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 "slug": "cryotomography",
 "title": "Cryotomography",
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 "excerpt": "Cryotomography, or cryo-electron tomography (cryo-ET), is an electron microscopy method that reconstructs 3D density maps of vitrified biological samples from projection images recorded at a series of tilt angles.",
 "snippet": "Cryotomography, or cryo-electron tomography (cryo-ET), is an electron microscopy method that reconstructs 3D density maps of vitrified biological samples from projection images recorded at a series of tilt angles.",
 "node": "life.biology.biochemistry.practice.methods",
 "markdown": "# Cryotomography\n\nCryotomography (cryo-electron tomography, cryo-ET) is an electron microscopy method that reconstructs three-dimensional density maps of vitrified biological samples from projection images recorded at a series of tilt angles. Because the sample is frozen so rapidly that water forms amorphous ice, structures are preserved in a near-native, hydrated state. The direct product is a tomogram, a 3D volume whose intensities are roughly proportional to the mass of the underlying atoms.<sup>[1](https://www.annualreviews.org/content/journals/10.1146/annurev-biophys-111622-091327)</sup> A single tomogram of a cell or organelle resolves features at roughly 2–5 nm; averaging many copies of a repeating particle by subtomogram averaging (STA) pushes resolution to 3–10 Å, and in situ reconstructions of abundant complexes such as ribosomes have reached 3.4 Å.<sup>[2](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)</sup><sup> • </sup><sup>[1](https://www.annualreviews.org/content/journals/10.1146/annurev-biophys-111622-091327)</sup>\n\n| Key fact | Value |\n|---|---|\n| Product | 3D density map (tomogram); intensities roughly proportional to mass<sup>[1](https://www.annualreviews.org/content/journals/10.1146/annurev-biophys-111622-091327)</sup> |\n| Resolution | ~2–5 nm per tomogram; 3–10 Å by subtomogram averaging<sup>[2](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)</sup> |\n| Tilt range and increment | typically −60° to +60° in 1–3° steps<sup>[2](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)</sup> |\n| Total dose per tilt series | typically 40–120 e⁻/Å²; reported ranges extend to 90–240 e⁻/Å²<sup>[3](https://cryoem101.org/chapter-4-et/)</sup><sup> • </sup><sup>[4](https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.934465/full)</sup> |\n| Acquisition time | ~20–40 min for a tilt series of ~100 images<sup>[5](https://doi.org/10.1016/j.cell.2022.06.034)</sup> |\n| Sample thickness for imaging | ≤~200 nm for TEM; direct imaging limited to ~500 nm, so most cells require thinning<sup>[2](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)</sup><sup> • </sup><sup>[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC8383006/)</sup> |\n| Detection limit for single particles | roughly 200–400 kDa, depending on shape and environment<sup>[5](https://doi.org/10.1016/j.cell.2022.06.034)</sup> |\n\n## How it works\n\nA transmission electron microscope forms a 2D projection of the sample's scattering potential along the beam direction. Tilting the vitrified sample in steps and recording one image per angle yields a tilt series, a set of projections of the same 3D object from different directions. Each projection samples a plane through the object's 3D [Fourier transform](https://www.edgepedia.org/fourier-transform), so a tilt series limited to ±60° leaves a wedge-shaped region of Fourier space unsampled, the missing wedge, which causes elongation artifacts parallel to the beam; collecting a second tilt series about a perpendicular axis (dual-axis tomography) reduces the missing region to a pyramid.