Department of Mathematics, University of Maryland College Park, College Park, Maryland, USA.
Graduate Program in Applied Mathematics & Statistics, and Scientific Computation, University of Maryland College Park, College Park, Maryland, USA.
mBio. 2019 May 28;10(3):e00972-19. doi: 10.1128/mBio.00972-19.
Quorum sensing (QS) enables coordinated, population-wide behavior. QS-active bacteria "communicate" their number density using autoinducers which they synthesize, collect, and interpret. Tangentially, chemotactic bacteria migrate, seeking out nutrients and other molecules. It has long been hypothesized that bacterial behaviors, such as chemotaxis, were the primordial progenitors of complex behaviors of higher-order organisms. Recently, QS was linked to chemotaxis, yet the notion that these behaviors can together contribute to higher-order behaviors has not been shown. Here, we mathematically link flocking behavior, commonly observed in fish and birds, to bacterial chemotaxis and QS by constructing a phenomenological model of population-scale QS-mediated phenomena. Specifically, we recast a previously developed mathematical model of flocking and found that simulated bacterial behaviors aligned well with well-known QS behaviors. This relatively simple system of ordinary differential equations affords analytical analysis of asymptotic behavior and describes cell position and velocity, QS-mediated protein expression, and the surrounding concentrations of an autoinducer. Further, heuristic explorations of the model revealed that the emergence of "migratory" subpopulations occurs only when chemotaxis is directly linked to QS. That is, behaviors were simulated when chemotaxis was coupled to QS and when not. When coupled, the bacterial flocking model predicts the formation of two distinct groups of cells migrating at different speeds in their journey toward an attractant. This is qualitatively similar to phenomena spotted in our chemotaxis experiments as well as in analogous work observed over 50 years ago. Our modeling efforts show how cell density can affect chemotaxis; they help to explain the roots of subgroup formation in bacterial populations. Our work also reinforces the notion that bacterial mechanisms are at times exhibited in higher-order organisms.
群体感应（QS）使细菌能够协调一致地进行群体行为。QS 活性细菌使用它们合成、收集和解释的自诱导物来“交流”它们的密度。顺便说一句，趋化性细菌会迁移，寻找营养物质和其他分子。长期以来，人们一直假设细菌的行为，如趋化性，是高等生物复杂行为的原始祖先。最近，QS 与趋化性相关联，但这些行为是否可以共同促成更高层次的行为尚未得到证明。在这里，我们通过构建一种基于群体规模 QS 介导现象的现象学模型，将鱼类和鸟类中常见的群集行为与细菌趋化性和 QS 联系起来。具体来说，我们重新制定了一个以前开发的群集数学模型，发现模拟的细菌行为与众所周知的 QS 行为非常吻合。这个相对简单的常微分方程组系统提供了对渐近行为的分析，并描述了细胞位置和速度、QS 介导的蛋白质表达以及自诱导物的周围浓度。此外，对模型的启发式探索表明，只有当趋化性直接与 QS 相关联时，才会出现“迁移”亚群。也就是说，当趋化性与 QS 耦合时和不耦合时进行了模拟。当耦合时，细菌群集模型预测会形成两个不同的细胞群体，以不同的速度向吸引物迁移。这与我们在趋化性实验中观察到的现象以及 50 多年前观察到的类似工作的现象在定性上是相似的。我们的建模工作表明细胞密度如何影响趋化性；它们有助于解释细菌群体中亚群形成的根源。我们的工作还强化了这样一种观点，即细菌机制有时会在高等生物中表现出来。
