Biophysical models and mechanisms for cellular adaptation to environmental stress

项目摘要/摘要 活细胞具有显著的适应环境条件变化的能力。调适 涉及细胞属性的改变，以响应外部提示，以调节重要的生理 功能和流程。虽然在鉴定分子成分和分子方面取得了很大进展 细胞应激反应的生化途径，细胞物理特性在适应性中的作用 应激反应大多是未知的。我们最近的研究提供了证据，细胞形状和细胞的变化 物理特性通过机械力化学反馈促进在某些应激条件下的适应性收益 流程。拟议研究的目标是发展量化理论和数据驱动的计算 揭示细胞对环境适应性反应的生物物理反馈机制的模型 压力。我们将利用一种跨学科的方法，将统计物理、系统 生物学和实验数据分析，以构建细胞行为的预测模型。我们将具体地 研究两种不同生物系统的适应性反应：1)对营养变化和抗生素的适应 2)对能量剥夺和细胞状态转变的适应。 线虫的胚胎。在这些系统中的每个系统中，我们都将开发基于以下内容的定量细胞级别模型 在实验数据中观察到的已知分子电路、细胞内生物物理相互作用和动力学。这个 模型将根据从我们的实验中获得的定量单细胞数据进行校准和测试 合作者。合成的模型将有助于测试不同的实验假说，分离和测试相对的 生化和物理途径在细胞适应性反应中的作用，并找出主要驱动力 在复杂的适应现象背后。除了开发细胞生物物理的定量模型之外 行为，我们的研究将生成各种计算工具，使高效的全细胞模拟成为可能 细菌的生长、形态发生、细胞内组织和单细胞发育。

Project Summary/Abstract Living cells possess the remarkable ability to adapt to changes in their environmental conditions. Adaptation involves changes in cellular properties in response to external cues in order to regulate vital physiological functions and processes. While much progress has been made in identifying the molecular components and biochemical pathways underlying cellular stress response, the role of cellular physical properties in adaptive stress response is mostly unknown. Our recent studies provide evidence that changes in cell shape and cellular physical properties promotes adaptive benefits in certain stressful conditions via mechanochemical feedback processes. The goal of the proposed research is to develop quantitative theory and data-driven computational models to uncover the biophysical feedback mechanisms underlying cellular adaptive response to environmental stresses. We will utilize an interdisciplinary approach that integrates tools from statistical physics, systems biology, and experimental data analysis to construct predictive models for cell behavior. We will specifically investigate adaptive response in two different biological systems: 1) adaptation to nutrient shifts and antibiotic stresses in proliferating bacterial cells, and 2) adaptation to energy deprivation and cell state transitions in nematode worm embryos. In each of these systems we will develop quantitative cell-level models based on known molecular circuits, intracellular biophysical interactions and dynamics observed in experimental data. The models will be calibrated and tested against quantitative single-cell data obtained from our experimental collaborators. The resultant models will help test different experimental hypotheses, isolate and test the relative roles of biochemical and physical pathways in cellular adaptive response, and pinpoint the main driving forces behind complex adaptive phenomena. In addition to developing quantitative models for cellular biophysical behaviors, our study will generate a variety of computational tools that will enable efficient whole-cell simulations of bacterial growth, morphogenesis, intracellular organization and single-cell development.