<sup>[7](https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.13948)</sup>\n\nThe aligned tilt series is reconstructed into a volume, most commonly by weighted back-projection (WBP), which operates in Fourier space, is non-iterative, and preserves high-resolution information, which matters for subtomogram averaging.<sup>[8](https://cryoem101.org/cryoet-chapter-5/)</sup><sup> • </sup><sup>[7](https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.13948)</sup>\n\n## How it is done\n\n**Vitrification.** Thin specimens are plunge-frozen into a cryogen such as liquid ethane, with cooling rates of about 10^6 °C/s; one protocol family applies this to samples below 500 nm, while practitioner reviews describe plunge freezing for specimens up to ~10 µm thick.<sup>[2](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)</sup><sup> • </sup><sup>[9](https://www.cambridge.org/core/journals/quarterly-reviews-of-biophysics/article/structural-biology-inside-multicellular-specimens-using-electron-cryotomography/089572D9BA1C6001DB3FDB5C77DA267F)</sup><sup> • </sup><sup>[33](https://pmc.ncbi.nlm.nih.gov/articles/PMC7617309/)</sup> Thicker specimens and tissue are vitrified by high-pressure freezing, which cools samples under roughly 2,000–2,100 bar and produces vitrified layers 10–200 µm thick.<sup>[10](https://www.osti.gov/servlets/purl/3020406)</sup><sup> • </sup><sup>[11](https://journals.asm.org/doi/10.1128/jvi.01085-23)</sup> Because TEM imaging requires samples no thicker than about 200 nm (some reviews quote 0.3–0.5 µm), cells are thinned by cryo-focused ion beam (cryo-FIB) milling at cryogenic temperature, which ablates material with a gallium ion beam until an electron-transparent lamella (thin milled slice of frozen sample, electron-transparent) remains.<sup>[2](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)</sup><sup> • </sup><sup>[10](https://www.osti.gov/servlets/purl/3020406)</sup><sup> • </sup><sup>[11](https://journals.asm.org/doi/10.1128/jvi.01085-23)</sup>\n\n**Fiducials and acquisition.** [Colloidal gold](https://www.edgepedia.org/colloidal-gold) beads, typically 5–20 nm, added before vitrification serve as alignment markers.<sup>[7](https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.13948)</sup> The stage is tilted, usually within ±60° (stages reach ±70°), in 1–3° increments, recording a movie stack of 3–7 frames at each tilt.<sup>[2](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)</sup><sup> • </sup><sup>[3](https://cryoem101.org/chapter-4-et/)</sup> Three tilt schemes are common: continuous, bidirectional, and dose-symmetric. The dose-symmetric scheme starts at 0° and then alternates between the two tilt sides at progressively larger absolute tilts, so that the most informative low-tilt images, which transfer more information because of the lower effective thickness, are recorded before dose accumulates.<sup>[7](https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.13948)</sup>\n\n**Alignment and reconstruction.** [Alignment](https://www.edgepedia.org/alignment) proceeds from coarse (whole-image shifts) to fine (shifts, rotations, magnifications, and sample deformation), using fiducials, patch tracking, or fiducialless cross-correlation aided by direct detectors.<sup>[8](https://cryoem101.org/cryoet-chapter-5/)</sup> The aligned series is back-projected into a tomogram.<sup>[2](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)</sup> Repeating particles are then extracted, aligned, and averaged (subtomogram averaging), which raises signal-to-noise and fills in the missing wedge because different particles lie in different orientations.