Abstract
Cryo-electron microscopy single particle analysis (cryo-EM SPA) and cryo-electron tomography (cryo-ET) have historically been employed as distinct approaches for investigating molecular structures of disparate sample types, focusing on highly purified biological macromolecules and in situ cellular contexts, respectively. However, these techniques offer inherently complementary structural insights that, when combined, provide a more comprehensive understanding of complex biological systems. For example, if both techniques are applied to the same purified biological macromolecules, cryo-ET has the ability to resolve highly flexible yet strong signal features on individual target molecule which will not be preserved in the high-resolution cryo-EM SPA results. In this review, we highlight recent achievements utilizing such application to unveil new insights into the chromatin assembly and activities of DNA-protein assemblies. This convergence of cryo-EM SPA and cryo-ET holds great promise for elucidating new structural aspects of these essential molecular processes.
Graphical Abstract

Complementary structural information provided by per-particle cryo-ET analysis and cryo-EM single particle analysis.
Cryo-EM single particle analysis generates a high-resolution map of the structurally conserved region among particles while cryo-ET characterizes, in 3D, the heterogeneous features on a per-particle basis. The joining of these techniques reveals heterogeneous organization about a highly resolved core structure.
In recent years, the field of structural biology has been revolutionized by cryogenic electron microscopy (cryo-EM), driven by advancements of its hardware, software, and sample preparation techniques [1]. Two prominent methods for structural elucidation, cryo-EM single particle analysis (SPA) and cryo-electron tomography (cryo-ET), have significantly contributed to this revolution. Cryo-EM SPA is the preferred choice for solving structures of highly purified biological macromolecules [1]. This technique relies on gathering 2D projections of thousands of randomly oriented molecules, which are then computationally aligned to generate high-resolution 3D density maps. While powerful, a caveat of this method is that only highly reoccurring and stable features are retained while unique and flexible features are often left unresolved. On the other hand, cryo-ET has established itself as the premier technique for resolving macromolecular structures within their native cellular context [2]. Unlike SPA, cryo-ET collects 2D projections of the same region of interest while tilting the sample, which are then used to calculate a 3D volume (tomogram) of that region with its unique and flexible features preserved [2].
While canonically applied to different type of samples, cryo-EM SPA and cryo-ET offer highly complementary information. Applying both methods on the same type of sample could allow for the unresolved flexible features lost in cryo-EM SPA to be visualized through cryo-ET and the high-resolution cryo-EM SPA result to supplement the relatively lower resolution but already 3D particles seen in cryo-ET. Therefore, a hybrid approach of cryo-EM SPA and cryo-ET will provide a more comprehensive structural view of biological macromolecules, especially those featuring highly flexible yet strong signal features, such as long DNA strains associated with protein molecules. Below we use the recent studies of chromatin organization and DNA-protein assemblies to highlight the power of this emerging usage of cryo-EM structural analysis.
Nucleosome arrangements inside cells
Cryo-EM SPA studies of nucleosomes have provided invaluable insights into DNA organizations of these subunits of chromatin [3–5*]. However, these studies are typically limited to a single nucleosome core particle or an array of a few particles. Interestingly, Arimura et al. isolated native interphase as well as metaphase nucleosomes from Xenopus egg extracts and used cryo-EM SPA to solve the structure of each nucleosome [5*]. The authors found that the structure of these native nucleosomes was, on average, indistinguishable from previous structures [5*]. However, such focus of SPA on stable and reoccurring features limits its ability to capture the full heterogeneity of chromatin that is necessary to accommodate dynamic biological processes such as DNA replication, repair, and transcription. In contrast, cryo-ET has the unique capability of visualizing individual nucleosomes in 3D [6–9]. Furthermore, cryo-ET can tolerate thicker sample thicknesses of about 400 nm [10]. These attributes have allowed cryo-ET to elucidate chromatin organization and map the position and orientation of nucleosomes in situ within the crowded nuclear environment [6–9]. There the nucleosomes were found to have an irregular distribution throughout the nucleus. In addition, variations of DNA packaging around each nucleosome were revealed [9,11]. The distance between DNA gyres per nucleosome spanned 2-4 nm compared to what was resolved by X-ray crystallography and cryo-EM SPA structures which is about 3 nm [11–13]. The entry and exit of DNA wrapped around nucleosomes were variable and deviated from the canonical 1.65 superhelical turns [9]. It is important to note that the characterization of chromatin organization in situ relied on a template matching approach to identify nucleosomes [6–9]. Therefore, the heterogeneity is further exacerbated because nucleosomes that are too conformationally heterogeneous or variably bound by different proteins may be missed in these analyses. This characterization of chromatin and individual nucleosomes in situ highlights the variability unable to be captured by cryo-EM SPA alone. Notably, these studies do not capture a critical aspect of chromatin organization, namely the interconnectivity. For example, nucleosomes positioned next to one another in 3D may be far apart along the linear DNA (i.e., topologically associating domains). Therefore, visualization of the interconnectivity will reveal insights into the nucleosome spacing along DNA, boundaries between chromatin regions, the trajectory of chromatin, and any patterns associated with these features. Cryo-ET is well positioned to visualize highly flexible yet strong signal features such as DNA, but these analyses have been limited. A primary reason for not assigning the interconnectivity was mostly because the linker DNA could not be unambiguously visualized due to its dense packing in situ.
