记忆是活细胞的基本属性，但定量理解仍然难以捉摸，因此预计该结果将具有广泛的意义，特别是在数学和生物科学的界面上。该项目将利用研究人员的新型微流体技术，为细胞生长和分裂动力学提供新的理论，从而为进一步的实验做出预测。总体目标是准确量化细菌的表观遗传记忆，阐明其决定因素，并测量其对应激诱导环境的敏感性。该目标将通过两个目标来实现：(1)使用离散时间随机建模来解开多代表观遗传记忆时间尺度的纠缠；(2)结合连续和离散时间随机建模来研究多代噪声传播。在这两个目标中，实验和理论将在数量上相互指导，从而对细菌表观遗传学有更丰富的了解。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

When a cell divides, each daughter cell contains an identical copy of its DNA. The DNA provides the blueprint for the molecules that the cell makes, and thus constitutes a genetic “memory”. However, the cell also passes a non-genetic, or “epigenetic”, memory to its daughters. Epigenetic memory consists of the molecules that the cell has already produced, and the chemical and conformational state of the DNA, which get inherited directly by the daughter cells. Even in simple organisms like bacteria, epigenetic memory is still poorly understood. In this project, the investigators will address basic questions about epigenetic memory, such as how many generations it lasts, using a new experimental device and new mathematical models. The research will be combined with the development of a course for high school teachers in the Pittsburgh area focused on interdisciplinary science. Because epigenetic memory is a fundamental property of living cells, and yet a quantitative understanding has remained elusive, the results are expected to have broad implications, particularly at the interface of the mathematical and biological sciences. The project will take advantage of the investigator's novel microfluidic technology to inform a new theory of cell growth and division dynamics, which in turn will make predictions for further experiments. The overarching goal is to accurately quantify epigenetic memory in bacteria, elucidate its determinants, and measure its sensitivity to stress-inducing environments. The goal will be achieved via two aims: (1) using discrete-time stochastic modeling to untangle multigenerational epigenetic memory timescales, and (2) combining continuous- and discrete-time stochastic modeling to investigate multigenerational noise propagation. In both aims, experiments and theory will guide each other quantitatively, leading to a richer understanding of bacterial epigenetics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.