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: 10237345
• 负责人: Jing Chen
• 金额: $ 37.08万
• 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/10237345
• 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.

项目摘要 PI的实验室着重于生活中空间时间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，但 时空和机械过程的理解还不足。在实验上，仍然不可能 类似地跟踪与 复杂的细胞功能，阻碍了连贯的机械理解。数学建模礼物 一个强大的工具，可以将异质数据与物理和化学的基本定律整合在一起，提案相干 机械框架，并指导新实验。由于许多强大的身体约束，建模 细胞中的时空和机械动力学比对复杂信号进行建模更容易理解 网络，可以提供一个中心框架，可以逐渐添加其他生物学细节。 配备了她丰富的经验，用于建模细胞时空和机械动力学及其 使用生化信号的反馈，PI将在未来五年内将研究重点放在几个主题上 细胞生物学的两个领域，涉及显着的空间时间和机械动力学。第一个区域是有丝分裂的 主轴组件和染色体分离。 PI在这一领域的研究将阐明 时空，机械和生化动力学相互作用，以实现适当的主轴组件和忠实 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。这些机制及其功能障碍的适当执行具有 对癌症的强烈影响。因此，从这项研究中获得的知识将阐明未来的创新 在癌症治疗中。第二个区域是细菌的运动和对照。 PI在该领域的研究将解决如何解决 细菌运动的驱动，调节和协调，这对于形成和组织至关重要 像生物膜这样的微生物群落。该研究将重点介绍两个新颖的滑行运动，在粘液中发现 黄牙和灌注梭状芽胞杆菌。这两种运动都涉及有趣的细胞间相互作用，要么 协调单个细胞之间或提供驱动力之间的运动。知识将由 该研究将刺激未来与健康相关的创新，例如新型抗菌治疗和细菌 治疗剂。最后但并非最不重要的一点是，PI将开发新方法来应对的挑战 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，她将向她的建模研究和简化贝叶斯的推断介绍 特定研究主题中数据和模型的方法。这些方法将转移到其他 定量细胞生物学领域的研究，在模型数据比较中存在类似的挑战。