Collaborative Research: Experiments and Modeling of the Fluid Flow of Beating Eukaryotic Flagella

鞭毛和纤毛是纤毛状的细胞结构，在许多基本的生命过程中起着重要的作用。鞭毛和纤毛通过有节奏的跳动，在细胞的局部环境中移动液体。例如，这种生物功能使呼吸道中的肺粘液清除和卵子从卵巢到子宫的运输成为可能。鞭毛和纤毛的功能障碍可导致一组严重的人类疾病，纤毛病，给社会造成沉重的经济和疾病负担。然而，尽管鞭毛和纤毛的普遍存在和重要性，但鞭毛和纤毛的液体运输的基本生物力学仍然知之甚少。特别是鞭毛和纤毛跳动引起的详细流场仍未得到解决。将最先进的显微镜技术与数据驱动的机器学习相结合，研究团队旨在解决这一困难的生物力学问题。本研究将利用协同实验和数值模拟的方法研究健康鞭毛以及与纤毛病相关的突变鞭毛的流场。研究一种潜在的解决方案，以弥补功能障碍鞭毛的流动不足。除了为本科生和研究生提供培训和研究机会外，该计划还将制作吸引人的科学视频和演示，以加强本科生的课程，并丰富两位主要研究人员在当地社区的外展活动。莱茵衣藻（Chlamydomonas reinhardtii）是绿藻鞭毛和纤毛形态和动力学的通用模型，本项目将对其进行研究。光学显微镜将用于跟踪三维（3D）流体流动周围跳动的鞭毛的单个藻类在微米尺度与亚毫秒的时间分辨率。将对不同游泳方式的野生型和突变型藻类进行研究。基于三维流场分析鞭毛动力学的力学效率。此外，利用实验流场作为参考基础，并利用现代机器学习算法，该团队计划开发一个最简单的数值模型，可以定量捕获藻类流。该模型将有助于研究鞭毛动力学和藻悬液集体动力学的优化和同步。通过协作实验和建模工作，本研究将揭示鞭毛动力学与由此产生的微观流体流动之间缺失的环节。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Flagella and cilia are thin hair-like cellular structures which play an essential role in many basic life processes. By beating rhythmically, flagella and cilia move fluid in the local environment of cells. This biological function enables pulmonary mucus clearance in airways and the transport of ovums from the ovary to the uterus for example. Malfunction of flagella and cilia can lead to a group of serious human disorders, ciliopathies, which cause a heavy economic and disease burden on society. However, despite the ubiquity and importance of flagella and cilia, fundamental biomechanics underlying the fluid transport of beating flagella and cilia are still poorly understood. Particularly, the detailed flow field induced by beating flagella and cilia remains unresolved. Combining state-of-the-art microscopy techniques with data-driven machine learning, the research team aims to address this difficult biomechanical problem. This research will investigate the flow field of healthy flagella as well as those of mutant flagella associated with ciliopathies using synergistic experimental and numerical modeling efforts. A potential solution to remedy the flow deficiency of malfunction flagella will be researched. In addition to the training and research opportunities for undergraduate and graduate students, the project will produce appealing scientific videos and demonstrations to enhance the undergraduate curriculum and enrich outreach activities at the local communities of the two principal investigators. As a generic model for the morphology and dynamics of flagella and cilia, green algae Chlamydomonas reinhardtii, will be studied in this research program. Optical microscopy will be used to track the three-dimensional (3D) fluid flow around the beating flagella of a single alga at micron scales with sub-millisecond temporal resolutions. Both wild-type and mutant algae of different swimming modes will be investigated. The mechanical efficiency of flagellar dynamics will be analyzed based on the 3D flow field. Moreover, using the experimental flow field as a basis of reference and taking advantage of modern machine-learning algorithms, the team plans to develop a numerical model of maximal simplicity that can quantitatively capture the algal flow. The model will facilitate the study of the optimization and synchronization of flagellar dynamics and the collective dynamics of algal suspensions. Through the collaborative experimental and modeling efforts, the missing link between the flagellar dynamics and the resulting microscopic fluid flow will be revealed by this research.This 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.