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CAREER: Theory of Membrane Shape Sensing at the Micron Scale

职业：微米级膜形状传感理论

基本信息

批准号：
1945141
负责人：
Brian Camley
金额：
$ 54.95万
依托单位：
Johns Hopkins University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2025-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1945141&HistoricalAwards=false
关键词：
CAREER Theory Membrane Shape Sensing

项目摘要

NONTECHNICAL SUMMARYThis CAREER award supports theoretical and computational research, and associated education to investigate how protein molecules can tell the shape of a cell membrane. For cells to divide or make protrusions, proteins must end up in the right position in the cell – for instance, being localized to parts of the membrane that have particular curved shapes. Surprisingly, this can happen even when the scale over which the membranes curve is far larger, some thousand times larger, than the size of a protein. Because membranes are soft, and can change their shape easily, they also can be very rough, making the problem of the proteins "sensing" the cell’s shape even harder. This project is about understanding how shape sensing can happen. Two broad possibilities for how proteins end up in these spots are either: 1) each single protein can make incredibly precise measurements of the local membrane, allowing it to find the right shape, or 2) many proteins can work together cooperatively to measure the cell’s shape over a length scale of many protein sizes. How precisely must single proteins measure the membrane’s shape in order to locate where they go? Could proteins instead position themselves based on something correlated with shape but easier to measure? If proteins work together to sense the membrane’s shape, how much better will they be at finding their locations? The PI will use computer models, mathematical calculations, and experimental data shared from collaborators to address these questions. This research will also provide a way to better understand how patterning is coupled to surface shape in a broader context; similar problems show up both in biology and in the formation of patterns on other rough surfaces.This project includes linking computational research to an education plan including development of a new class focused on the physics of cells, as well as mentoring and training students from high school to graduate school. People supported by this grant will work in collaboration with Baltimore City public high school students, with Baltimore City students within the group as well as group members working with the public high school. In particular, the PI and graduate student will work with local high school teachers to develop computational “labs” to teach high school students about the role of randomness in physics and biology and assist in presenting these labs. TECHNICAL SUMMARYThis CAREER award supports theoretical and computational research, and associated education to investigate how nanometer-scale proteins sense micron-scale curvature of the cell membrane. Curvature sensing is a critical soft matter physics problem, but the guiding principles of how it operates at the micron scale are still unclear. The PI aims to develop useful predictive bounds showing the limiting factors in shape sensing. If successful, this research will lead to a broad understanding of how biochemical polarity and cell geometry are coupled by using both minimal phenomenological models and detailed reaction-diffusion approaches. Interesting connections at the interfaces of membrane dynamics, statistical sensing limits like the Berg-Purcell limit, and biochemical models, will be developed with the aim to gain new insight into of the organization and dynamics of cell membranes and related biological systems. This insight will be used in building predictive models. This research will be pursued along two primary directions:1. Determining the accuracy with which single proteins can sense membrane curvature. Even if a protein could perfectly measure the local membrane shape, it could not precisely determine the micron-scale membrane curvature, because thermal