
==== Front
Nat Commun
Nat Commun
Nature Communications
2041-1723
Nature Publishing Group UK London

39231985
52091
10.1038/s41467-024-52091-1
Article
Small LEA proteins mitigate air-water interface damage to fragile cryo-EM samples during plunge freezing
http://orcid.org/0000-0001-6055-5604
Abe Kaitlyn M. 1
Li Gan 12
http://orcid.org/0000-0002-0738-679X
He Qixiang 1
http://orcid.org/0000-0002-4855-8703
Grant Timothy 12
http://orcid.org/0000-0003-3327-1926
Lim Ci Ji ciji.lim@wisc.edu

1
1 https://ror.org/01y2jtd41 grid.14003.36 0000 0001 2167 3675 Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706 USA
2 https://ror.org/05cb4rb43 grid.509573.d 0000 0004 0405 0937 John and Jeanne Rowe Center for Research in Virology, Morgridge Institute for Research, Madison, WI 53715 USA
4 9 2024
4 9 2024
2024
15 770517 2 2024
27 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Air-water interface (AWI) interactions during cryo-electron microscopy (cryo-EM) sample preparation cause significant sample loss, hindering structural biology research. Organisms like nematodes and tardigrades produce Late Embryogenesis Abundant (LEA) proteins to withstand desiccation stress. Here we show that these LEA proteins, when used as additives during plunge freezing, effectively mitigate AWI damage to fragile multi-subunit molecular samples. The resulting high-resolution cryo-EM maps are comparable to or better than those obtained using existing AWI damage mitigation methods. Cryogenic electron tomography reveals that particles are localized at specific interfaces, suggesting LEA proteins form a barrier at the AWI. This interaction may explain the observed sample-dependent preferred orientation of particles. LEA proteins offer a simple, cost-effective, and adaptable approach for cryo-EM structural biologists to overcome AWI-related sample damage, potentially revitalizing challenging projects and advancing the field of structural biology.

Cryo-EM faces a problem of sample damage at the air-water interface. In this work, the authors show that stress-response proteins from dehydration-tolerant organisms can be used as a simple sample additive to mitigate the sample damage problem.

Subject terms

Cryoelectron microscopy
Cryoelectron microscopy
Structural biology
Structure determination
https://doi.org/10.13039/100000057 U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R00GM131023 DP2GM150023 T32GM130550 Abe Kaitlyn M. Lim Ci Ji U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS)U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS)issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

The “resolution revolution” of cryogenic-electron microscopy (cryo-EM) marked a significant shift in the field of structural biology1. However, the continued growth of cryo-EM single-particle analysis faces a critical problem, namely sample damage that occurs during grid preparation2–9. The standard method for cryo-EM single-particle analysis sample preparation is plunge freezing, where small volumes of sample are applied onto a pretreated cryo-EM grid, blotted, and rapidly plunged into a cryogen such as liquid ethane (Fig. 1a). This process forms a thin layer (~10–100 nm)5,10 of sample-embedded vitreous ice for transmission electron microscopy imaging11,12 (Fig. 1b). Between the blotting and rapid freezing steps, the sample exists as a thin aqueous film with a high surface-to-volume ratio. During this transitional phase (typically lasting for seconds), the proteins in the aqueous solution collide with the air–water interface (AWI) thousands of times before finally being vitrified5,9.Fig. 1 Cryo-EM sample grid preparation and potential role of LEA proteins on AWI damage mitigation.

Cartoon illustration of the process and outcomes of preparing cryo-EM SPA grids and the hypothesized effects of LEA proteins on sample structural integrity. a Shows a Cryo-EM SPA grid preparation robot alongside a detailed view of a typical holey grid with vitrified ice, which is used for embedding protein samples. b–d Depict different states of protein sample distribution within the vitrified ice. In panel (b), an ideal sample distribution is shown where proteins are evenly dispersed without any structural damage. c Illustrates the typical impact of air–water interface (AWI) damage on protein samples, leading to preferred orientation, complex dissociation, and protein denaturation. d Demonstrates how LEA proteins can mitigate sample damage by forming a barrier at the AWI, which significantly mitigates these damages and preserves protein integrity in vitrified ice.

