Physics of Bacterial Growth Control and Antibiotic Resistance

生命系统的运行远离平衡，不断地消耗和耗散能量，以执行其生长、复制和适应不同环境条件的定义功能。虽然控制非平衡系统动力学的物理原理在过去二十年中已经出现，但如何实现这些原理来调节重要的生物过程仍然知之甚少。提出的研究目标是深入了解控制细菌生长，形状发育和对抗生素的适应性反应的调节机制。细菌的生长和形状是由细胞壁决定的，细胞壁是一种刚性的蛋白质结构，在驱动细胞伸长的同时可以承受高渗透压。一个突出的挑战是将细胞壁物理性质的改变与细菌的适应性形状变化和适应性控制联系起来。这对于理解细菌如何在抑制细胞壁生长机制的抗生素治疗下恢复其生长和分裂的适应性非常重要。我们试图通过提出一个新的框架来解决这一挑战，在这个框架中，理论建模和实验数据相结合，来剖析蛋白质合成和随机细胞周期过程如何控制单个细菌细胞的强劲生长和适应行为。利用统计力学和软物质物理学的工具，我们将开发一个与细胞大小和分裂控制的随机决策过程相耦合的生长细胞壁结构的定量模型。我们将扩展这个模型来剖析单个细菌细胞如何利用机械力和生化反应之间的反馈来适应生长抑制压力。特别是，我们将剖析棒状细菌在核糖体靶向抗生素下的适应性恢复机制，核糖体靶向抗生素是临床使用的主要抗菌药物。我们将比较理论模型预测与在正常和抗生素治疗条件下的单细菌形状和生长的高通量实验测量。这种综合方法将使我们能够确定与抗生素适应细胞能量消耗预算的速度和准确性有关的物理原理。本研究的结果将通过建立适应性生物物理过程的成本-性能权衡关系，从根本上推进我们对生命系统非平衡物理的理解。此外，我们将在单细胞水平上直接解决抗菌药物对细菌适应性的物理影响，这将对开发和设计能够有效控制抗生素耐药性进化的新药具有广泛的意义。

Living systems operate far from equilibrium, constantly consuming and dissipating energy to perform their defining functions of growth, replication, and adaptation to diverse environmental conditions. While the physical principles governing the dynamics of non-equilibrium systems have emerged over the past two decades, how these principles are realised for the regulation of vital biological processes remains poorly understood. The goal of the proposed research is to develop an in-depth physical understanding of the regulatory mechanisms controlling bacterial growth, shape development, and adaptive response to antibiotics. Bacterial growth and shapes are determined by the cell wall, a rigid protein-based structure that can withstand high amounts of osmotic pressure while driving cell elongation. An outstanding challenge is to relate alterations in physical properties of the cell wall to adaptive shape changes and fitness control in bacteria. This is important for understanding how bacteria can recover their fitness for growth and division under antibiotic treatment that inhibit the cell wall growth machinery. We seek to address this challenge by proposing a novel framework in which theoretical modelling and experimental data are integrated to dissect how protein synthesis and stochastic cell cycle processes control robust growth and adaptive behaviour in single bacterial cells.Using tools from statistical mechanics and soft matter physics, we will develop a quantitative model for growing cell wall structures that is coupled to stochastic decision-making processes for cell size and division control. We will extend this model to dissect how single bacterial cells harness the feedback between mechanical forces and biochemical reactions to adapt to growth inhibitory stresses. In particular, we will dissect the mechanisms of fitness recovery in rod-shaped bacterium under ribosome-targeting antibiotics that constitute a major class of clinically used antibacterial drugs. We will compare the theoretical model predictions against high-throughput experimental measurements of single bacterial shape and growth in normal and antibiotic-treated conditions. This integrated approach will allow us to determine the physical principles relating the speed and the accuracy of antibiotic adaptation to the energy consumption budget of a cell. The outcome of this research will fundamentally advance our understanding of non-equilibrium physics of living systems by establishing a cost-performance tradeoff relation in adaptive biophysical processes. Furthermore we will directly address the physical impacts of antibacterial drugs on bacterial fitness at the single-cell level, which will have wide ranging implications for the development and design of new drugs that can effectively control the evolution of antibiotic resistance.