Inferring the Physics of Living Systems from Dynamic Light Microscopy Data

从动态光学显微镜数据推断生命系统的物理原理

• 批准号: 1305537
• 负责人: Mark Bathe
• 金额: $ 54万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1305537&HistoricalAwards=false
• 关键词: Inferring; Physics; Living; Systems; Dynamic

In this project the PI will investigate the role of contractile actin networks in driving shape changes and morphogenesis in Drosophila embryos. Contractile actin networks are increasingly being shown to play a central role in fundamental biological processes involving cellular transport including cell division and embryogenesis. A physics-based approach that integrates quantitative analysis of fluorescence microscopy data with mechanistic, physics based modeling is proposed to investigate these processes. A major challenge posed by this data-driven modeling approach is the unbiased evaluation of competing physical models. To meet this challenge, a Bayesian inference framework is explored that models noise in the data generation process to systematically test competing hypotheses of transport mechanisms. Specific contributions of this research project include a unified, physical understanding of how dynamic, contractile actin meshworks operate to transport organelles and entire cells during basic biological processes including cell division and embryogenesis. Further, a data-driven approach to bridging physics-based transport models with fluorescence microscopy data sets is explored that will be of broad utility to the biological physics community. Contractile actin networks are protein networks present in eukaryotic cells that play an important role in cell division, cell movement, and tissue development. However, a mechanistic, physical understanding of how short time-scale, dynamic contractions of actin at the subcellular scale interact mechanically to coordinate cellular transport at larger length and time-scales does not exist. Resolving this mechanism requires a quantitative, physics-based approach that models contraction-driven transport at multiple scales ranging from single cells to collections thereof. The present project is at the forefront of this research area, which is of great importance to our scientific understanding the roles of contractile actin networks in development. Educational initiatives being advanced by the PI include undergraduate and graduate curriculum enhancement, including the new graduate elective offered in the Department of Biological Engineering, Physical Biology, and a new Institute-wide seminar series in Biophysics at MIT. As a result of the present research project, the PI is establishing a webserver for objective, Bayesian analysis of transport measurements to infer physical transport models in a variety of scientific disciplines, updating a webserver for integration of physics-based modeling into molecular animations of proteins, protein assemblies, and cytoskeletal dynamics for educational purposes, and developing a virtual laboratory in molecular and cellular biophysics for students at City on a Hill, a local charter high school serving under-represented minorities in the Boston area. Educational and research activities of the PI will be further disseminated via continuous rotation of undergraduate students from the Biological Engineering Research Experience for Undergraduates program and MIT's Undergraduate Research Opportunities Program, as well as from developing foreign countries.

在该项目中，PI将研究收缩肌动蛋白网络在果蝇胚胎中变化和形态发生中的作用。收缩肌动蛋白网络越来越多地证明在涉及细胞运输（包括细胞分裂和胚胎发生）的基本生物过程中起着核心作用。提出了一种基于物理学的方法，该方法将荧光显微镜数据的定量分析与机械基于物理学的建模进行了研究以研究这些过程。这种数据驱动的建模方法提出的一个重大挑战是对竞争物理模型的无偏评估。为了应对这一挑战，探索了贝叶斯推理框架，该框架将数据生成过程中的噪声模拟系统地测试运输机制的竞争假设。该研究项目的具体贡献包括对动态，收缩肌动蛋白网格Workss在基本生物学过程中如何运输细胞器和整个细胞的统一的物理理解，包括细胞分裂和胚胎发生。此外，还探索了与荧光显微镜数据集桥接基于物理的传输模型的数据驱动方法，这将是生物物理学界的广泛实用性。收缩肌动蛋白网络是真核细胞中存在的蛋白质网络，在细胞分裂，细胞运动和组织发育中起着重要作用。然而，对肌动蛋白在亚细胞尺度上的时间尺度短，动态收缩的机械性，物理的理解在机械上相互作用，以更大的长度和时间尺度来协调细胞转运。解决这种机制需要一种基于定量的，基于物理的方法，该方法在多个尺度上对收缩驱动的转运进行建模，从单个细胞到其收集。本项目是该研究领域的最前沿，这对于我们科学理解收缩肌动蛋白网络在开发中的作用至关重要。 PI提出的教育举措包括大学课程和研究生课程的增强，包括生物工程系，物理生物学系和麻省理工学院生物物理学范围内新的研究所的新研究生选修课。由于本研究项目，PI正在建立一个网络服务器，以进行客观，贝叶斯对运输测量的分析，以推断各种科学学科的物理运输模型，更新网络服务器，以将基于物理的建模集成到蛋白质分子动画中，用于教育目的的蛋白质组件和细胞骨架动力学，并为山上的纽约市的学生开发一个虚拟实验室，该实验室是在山上的学生，这是一所当地的特许宪章高中，为波士顿地区代表性不足的少数群体提供服务。 PI的教育和研究活动将通过从本科生的生物工程研究经验和麻省理工学院的本科研究机会计划以及发展中国的国外研究经验以及发展中的国外研究中进一步传播。