<sup>[8](https://cryoem101.org/cryoet-chapter-5/)</sup><sup> • </sup><sup>[12](https://pmc.ncbi.nlm.nih.gov/articles/PMC3254243/)</sup>\n\n## Origin\n\nThe method rests on two earlier developments consolidated in the literature: cryo-electron microscopy of vitrified specimens, reviewed by [Jacques Dubochet](https://www.edgepedia.org/jacques-dubochet), Marc Adrian, and colleagues in 1988, and the programmatic perspective on molecular and cellular electron tomography by Abraham J. Koster, Rudo Grimm, and colleagues in 1997.<sup>[13](https://doi.org/10.1017/s0033583500004297)</sup><sup> • </sup><sup>[14](https://doi.org/10.1006/jsbi.1997.3933)</sup> An early cellular demonstration came from Rudo Grimm and colleagues in 1998, who reconstructed plunge-frozen archaeal cells by automated energy-filtered tomography at 120 kV to 20–40 nm resolution from tilt series of 50–140 images.<sup>[15](https://doi.org/10.1016/s0006-3495%2898%2974028-7)</sup> Ohad Medalia, Igor Weber, and colleagues reported in 2002 the first cryo-electron tomography of an intact eukaryotic cell, resolving the actin cytoskeleton of <i>Dictyostelium</i> at 5–6 nm and identifying single macromolecules such as the 26S proteasome.<sup>[16](https://doi.org/10.1126/science.1076184)</sup> Eukaryotic cells beyond thin peripheral regions became accessible after Michael Marko, Chyongere Hsieh, and colleagues published the first cryo-FIB thinning of frozen-hydrated biological specimens in 2007.<sup>[17](https://doi.org/10.1038/nmeth1014)</sup><sup> • </sup><sup>[5](https://doi.org/10.1016/j.cell.2022.06.034)</sup> The dose-symmetric tilt scheme was implemented in a paper by Wim J.H. Hagen, William Wan, and John A.G. Briggs in 2016 and has since become standard.<sup>[18](https://doi.org/10.1016/j.jsb.2016.06.007)</sup><sup> • </sup><sup>[19](https://www.nature.com/articles/s41592-023-01783-5)</sup>\n\n## Variants\n\n**Whole cells versus lamellae.** Plunge-frozen cells, virus particles, and isolated complexes can be imaged directly if thin enough. Thicker cells and tissue require cryo-FIB lamellae.<sup>[1](https://www.annualreviews.org/content/journals/10.1146/annurev-biophys-111622-091327)</sup><sup> • </sup><sup>[20](https://www.mdpi.com/2073-4409/8/1/57)</sup><sup> • </sup><sup>[9](https://www.cambridge.org/core/journals/quarterly-reviews-of-biophysics/article/structural-biology-inside-multicellular-specimens-using-electron-cryotomography/089572D9BA1C6001DB3FDB5C77DA267F)</sup> Cryo-FIB lift-out detaches a lamella from bulk vitrified tissue, enabling molecular-resolution cryo-ET within native <i>[Caenorhabditis elegans](https://www.edgepedia.org/caenorhabditis-elegans)</i> tissue.<sup>[21](https://doi.org/10.1038/s41592-019-0497-5)</sup> Plasma-source FIB milling (xenon plasma) has been developed for higher-throughput thinning and in situ structure determination.<sup>[22](https://doi.org/10.1038/s41467-023-36372-9)</sup><sup> • </sup><sup>[11](https://journals.asm.org/doi/10.1128/jvi.01085-23)</sup>\n\n**Subtomogram averaging.** STA accounts for 8% of maps in the EMDB, more than helical reconstruction and electron crystallography combined, and has produced structures below 4 Å for in situ complexes and 2–4 Å for ex vivo or in vitro complexes.<sup>[23](https://www.mdpi.com/1422-0067/22/12/6177)</sup> Software packages include Dynamo, EMAN2, emClarity (Benjamin A. Himes and [Peijun Zhang](https://www.edgepedia.org/peijun-zhang), 2018), M, PEET, i3, PyTom, StopGap, and RELION, whose electron-tomography pipeline appeared in RELION-5 (Alister Burt, Bogdan Toader, and colleagues, 2024); AreTomo (Shawn Zheng and colleagues, 2022) provides automated marker-free alignment and reconstruction.<sup>[1](https://www.annualreviews.org/content/journals/10.1146/annurev-biophys-111622-091327)</sup><sup> • </sup><sup>[23](https://www.mdpi.com/1422-0067/22/12/6177)</sup><sup> • </sup><sup>[24](https://doi.org/10.1038/s41592-018-0167-z)</sup><sup> • </sup><sup>[25](https://doi.org/10.1002/2211-5463.13873)</sup><sup> • </sup><sup>[26](https://doi.org/10.1016/j.yjsbx.2022.100068)</sup>\n\n**Contrast enhancement.