Mathematical modeling of spatiotemporal and mechanical processes in cellular functions

细胞功能时空和机械过程的数学建模

• 批准号: 10028816
• 负责人: Jing Chen
• 金额: $ 37.32万
• 依托单位: VIRGINIA POLYTECHNIC INST AND ST UNIV
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10028816
• 关键词: Address; Area; Bayesian Analysis; Biochemical; Biochemical Pathway; Biological; Cell model; Cell physiology; Cells; Cellular biology; Centrosome; Chemistry; Chromosome Segregation; Chromosomes; Clostridium perfringens; Complex; Coupling; Data; Feedback; Functional disorder; Future; Health; Individual; Knowledge; Laboratories; Laws; Malignant Neoplasms; Mechanics; Methodology; Methods; Microbial Biofilms; Mitosis; Mitotic spindle; Modeling; Molecular; Myxococcus xanthus; Physics; Process; Regulatory Pathway; Research; Role; Signal Transduction; Technology; Therapeutic Agents; antimicrobial; base; cancer therapy; cell motility; driving force; experience; experimental study; heterogenous data; innovation; mathematical model; microbial community; novel; spatiotemporal; tool

Project Summary The PI’s laboratory focuses on mathematical modeling of spatiotemporal and mechanical processes in living cells, as well as their coupling to biochemical regulatory pathways. Although critical for many cellular functions, spatiotemporal and mechanical processes remain poorly understood. Experimentally, it is yet impossible to simultaneously track the spatiotemporal and mechanical dynamics of multiple molecular species involved in complex cellular functions, which hinders coherent mechanistic understanding. Mathematical modeling presents a powerful tool that can integrate heterogeneous data with basic laws of physics and chemistry, propose coherent mechanistic frameworks, and guide new experiments. Due to many strong physical constraints, modeling the spatiotemporal and mechanical dynamics in a cell can be more tractable than modeling the complex signaling networks, and can provide a central framework to which additional biological details can be gradually added. Equipped with her rich experience in modeling cellular spatiotemporal and mechanical dynamics and their feedback with biochemical signaling, the PI will focus her research over the next five years on several topics in two areas of cell biology that involve salient spatiotemporal and mechanical dynamics. The first area is mitotic spindle assembly and chromosome segregation. The PI’s research in this area will elucidate how the spatiotemporal, mechanical and biochemical dynamics interplay to achieve proper spindle assembly and faithful chromosome segregation. The research will particularly focus on the cellular mechanisms behind centrosome clustering and chromosome oscillation. The proper execution of these mechanisms and their dysfunction have strong implications in cancer. Hence, knowledge to be obtained from this study will illuminate future innovations in cancer therapy. The second area is bacterial motility and control. The PI’s research in this area will tackle how bacterial motility is driven, regulated and coordinated, processes that are critical for formation and organization of microbial communities like biofilms. The research will focus on two novel gliding motilities found in Myxococcus xanthus and Clostridium perfringens. Both motilities involve intriguing intercellular interactions, either for coordinating motility between individual cells, or for supplying the driving force. Knowledge to be generated by the study will stimulate future health-related innovations, such as novel antimicrobial treatments and bacterial therapeutic agents. Last but not least, the PI will develop new methodology to address the challenge of comparing traditional, physics-based models with noisy data obtained through the latest experimental technologies. Particularly, she will introduce Bayesian inference to her modeling research and streamline the methodology for the data and models in the specific research topics. These methods will be transferable to other research in the field of quantitative cell biology where similar challenges in model-data comparison arise.

项目概要 PI 的实验室专注于生活中时空和机械过程的数学建模 细胞，以及它们与生化调节途径的耦合。尽管对于许多细胞功能至关重要， 时空和机械过程仍然知之甚少。实验上目前还不可能 同时跟踪参与的多个分子种类的时空和机械动力学 复杂的细胞功能，阻碍了连贯的机制理解。数学建模呈现 一个强大的工具，可以将异构数据与物理和化学的基本定律相结合，提出一致的 机制框架，并指导新的实验。由于许多强大的物理约束，建模 细胞中的时空和机械动力学比模拟复杂的信号传导更容易处理 网络，并且可以提供一个中央框架，可以逐渐添加额外的生物学细节。 拥有丰富的细胞时空和机械动力学及其建模经验 通过生物化学信号反馈，PI 将在未来五年将她的研究重点集中在以下几个主题上： 细胞生物学的两个领域涉及显着的时空动力学和机械动力学。第一个区域是有丝分裂 纺锤体组装和染色体分离。 PI 在该领域的研究将阐明如何 时空、机械和生化动力学相互作用，以实现正确的主轴组装和忠实 染色体分离。该研究将特别关注中心体背后的细胞机制 聚类和染色体振荡。这些机制的正确执行及其功能障碍 对癌症有很强的影响。因此，从这项研究中获得的知识将照亮未来的创新 在癌症治疗中。第二个领域是细菌的运动和控制。 PI 在该领域的研究将解决如何 细菌的运动受到驱动、调节和协调，这些过程对于形成和组织至关重要 微生物群落，如生物膜。该研究将重点关注粘球菌中发现的两种新型滑动运动 xanthus 和产气荚膜梭菌。这两种运动都涉及有趣的细胞间相互作用，要么是为了 协调单个细胞之间的运动，或提供驱动力。知识生成 该研究将刺激未来与健康相关的创新，例如新型抗菌疗法和细菌疗法 治疗剂。最后但并非最不重要的一点是，PI 将开发新的方法来应对挑战 将传统的基于物理的模型与通过最新实验获得的噪声数据进行比较 技术。特别是，她将把贝叶斯推理引入她的建模研究并简化 特定研究主题中的数据和模型的方法论。这些方法可以移植到其他地方 定量细胞生物学领域的研究在模型数据比较方面出现了类似的挑战。