CAREER: Cryo-electron tomography derived multiscale integrative modeling of subcellular organization

低温电子断层成像(Cryo-Et)可以在亚分子分辨率下以接近自然的状态对单个细胞内的亚细胞结构及其空间排列进行三维可视化。该学院早期职业发展计划(CALEAR)项目旨在开发计算方法，以整合冷冻-ET和荧光显微镜，以了解哪些蛋白质存在于不同的细胞结构中，以及这些结构是如何相对于彼此排列的。这项提议的研究部分将有助于在广泛的生物学研究中理解复杂的细胞过程的新的计算方法和开放源码软件。这项建议的教育目标是推进和促进生物图像的计算分析和理解(也称为生物图像信息学)的教学和培训。研究活动和成果将被整合到课堂教学、公共在线教育和针对不同学生的推广计划中，包括代表性不足的学生。不断扩大的参与努力将为不同的人群提供重要的生物图像信息学培训，以满足这一重要领域快速增长的需求。研究人员的长期研究目标是开发低温衍生的多尺度综合模型的计算方法。这个职业项目将开发计算方法，通过整合来自低温和荧光显微镜的信息来构建细胞群体的多尺度亚细胞组织模型。该研究计划包括三个目标：1)从细胞群体的低温图像中构建亚细胞组织的生成模型；2)通过低温与荧光数据之间的空间模式匹配进行多尺度建模；3)推断低温ET中识别的大分子结构的蛋白质组成。它将为使用Cryo-ET作为从亚分子尺度到细胞尺度的亚细胞组织建模的忠实和空间精确的数据源带来前所未有的机会。这样的建模对于将形态与产生形态的机制联系起来是必不可少的。该项目的成果将在“https://github.com/xulabs/modeling”上公布。这一奖项反映了国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Cryo-Electron Tomography (Cryo-ET) enables the 3D visualization of subcellular structures and their spatial arrangement inside single cells in close-to-native state at submolecular resolution. This Faculty Early Career Development Program (CAREER) project aims to develop computational methods to integrate cryo-ET and fluorescence microscopy in order to learn which proteins are present in different cell structures and how these structures are arranged relative to each other. The research component of this proposal will contribute novel computational methods and open-source software that are applicable to understanding complex cellular processes in a broad range of biological studies. The educational objective of this proposal is to advance and promote the teaching and training of computational analysis and understanding of biological Images (also referred to as bioimage informatics). The research activities and outcomes will be integrated into classroom teaching, public online education, and outreach programs for various students, including underrepresented students. The broadening participation efforts will provide important training in bioimage informatics for a diverse population to meet the fast-increasing demand in this important area.The investigator’s long-term research goal is to develop computational methods for cryo-ET derived multiscale integrative modeling. This CAREER project will develop computational methods for constructing multiscale subcellular organization models of cell populations by integrating information from cryo-ET and fluorescence microscopy. The Research Plan includes three objectives: 1) constructing generative models of subcellular organization from cryo-ET images of cell populations; 2) multiscale modeling by spatial pattern matching between cryo-ET and fluorescence data; 3) inferring protein composition of macromolecular structures identified in cryo-ET. It will bring unprecedented opportunities for using Cryo-ET as a faithful and spatially precise data source for modeling subcellular organization from the submolecular scale to the cellular scale. Such modeling is essential for connecting morphology to the mechanisms that produce it. The project outputs will be available at “https://github.com/xulabs/modeling”.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.