DNA arrangement in isolated chromatin
To investigate linker DNA conformation within the context of chromatin organization, cryo-ET has been employed to image reconstituted and native chromatin with different components. Therefore, a more direct relationship between chromatin organization and different sample conditions may be observed. Furthermore, this approach allows for the sample freezing in thinner ice, enhancing contrast for 3D visualization and quantitative conformational analysis of linker DNA.
Reconstituted Chromatin
The assembly of reconstituted chromatin has allowed researchers to dissect linker DNA organization as a function of various histones. For example, it was observed that centromere protein A (CENP-A), a histone H3 variant, reduces the angle between entry and exit linker DNA strands, resulting in greater compaction of nucleosome arrays compared to canonical histone H3 [14]. Additionally, histone H1 was found to facilitate the invasion of free entry DNA into one of the inner nucleosome core particles of a nucleosome array, with the rate of condensate formation of nucleosome arrays increasing in correlation with histone H1 concentration [15].
While linker DNA was characterized under various conditions, these investigations utilized the Widom 601 nucleosome positioning sequence to reconstitute the chromatin [14–16]. It is worth noting that this sequence, although valuable for biochemical studies due to its reliable nucleosome positioning, may not fully represent biological conditions as it can adopt non-natural configurations and bias the analysis [17–19**].
Chromosomes
To capture a more natural chromatin organization, Beel et al. inspected purified mitotic chromosomes by cryo-ET [20**]. This approach, distinct from previous studies inspecting native chromatin in densely packed in situ conditions, allowed for partial chromatin decondensation within the physiological range. As a result, the authors were able to clearly visualize the connectivity between nucleosomes (Figure 1A) [20**]. It was observed that the DNA linker lengths covered a broad range (10-110 bp) (Figure 1B) and the angle between entry and exit linker per nucleosome also varied between 40 and 80 degrees (Figure 1C). These key observations highlight that the canonical 146bp nucleosome core particle represents an average and that nucleosomes are variably spaced apart and over- or under-wrapped. Similarly, Jentik et al. characterized purified human chromatin that was decondensed by fragmentation via micrococcal nuclease (MNase) [19**]. Additionally, the authors of this study utilized deep-learning-based regression models to denoise the tomograms to facilitate segmentation. Through this approach, linker DNA and even histone tails were visualized and allowed characterization of chromatin organization as a function of Mg2+ and PAD4 dependent citrullination. Interestingly, non-uniform nucleosome stacking was abundant and condensed by the addition of Mg2+ and unfolded by PAD4 mediated citrullination (Figure 1D and 1E). Altogether, 3D analysis by cryo-ET of purified chromatin has revealed DNA organization between nucleosomes at a per-particle level, and these analyses have propelled our understanding of chromatin organization.
Figure 1.

Characterization of Linker DNA and chromatin organization.
