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

Carnegie Mellon University, Pittsburgh PA

Investigators

Abstract

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 students. The broadening participation efforts will provide important training in bioimage informatics for a number of trainees to help the nation 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.