Computational models of eukaryotic cell polarization/motility

细胞运动性在真核生物的发育、免疫监视和伤口愈合中具有根本的重要性。它还在癌症转移中起着邪恶的作用。肌动蛋白细胞骨架，它塑造细胞和驱动的伸缩运动是由多层信号通路调节。激发我研究的一个焦点问题是这些信号分子的时空动力学是如何协调的，以及这些分子如何联合收割机产生定向细胞运动。我的工作包括数学模型的推导和分析（详细和简化的分析），细胞内信号分子的时间行为和空间分布的模拟，以及实验验证（与实验合作者）。 我计划（1）进一步开发信号蛋白之间反馈的模型（Rho GTP酶Cdc42、Rac、Rho），脂质（磷酸肌醇PIP2，PIP3）和肌动蛋白（2）在Andre Levchenko进行的进一步的微流控细胞极化实验中验证了这些模型（J.霍普金斯），（3）在一维和二维细胞运动计算中模拟修改后的模型（与Stan Maree和博士后研究员），（4）开发细胞分裂中GTdR动力学的新模型（与凯伦·奥格玛合著），在侵入伪足等结构中，（与约翰·康迪利斯合作），在单细胞伤口中，（与W Bement），（5）进一步将建模技术扩展到乳腺癌细胞中cofilin激活和爆发性增殖活性背景下的GT3信号传导（与John Condeelis）。HQP培训将参与研究的各个方面。 数学建模已成为细胞生物学服务的重要工具。它可以帮助形式化和测试假设，建议和设计新的实验，并预测不容易通过实验测量的变量。我的工作包括建模、分析、计算，以及与能够提供数据和进行新实验的专家进行详细合作。

Cell motility is of fundamental importance in development, immune surveillance, and wound healing in eukaryotes. It also plays a nefarious role in metastasis in cancer. The actin cytoskeleton, which shapes the cell and drives protrusive motility is regulated by layers of signaling pathways. A focal question that motivates my research is how spatio-temporal dynamics of such signaling molecules are coordinated, and how these then combine to produce directed cell motility. My work includes derivation and analysis of mathematical models (both detailed and simplified for analysis), simulations of the time behaviour and spatial distribution of intracellular signaling molecules, and experimental validation (with experimental collaborators). I plan to (1) further develop models for feedback between signaling proteins (Rho GTPases Cdc42, Rac, Rho), lipids (phosphoinositides PIP2, PIP3), and actin (2) validate such models in further rounds of microfluidic cell polarization experiments carried out by Andre Levchenko (J. Hopkins), (3) simulate the revised models in1D and in 2D cell motility computations (with Stan Maree and post-doctoral fellows), (4) develop new models for GTPase dynamics in cell division (with Karen Oegema), in structures such as invadopodia (with John Condeelis) , and in single-cell wounds (with W Bement), (5) further extend modeling techniques to GTPase signaling in the context of cofilin activation and a burst of protrusive activity in mammary carcinoma cells (with John Condeelis). HQP training will be involved in every aspect of the research. Mathematical modeling has emerged as an important tool in the service of cell biology. It can help to formalize and test hypotheses, to suggest and design new experiments, and to predict variables that are not easy to measure experimentally. My work uses modeling, analysis, computations, and detailed collaboration with experts that can supply data and carry out new experiments.