EMPIAR-13107 - Leopard-EM: An extensible 2DTM package to accelerate in situ structural biology [multiple data sets in MRC and EER formats]

EMPIAR-13107

Leopard-EM: An extensible 2DTM package to accelerate in situ structural biology [multiple data sets in MRC and EER formats]

Publication:

Leopard-EM: An extensible 2DTM package to accelerate in situ structural biology

Giammar MD, Dickerson JL, Hall LN, Lucas BA

Acta Crystallographica Section D: Structural Biology (---)

Related EMDB entry:

Deposited:

2025-05-27

Released:

2025-12-19

Last modified:

2025-12-19

Imageset size:

482.66 GB

Imageset DOI:

10.6019/EMPIAR-13107

Experimental metadata:

Download xml json

Contains:

micrographs - single frame
micrographs - multiframe
reconstructed volumes

Image Sets

1. Motion corrected and dose weighted micrographs of yeast cytoplasm used as inputs for 2DTM

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

Image size:

(4096, 4096)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.936, 0.936)

Details:

---

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2. Raw .eer frames of Saccharomyces services cytoplasm used for downstream 2DTM processing

Category:

micrographs - multiframe

Image format:

EER

No. of images or tilt series:

Image size:

(4096, 4096)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.936, 0.936)

Details:

Micrographs collected using a Thermo Fisher Krios 300 kV electron microscope equipped with a Falcon 4 camera and Selectris X energy filter at a nominal magnification of 81,000× (pixel size of 0.936 Angstrom) and a 100 µm objective aperture. Movies were collected to a total fluence of 50 electrons per angstom squared with 1800 frames in EER mode targeting a defocus of 0.5 µm. Cytoplasm was targeted by selecting regions of interest in a low-magnification overview.

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3. Two-Dimensional Template Matching results for the ribosome LSU.

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

632

Image size:

(3585, 3585)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.936, 0.936)

Details:

Two-dimensional template matching result files from the leopard em program match template where the file patterns follow the base name of the reference micrograph plus the result type. The file “*output_mip.mrc” Corresponds to the maximum intensity projection over the entire search space. The files “*output_phi.mrc”, “*output_theta.mrc”, “*output_psi.mrc”, and “*output_relative_defocus” correspond to the orientations, in ZYZ Euler angle format, and defocus offset from the micrograph which produced the maximum intensity projection. The files “*output_correlation_average.mrc” and “*output_correlation_variance.mrc” correspond to the mean and variance of the cross-correlation value over the entire search space. The files “*output_scaled_mip.mrc” are the maximum intensity projection values scaled to be z-scores over the whole search space.

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4. Two-Dimensional Template Matching results for the ribosome SSU body.

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

632

Image size:

(3585, 3585)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.936, 0.936)

Details:

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5. Two-Dimensional Template Matching results for 20S proteasome run with C2 symmetry

Category:

micrographs - single frame

Image format:

MRC

No. of images or tilt series:

224

Image size:

(5377, 3709)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(1.06, 1.06)

Details:

Files:

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6. Simulated reference template volumes for LSU and SSU used for 2DTM

Category:

reconstructed volumes

Image format:

MRC

No. of images or tilt series:

Image size:

(512, 512)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.936, 0.936)

Details:

60S_map_px0.936_bscale0.5.mrc corresponds to the 60S ribosome template simulated at 0.936 Angstroms per pixel with a B-factor scaling of 0.5 applied to the deposited PDB per-atom B-factors.
60S_map_px0.95_bscale0.5.mrc is the same, except simulated at 0.95 Angstroms per pixel.
SSU-body_map_px0.936_bscale0.5.mrc is the simulated volume of the 40S ribosome body template (no head) at 0.936 Angstroms per pixel. All simulations were done with the Python package ttsim3D.

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7. Reconstructions of the ribosome from constrained template matching results shown in paper

Category:

reconstructed volumes

Image format:

MRC

No. of images or tilt series:

Image size:

(512, 512)

Pixel type:

32 BIT FLOAT

Pixel spacing:

(0.936, 0.936)

Details:

The particle positions from the Leopard-EM results files were used to extract the particles in 512 by 512 pixel boxes, which were then normalized to have a mean of zero and a standard deviation of one. These extracted particles were saved as .mrcs files, with one file generated per micrograph. Subsequently, RELION compatible STAR files were created using the Euler angles and CTF parameters in the Leopard-EM results. 3D volumes were generated for all particles, non-rotated particles, and rotated particles, using RELION's reconstruct program. After low-pass filtering the maps to 30 Angstrom, masks for the full 80S ribosome were generated in RELION. These masks were manually modified in ChimeraX to create a mask for the SSU body. Postproccesing was performed in
RELION with an automatically determined B-factor to generate the masked 3D maps and estimate the resolution.

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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)

DiameTR: A cryo-EM tool for diameter sorting of tubular samples.

Peng R, Elkhaligy H, Grant T, Stagg SM. (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)

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