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Collaborative Research: Elucidating the Diversity of Bacterial Flagellation and Motility Through Mechanics

合作研究：通过力学阐明细菌鞭毛和运动的多样性

基本信息

批准号：
2027410
负责人：
Jeffrey Guasto
金额：
$ 31.25万
依托单位：
Tufts University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-01-01 至 2024-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2027410&HistoricalAwards=false
关键词：
Collaborative Research Elucidating Diversity Bacterial

项目摘要

The ability of bacteria to swim crucial to survival. Swimming is made possible by rotating thin filaments called flagella. There are many different ways that flagella are arranged on bacteria, and many different movement patterns, all of which enable swimming. Despite the success of bacteria swimming, few of these mechanisms are well understood. The objective of this project is to determine how the arrangements and flexible mechanics of flagella combine to produce differences in bacterial motility. The results of this project will have numerous potential societal impacts, since motility enables bacteria to spread through water supplies, and to establish microbiomes or infections in humans. This work will have important effects at multiple levels. At the cellular level, better understanding bacterial motility will help us understand cell resource uptake. At the ecosystem scale, motility affects the food web. The results of this work could lead to new approaches to mediate bacterial infection, further our understanding of bacterial evolution, and inspire biomimetic microrobots with enhanced functionality. In addition, the award will support outreach programs that teach the public about bacterial locomotion and its importance to society through health and ecology.Bacterial flagellar motility has largely been relegated to two idealized paradigms for uni- and multiflagellated cells, respectively. However, mounting evidence suggests that bacteria exhibit a plethora of flagellar arrangements and associated motility patterns that do not fit into the existing paradigms. It is not understood how flagellar motility patterns emerge from variations in arrangements and the flexible mechanics of flagella. This work will develop a mechanistic understanding of the vast understudied diversity of flagellar arrangements and motility patterns by linking them to the geometry and mechanics of flagella. This biomechanical understanding has been hindered by a lack of quantitative imaging of flagella, limited ability to experimentally perturb flagellar properties, and overly simplified models. We will overcome these challenges by using unique imaging capabilities, which enable data-driven and experimentally validated numerical modeling and hypothesis testing. Experimentally, this work incorporates advanced high-speed video microscopy techniques to capture the time-resolved kinematics of 10-nanometer diameter flagella, pushing the envelope of existing quantification methods for fluid-structure interactions. Numerically, this work advances the state-of-the-art in modeling elastohydrodynamics of actuated filaments. This work will establish a unique data set comprising the mechanical properties of flagella and the kinematics of bacterial motility from diverse species. It will use modeling to determine the physical mechanisms leading to observed motility patterns, and combine physical and numerical experiments to elucidate and classify the originsThis 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.

细菌的游泳能力对生存至关重要。游泳是通过旋转称为鞭毛的细丝实现的。鞭毛在细菌上有许多不同的排列方式，以及许多不同的运动模式，所有这些都使游泳成为可能。尽管细菌游泳的成功，这些机制很少被很好地理解。本项目的目的是确定鞭毛联合收割机的排列和灵活机制如何结合以产生细菌运动性的差异。该项目的结果将产生许多潜在的社会影响，因为能动性使细菌能够通过供水传播，并在人类中建立微生物组或感染。这项工作将在多个层面产生重要影响。在细胞水平上，更好地了解细菌的运动性将有助于我们了解细胞资源的摄取。在生态系统尺度上，能动性影响着食物网。这项工作的结果可能会导致新的方法来介导细菌感染，进一步了解细菌进化，并激发具有增强功能的仿生微型机器人。此外，该奖项将支持外展计划，教导公众有关细菌运动及其对社会的重要性，通过健康和生态。细菌鞭毛运动在很大程度上已降级到两个理想化的范式为单和多鞭毛细胞，分别。然而，越来越多的证据表明，细菌表现出过多的鞭毛排列和相关的运动模式，不适合现有的范例。目前还不清楚鞭毛运动模式是如何从鞭毛的排列和灵活机制的变化中出现的。这项工作将开发一个机械的理解巨大的未充分研究的多样性鞭毛的安排和运动模式，将它们连接到鞭毛的几何形状和力学。这种生物力学的理解受到了阻碍，缺乏定量成像的鞭毛，有限的能力，实验扰动鞭毛的性质，和过于简化的模型。我们将通过使用独特的成像功能来克服这些挑战，这些功能可以实现数据驱动和实验验证的数值建模和假设检验。在实验上，这项工作采用了先进的高速视频显微镜技术来捕获10纳米直径鞭毛的时间分辨运动学，推动了现有流体-结构相互作用量化方法的极限。数值上，这项工作的先进国家的最先进的驱动细丝的弹性流体动力学建模。这项工作将建立一个独特的数据集，包括鞭毛的机械性能和不同物种的细菌运动的运动学。它将使用建模来确定导致观察到的运动模式的物理机制，并结合联合收割机物理和数值实验来阐明和分类的originsThis奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。