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为细胞制造的分子提供蓝图，因此构成了遗传“记忆”。然而，细胞也会将非遗传或“表观遗传”的记忆传递给它的子细胞。表观遗传记忆由细胞已经产生的分子以及DNA的化学和构象状态组成，这些分子直接由子细胞继承。即使在细菌这样简单的生物体中，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，例如它持续了多少代。这项研究将与匹兹堡地区高中教师的跨学科科学课程的开发相结合。由于表观遗传记忆是活细胞的一个基本特性，但定量的理解仍然难以捉摸，因此预计这些结果将具有广泛的影响，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的新理论提供信息，从而为进一步的实验做出预测。总体目标是准确地量化细菌中的表观遗传记忆，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，以及（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，实验和理论将相互指导，定量，导致细菌表观遗传学的更丰富的理解。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.