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- EMDB-51653: Subtomogram average of S. pombe 80S ribosomes from DEF tomograms ... -

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Basic information

Entry
Database: EMDB / ID: EMD-51653
TitleSubtomogram average of S. pombe 80S ribosomes from DEF tomograms acquired on cryo-FIB-lamellae based on Template Learning additional annotations non-overlapping with previous expert-validated annotations
Map dataSubtomogram average of additional positive annotations from Template Learning that are missed by previous expert-validations
Sample
  • Organelle or cellular component: S. pombe cells
KeywordsComplex / RIBOSOME
Biological speciesSchizosaccharomyces pombe (fission yeast)
Methodsubtomogram averaging / cryo EM / Resolution: 18.0 Å
AuthorsEltsov M / Harastani M
Funding support France, 5 items
OrganizationGrant numberCountry
Agence Nationale de la Recherche (ANR)ANR-10-INSB-005 France
Agence Nationale de la Recherche (ANR)ANR-20-CE11-0020-02 France
Agence Nationale de la Recherche (ANR)ANR-23-CE45-0012-01 France
Agence Nationale de la Recherche (ANR)ANR-17-EURE-0023 France
Agence Nationale de la Recherche (ANR)ANR-23-CE45-0012-03 France
CitationJournal: Nat Commun / Year: 2025
Title: Template Learning: Deep learning with domain randomization for particle picking in cryo-electron tomography.
Authors: Mohamad Harastani / Gurudatt Patra / Charles Kervrann / Mikhail Eltsov /
Abstract: Cryo-electron tomography (cryo-ET) enables three-dimensional visualization of biomolecules and cellular components in their near-native state. A key challenge in cryo-ET data analysis is particle ...Cryo-electron tomography (cryo-ET) enables three-dimensional visualization of biomolecules and cellular components in their near-native state. A key challenge in cryo-ET data analysis is particle picking, often performed by template matching, which relies on cross-correlating tomograms with known structural templates. Current deep learning-based methods improve accuracy but require labor-intensive annotated datasets for supervised training. Here, we present Template Learning, a technique that combines deep learning accuracy with the convenience of training on biomolecular templates via domain randomization. Template Learning automates synthetic dataset generation, modeling molecular crowding, structural variability, and data acquisition variation, thereby reducing or eliminating the need for annotated experimental data. We show that models trained using Template Learning, and optionally fine-tuned with experimental data, outperform those trained solely on annotations. Furthermore, Template Learning provides higher precision and more uniform orientation detection than template matching, particularly for small non-spherical particles. Template Learning software is open-source, Python-based, and GPU/CPU parallelized.
History
DepositionSep 29, 2024-
Header (metadata) releaseOct 8, 2025-
Map releaseOct 8, 2025-
UpdateOct 15, 2025-
Current statusOct 15, 2025Processing site: PDBe / Status: Released

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Structure visualization

Supplemental images

emd_51653.png

Downloads & links

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Map

FileDownload / File: emd_51653.map.gz / Format: CCP4 / Size: 10.5 MB / Type: IMAGE STORED AS FLOATING POINT NUMBER (4 BYTES)
AnnotationSubtomogram average of additional positive annotations from Template Learning that are missed by previous expert-validations
Projections & slices

Image control

Size
Brightness
Contrast
Others
AxesZ (Sec.)Y (Row.)X (Col.)
3.37 Å/pix.
x 140 pix.
= 471.8 Å		3.37 Å/pix.
x 140 pix.
= 471.8 Å		3.37 Å/pix.
x 140 pix.
= 471.8 Å

Surface

Projections

Slices (1/3)

Slices (1/2)

Slices (2/3)

Images are generated by Spider.

Voxel sizeX=Y=Z: 3.37 Å
Density

Histogram

Histogram (log scale)
Contour LevelBy AUTHOR: 0.4
Minimum - Maximum-0.7907679 - 1.6368662
Average (Standard dev.)-0.0033377183 (±0.16319938)
SymmetrySpace group: 1
Details

EMDB XML:

Map geometry
Axis orderXYZ
Origin000
Dimensions140140140
Spacing140140140
CellA=B=C: 471.8 Å
α=β=γ: 90.0 °

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Supplemental data

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Half map: half map 2

Fileemd_51653_half_map_1.map
Annotationhalf map 2
Projections & Slices
AxesZYX

Projections

Slices (1/2)
Density Histograms

Histogram

Histogram (log scale)

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Half map: half map 1

Fileemd_51653_half_map_2.map
Annotationhalf map 1
Projections & Slices
AxesZYX

Projections

Slices (1/2)
Density Histograms

Histogram

Histogram (log scale)

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Sample components

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Entire : S. pombe cells

EntireName: S. pombe cells
Components
  • Organelle or cellular component: S. pombe cells

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Supramolecule #1: S. pombe cells

SupramoleculeName: S. pombe cells / type: organelle_or_cellular_component / ID: 1 / Parent: 0
Details: This STA experiment used previously published cryo-ET data deposited in EMPIAR under entry number EMPIAR-10988 (original citation: https://doi.org/10.1038/s41592-022-01746-2). No sample ...Details: This STA experiment used previously published cryo-ET data deposited in EMPIAR under entry number EMPIAR-10988 (original citation: https://doi.org/10.1038/s41592-022-01746-2). No sample preparation or data collection was performed by the authors.
Source (natural)Organism: Schizosaccharomyces pombe (fission yeast)

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Experimental details

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Structure determination

Methodcryo EM
Processingsubtomogram averaging
Aggregation statecell

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Sample preparation

BufferpH: 7
VitrificationCryogen name: ETHANE
DetailsThis STA experiment used previously published cryo-ET data deposited in EMPIAR under entry number EMPIAR-10988 (original citation: https://doi.org/10.1038/s41592-022-01746-2). No sample preparation or data collection was performed by the authors.

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Electron microscopy

MicroscopeTFS KRIOS
DetailsThis STA experiment used previously published cryo-ET data deposited in EMPIAR under entry number EMPIAR-10988 (original citation: https://doi.org/10.1038/s41592-022-01746-2). No sample preparation or data collection was performed by the authors.
Image recordingFilm or detector model: GATAN K2 SUMMIT (4k x 4k) / Average electron dose: 3.0 e/Å2
Electron beamAcceleration voltage: 300 kV / Electron source: FIELD EMISSION GUN
Electron opticsIllumination mode: OTHER / Imaging mode: BRIGHT FIELD / Nominal defocus max: 4.5 µm / Nominal defocus min: 1.5 µm
Experimental equipment
Model: Titan Krios / Image courtesy: FEI Company

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Image processing

Final reconstructionApplied symmetry - Point group: C1 (asymmetric) / Resolution.type: BY AUTHOR / Resolution: 18.0 Å / Resolution method: FSC 0.143 CUT-OFF / Number subtomograms used: 1600
ExtractionNumber tomograms: 10 / Number images used: 1600
CTF correctionType: PHASE FLIPPING AND AMPLITUDE CORRECTION
Final angle assignmentType: MAXIMUM LIKELIHOOD
FSC plot (resolution estimation)

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