EMPIAR-10741 - Single particle cryo-EM dataset of Sars-CoV2 Rna dependent RNA polymerase [7043 multi-frame micrographs composed of 80 frames each in TIFF format]

EMPIAR-10741

Single particle cryo-EM dataset of Sars-CoV2 Rna dependent RNA polymerase [7043 multi-frame micrographs composed of 80 frames each in TIFF format]

Publication:

The structure of a dimeric form of SARS-CoV-2 polymerase

Jochheim FA, Tegunov D, Hillen HS, Schmitzová J, Kokic G, Dienemann C, Cramer P

Communications biology 4 (2021)

PMID: 34429502

DOI: 10.1038/s42003-021-02529-9

Related EMDB entry:

EMD-13116

Deposited:

2021-06-24

Released:

2021-10-25

Last modified:

2022-02-25

Imageset size:

2.72 TB

Imageset DOI:

10.6019/EMPIAR-10741

Experimental metadata:

Download xml json

Contains:

micrographs - multiframe

Image Sets

1. Unaligned TIF movies of SARS-CoV2 RdRp in complex with nsp7, nsp8 and RNA

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

7043

Image size:

(5760, 4092)

Pixel type:

UNSIGNED BYTE

Pixel spacing:

(0.834, 0.834)

Details:

Movies are in the 2020-09-XX subfolders. They are from K3 (non-superres) and uncorrected (gain can be found in ./gain subfolders). Each LZW compressed.tif movie is accompanied with its respective .xml metadata file generated by Warp. Movies contain 80 frames collected over 2.2 seconds with a total dose of 60 e-/A2. Data was collected at 30 degree stage tilt. Particle locations were picked with Warp (locations are stored in ./matching subfolder and combined in the allparticles star file, extracted particles are in the ./particles). Micrograph thumbnails can be found in ./thumbnails subfolders.

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Citations

GTpick: A deep neural network for Cryo-EM particle detection.

Ni S, Yang C, Liu Y, Zhang Y, Shi Y, Qian A, Kong R, Chang S. (2025)

High-resolution ab initio reconstruction enables cryo-EM structure determination of small particles

Kim K, Li H, Clarke OB. (2025)

CLEM-Reg: an automated point cloud-based registration algorithm for volume correlative light and electron microscopy.

Krentzel D, Elphick M, Domart MC, Peddie CJ, Laine RF, Shand C, Henriques R, Collinson LM, Jones ML. (2025)

CryoEMNet driven symmetry-aware molecular reconstruction through deep learning enhanced electron microscopy.

Arora S, Pan SH, Kumar S, Singh SK, Chauhan U, Alhalabi W, Arya V, Alsulami BS, Hsu CH, Chui KT, Gupta BB. (2025)

PERC: a suite of software tools for the curation of cryoEM data with application to simulation, modeling and machine learning.

Costa-Gomes B, Greer J, Juraschko N, Parkhurst J, Mirecka J, Famili M, Rangel-Smith C, Strickson O, Lowe A, Basham M, Burnley T. (2025)

Self-supervised learning for generalizable particle picking in cryo-EM micrographs.

Zamanos A, Koromilas P, Bouritsas G, Kastritis PL, Panagakis Y. (2025)

Localization of macromolecules in crowded cellular cryo-electron tomograms from extremely sparse labels.

Uddin MR, Ahmed AY, Tabib HMS, Tahmid MT, Alam MZU, Freyberg Z, Xu M. (2025)

Structural insight into bicarbonate-mediated carboxylation by human vitamin K-dependent carboxylase.

Wu K, Wang Z, Yao D, Li S, Wang X, Zhang Y, Cao M, Shen Y, Xing S, Wu J, Lei M, Lan P. (2025)

Conserved hydrophilic checkpoints tune FocA-mediated formate:H<sup>+</sup> symport.

Tüting C, Janson K, Kammel M, Ihling C, Lorenz J, Kyrilis FL, Hamdi F, Erdmann C, Sinz A, Sawers RG, Kastritis PL. (2025)

Laser flash melting cryo-EM samples to overcome preferred orientation.

Straub MS, Harder OF, Mowry NJ, Barrass SV, Hruby J, Drabbels M, Lorenz UJ. (2025)

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