** Direct electron detectors replaced CCDs, offering single-electron sensitivity, higher signal-to-noise, and movie-frame dose fractionation for drift correction.<sup>[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC8383006/)</sup>\n\n**Deep learning and throughput.** Topaz-denoise (Tristan Bepler, Kotaro Kelley, and colleagues, 2020) trained general denoising models on thousands of cryo-EM micrographs collected across a wide range of imaging conditions, with applicability to cryo-ET tomograms, and DeepDeWedge (Simon Wiedemann and Reinhard Heckel, 2024) performs simultaneous denoising and missing-wedge reconstruction.<sup>[27](https://doi.org/10.1038/s41467-020-18952-1)</sup><sup> • </sup><sup>[28](https://doi.org/10.1038/s41467-024-51438-y)</sup> For heterogeneity, tomoDRGN (Barrett M. Powell and Joseph H. Davis, 2024) extends the cryoDRGN architecture to cryo-ET and is described as the first neural network framework modeling compositional and conformational heterogeneity per particle.<sup>[29](https://doi.org/10.1038/s41592-024-02210-z)</sup> Throughput has risen on several fronts: PACE-tomo (Fabian Eisenstein and colleagues, 2022) collects hundreds of tilt series per session, SPACE-tomo automates lamella definition and acquisition with machine learning, and the Waffle method (Kotaro Kelley and colleagues, 2022) raised FIB-milling yield to ~32 tomograms per lamella when combined with high-pressure freezing versus ~8 for plunge freezing plus FIB-SEM.<sup>[9](https://www.cambridge.org/core/journals/quarterly-reviews-of-biophysics/article/structural-biology-inside-multicellular-specimens-using-electron-cryotomography/089572D9BA1C6001DB3FDB5C77DA267F)</sup><sup> • </sup><sup>[30](https://doi.org/10.1038/s41592-022-01690-1)</sup><sup> • </sup><sup>[31](https://doi.org/10.1038/s41467-022-29501-3)</sup>\n\n## Applications\n\nIn situ STA has resolved the nuclear pore complex, ribosomes, microtubules, proteasomes, LRRK2 on microtubules, Arp2/3, the COPI coat, nucleosomes, a bacterial chemosensory array, and a bacterial gap junction.<sup>[1](https://www.annualreviews.org/content/journals/10.1146/annurev-biophys-111622-091327)</sup> In virology, cryo-ET of FIB-milled lamellae revealed the compartmentalization of phage 201φ2-1 in <i>[Pseudomonas chlororaphis](https://www.edgepedia.org/pseudomonas-chlororaphis)</i>, with a bipolar tubulin-based spindle separating DNA processing from translation.<sup>[11](https://journals.asm.org/doi/10.1128/jvi.01085-23)</sup> Early STA on FIB lamellae mapped the molecular sociology of the HeLa cell nuclear periphery.<sup>[32](https://doi.org/10.1126/science.aad8857)</sup>\n\n## Limitations and alternatives\n\nThe missing wedge anisotropy is fundamental; subtomogram averaging corrects it for repeated particles, but unique cellular structures cannot be averaged, and neural-network approaches such as IsoNet fill the wedge only up to about 30 Å structural information at 10 Å pixel size.<sup>[8](https://cryoem101.org/cryoet-chapter-5/)</sup> [Radiation damage](https://www.edgepedia.org/radiation-damage) sets a hard dose budget; extensive damage with ice bubbling is reported around 120–160 e⁻/Å².<sup>[23](https://www.mdpi.com/1422-0067/22/12/6177)</sup><sup> • </sup><sup>[7](https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.13948)</sup> Thickness is limited by the electron mean free path; most cells exceed 500 nm and must be milled.<sup>[1](https://www.annualreviews.org/content/journals/10.1146/annurev-biophys-111622-091327)</sup><sup> • </sup><sup>[23](https://www.mdpi.com/1422-0067/22/12/6177)</sup><sup> • </sup><sup>[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC8383006/)</sup> Gallium-ion milling damages specimen to 30–60 nm depth from the lamella surface, and lamellae thinner than 180 nm give no significant STA resolution gain, likely due to radiation damage.