Molecular and biophysical mechanism of plasma membrane internalization during nonclathrin endocytosis

在内吞的过程中，细胞的质膜发生变形并内化，从而将细胞外带进来。 货物受体和跨膜受体。非网状蛋白/非空泡(CLIC/GEEC)内吞作用内化 糖基化受体和胞外液，与细胞极性发育、起泡和 癌转移过程中上皮向间充质的转变。对分子和力学的理解 CLIC是理解CLIC如何协调膜曲率和肌动蛋白聚合来 使质膜内化以对抗膜张力。 研究CLIC的主要限制是缺乏对这一过程的明确标记。一个 赤松博士的博士后实验室使用机器学习方法对真正的内吞事件进行分类将 适用于区分CLIC内吞作用相对于其他类型的内吞作用的标志物。这将是 为CLIC定义第一个独特的标记，并将揭示CLIC膜中蛋白质组装的顺序 内化，这是理解每种蛋白质的功能所必需的。来检验这一假设 膜张力控制CLIC进展，Akamatsu博士将结合晶格光片显微镜和 他在博士后研究期间开发了一种将荧光强度转换为数字的校准方法 活细胞中的分子。有了这种新方法，分子计数晶格光片显微镜，他将 测量CLIC内吞蛋白在根尖和基底外侧表面的分子数 极化的iPS细胞，它们的膜张力不同。他会将渗透压力下的细胞成像到 增加细胞膜张力。最后，了解膜之间的反馈关系 在CLIC膜内化过程中，曲率感应杆蛋白和肌动蛋白聚合，他将 Bar蛋白介导的膜微管作用及其与肌动蛋白细丝的相互作用 将蛋白质成核成多尺度数学模型是他在博士后工作期间开发的。模拟 该模型可以预测质膜曲率、张力和膜张力之间的临界反馈关系。 肌动蛋白聚合需要及时完成CLIC的内吞作用。模型中的预测将会 在他自己的实验室里通过对内源性表达蛋白质结构域截断的细胞进行成像进行测试 肌动蛋白成核和聚合的抑制剂。 Akamatsu博士长期以来一直对将物理建模与活细胞定量相结合感兴趣 实验。一到两年的额外博士后培训将使他充分发展这两项技能 以便在他自己的实验室中有效地实施高度协同的反馈回路。在实验中提供联合建议 加州大学圣迭戈分校的大卫·杜鲁宾和帕德米尼·兰加马尼的计算建模方法给了他 这是这种综合方法的基础。Padmini Rangamani和Hernan提供的额外理论培训 加西亚，以及埃里克·贝齐格、马特·韦尔奇和丹·弗莱彻的定量实验方法将完全 让他做好准备，领导自己的综合建模和实验实验室。

During endocytosis, the cell's plasma membrane is deformed and internalized to bring in extracellular cargo and transmembrane receptors. Nonclathrin/noncaveolar (CLIC/GEEC) endocytosis internalizes glycosylated receptors and extracellular fluid, and is connected to cell polarity development, blebbing, and the epithelial-to-mesenchymal transition during cancer metastasis. A molecular and mechanical understanding of CLIC is necessary to understand how CLIC coordinates membrane curvature and actin polymerization to internalize the plasma membrane against membrane tension. The primary limitation in studying CLIC has been the lack of unambiguous markers for the process. A machine learning approach used in Dr. Akamatsu's postdoctoral lab to classify bona fide endocytic events will be adapted to disambiguate markers for CLIC endocytosis relative to other types of endocytosis. This will define the first unique markers for CLIC and will reveal the order of protein assembly during CLIC membrane internalization, which is essential for understanding the function of each protein. To test the hypothesis that membrane tension controls CLIC progression, Dr. Akamatsu will combine lattice light-sheet microscopy with a calibration method he developed during his postdoctoral research to convert fluorescence intensity to numbers of molecules in live cells. With this new method, molecule-counting lattice light-sheet microscopy, he will measure the numbers of molecules of CLIC endocytic proteins at both the apical and basolateral surfaces of polarized iPS cells, which differ in their membrane tension. He will image the cells under osmotic stress to increase cellular membrane tension. Finally, to understand the feedback relationship between membrane curvature-sensing BAR proteins and actin polymerization during CLIC membrane internalization, he will incorporate membrane tubulation by BAR proteins and their reciprocal interactions with actin filament nucleation proteins into a multi-scale mathematical model developed during his postdoctoral work. Simulations of this model will predict the critical feedback relationships between plasma membrane curvature, tension and actin polymerization necessary for the timely completion of CLIC endocytosis. Predictions from the model will be tested in his own lab by imaging cells endogenously expressing protein domain truncations in the presence of inhibitors of actin nucleation and polymerization. Dr. Akamatsu has a longstanding interest in combining physical modeling with live-cell quantitative experiments. One to two years of additional postdoctoral training will allow him to fully develop both skills in order to effectively implement a highly synergistic feedback loop in his own lab. Co-advising in experimental approaches by David Drubin and in computational modeling by Padmini Rangamani at UCSD have given him the foundation for this integrated approach. Additional training in theory from Padmini Rangamani and Hernan Garcia, and in quantitative experimental methods from Eric Betzig, Matt Welch, and Dan Fletcher will fully prepare him to lead an integrated modeling and experimental lab of his own.