fluctuations create local curvature. Distinguishing curved membrane regions from flat is harder at larger radii of curvature – the signal-to-noise ratio decreases. Are proteins that sense micron-scale curvature near this basic physical limit? To determine this, the research group will apply estimation theory to continuum models of fluctuating membranes in and out of confinement. Protein binding may depend on proxies for membrane curvature, for example local defects in lipid packing. These effects, as well as lipid tilt and non-thermal origins of membrane fluctuations will also be studied. In combination, these models predict how curvature-dependent binding depends on membrane tension, bending modulus, the presence of a solid support, and lipid asymmetries between leaflets. 2. Emergent shape sensing by pattern formation on a fluctuating membrane. Initial simulations suggest simple bistable reactions on a membrane surface can reproduce the shape sensing observed in C. elegans embryos, where proteins localize to narrow ends of a cell. However, cell membranes are highly dynamic – fluctuating and undergoing lipid flow. Will these shape changes and flows prevent cells from sensing their own shape or help them? The PI will begin by developing and testing an energy landscape model of shape sensing, to describe how protein localization depends on membrane shape. Simulations of reaction-diffusion dynamics on fluctuating membranes will be carried out in order to determine when shape fluctuations can help or hinder shape sensing. These models will predict the extent to which the cell's patterning depends on membrane-cortex attachment, cytosol viscosity, and other factors known to modulate active membrane fluctuations. This project includes linking computational research to an education plan including development of a new class focused on the physics of cells, as well as mentoring and training students from high school to graduate school. People supported by this grant will work in collaboration with Baltimore City public high school students, with Baltimore City students within the group as well as group members working with the public high school. In particular, the PI and graduate student will work with local high school teachers to develop computational “labs” to teach high school students about the role of randomness in physics and biology and assist in presenting these labs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非技术摘要该职业奖支持理论和计算研究以及相关教育，以研究蛋白质分子如何判断细胞膜的形状。为了使细胞分裂或形成突起，蛋白质必须最终位于细胞中的正确位置，例如，定位于具有特定弯曲形状的膜部分。令人惊讶的是，即使膜弯曲的尺寸比蛋白质的尺寸大数千倍，这种情况也会发生。由于细胞膜很柔软，很容易改变形状，但它们也可能非常粗糙，使得蛋白质“感知”细胞形状的问题变得更加困难。该项目旨在了解形状传感是如何发生的。蛋白质如何最终出现在这些点上有两种广泛的可能性：1）每种蛋白质都可以对局部膜进行极其精确的测量，使其找到正确的形状，或者2）许多蛋白质可以协同工作，在多种蛋白质尺寸的长度范围内测量细胞的形状。单个蛋白质必须多精确地测量膜的形状才能定位它们的去向？蛋白质能否根据与形状相关但更容易测量的东西来定位自己？如果蛋白质共同作用来感知膜的形状，它们在寻找位置方面会好多少？ PI 将使用计算机模型、数学计算和合作者共享的实验数据来解决这些问题。这项研究还将提供一种更好地理解图案如何在更广泛的背景下与表面形状耦合的方法；类似的问题也出现在生物学和其他粗糙表面上的图案形成中。该项目包括将计算研究与教育计划联系起来，包括开发一个专注于细胞物理学的新课程，以及指导和培训从高中到研究生院的学生。受这笔赠款支持的人将与巴尔的摩市公立高中的学生、小组内的巴尔的摩市学生以及与公立高中合作的小组成员合作。特别是，PI和研究生将与当地高中教师合作开发计算“实验室”，向高中生讲授随机性在物理和生物学中的作用，并协助展示这些实验室。技术摘要该职业奖支持理论和计算研究以及相关教育，以研究纳米级蛋白质如何感知细胞膜的微米级曲率。曲率传感是一个关键的软物质物理问题，但其在微米尺度上如何运作的指导原则仍不清楚。该 PI 旨在开发有用的预测范围，显示形状传感中的限制因素。如果成功，这项研究将通过使用最小现象学模型和详细的反应扩散方法，对生化极性和细胞几何形状如何耦合产生广泛的理解。将开发膜动力学、统计传感极限（如 Berg-Purcell 极限）和生化模型之间的有趣联系，旨在获得对细胞膜和相关生物系统的组织和动力学的新见解。这种见解将用于构建预测模型。这项研究将沿着两个主要方向进行：1．确定单个蛋白质感知膜曲率的准确性。即使蛋白质可以完美地测量局部膜形状，它也无法精确确定微米级膜曲率，因为热波动会产生局部曲率。曲率半径越大，区分弯曲膜区域和平坦膜区域就越困难——信噪比会降低。感知微米级曲率的蛋白质是否接近这个基本物理极限？为了确定这一点，研究小组将应用估计理论来研究进出约束的波动膜的连续介质模型。蛋白质结合可能取决于膜曲率的指标，例如脂质堆积的局部缺陷。这些效应以及脂质倾斜和膜波动的非热起源也将被研究。结合起来，这些模型预测了曲率依赖性结合如何取决于膜张力、弯曲模量、固体支持物的存在以及小叶之间的脂质不对称性。 2. 通过在波动膜上形成图案来进行紧急形状传感。初步模拟表明，膜表面上的简单双稳态反应可以重现在线虫胚胎中观察到的形状感知，其中蛋白质定位于细胞的狭窄末端。然而，细胞膜是高度动态的——波动并经历脂质流动。这些形状变化和流动会阻止细胞感知自己的形状还是帮助它们？ PI 将首先开发和测试形状传感的能量景观模型，以描述蛋白质定位如何依赖于膜形状。将进行波动膜上的反应扩散动力学模拟，以确定形状波动何时有助于或阻碍形状传感。这些模型将预测细胞模式对膜-皮质附着、细胞质粘度和其他已知调节活性膜波动的因素的依赖程度。该项目包括将计算研究与教育计划联系起来，包括开发一个专注于细胞物理学的新课程，以及指导和培训从高中到研究生院的学生。受这笔赠款支持的人将与巴尔的摩市公立高中的学生、小组内的巴尔的摩市学生以及与公立高中合作的小组成员合作。特别是，PI 和研究生将与当地高中教师合作开发计算“实验室”，向高中生传授随机性在物理和生物学中的作用，并协助展示这些实验室。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。