Research Project
10237345
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.
