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Kelley, R.K.* ; Khavnekar, S.* ; Righetto, R.D.* ; Heebner, J.* ; Obr, M.* ; Zhang, X.* ; Chakraborty, S.* ; Tagiltsev, G.* ; Michael, A.K.* ; van Dorst, S.* ; Waltz, F.* ; McCafferty, C.L.* ; Lamm, L. ; Zufferey, S.* ; Van der Stappen, P.* ; van den Hoek, H.* ; Wietrzynski, W.* ; Harar, P.* ; Wan, W.* ; Briggs, J.A.G.* ; Plitzko, J.M.* ; Engel, B.D.* ; Kotecha, A.*

Toward community-driven visual proteomics with large-scale cryo-electron tomography of Chlamydomonas reinhardtii.

Mol. Cell, DOI: 10.1016/j.molcel.2025.11.029 (2025)
Verlagsversion DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
In situ cryo-electron tomography (cryo-ET) has emerged as the method of choice to investigate the structures of biomolecules in their native context. However, challenges remain for the efficient production and sharing of large-scale cryo-ET datasets. Here, we combined cryogenic plasma-based focused ion beam (cryo-PFIB) milling with recent advances in cryo-ET acquisition and processing to generate a dataset of 1,829 annotated tomograms of the green alga Chlamydomonas reinhardtii, which we provide as a community resource to drive method development and inspire biological discovery. To assay data quality, we performed subtomogram averaging of both soluble and membrane-bound complexes ranging in size from >3 MDa to ∼200 kDa, including 80S ribosomes, Rubisco, nucleosomes, microtubules, clathrin, photosystem II, and mitochondrial ATP synthase. The majority of these density maps reached sub-nanometer resolution, demonstrating the potential of this C. reinhardtii dataset as well as the promise of modern cryo-ET workflows and open data sharing to empower visual proteomics.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Atp Synthase ; Chlamydomonas ; Empiar ; Clathrin ; Cryo-electron Tomography ; Focused Ion Beam ; Nucleosome ; Open Data ; Segmentation ; Visual Proteomics
ISSN (print) / ISBN 1097-2765
e-ISSN 1097-4164
Zeitschrift Molecular Cell
Verlag Elsevier
Begutachtungsstatus Peer reviewed
Institut(e) Helmholtz Artifical Intelligence Cooperation Unit (HAICU)