<sup>[9](https://www.cambridge.org/core/journals/quarterly-reviews-of-biophysics/article/structural-biology-inside-multicellular-specimens-using-electron-cryotomography/089572D9BA1C6001DB3FDB5C77DA267F)</sup> The alternative of vitreous sectioning (CEMOVIS) suffers knife marks, crevasses, and compression artifacts.<sup>[4](https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.934465/full)</sup> Compared with single-particle cryo-EM, cryo-ET spends far more dose per dataset (90–240 versus 10–50 e⁻/Å²), and direct (in vitro) cryo-ET is restricted to samples thinner than ~300 nm.<sup>[4](https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.934465/full)</sup>\n\n## References\n\n1. [Bringing Structure to Cell Biology with Cryo-Electron Tomography](https://www.annualreviews.org/content/journals/10.1146/annurev-biophys-111622-091327)\n2. [CryoET Workflow - CryoET Data Portal Documentation](https://chanzuckerberg.github.io/cryoet-data-portal/stable/cryoet_workflow.html)\n3. [Cryo-ET Chapter 4 – Cryo EM 101](https://cryoem101.org/chapter-4-et/)\n4. [Quantitative Cryo-Electron Tomography](https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.934465/full)\n5. [Cryo-electron tomography: A long journey to the inner space of cells (Cell, 2022)](https://doi.org/10.1016/j.cell.2022.06.034)\n6. [Challenges and triumphs in cryo-electron tomography](https://pmc.ncbi.nlm.nih.gov/articles/PMC8383006/)\n7. [Cryo-electron tomography of cellular landscapes (FEBS Letters review)](https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.13948)\n8. [CryoET Chapter 5 – Cryo EM 101](https://cryoem101.org/cryoet-chapter-5/)\n9. [Structural biology inside multicellular specimens using electron cryotomography](https://www.cambridge.org/core/journals/quarterly-reviews-of-biophysics/article/structural-biology-inside-multicellular-specimens-using-electron-cryotomography/089572D9BA1C6001DB3FDB5C77DA267F)\n10. [Cryogenic electron tomography by the numbers: Charting underexplored lineages in structural cell biology](https://www.osti.gov/servlets/purl/3020406)\n11. [Visualizing the virus world inside the cell by cryo-electron tomography](https://journals.asm.org/doi/10.1128/jvi.01085-23)\n12. [Cryo-Electron Tomography for Structural Characterization of Macromolecular Complexes](https://pmc.ncbi.nlm.nih.gov/articles/PMC3254243/)\n13. [Jacques Dubochet and colleagues (1988). Cryo-electron microscopy of vitrified specimens. Quarterly Reviews of Biophysics.](https://doi.org/10.1017/s0033583500004297)\n14. [Abraham J. Koster and colleagues (1997). Perspectives of Molecular and Cellular Electron Tomography. Journal of Structural Biology.](https://doi.org/10.1006/jsbi.1997.3933)\n15. [Electron Tomography of Ice-Embedded Prokaryotic Cells (Biophysical Journal, 1998)](https://doi.org/10.1016/s0006-3495%2898%2974028-7)\n16. [Ohad Medalia and colleagues (2002). Macromolecular Architecture in Eukaryotic Cells Visualized by Cryoelectron Tomography. Science.](https://doi.org/10.1126/science.1076184)\n17. [Michael Marko and colleagues (2007). Focused-ion-beam thinning of frozen-hydrated biological specimens for cryo-electron microscopy. Nature Methods.](https://doi.org/10.1038/nmeth1014)\n18. [Wim J.H. Hagen, William Wan, John A.G. Briggs (2016). Implementation of a cryo-electron tomography tilt-scheme optimized for high resolution subtomogram averaging. Journal of Structural Biology.](https://doi.org/10.1016/j.jsb.2016.06.007)\n19. [Cryo-electron tomography on focused ion beam lamellae transforms structural cell biology](https://www.nature.com/articles/s41592-023-01783-5)\n20. [Cellular and Structural Studies of Eukaryotic Cells by Cryo-Electron Tomography](https://www.mdpi.com/2073-4409/8/1/57)\n21. [Miroslava