(A) A 4-nm slab of a tomogram displayed with inverted contrast. Selected fibers with nucleosome core particle map (8140-EMD [13]) manually docked and linker DNA traced. Scale bars, 10 nm. (B) Cropped densities depicted in mesh representation, with nucleosome core particle map (8140-EMD [13]) manually docked and linker DNA length indicated. (C) Example of DNA entering and exiting nucleosomes. Highlighting the variable angles between DNA entering and exiting nucleosomes. (D) Example subtomogram of fragmented native chromatin treated with 0.75 mM Mg2+(left) with centroid, axis, plane (CAP) modeling of nucleosomes and linker DNA (right). Scale bar, 30 nm. (E) Same as (D) but treated with PAD4. Scale bar, 30 nm. Panels A-C adapted from Beel et al. [20**]; panels D-E adapted from Jentik et al. [19**].
Conformational landscape of purified macromolecular assemblies
The scope of cryo-ET imaging purified DNA-protein assemblies has been expanded beyond the above-mentioned chromatin to isolated DNA containing macromolecules. These complexes offer a particular intriguing subject for cryo-ET analysis, as they may exist in unique states that are challenging to be resolved by cryo-EM SPA.
For example, DNA and RNA origami structures have been analyzed by cryo-ET to elucidate their conformational dynamics and inform their optimization [21–23]. Researchers were able to assess distinct DNA origami structures as a function of gold nanoparticle size [21]. The authors of this study found that 5 nm gold nanoparticles facilitated formation of two different structures while 10 nm gold nanoparticles biased formation into one structure. As these confirmations were not homogeneous, each unique 3D structure was only able to be determined by cryo-ET.
Similarly, cryo-ET was utilized to characterize the assembly process of Mediator Preinitiation Complex (Med-PIC) along DNA and its regulation of transient promoter-enhancer communication using S. cerevisiae as a model system [24**]. Gorbea et al. assembled highly purified transcription factors and prepared the same sample for both cryo-EM SPA and cryo-ET. There, the core protein components were highly resolved using cryo-EM SPA but the DNA was largely missing from the averaged electron density (Figure 2, upper left row). Therefore, the interplay between DNA and the core complex was not understood and its relationship throughout transcription activation remained to be determined. However, cryo-ET and its unique ability to visualize individual molecules in 3D was able to clearly visualize the DNA and trace its organization about the core complex (Figure 2, lower left row). To elucidate the interplay between DNA and the core complex, subtomogram averaging was performed in which each individual particle in a 3D volume (subtomogram) was aligned in 3D and averaged to generate higher-resolution density map of the core protein structure. This procedure allowed the subtomogram average to be fit back into each individually aligned subtomogram to systematically trace DNA and study DNA-protein interaction sites and configurations on a per-particle basis for statistical analysis (Figure 2, lower left row).
Figure 2.

Hybrid application of Cryo-ET and cryo-EM SPA.
Cryo-EM SPA generates a high-resolution map while cryo-ET characterizes the flexible DNA on a per-particle basis. The joining of these techniques reveals flexible DNA organization about a highly resolved core complex which can be studied in the presence of additional transcription factors. Adapted from Gorbea et al. [24**]
The authors of this study observed that Med-PIC is predominantly assembled at the upstream activating sequence (enhancers in higher eukaryotes) in contact with Mediator (Figure 2, upper right panel). Since this configuration is not immediately poised for transcription, this prompted the addition of another general transcription factor to the purified system to generate a more complete Med-PIC (Med-PIC+). The presence of the additional general transcription factor dramatically altered the organization in which Med-PIC+ is primarily assembled at the core promoter in a form amenable to transcription (Figure 2, lower right panel). Furthermore, cryo-ET visualized simultaneous dual DNA contact of both promoters on each PIC suggesting a role in bidirectional transcription. This highlights the utility of cryo-ET per-particle analysis since SPA alone would not have been able to distinguish between simultaneous dual DNA contact of each promoter or individual DNA contact at one promoter. Therefore, the combination of cryo-EM SPA and cryo-ET per-particle analysis facilitated a more complete description of the assembly process of Med-PIC along DNA as it becomes poised for transcription.
Challenges and opportunities for per-particle 3D analysis by cryo-ET
Although there have been significant advances in per-particle 3D analysis by cryo-ET, challenges remain that limit its widespread use.
