Elucidating the dynamic characteristics of antigen recognition

细胞利用表面受体来感知周围环境。传感依赖于受体对分子的识别。识别的有效性通常在稳定状态下在单个受体和它们的结合分子之间测量。然而，新的实验表明，免疫系统所必需的细胞可以通过触觉以高度动态和集体的方式探测其抗原受体的结合质量（即，既不处于稳态也不使用独立受体）。奇怪的是，通过形成短暂的细胞-细胞接触，免疫细胞将受体结合的抗原聚集成簇，并利用细胞内产生的拉力将它们提取出来。PI旨在研究细胞主动物理感知的功能影响、设计和控制。通过理论和实验之间的密切协同作用，拟议的研究将阐明抗原识别动态特征背后的物理原理，推进我们对细胞间相互作用信息传递的理解，并揭示主动传感可能带来的适应性益处。该项目的更广泛的影响在于教育和推广活动与研究计划的紧密结合，使各级学生参与物理学在细胞动力学，功能和适应中的作用。PI将开发基于网络的学习模块，以加深对膜介导的相互作用以及分子协同性和拮抗性起源的理解。她将扩展一门新课程，教授信息和控制理论的要素，并将其应用于生物学中的传感和动态适应。PI将继续在她的实验室提供真实的研究经验，通过加州大学洛杉矶分校的计算和系统生物学项目担任教师导师。 不同的淋巴细胞表达独特的表面受体共同工作，以识别无数的和不断变化的微观实体入侵一个活的有机体。有效的保护依赖于表达高亲和力抗原受体的免疫细胞的阳性选择。然而，这种选择过程似乎令人惊讶地无效，并且达到了比预期低得多的结合亲和力的适度上限。实验数据已经开始揭示，免疫识别远远超出了平衡受体-抗原结合;相反，细胞施加收缩力以主动从抗原呈递细胞提取抗原。PI假设选择的明显无效性不是由于不可避免的随机性造成的人为因素，而是抗原识别的非平衡性质的直接后果。她建议通过建立从分子识别到生物体反应的映射，通过细胞动力学和主动力的使用来探索解释。该项目将侧重于（a）确定细胞如何以及为什么在抗原识别过程中产生和维持多灶接触模式;（B）检查物理提取抗原在宽动态范围内实现亲和力识别的能力;以及（c）确定信息边界并发现优化竞争功能的细胞策略。数学和计算建模将与体外和体内实验相结合，以澄清抗原识别的非平衡性质和动态特性的功能后果，并访问细胞是否以及如何利用物理获得的信息来指导适应。虽然生物化学回路在实现免疫识别的显著特异性和敏感性方面的作用已被广泛探索，但这项关于天然环境中免疫细胞物理动力学的研究是对该领域大多数正在进行的工作的补充，该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的学术价值和更广泛的影响评审标准。

Cells use surface receptors to sense their surroundings. Sensing relies on recognition of molecules by receptors. Effectiveness of recognition is routinely measured at steady state between single receptors and their bound molecules. However, new experiments showed that cells essential for the immune system may probe the binding quality of their antigen receptors in a highly dynamic and collective manner via tactile senses (i.e., neither at steady state nor using independent receptors). Curiously, by forming transient cell-cell contact, immune cells collect receptor-bound antigens into clusters and extract them using pulling forces generated inside the cell. The PI aims to investigate the functional impacts, design, and control of active, physical sensing of cells. Through a close synergy between theory and experiment, the proposed research will elucidate the physical principles behind the dynamic characteristics of antigen recognition, advance our understanding of information transfer via cell-cell interaction, and uncover adaptive benefit that active sensing might confer. Broader impacts of the project lie in a close integration of education and outreach activities with the research program, to engage students at all levels with the role of physics in cellular dynamics, function, and adaptation. The PI will develop web-based learning modules to deepen the understanding of membrane-mediated interactions and the origin of molecular cooperativity and antagonism. She will expand on a new course to teach the elements of information and control theory with applications to sensing and dynamic adaptation in biology. The PI will continue to provide authentic research experiences in her lab by serving as a faculty mentor through the Computational and Systems Biology program at UCLA. Diverse lymphocytes expressing unique surface receptors work collectively to recognize myriad and changing microscopic entities invading a living organism. Potent protection relies on positive selection of immune cells expressing high-affinity antigen receptors. However, this process of selection appears surprisingly ineffective and hits a modest ceiling of binding affinity much lower than expected. Experimental data have started to reveal that immune recognition is far beyond equilibrium receptor-antigen binding; instead, cells exert contractile forces to actively extract antigen from antigen-presenting cells. The PI hypothesizes that the apparent ineffectiveness of selection is not an artifact due to unavoidable randomness, but rather, can be a direct consequence of the non-equilibrium nature of antigen recognition. She proposes to explore an explanation by establishing a mapping from molecular recognition to organismal responses via cellular dynamics and active force usage. This project will focus on (a) determining how and why cells create and maintain a multifocal contact pattern during antigen recognition; (b) examining the capacity of physical extraction of antigen in achieving affinity discrimination over a broad dynamic range; and (c) identifying information bounds and discovering cellular strategies to optimize competing functions. Mathematical and computational modeling will be combined with in vitro and in vivo experiments to clarify the functional consequences of the nonequilibrium nature and dynamic characteristics of antigen recognition, and to access whether and how cells can utilize physically acquired information to guide adaptation. While the role of biochemical circuitry in achieving the remarkable specificity and sensitivity of immune recognition has been extensively explored, this research on physical dynamics of immune cells in native environment is complementary to most ongoing work in the field, and could uncover unexpected functional objectives of active sensing by cells.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.