Computational models of eukaryotic cell polarization/motility

细胞运动在真核生物的发育、免疫监视和伤口愈合中具有重要作用。它在癌症转移中也扮演着邪恶的角色。肌动蛋白细胞骨架，它塑造细胞并驱动突起运动，由一层信号通路调节。激励我研究的一个焦点问题是，这些信号分子的时空动态是如何协调的，以及这些分子是如何结合在一起产生定向的细胞运动的。我的工作包括推导和分析数学模型(包括详细和简化的分析)，模拟细胞内信号分子的时间行为和空间分布，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(Rho GTPase，CDC42，Rac，Rho)、脂类(磷脂酰肌醇PIP2，PIP3)和肌动蛋白之间的反馈模型(2)在Andre Levchenko(J.Hopkins)进行的更多轮微流控细胞极化实验中验证这些模型，(3)在一维和2D细胞运动计算中模拟修订后的模型(与Stan Maree和博士后研究员一起)，(4)开发新的GTPase动态模型，用于细胞分裂(与Karen Oegema)，在invadodia(与John Condeelis)等结构中，以及在单细胞伤口(与WBement)，(与Karen Oegema(5)进一步将建模技术扩展到在cofilin激活和乳腺癌细胞突起活动的背景下的GTPase信号(与John Condeelis)。HQP培训将涉及到研究的各个方面。 数学建模已经成为细胞生物学服务的一个重要工具。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。我的工作使用建模、分析、计算和与专家的详细合作，这些专家可以提供数据并进行新的实验。

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.