IBM T. J. Watson Research Center, Yorktown Heights, New York, United States of America.
PLoS Comput Biol. 2014 Jun 19;10(6):e1003672. doi: 10.1371/journal.pcbi.1003672. eCollection 2014 Jun.
Navigation of cells to the optimal environmental condition is critical for their survival and growth. Escherichia coli cells, for example, can detect various chemicals and move up or down those chemical gradients (i.e., chemotaxis). Using the same signaling machinery, they can also sense other external factors such as pH and temperature and navigate from both sides toward some intermediate levels of those stimuli. This mode of precision sensing is more sophisticated than the (unidirectional) chemotaxis strategy and requires distinctive molecular mechanisms to encode and track the preferred external conditions. To systematically study these different bacterial taxis behaviors, we develop a continuum model that incorporates microscopic signaling events in single cells into macroscopic population dynamics. A simple theoretical result is obtained for the steady state cell distribution in general. In particular, we find the cell distribution is controlled by the intracellular sensory dynamics as well as the dependence of the cells' speed on external factors. The model is verified by available experimental data in various taxis behaviors (including bacterial chemotaxis, pH taxis, and thermotaxis), and it also leads to predictions that can be tested by future experiments. Our analysis help reveal the key conditions/mechanisms for bacterial precision-sensing behaviors and directly connects the cellular taxis performances with the underlying molecular parameters. It provides a unified framework to study bacterial navigation in complex environments with chemical and non-chemical stimuli.
细胞向最佳环境条件的导航对于其生存和生长至关重要。例如，大肠杆菌细胞可以检测到各种化学物质，并在这些化学梯度上向上或向下移动（即趋化性）。利用相同的信号机制，它们还可以感知其他外部因素，如 pH 值和温度，并从两侧向这些刺激物的中间水平移动。这种精确感应模式比（单向）趋化性策略更为复杂，需要独特的分子机制来编码和跟踪首选的外部条件。为了系统地研究这些不同的细菌趋性行为，我们开发了一个连续统模型，将单细胞中的微观信号事件纳入宏观群体动力学中。我们得到了一个简单的理论结果，用于一般的稳态细胞分布。特别是，我们发现细胞分布受细胞内传感器动态以及细胞速度对外界因素的依赖性控制。该模型通过各种趋性行为（包括细菌趋化性、pH 趋化性和热趋化性）的现有实验数据进行了验证，并且还提出了可以通过未来实验进行检验的预测。我们的分析有助于揭示细菌精密感应行为的关键条件/机制，并将细胞趋性表现与潜在的分子参数直接联系起来。它提供了一个统一的框架，用于研究具有化学和非化学刺激的复杂环境中的细菌导航。
