Endocytosis optimizes the dynamic localization of membrane proteins that regulate cortical polarity
Endocytosis optimizes the dynamic localization of membrane proteins that regulate cortical polarity
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DOI：
10.1016/j.cell.2007.02.043
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发表时间：
2007-04-20
期刊：
影响因子：
64.5
通讯作者：
Wu, Lani F.
中科院分区：
文献类型：
--
作者：
Marco, Eugenio;Wedlich-Soldner, Roland;Wu, Lani F.
不同的细胞类型需要通过平衡运输和扩散来维持动态极化的膜蛋白分布的能力。然而，设计原则的基础上动态维持皮质极性还没有很好地理解。在这里，我们构建了一个数学模型来表征动态极化蛋白质分布的形态。我们开发的分析方法，测量所有模型参数的单细胞实验。我们将我们的方法应用于一个良好的特点系统研究极化膜蛋白：芽殖酵母细胞表达活化Cdc42。我们发现，扩散，定向运输和内吞作用的平衡是足够的准确描述极化形态。令人惊讶的是，该模型预测，极化区域被定义的精度，测量的内吞率几乎是最佳的，极性可以动态稳定，通过正反馈与定向运输。我们的方法提供了一个了解生物系统如何形状空间精确，明确的皮质极性域使用dynamicprocesses.Diverse细胞类型需要通过平衡运输和扩散的能力，以保持动态极化的膜蛋白分布。然而，动态维持皮质极性的设计原理还没有得到很好的理解。在这里，我们构建了一个数学模型来表征动态极化蛋白质分布的形态。我们开发的分析方法，测量所有模型参数的单细胞实验。我们将我们的方法应用于一个良好的特点系统研究极化膜蛋白：芽殖酵母细胞表达活化Cdc42。我们发现，扩散，定向运输和内吞作用的平衡是足够的准确描述极化形态。令人惊讶的是，该模型预测，极化区域被定义的精度，测量的内吞率几乎是最佳的，极性可以动态稳定，通过正反馈与定向运输。我们的方法提供了一个步骤，了解生物系统如何形状空间精确，明确的皮质极性域使用dynamicprocesses.Diverse细胞类型需要通过平衡运输和扩散的能力，以保持动态极化的膜蛋白分布。然而，动态维持皮质极性的设计原理还没有得到很好的理解。在这里，我们构建了一个数学模型来表征动态极化蛋白质分布的形态。我们开发的分析方法，测量所有模型参数的单细胞实验。我们将我们的方法应用于一个良好的特点系统研究极化膜蛋白：芽殖酵母细胞表达活化Cdc42。我们发现，扩散，定向运输和内吞作用的平衡是足够的准确描述极化形态。令人惊讶的是，该模型预测，极化区域被定义的精度，测量的内吞率几乎是最佳的，极性可以动态稳定，通过正反馈与定向运输。我们的方法提供了一个步骤，了解生物系统如何形状空间精确，明确的皮质极性域使用dynamicprocesses.Diverse细胞类型需要通过平衡tranport和diffusion保持动态极化的膜蛋白分布的能力。然而，动态维持皮质极性的设计原理还没有得到很好的理解。在这里，我们构建了一个数学模型来表征动态极化蛋白质分布的形态。我们开发的分析方法，测量所有模型参数的单细胞实验。我们将我们的方法应用于一个良好的特点系统研究极化膜蛋白：芽殖酵母细胞表达活化Cdc42。我们发现，扩散，定向运输和内吞作用的平衡是足够的准确描述极化形态。令人惊讶的是，该模型预测，极化区域被定义的精度，测量的内吞率几乎是最佳的，极性可以动态稳定，通过正反馈与定向运输。我们的方法提供了一个步骤，了解生物系统的形状空间精确，明确的皮质极性域使用动态过程。
Diverse cell types require the ability to maintain dynamically polarized membrane-protein distributions through balancing transport and diffusion. However, design principles underlying dynamically maintained cortical polarity are not well understood. Here we constructed a mathematical model for characterizing the morphology of dynamically polarized protein distributions. We developed analytical approaches for measuring all model parameters from single-cell experiments. We applied our methods to a well-characterized system for studying polarized membrane proteins: budding yeast cells expressing activated Cdc42. We found that a balance of diffusion, directed transport, and endocytosis was sufficient for accurately describing polarization morphologies. Surprisingly, the model predicts that polarized regions are defined with a precision that is nearly optimal for measured endocytosis rates and that polarity can be dynamically stabilized through positive feedback with directed transport. Our approach provides a step toward understanding how biological systems shape spatially precise, unambiguous cortical polarity domains using dynamic processes.Diverse cell types require the ability to maintain dynamically polarized membrane-protein distributions through balancing transport and diffusion. However, design principles underlying dynamically maintained cortical polarity are not well understood. Here we constructed a mathematical model for characterizing the morphology of dynamically polarized protein distributions. We developed analytical approaches for measuring all model parameters from single-cell experiments. We applied our methods to a well-characterized system for studying polarized membrane proteins: budding yeast cells expressing activated Cdc42. We found that a balance of diffusion, directed transport, and endocytosis was sufficient for accurately describing polarization morphologies. Surprisingly, the model predicts that polarized regions are defined with a precision that is nearly optimal for measured endocytosis rates and that polarity can be dynamically stabilized through positive feedback with directed transport. Our approach provides a step toward understanding how biological systems shape spatially precise, unambiguous cortical polarity domains using dynamic processes.Diverse cell types require the ability to maintain dynamically polarized membrane-protein distributions through balancing transport and diffusion. However, design principles underlying dynamically maintained cortical polarity are not well understood. Here we constructed a mathematical model for characterizing the morphology of dynamically polarized protein distributions. We developed analytical approaches for measuring all model parameters from single-cell experiments. We applied our methods to a well-characterized system for studying polarized membrane proteins: budding yeast cells expressing activated Cdc42. We found that a balance of diffusion, directed transport, and endocytosis was sufficient for accurately describing polarization morphologies. Surprisingly, the model predicts that polarized regions are defined with a precision that is nearly optimal for measured endocytosis rates and that polarity can be dynamically stabilized through positive feedback with directed transport. Our approach provides a step toward understanding how biological systems shape spatially precise, unambiguous cortical polarity domains using dynamic processes.Diverse cell types require the ability to maintain dynamically polarized membrane-protein distributions through balancing tranport and diffusion. However, design principles underlying dynamically maintained cortical polarity are not well understood. Here we constructed a mathematical model for characterizing the morphology of dynamically polarized protein distributions. We developed analytical approaches for measuring all model parameters from single-cell experiments. We applied our methods to a well-characterized system for studying polarized membrane proteins: budding yeast cells expressing activated Cdc42. We found that a balance of diffusion, directed transport, and endocytosis was sufficient for accurately describing polarization morphologies. Surprisingly, the model predicts that polarized regions are defined with a precision that is nearly optimal for measured endocytosis rates and that polarity can be dynamically stabilized through positive feedback with directed transport. Our approach provides a step toward understanding how biological systems shape spatially precise, unambiguous cortical polarity domains using dynamic processes.