Laboratoire de Physique et Mécanique des Milieux Hétérogènes, PMMH, ESPCI Paris, PSL University, CNRS, Sorbonne Université, Université de Paris, 75005 Paris, France.
Department of Biomedical Engineering, The Pennsylvania State University, PA 16802, USA.
Sci Adv. 2020 Mar 13;6(11):eaay0155. doi: 10.1126/sciadv.aay0155. eCollection 2020 Mar.
One notable feature of bacterial motion is their ability to swim upstream along corners and crevices, by leveraging hydrodynamic interactions. This motion through anatomic ducts or medical devices might be at the origin of serious infections. However, it remains unclear how bacteria can maintain persistent upstream motion while exhibiting run-and-tumble dynamics. Here, we demonstrate that can travel upstream in microfluidic devices over distances of 15 mm in times as short as 15 min. Using a stochastic model relating the run times to the time that bacteria spend on surfaces, we quantitatively reproduce the evolution of the contamination profiles when considering a broad distribution of run times. The experimental data cannot be reproduced using the usually accepted exponential distribution of run times. Our study demonstrates that the run-and-tumble statistics determine macroscopic bacterial transport properties. This effect, which we name "super-contamination," could explain the fast onset of some life-threatening medical emergencies.
细菌运动的一个显著特点是，它们能够通过水动力相互作用在拐角和缝隙处逆流而上。这种在解剖管道或医疗设备中的运动可能是导致严重感染的原因。然而，目前尚不清楚细菌如何在表现出随机游走动态的同时保持持续的逆流运动。在这里，我们证明了 可以在微流控设备中逆流而上，在 15 分钟内行进 15 毫米的距离。使用一个将运行时间与细菌在表面上停留的时间相关联的随机模型，我们定量地再现了在考虑广泛的运行时间分布时污染分布的演变。实验数据不能用通常接受的运行时间的指数分布来再现。我们的研究表明，随机游走的统计数据决定了细菌的宏观输运特性。这种我们称之为“超级污染”的效应可能解释了一些危及生命的医疗紧急情况的快速发生。
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