Data collection speed and quality
A large number of particles is necessary to confidently sample the conformational landscape. However, cryo-ET suffers from lower throughput than cryo-EM SPA. This is mostly due to the time required for accurate tracking during the imaging of the sample from a wide range of angles. Several recent method developments have significantly improved cryo-ET data collection speed, including fast-incremental single exposure methods [25] or parallel/montage imaging of adjacent regions during tilt series collection [26–28]. However, several qualifications about the local geometry of the sample and precision of the electron microscope stage must be met. Therefore, data collection schemes and technology need to be further optimized to make it more widely applicable.
Image restoration and segmentation
For high-resolution structural study, biological samples in general can only tolerate a total electron dosage of ~40-80e/A2 which must be distributed amongst several 2D projections for cryo-ET. This reduces the contrast and number of frames per tilt angle for accurate motion correction. This problem is further exacerbated at higher tilt angles in which the sample thickens. A solution to compensate for the sample thickening for enough image contrast is to increase the dose as the tilt angle increases. However, this causes one to reach the tolerated dose limit much quicker. Collections schemes that reduce the number of 2D projections (e.g., smaller tilt range and larger tilt increments) help stay beneath the tolerated dose limit but are at the expense of increased missing information in the Fourier space. Recent methods have improved data quality post data collection [29**–31*]. For example, deep learning models have been shown to dramatically improve the contrast to aid in per-particle characterization and these methods have been applied to chromatin both purified and in situ [19**,29**–32]. Furthermore, utilizing high-resolution maps obtained by single particle analysis may help deep learning models to facilitate subtomogram averaging and per-particle characterization for other biological samples. It will be exciting to see how these perform on more complex macromolecules.
Current segmentation methods exhibit robustness when it comes to segmenting large, highly contrasting, and repetitive features like membranes, ribosomes, or nucleosomes [33,34]. However, these methods have yet to demonstrate reliability in tracing flexible DNA strands in various context [20**,24**]. Consequently, manual tracing remains the predominant approach, despite being exceedingly laborious and susceptible to user error and bias. Current deep learning models assist in assigning unmodeled density but are restricted to higher-resolution density maps [32,35]. Therefore, the development of new computational approaches capable of assigning unmodeled density during per-particle characterization would greatly benefit these research directions.
Targeting
The development of cryo-ET along with techniques to identify molecules of interest such as cryo-correlative super-resolution light and electron microscopy yields exciting opportunities to explore fundamental biology [36–41]. For example, the overall organization of native chromosomes can be further dissected by relating the local organization to particular proteins of interest (e.g., CENP-A, PAD4) identified by super-resolution cryo-fluorescence microscopy. Similarly, the sub-chromosomal regions such as heterochromatin, euchromatin, or the centromere can be locally analyzed. Additionally, identification of post-translational modifications on particular proteins (e.g., histone citrullination) and their effect on local chromatin organization present another avenue of exploration.
Conclusion:
Cryo-ET, especially on purified samples, is at the forefront to resolve highly flexible yet strong signal features on a per-particle basis. Although this review uses long DNA strands as the example of such features, this approach has the potential for a variety of samples and questions. For example, the core of the nuclear pore complex has been resolved to high resolution while the disordered linker nucleoporins remain to be observed [42–44]. How the disordered nucleoporins are organized about the nuclear pore complex may reveal critical insight into its mechanism and presents as an attractive avenue for this method. Similarly, one may characterize the conformational space of a system as a function of time and visualize conformational transitions and transient states (i.e., time-resolved per-particle characterization). The use of purified samples is ideal because time-resolved cryo-EM requires precise conditions to establish the kinetics of the system [45]. Therefore, sample preparation for time-resolved cryo-EM aligns well with that for cryo-ET per-particle characterization. The dual utilization of cryo-EM SPA and cryo-ET presents an exciting new approach to deepen our structural understanding of these complex molecular processes.
Acknowledgement:
We thank Professor Ben E. Black at the University of Pennsylvania for providing critical reading and comments on this manuscript. This study was supported by a David and Lucile Packard Fellowship for Science and Engineering (2019-69645) and NIH R01GM134020 to Y.-W.C.; NIH R01-GM123233 to K.M.; and NIH F31GM147945 to L.P.
