AI-assisted Cryo-ET workflow for 3D visualization of chromatin during cellular differentiation
Understanding how chromatin architecture changes during cellular differentiation requires structural methods that can resolve native genomic organization at high resolution. Here, we present an AI-assisted cryo-electron tomography (cryo-ET) and segmentation workflow to quantify chromatin compaction across various stages of motor neuron differentiation from induced pluripotent stem cells (iPSC). By directly imaging extracted and vitrified chromatin, we preserve native structure and avoid artifacts from heavy metal staining and resin embedding. Using three-dimensional (3D) density analysis, we measure chromatin density and capture the progressive increase in chromatin compaction with lineage commitment. This is then correlated with population-averaged Hi-C experiments, observing consistency between the microscale higher order structure of chromatin and global contact patterns. Our approach enables direct visualization of chromatin organization under near-physiological conditions, bridging the gap between structural imaging and genome-wide contact mapping. This platform therefore establishes an AI-assisted experimental framework for linking chromatin architecture to regulatory mechanisms during differentiation.
Authors
- Shawn R. Starkenburg (ORCID: https://orcid.org/0000-0002-8564-1274)
- Alexander S. Hall (ORCID: https://orcid.org/0000-0002-3807-1395)
- Sofiya Micheva–Viteva
- I Huber
- Karissa Y. Sanbonmatsu (ORCID: https://orcid.org/0000-0002-7965-7392)
- Manish Kumar Singh (ORCID: https://orcid.org/0000-0001-5004-7809)
- John Watt (ORCID: https://orcid.org/0000-0002-8012-9837)
- Cullen Roth (ORCID: https://orcid.org/0000-0003-4934-6160)
- Christina R. Steadman
Institutions
- Los Alamos National Laboratory (US)
- Thermo Fisher Scientific (United States) (US)
Publication Details
- Journal
- Biochemistry and Biophysics Reports
- Published
- 2026-09-11
- DOI
- https://doi.org/10.1016/j.bbrep.2026.102789
- Primary Topic
- Advanced Electron Microscopy Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Advanced Scientific Computing Research
- Biological and Environmental Research
- Los Alamos National Laboratory