Adsorption to the AWI can destroy the protein’s structural integrity, causing it to denature, or disintegrate2,5,7,13 (Fig. 1c). In a scenario where the protein maintains its structure after AWI adsorption, the sample interaction with the AWI may be biased towards certain regions, leading to preferred sample orientations and an anisotropic 3D reconstruction of the sample2,3,14,15. To mitigate the AWI problem, researchers have developed a variety of solutions. These include the addition of mild detergents to the sample16,17, using chemical crosslinking18–21, and adsorbing or tethering samples to surfaces to prevent sample contact with the AWI4,22–30. More sophisticated techniques involve rapidly freezing the sample before the proteins can diffuse to the AWIs30–35. However, these methods are often technically challenging, cost-prohibitive and demonstrate sample-specific results.

Here we show an AWI mitigation strategy that is accessible, cost-effective, and readily deployable in all cryo-EM facilities and research laboratories.

Results

AavLEA1 mitigates AWI damage to fragile cryo-EM samples during grid plunge freezing

In search of a new solution to mitigate AWI damage, we explored the biological world, hypothesizing that cellular response mechanisms to desiccation stress could offer an evolved solution for mitigating protein damage caused by AWI interaction. We identified late embryogenesis abundant (LEA) proteins36–38, specifically a group 3 LEA protein, AavLEA1, from the roundworm (nematode) Aphelenchus avenae39 as a potential candidate. Studies have indicated that AavLEA1, which has a molecular weight of ~16 kDa, prevents protein aggregation due to desiccation39. This is likely due to the formation of an AavLEA1 barrier which mitigates damage caused by direct interaction of the sample with the AWI38. We thus propose that AavLEA1 can be used as a sample additive to mitigate damage to protein samples caused by AWI interaction during cryo-EM grid plunge freezing (Fig. 1d). The relatively small molecular mass of AavLEA1 (approximately 16 kDa) compared to a typical sample of interest (several hundred kDa) should allow AavLEA1 to reach the AWI faster than the larger samples.

To evaluate the AWI damage mitigation effects of LEA proteins, we used two protein complexes that are AWI-sensitive as model systems: human DNA polymerase-α-primase (PP)40–42 and Polycomb repressive complex 2 (PRC2)20,43,44. It is important to note that in this study, both complexes were tested in their apo-state, and all data collection was performed using a 200 keV electron microscope with a direct electron detector (for details, please see the Methods section). Reported cryo-EM structures of apo-state PP complexes were solved using chemically crosslinked samples42, suggesting that the PP particles fell apart due to AWI damage during plunge freezing. Another arguably more challenging structure to solve for cryo-EM single-particle analysis is that of PRC2. Reported PRC2 cryo-EM structures were solved by highly specialized strategies using either chemically crosslinked samples on thin carbon-support grids20,45 or biotinylated samples tethered onto Streptavidin-crystal grids43,44.

We found that the addition of AavLEA1 to PP and PRC2 before freezing eliminates the need for the abovementioned methods, allowing us to solve their structures at comparable or higher resolutions (Fig. 2). The optimal addition amount was found to be between 1:8–1:40 molar ratio of the sample to the LEA proteins (Supplementary Figs. 1–3). The addition of AavLEA1 at a 1:40 PP:AavLEA1 molar ratio before plunge freezing led to considerably better grids than freezing the PP sample alone; with clear and homogeneously sized particles (Fig. 2a). Multiple high-resolution two-dimensional (2D) class averages of PP were obtained from these particles (Fig. 2b), and subsequent image processing led to a 3.0 Å global resolution map of the apo-state PP (Fig. 2c and Supplementary Fig. 3). This is the highest resolution cryo-EM map reported for the human apo-state PP; the previous X-ray structure was solved at 3.6 Å46 and a chemically crosslinked cryo-EM structure determined at a 3.8 Å global resolution42. Most importantly, we demonstrated that AavLEA1 can be used to mitigate sample damage from AWI interactions during plunge freezing, resulting in high-resolution cryo-EM maps.Fig. 2 High-resolution cryo-EM structure determination of fragile human Polymerase alpha-Primase and Polycomb repressive complex 2 using nematode AavLEA1.