Footnotes
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Declaration of competing interest:
The authors declare no conflict of interest.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
References:
- 1.Kühlbrandt W: The Resolution Revolution. Science 2014, 343:1443–1444. [DOI] [PubMed] [Google Scholar]
- 2.Turk M, Baumeister W: The promise and the challenges of cryo-electron tomography. FEBS Lett 2020, 594:3243–3261. [DOI] [PubMed] [Google Scholar]
- 3.Allu PK, Dawicki-McKenna JM, Van Eeuwen T, Slavin M, Braitbard M, Xu C, Kalisman N, Murakami K, Black BE: Structure of the Human Core Centromeric Nucleosome Complex. Curr Biol 2019, 29:2625–2639 e2625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Takizawa Y, Ho CH, Tachiwana H, Matsunami H, Kobayashi W, Suzuki M, Arimura Y, Hori T, Fukagawa T, Ohi MD, et al. : Cryo-EM Structures of Centromeric Tri-nucleosomes Containing a Central CENP-A Nucleosome. Structure 2020, 28:44–53 e44. [DOI] [PubMed] [Google Scholar]
- 5*.Arimura Y, Shih RM, Froom R, Funabiki H: Structural features of nucleosomes in interphase and metaphase chromosomes. Mol Cell 2021, 81:4377–4397 e4312. [DOI] [PMC free article] [PubMed] [Google Scholar]; The authors resolve the structures of interphase and metaphase nucleosomes using cryo-EM SPA and find them to be virtually identical despite different DNA sequences and existence in different stages of the cell cycle.
- 6.Cai S, Bock D, Pilhofer M, Gan L: The in situ structures of mono-, di-, and trinucleosomes in human heterochromatin. Mol Biol Cell 2018, 29:2450–2457. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Cai S, Chen C, Tan ZY, Huang Y, Shi J, Gan L: Cryo-ET reveals the macromolecular reorganization of S. pombe mitotic chromosomes in vivo. Proc Natl Acad Sci U S A 2018, 115:10977–10982. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Cai S, Song Y, Chen C, Shi J, Gan L: Natural chromatin is heterogeneous and self-associates in vitro. Mol Biol Cell 2018, 29:1652–1663. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tan ZY, Cai S, Noble AJ, Chen JK, Shi J, Gan L: Heterogeneous non-canonical nucleosomes predominate in yeast cells in situ. Elife 2023, 12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Lam V, Villa E: Practical Approaches for Cryo-FIB Milling and Applications for Cellular Cryo-Electron Tomography. Methods Mol Biol 2021, 2215:49–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Eltsov M, Grewe D, Lemercier N, Frangakis A, Livolant F, Leforestier A: Nucleosome conformational variability in solution and in interphase nuclei evidenced by cryo-electron microscopy of vitreous sections. Nucleic Acids Res 2018, 46:9189–9200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Luger KM A; Richmond R; Sargent D; Richmond T: Crystal structure of the nucleosome core particle at 2.8 Å resolution. Nature 1997:251–260. [DOI] [PubMed] [Google Scholar]
- 13.Chua EY, Vogirala VK, Inian O, Wong AS, Nordenskiold L, Plitzko JM, Danev R, Sandin S: 3.9 A structure of the nucleosome core particle determined by phase-plate cryo-EM. Nucleic Acids Res 2016, 44:8013–8019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Geiss CP, Keramisanou D, Sekulic N, Scheffer MP, Black BE, Frangakis AS: CENP-A arrays are more condensed than canonical arrays at low ionic strength. Biophys J 2014, 106:875–882. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Zhang MC D; Liu J; Bustamante C; Gang Ren: Conformational Change of Nucleosome Arrays prior to Phase Separation. Research Square 2023. [Google Scholar]
- 16.Lowary PTW J.: New DNA Sequence Rules for High Affinity Binding to Histone Octamer and Sequence directed Nucleosome Positioning. Journal of Molecular Biology 1998, 276:19–42. [DOI] [PubMed] [Google Scholar]
- 17.Mauney AW, Tokuda JM, Gloss LM, Gonzalez O, Pollack L: Local DNA Sequence Controls Asymmetry of DNA Unwrapping from Nucleosome Core Particles. Biophys J 2018, 115:773–781. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Lancrey A, Joubert A, Duvernois-Berthet E, Routhier E, Raj S, Thierry A, Sigarteu M, Ponger L, Croquette V, Mozziconacci J, et al. : Nucleosome Positioning on Large Tandem DNA Repeats of the ‘601’ Sequence Engineered in Saccharomyces cerevisiae. Journal of Molecular Biology 2022, 434. [DOI] [PubMed] [Google Scholar]
- 19**.Jentink N, Purnell C, Kable B, Swulius MT, Grigoryev SA: Cryoelectron tomography reveals the multiplex anatomy of condensed native chromatin and its unfolding by histone citrullination. Mol Cell 2023, 10.1016/j.molcel.2023.08.017. [DOI] [PMC free article] [PubMed] [Google Scholar]; The authors isolate native chromatin fragmented by MNase and define the relation between chromatin organization and Mg2+ and citrullination by PAD4. They observe that citrullation and Mg2+ have opposite effects.
