CAREER: Mathematical Framework for Elucidating Mechanics at Immune Cell Interfaces

职业：阐明免疫细胞界面力学的数学框架

• 批准号: 1454739
• 负责人: Jun Allard
• 金额: $ 46.94万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1454739&HistoricalAwards=false
• 关键词: CAREER; Mathematical; Framework; Elucidating; Mechanics

In many biological processes, two or more cells come into physical contact to form a cell-cell interface. Examples in humans include wound healing, tissue development, tumor growth, and some bioengineered diagnostic tools. Experiments have shown that molecules in cell-cell interfaces experience forces (squeezing, pulling) and that these forces influence cell behavior and cellular decision-making. One important example is offered by immune cells, which must attach to the surface of other cells in order to decipher information about disease. Their nanometer size and inaccessible geometry make cell-cell interfaces challenging to explore experimentally. The investigator will develop mathematical equations that predict forces on molecules at cell-cell interfaces, using immune cells as a prototype. Results will have direct implications for understanding immune function, impacting research on autoimmune disease and immunotherapy. Additionally, these mathematical models can be readily generalized to abstract, generic cell-cell interfaces, thereby highlighting the biophysical similarities between biologically disparate systems to help understand the general principles of the cellular tactile sense. In coordination with his research goals, the investigator has an educational goal of using cell mechanics (i.e., forces in cells) as a venue to teach mathematics, biology and physics with tangible, accessible examples to audiences in K-12, undergraduate, graduate and general public education. Unlike cell biology based on biochemistry or genetics, many cell-mechanical phenomena have direct analogies with everyday life that are useful in establishing a three-way correspondence between cell phenomena, everyday intuition of mechanical forces, and their mathematical representation.Of many ways in which cells interact, an increasingly recognized interaction is through the establishment of transient, dynamic cell-cell interfaces. The investigator will develop mathematical models of cell-cell interfaces to describe and predict mechanical forces and their influence on cell signaling. The dynamics at cell-cell interfaces involve an interplay between transport, mechanics and chemical kinetics, and play out over a range of length- and time-scales, necessitating a combination of mathematical techniques: Coupled systems of elliptic, parabolic and stochastic differential equations; computational fluid dynamics of fluid-structure interactions including thermal fluctuations in 3D; Brownian dynamics; and Bayesian statistics to leverage quantitative experimental data from the investigator's collaborators. Specific aims of the investigator through this research are to: (1) Understand how cells overcome and exploit the physical constraints to cell-cell contact, by developing a model that integrates motion of the intracellular and extracellular fluid, Brownian motion of molecules embedded in the cells' membranes, and active forces. (2) Explore the mechanism and evolutionary advantages of molecular clustering at interfaces to address the large class of molecules that aggregate into clusters containing tens to hundreds of molecules. (3) develop, validate and use mesoscale models of large flexible biomolecules to decipher their mechanical properties and biological role. In mesoscale models, individual molecules are represented as combinations of rigid bodies such as rods, spheres and semi-flexible joints undergoing Langevin dynamics. The biological novelty lies in new hypotheses that will emerge from the models, including the hypothesis that within-cluster load sharing can allow for nontrivial kinetics, such as co-operativity, multi-stability and ultra-sensitivity - regulatory modules that have classically been assumed to arise from biochemical reaction networks. The mesoscale models will allow us to access timescales that all-atom molecular dynamics cannot, while capturing details that particle-based simulations miss. Students at all educational levels will gain exposure to contemporary work at the interface of mathematics, biology and physics.

在许多生物过程中，两个或更多个细胞发生物理接触以形成细胞-细胞界面。人类的例子包括伤口愈合、组织发育、肿瘤生长和一些生物工程诊断工具。实验表明，细胞-细胞界面中的分子会受到力（挤压，拉动），这些力会影响细胞行为和细胞决策。一个重要的例子是免疫细胞，它必须附着在其他细胞的表面，以破译有关疾病的信息。它们的纳米尺寸和难以接近的几何形状使得细胞-细胞界面在实验上具有挑战性。研究人员将开发数学方程，以免疫细胞为原型，预测细胞-细胞界面上分子的作用力。结果将对理解免疫功能，影响自身免疫性疾病和免疫治疗的研究产生直接影响。此外，这些数学模型可以很容易地推广到抽象的，通用的细胞-细胞界面，从而突出了生物学上不同的系统之间的生物物理相似性，以帮助理解细胞触觉的一般原理。与他的研究目标相协调，研究者有一个使用细胞力学的教育目标（即，细胞中的力量）作为一个场地，教数学，生物学和物理与有形的，可访问的例子，观众在K-12，本科生，研究生和一般公共教育。与基于生物化学或遗传学的细胞生物学不同，许多细胞力学现象与日常生活有直接的类比，这有助于在细胞现象、对机械力的日常直觉和它们的数学表示之间建立三种方式的对应关系。在细胞相互作用的许多方式中，越来越多地认识到的相互作用是通过建立瞬时的、动态的细胞-细胞界面。研究人员将开发细胞-细胞界面的数学模型，以描述和预测机械力及其对细胞信号传导的影响。细胞-细胞界面的动力学涉及运输，力学和化学动力学之间的相互作用，并在一系列长度和时间尺度上发挥作用，需要数学技术的组合：椭圆，抛物和随机微分方程的耦合系统;流体-结构相互作用的计算流体动力学，包括3D中的热波动;布朗动力学;和贝叶斯统计，以利用定量的实验数据，从研究者的合作者。研究者通过本研究的具体目的是：（1）通过开发整合细胞内和细胞外液的运动、嵌入细胞膜中的分子的布朗运动和主动力的模型，了解细胞如何克服和利用细胞-细胞接触的物理约束。(2)探索分子在界面上聚集的机制和进化优势，以解决聚集成包含数十至数百个分子的簇的大类分子。 (3)开发、验证和使用大型柔性生物分子的中尺度模型，以破译其机械特性和生物作用。在介观尺度模型中，单个分子被表示为经历朗之万动力学的刚性体（例如杆、球和半柔性接头）的组合。生物学的新奇在于新的假设，将出现从模型，包括假设内集群负载共享可以允许非平凡的动力学，如协同性，多稳定性和超灵敏度调节模块，已被经典地假定为从生化反应网络。中尺度模型将使我们能够访问全原子分子动力学无法访问的时间尺度，同时捕获基于粒子的模拟错过的细节。所有教育水平的学生都将接触到数学，生物学和物理学界面的当代工作。