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.

在这个项目中，PI将研究收缩肌动蛋白网络在驱动果蝇胚胎形状变化和形态发生中的作用。收缩肌动蛋白网络越来越多地被证明在涉及细胞运输的基本生物过程中发挥核心作用，包括细胞分裂和胚胎发生。一个基于物理的方法，结合定量分析的荧光显微镜数据与机械，物理为基础的建模提出了调查这些过程。这种数据驱动的建模方法带来的一个主要挑战是对竞争物理模型的无偏见评估。为了应对这一挑战，我们探索了一个贝叶斯推理框架，该框架在数据生成过程中对噪音进行建模，以系统地测试传输机制的竞争假设。该研究项目的具体贡献包括对动态收缩肌动蛋白网络如何在基本生物过程（包括细胞分裂和胚胎发生）中运输细胞器和整个细胞的统一物理理解。此外，一个数据驱动的方法来桥接物理为基础的运输模型与荧光显微镜数据集进行了探索，这将是广泛的实用生物物理界。收缩肌动蛋白网络是存在于真核细胞中的蛋白质网络，其在细胞分裂、细胞运动和组织发育中起重要作用。然而，一个机械的，物理的理解如何短的时间尺度，动态收缩的肌动蛋白在亚细胞尺度上相互作用，以协调细胞运输在更大的长度和时间尺度不存在。解决这一机制需要一种定量的、基于物理学的方法，该方法在从单个细胞到其集合的多个尺度上对收缩驱动的运输进行建模。本项目处于这一研究领域的前沿，这对我们科学地理解收缩肌动蛋白网络在发育中的作用具有重要意义。PI正在推进的教育举措包括本科生和研究生课程的增强，包括生物工程，物理生物学系提供的新研究生选修课，以及麻省理工学院生物物理学的新研究所范围内的系列研讨会。作为本研究项目的结果，PI正在建立一个网络服务器，用于对运输测量进行客观的贝叶斯分析，以推断各种科学学科中的物理运输模型，更新一个网络服务器，用于将基于物理的建模整合到蛋白质的分子动画中，蛋白质组装，以及用于教育目的的细胞骨架动力学，并为波士顿地区一所为少数族裔服务的当地特许高中山上城市的学生开发了一个分子和细胞生物物理学虚拟实验室。PI的教育和研究活动将通过本科生生物工程研究经验计划和麻省理工学院本科生研究机会计划以及来自发展中国家的本科生的持续轮换来进一步传播。