- 20**.Beel AJ, Azubel M, Mattei PJ, Kornberg RD: Structure of mitotic chromosomes. Mol Cell 2021, 81:4369–4376 e4363. [DOI] [PMC free article] [PubMed] [Google Scholar]; The authors isolate whole native mitotic chromosomes and characterize linker DNA. They observe a wide range in linker DNA lengths and angles which highlight the heterogeneity of chromatin.
- 21.Sharma J, Chhabra R, Cheng A, Brownell J, Liu Y, Yan H: Control of self-assembly of DNA tubules through integration of gold nanoparticles. Science 2009, 323:112–116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.McRae EKS, Rasmussen HO, Liu J, Boggild A, Nguyen MTA, Sampedro Vallina N, Boesen T, Pedersen JS, Ren G, Geary C, et al. : Structure, folding and flexibility of co-transcriptional RNA origami. Nat Nanotechnol 2023, 18:808–817. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Liu J, McRae EKS, Zhang M, Geary C, Andersen ES, Ren G: Tertiary structure of single-instant RNA molecule reveals folding landscape. bioRxiv 2023, 10.1101/2023.05.19.541511. [DOI] [Google Scholar]
- 24**.Gorbea Colon JJ, Palao L 3rd, Chen SF, Kim HJ, Snyder L, Chang YW, Tsai KL, Murakami K: Structural basis of a transcription pre-initiation complex on a divergent promoter. Mol Cell 2023, 83:574–588 e511. [DOI] [PMC free article] [PubMed] [Google Scholar]; The authors assemble Mediator-Preinitiation Complex and analyze the rearrangement of DNA dependent on the addition of a general transcription factor. Here they utilize cryo-EM SPA and cryo-ET to resolve the core complex to high resolution and flexible DNA organization.
- 25.Chreifi G, Chen S, Jensen GJ: Rapid tilt-series method for cryo-electron tomography: Characterizing stage behavior during FISE acquisition. J Struct Biol 2021, 213:107716. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Eisenstein F, Yanagisawa H, Kashihara H, Kikkawa M, Tsukita S, Danev R: Parallel cryo electron tomography on in situ lamellae. Nat Methods 2023, 20:131–138. [DOI] [PubMed] [Google Scholar]
- 27.Bouvette J, Liu HF, Du X, Zhou Y, Sikkema AP, da Fonseca Rezende EMJ, Klemm BP, Huang R, Schaaper RM, Borgnia MJ, et al. : Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography. Nat Commun 2021, 12:1957. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Yang JE, Larson MR, Sibert BS, Kim JY, Parrell D, Sanchez JC, Pappas V, Kumar A, Cai K, Thompson K, et al. : Correlative montage parallel array cryo-tomography for in situ structural cell biology. Nat Methods 2023, 10.1038/s41592-023-01999-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29**.Purnell C, Heebner J, Swulius MT, Hylton R, Kabonick S, Grillo M, Grigoryev S, Heberle F, Waxham MN, Swulius MT: Rapid Synthesis of Cryo-ET Data for Training Deep Learning Models. bioRxiv 2023, 10.1101/2023.04.28.538636. [DOI] [Google Scholar]; This manuscript descibes the utility of simulating tomography data from existing structures to aid training deep learning models to denoise real tomographic data.
