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

鞭毛和纤毛是细的毛发状细胞结构，在许多基本生命过程中起着重要作用。通过有节奏地跳动，鞭毛和纤毛在细胞的局部环境中移动液体。这种生物学功能使肺粘液在气道中清除，并将卵子从卵巢运输到子宫。鞭毛和纤毛的功能异常可导致一组严重的人类疾病，即纤毛病，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性和重要性，基本的生物力学基础的流体运输殴打鞭毛和纤毛仍然知之甚少。特别是，详细的流场诱导殴打鞭毛和纤毛仍然没有得到解决。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。本研究将探讨健康鞭毛的流场，以及与纤毛疾病相关的突变鞭毛使用协同实验和数值模拟的努力。一个潜在的解决方案，以弥补流量不足的故障鞭毛将研究。除了为本科生和研究生提供培训和研究机会外，该项目还将制作有吸引力的科学视频和演示，以加强本科生课程，丰富两位主要调查员在当地社区的外联活动。 作为鞭毛和纤毛的形态和动力学的通用模型，绿色藻类莱茵衣藻，将在本研究计划中进行研究。光学显微镜将被用来跟踪三维（3D）流体流动周围的跳动鞭毛的一个单一的微尺度与亚毫秒的时间分辨率。本研究将探讨不同游动模式的野生型及突变藻。基于三维流场分析鞭毛动力学的机械效率。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。该模型将有助于鞭毛动力学和藻类悬浮液集体动力学的优化和同步研究。通过合作实验和建模的努力，鞭毛动力学和由此产生的微观流体流动之间的缺失环节将被揭示由本research.This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。

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.