Computational Methods for In-Situ Structure Determination using Cryo-ET

NIH RePORTER · GM · R35 · $482,750 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY Understanding how proteins interact within the cell to perform specific functions is a central goal of modern biology and crucial for understanding the diverse roles these molecules play in biomedicine. Single-particle cryo-electron tomography (SP-cryo-ET) is currently the only technology capable of visualizing macromolecules in their native environment at high resolution. Despite recent advances in sample preparation, data acquisition, and image processing, structural analysis by SP-cryo-ET is still largely confined to naturally abundant targets—such as ribosomes or ordered supramolecular assemblies—or to resolutions that are insufficient to reveal molecular-level interactions. Furthermore, the complexity and high computational demands of SP-cryo-ET workflows for data processing have restricted access to the technology for structural biologists. These challenges present a significant barrier to fully unlocking the potential of SP-cryo-ET in advancing our understanding of how proteins interact within cells to carry out specific functions and the essential roles they play in biology and disease. Building on recent progress made by our group, the goal of this project is to develop methods to address remaining bottlenecks in the SP-cryo-ET workflow that will result in broader applicability and improved access. Our long-term goal is to enable the routine visualization of a wide range of biomedically important targets in the cellular context at near-atomic resolution. By working closely with a network of experimental collaborators, we will ensure that our method development efforts are driven by diverse and impactful biological projects. Ultimately, our tools will help expand the applicability of SP-cryo-ET and accelerate its adoption, empowering structural biologists to tackle new questions regarding molecular interactions and cellular mechanisms.

Key facts

NIH application ID
11330742
Project number
1R35GM163737-01
Recipient
DUKE UNIVERSITY
Principal Investigator
Alberto Bartesaghi
Activity code
R35
Funding institute
GM
Fiscal year
2026
Award amount
$482,750
Award type
1
Project period
2026-05-01T00:00:00 → 2031-02-28T00:00:00