- 30.Zhang H, Li Y, Liu Y, Li D, Wang L, Song K, Bao K, Zhu P: A method for restoring signals and revealing individual macromolecule states in cryo-ET, REST. Nat Commun 2023, 14:2937. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31*.Fatmaoui F, Carrivain P, Grewe D, Jakob B, Victor J-M, Leforestier A, Eltsov M: Cryo-electron tomography and deep learning denoising reveal native chromatin landscapes of interphase nuclei. bioRxiv 2022, 10.1101/2022.08.16.502515. [DOI] [Google Scholar]; The authors use deep learning denoising to visualize the linker DNA in situ.
- 32.Kim HH, Uddin MR, Xu M, Chang YW: Computational Methods Toward Unbiased Pattern Mining and Structure Determination in Cryo-Electron Tomography Data. J Mol Biol 2023, 435:168068. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Dimchev G, Amiri B, Fassler F, Falcke M, Schur FK: Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data. J Struct Biol 2021, 213:107808. [DOI] [PubMed] [Google Scholar]
- 34.Tang G, Peng L, Baldwin PR, Mann DS, Jiang W, Rees I, Ludtke SJ: EMAN2: an extensible image processing suite for electron microscopy. J Struct Biol 2007, 157:38–46. [DOI] [PubMed] [Google Scholar]
- 35.Mosalaganti S, Obarska-Kosinska A, Siggel M, Taniguchi R, Turonova B, Zimmerli CE, Buczak K, Schmidt FH, Margiotta E, Mackmull MT, et al. : AI-based structure prediction empowers integrative structural analysis of human nuclear pores. Science 2022, 376:eabm9506. [DOI] [PubMed] [Google Scholar]
- 36.Dahlberg PD, Moerner WE: Cryogenic Super-Resolution Fluorescence and Electron Microscopy Correlated at the Nanoscale. Annu Rev Phys Chem 2021, 72:253–278. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Chang YW, Chen S, Tocheva EI, Treuner-Lange A, Lobach S, Sogaard-Andersen L, Jensen GJ: Correlated cryogenic photoactivated localization microscopy and cryo-electron tomography. Nat Methods 2014, 11:737–739. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Tuijtel MW, Koster AJ, Jakobs S, Faas FGA, Sharp TH: Correlative cryo super-resolution light and electron microscopy on mammalian cells using fluorescent proteins. Sci Rep 2019, 9:1369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Moser F, Prazak V, Mordhorst V, Andrade DM, Baker LA, Hagen C, Grunewald K, Kaufmann R: Cryo-SOFI enabling low-dose super-resolution correlative light and electron cryo-microscopy. Proc Natl Acad Sci U S A 2019, 116:4804–4809. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Liu B, Xue Y, Zhao W, Chen Y, Fan C, Gu L, Zhang Y, Zhang X, Sun L, Huang X, et al. : Three-dimensional super-resolution protein localization correlated with vitrified cellular context. Sci Rep 2015, 5:13017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Dahlberg PD, Saurabh S, Sartor AM, Wang J, Mitchell PG, Chiu W, Shapiro L, Moerner WE: Cryogenic single-molecule fluorescence annotations for electron tomography reveal in situ organization of key proteins in Caulobacter. Proc Natl Acad Sci U S A 2020, 117:13937–13944. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Zimmerli CE, Allegretti M, Rantos V, Goetz SK, Obarska-Kosinska A, Zagoriy I, Halavatyi A, Hummer G, Mahamid J, Kosinski J, et al. : Nuclear pores dilate and constrict in cellulo. Science 2021, 374:eabd9776. [DOI] [PubMed] [Google Scholar]
- 43.Schuller AP, Wojtynek M, Mankus D, Tatli M, Kronenberg-Tenga R, Regmi SG, Dip PV, Lytton-Jean AKR, Brignole EJ, Dasso M, et al. : The cellular environment shapes the nuclear pore complex architecture. Nature 2021, 598:667–671. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Akey CW, Singh D, Ouch C, Echeverria I, Nudelman I, Varberg JM, Yu Z, Fang F, Shi Y, Wang J, et al. : Comprehensive structure and functional adaptations of the yeast nuclear pore complex. Cell 2022, 185:361–378 e325. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Torino S, Dhurandhar M, Stroobants A, Claessens R, Efremov RG: Time-resolved cryo-EM using a combination of droplet microfluidics with on-demand jetting. Nat Methods 2023, 20:1400–1408. [DOI] [PubMed] [Google Scholar]
