Elucidating the origin and consequences of dimensional reduction in bacterial growth control

在系统水平上理解活细胞的最大科学挑战之一是细胞水平上简单行为之间的脱节（例如，生长和运动）以及分子水平上的复杂相互作用。尽管在表征分子相互作用方面投入了巨大的努力，但它们的复杂性使得预测和操纵细胞对环境和遗传扰动的反应非常困难。本项目旨在阐明细胞实现“降维”的策略，即，细胞自身如何设法减少分子信息的多样性并指导简单的连贯行为。具体的主题将是细菌的生长，重点是细菌细胞如何决定它的生长速度以及它如何使用这些信息来协调代谢和基因表达。由该资助支持的学生和博士后研究人员将学习进行分子和行为表征，开发数学模型来关联这些测量，并测试有关降维机制的特定假设。所吸取的经验教训将被整合到研究生水平的定量生物学课程正在开发的PI，无论是生物科学的学生学习降维的数学和物理科学的学生学习不同类型的实验，以表征分子的相互作用和行为。本研究计划将集中在ppGpp信号系统潜在的生长控制E。coli作为实现降维的特定分子系统。从已知的定性特征ppGpp为基础的控制在E。大肠杆菌中，生长控制的定量模型提出了基于蛋白质合成的积极和消极的调控通过ppGpp信号。 这项研究计划将测试和阐明这种基于ppGpp的生长控制模式的细节，探测其对信号和控制电路的关键组件的依赖性，这些组件设置其少数参数，并通过E.大肠杆菌，从一个指数生长状态到另一个通过生长停滞期。这项研究的最终成果是一个预测性的，细菌生长动力学的机制模型，以响应环境的变化，包括营养物质的可用性和抗生素。这项工作是由MCB的合成和系统生物学和MPS物理学中的生命系统物理学共同创立的。该奖项反映了NSF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。

One of the biggest scientific challenges in understanding living cells at a systems level is the disconnect between simple behaviors at the cellular level (e.g., growth and movement) and the complex interactions at the molecular level. Despite enormous efforts invested into characterizing molecular interactions, their complexities make it very difficult to predict and manipulate cellular responses to environmental and genetic perturbations. This project aims to elucidate the strategies by which cells achieve "dimensional reduction", i.e., how cells themselves manage to reduce the multiplicity of molecular information and direct simple coherent behaviors. The specific topic will be on bacteria growth, with focus on how a bacterium cell determines how fast it grows and how it uses this information to coordinate metabolism and gene expression. Student and post-doctoral researchers supported by this grant will learn to make molecular and behavioral characterization, develop mathematical models to relate these measurements, and test specific hypotheses on the mechanism of dimensional reduction. The lessons learned will be integrated into the graduate-level curriculum in Quantitative Biology being developed by the PI, both for students of biological sciences to learn the mathematics of dimensional reduction and for students of physical sciences to learn different types of experiments to characterize molecular interactions and behaviors. This research program will focus on the ppGpp signaling system underlying growth control of E. coli as a specific molecular system implementing dimensional reduction. From known qualitative features of ppGpp-based control in E. coli, a quantitative model of growth control is proposed based on both positive and negative regulation of protein synthesis via ppGpp signaling. This research program will test and elucidate the details of this ppGpp-based mode of growth control, probe its dependences on key components of the signaling and control circuit which set its few parameters, and determine its consequences on the kinetics growth transitions by E. coli, from one exponential growth state to another through periods of growth arrest. The final output of this research is a predictive, mechanistic model of bacterial growth dynamics in response to changes in the environment, including nutrient availability and antibiotics. This work is cofounded by MCB's Synthetic and Systems Biology and Physics of Living Systems in Physics in MPS.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.