Empirical and mathematical approaches to study gradient sensing using yeast as a model

使用酵母作为模型研究梯度传感的经验和数学方法

• 批准号: 1415589
• 负责人: David Stone
• 金额: $ 107.95万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1415589&HistoricalAwards=false
• 关键词: Empirical; mathematical; approaches; study; gradient

The individual cells of multicellular organisms sense chemical signals that are essential both to maintain the organisms and to enable them to respond to changes in the environment. Cells have developed complex biochemical events (signaling) that allow them to sense very subtle changes in the concentration of these chemical signals (gradients). The PI uses yeast cells as a model to study these signaling events, but they are likely broadly applicable to cells in more complex organisms as well. In previous studies, he identified a variety of biochemical events that are required for cells to interpret chemical gradients. In this project, he will investigate the contributions of two novel signaling events, using the classic tools of cell biology, molecular genetics, molecular biology, biochemistry, and imaging. In addition, the PI will develop a mathematical model that not only describes the known components of the signaling system, but also predicts novel components of the pathway. This approach is particularly exciting because it will allow the PI to identify signaling events that might not have been identified through experimentation alone. In short, this project will work at the interface of mathematics and biology to identify the critical regulators of cells' responses to the chemical signals that allow them to function appropriately. The PI is committed to science education at all levels and will use the project to train undergraduates and students in an AP biology class. Every other year, the PI will offer his newly developed graduate seminar course, "Explaining Science" designed to teach graduate students how to talk about their work with anyone, from a child to a congressperson. The project will give the PI's students and postdoc the chance to work with collaborators who are experts in diverse areas. Because the project is at the interface of math and biology, researchers in each discipline will gain a better understanding of how those in the other discipline think.Chemotropism, directed cell growth in response to a chemical gradient, is integral to axon guidance, angiogenesis, pollen tube guidance, and fungal infection. Naturally occurring chemical gradients are very shallow and dynamic. Models of chemotactic phenomena invoke positive feedback loops that amplify small differences in receptor activation across the cell surface into a substantially steeper intracellular signaling gradient. It is presumed that the response of chemotropic cells to shallow chemical gradients is also amplified by interacting feedback loops, but a mechanistic understanding of such loops is lacking. The goal of this project is to understand how the chemotropic growth site is established upstream of directed secretion, and how the cell responds to changes in the gradient after initial orientation. Observations made during the current project suggest that two interconnected positive feedback loops underlie the establishment of receptor polarity upstream of directed secretion. A mathematical reaction/diffusion model of these mechanisms has been developed, and will be used in combination with experimental approaches to provide a better understanding of how gradient-aligned receptor polarity is established and maintained. The degree to which the model mimics the behavior of gradient-stimulated yeast cells will guide both experimentation and the evolution of the model itself. This project will lead to a deeper and more comprehensive understanding of gradient sensing while simultaneously developing mathematical modeling as a tool for biologists. During this project period, the PI will continue to administer and train students in the NSF-Capstone Undergraduate Research Program, which he co-developed. He has also developed a graduate course, "Explaining Science", designed to teach graduate students how to explain their science to laypersons. He will meet annually with a high school AP biology class to discuss his research. The project will provide the PI's students and postdoc with interdisciplinary training, through interactions with collaborators who are experts in diverse areas. Specifically, the project is at the interface of math and biology and will provide students and postdoctoral researchers with training in this emerging area.This project is funded jointly by the Cellular Dynamics and Function Cluster in the Molecular and Cellular Biosciences Division and by the Mathematical Biology Program in the Division of Mathematical Sciences.

多细胞生物体的单个细胞感知化学信号，这些信号对于维持生物体并使它们能够对环境变化做出反应至关重要。细胞已经发展了复杂的生化事件（信号），使它们能够感知这些化学信号（梯度）浓度的非常微妙的变化。PI使用酵母细胞作为模型来研究这些信号事件，但它们也可能广泛适用于更复杂的生物体中的细胞。在以前的研究中，他确定了细胞解释化学梯度所需的各种生化事件。在这个项目中，他将研究两个新的信号事件的贡献，使用细胞生物学，分子遗传学，分子生物学，生物化学和成像的经典工具。此外，PI将开发一个数学模型，不仅描述了信号系统的已知组件，而且还预测了途径的新组件。这种方法特别令人兴奋，因为它将允许PI识别单独通过实验可能无法识别的信号事件。简而言之，该项目将在数学和生物学的界面上工作，以确定细胞对化学信号反应的关键调节剂，使它们能够适当地发挥作用。PI致力于各级科学教育，并将利用该项目在AP生物课上培训本科生和学生。每隔一年，PI将提供他新开发的研究生研讨会课程，“解释科学”旨在教研究生如何与任何人谈论他们的工作，从一个孩子到国会议员。该项目将使PI的学生和博士后有机会与不同领域的专家合作。由于该项目是在数学和生物学的接口，每个学科的研究人员将获得如何在其他学科的思考更好的理解。趋化性，定向细胞生长响应化学梯度，是不可或缺的轴突导向，血管生成，花粉管导向，真菌感染。自然发生的化学梯度是非常浅和动态的。趋化现象的模型引起正反馈回路，其将跨细胞表面的受体活化的微小差异放大成实质上更陡的细胞内信号梯度。据推测，趋化性细胞的反应浅的化学梯度也被放大的相互作用的反馈回路，但这样的回路缺乏一个机械的理解。该项目的目标是了解向化生长位点是如何在定向分泌的上游建立的，以及细胞如何在初始定向后对梯度的变化做出反应。在目前的项目中所作的观察表明，两个相互关联的正反馈回路的基础上建立受体极性上游定向分泌。这些机制的数学反应/扩散模型已经开发出来，并将与实验方法结合使用，以更好地了解如何建立和维持梯度排列的受体极性。模型模拟梯度刺激酵母细胞行为的程度将指导实验和模型本身的进化。该项目将导致更深入和更全面的了解梯度传感，同时开发数学建模作为生物学家的工具。在此项目期间，PI将继续管理和培训学生在NSF的顶点本科研究计划，他共同开发。他还开发了一门研究生课程，“解释科学”，旨在教研究生如何向外行解释他们的科学。他将每年与高中AP生物课讨论他的研究。该项目将通过与不同领域的专家合作者的互动，为PI的学生和博士后提供跨学科的培训。具体来说，该项目是在数学和生物学的接口，并将提供学生和博士后研究人员在这一新兴领域的培训。该项目是由分子和细胞生物科学部的细胞动力学和功能集群和数学科学部的数学生物学计划共同资助。