Schaffer and colleagues (2019). A cryo-FIB lift-out technique enables molecular-resolution cryo-ET within native Caenorhabditis elegans tissue. Nature Methods.](https://doi.org/10.1038/s41592-019-0497-5)\n22. [Casper Berger and colleagues (2023). Plasma FIB milling for the determination of structures in situ. Nature Communications.](https://doi.org/10.1038/s41467-023-36372-9)\n23. [Coming of Age: Cryo-Electron Tomography as a Versatile Tool to Generate High-Resolution Structures at Cellular/Biological Interfaces](https://www.mdpi.com/1422-0067/22/12/6177)\n24. [Benjamin A. Himes, Peijun Zhang (2018). emClarity: software for high-resolution cryo-electron tomography and subtomogram averaging. Nature Methods.](https://doi.org/10.1038/s41592-018-0167-z)\n25. [Alister Burt and colleagues (2024). An image processing pipeline for electron cryo‐tomography in RELION ‐5. FEBS Open Bio.](https://doi.org/10.1002/2211-5463.13873)\n26. [Shawn Zheng and colleagues (2022). AreTomo: An integrated software package for automated marker-free, motion-corrected cryo-electron tomographic alignment and reconstruction. Journal of Structural Biology X.](https://doi.org/10.1016/j.yjsbx.2022.100068)\n27. [Tristan Bepler and colleagues (2020). Topaz-Denoise: general deep denoising models for cryoEM and cryoET. Nature Communications.](https://doi.org/10.1038/s41467-020-18952-1)\n28. [Simon Wiedemann, Reinhard Heckel (2024). A deep learning method for simultaneous denoising and missing wedge reconstruction in cryogenic electron tomography. Nature Communications.](https://doi.org/10.1038/s41467-024-51438-y)\n29. [Barrett M. Powell, Joseph H. Davis (2024). Learning structural heterogeneity from cryo-electron sub-tomograms with tomoDRGN. Nature Methods.](https://doi.org/10.1038/s41592-024-02210-z)\n30. [Fabian Eisenstein and colleagues (2022). Parallel cryo electron tomography on in situ lamellae. Nature Methods.](https://doi.org/10.1038/s41592-022-01690-1)\n31. [Kotaro Kelley and colleagues (2022). Waffle Method: A general and flexible approach for improving throughput in FIB-milling. Nature Communications.](https://doi.org/10.1038/s41467-022-29501-3)\n32. [Julia Mahamid and colleagues (2016). Visualizing the molecular sociology at the HeLa cell nuclear periphery. Science.](https://doi.org/10.1126/science.aad8857)\n33. [pmc.ncbi.nlm.nih.gov](https://pmc.ncbi.nlm.nih.gov/articles/PMC7617309/)\n\n---\n*Topic: Encyclopedia › Life and health › Biological foundations › Biochemistry and metabolism › Biochemistry field and methods › Biochemical methods and techniques*\n\n*Initially written Sep 29, 2026 · Reviewed: Sep 30, 2026 · Edited: Sep 30, 2026 · Last review: Sep 30, 2026*\n\n*Copyright 2026 EdgeChat AI, a subsidiary of Biostate AI.*\n\nLicense: Edgepedia Community License 1.0, https://www.edgepedia.org/edgepedia/license\n",
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 "credit": "\"Cryotomography\", Edgepedia (EdgeChat), https://www.edgepedia.org/cryotomography. Edgepedia Community License 1.0.",
 "credit_md": "\"[Cryotomography](https://www.edgepedia.org/cryotomography)\", Edgepedia (EdgeChat), [https://www.edgepedia.org/cryotomography](https://www.edgepedia.org/cryotomography). [Edgepedia Community License 1.0](https://www.edgepedia.org/edgepedia/license).",
 "credit_html": "\"<a href=\"https://www.edgepedia.org/cryotomography\">Cryotomography</a>\", Edgepedia (EdgeChat), <a href=\"https://www.edgepedia.org/cryotomography\">https://www.edgepedia.org/cryotomography</a>. <a href=\"https://www.edgepedia.org/edgepedia/license\">Edgepedia Community License 1.0</a>.",
 "speakable": "Cryotomography, or cryo-electron tomography, is an electron microscopy method that reconstructs 3D density maps of vitrified biological samples from projection images recorded at a series of tilt angles."
}