Cryo-EM single-particle analysis of human polymerase α-primase complex (PP), (a–c), and polycomb repressive complex 2 (PRC2), panels (d–f), both with the addition of Nematode AavLEA1. a, d Display representative micrographs and CTFs-cropped up to the ice ring for the complexes both alone and with AavLEA1 added at a 1:40 ratio, highlighting improved sample preservation due to LEA protein addition. Representative micrographs were chosen out of 42 (a) top, 4403 (a) bottom, 5 (d) top, and 2843 (d) bottom. b, e Depict 2D class averages, illustrating defined and consistent particle shapes with visible protein features when AavLEA1 was used. Finally, c, f show reconstructed cryo-EM maps of the complexes from the AavLEA1 datasets, presented in two orientations.

Initially, we had some potential concerns with the AavLEA1 approach. Firstly, the addition of AavLEA1 could have led to an elevated background signal in the micrograph. Secondly, interaction with AavLEA1 could have distorted the sample conformation. Given that we obtained a 3.0 Å resolution cryo-EM map for human PP apo-state complex in the presence of excess AavLEA1 (sample:AavLEA1 of 1:40), we deduce that background AavLEA1 did not significantly affect image alignment or hinder high-resolution reconstruction. Additionally, we did not find any extra map density that would indicate AavLEA1 binding to PP in a consistent manner, nor a significant change in the PP conformation; we calculated a RMSD of 1.2 Å when a refined model derived from the 3.0 Å cryo-EM map was aligned to a published crystal structure of an apo-state human PP (PDB: 5EXR)46 (Supplementary Figs. 4, 5 and Table 1). In short, AavLEA1 addition did not alter the PP apo-state conformation.

We saw similar results for PRC2 with the addition of AavLEA1 (1:40 PRC2:AavLEA1 molar ratio)—Adding AavLEA1 resulted in clear and homogeneously sized particles (Fig. 2d). Without additives, we saw smaller sized particles in the micrographs, indicating broken PRC2 complexes, consistent with previous studies47. Subsequent cryo-EM image processing led to a 3.8 Å global resolution map of PRC2 (Fig. 2e, f and Supplementary Fig. 6). This result further exemplifies the efficacy of AavLEA1 in facilitating the determination of high-resolution cryo-EM structures of protein samples sensitive to the air–water interface.

A truncated form of LEA protein from tardigrade also mitigates AWI sample damage

Encouraged by the success of using nematode AavLEA1 to mitigate AWI sample damage, we pondered whether LEA proteins from other organisms could provide comparable results. Tardigrades, also known as water bears, are tolerant of desiccation stress48, and the species Ramazzottius varieornatus has a group 3 LEA protein, RvLEAM49. Because RvLEAM has nine LEA-like motifs and is about 30 kDa in mass, we truncated it to ~15 kDa to increase its diffusion coefficient and match the size of AavLEA1 for ease of comparison (refer to the Methods section for details). The truncated RvLEAM is hereafter termed RvLEAMshort.

Similar to AavLEA1, adding RvLEAMshort to PP or PRC2 sample at a molar ratio of 1:6 sample:RvLEAMshort before plunge freezing led to the appearance of monodisperse and discernable particles (Fig. 3). From datasets collected over a single night, we successfully reconstructed cryo-EM maps of human apo-state PP and PRC2 at a reported global resolution of 4.5 and 3.7 Å, respectively (Fig. 3c, f and Supplementary Figs. 7, 8). The final resolution of PP and RvLEAMshort in this dataset is lower than our other PP dataset because significantly fewer movies were collected (see methods). Given that this is the second LEA protein we have tested that successfully rescued the cryo-EM structure determination of two challenging AWI-sensitive protein complexes, we believe group 3 LEA proteins, as a cryo-EM single-particle analysis sample additive, offers a promising and powerful method for structural biologists to mitigate sample damage caused by AWI during plunge freezing.Fig. 3 A truncated form of LEA protein from tardigrade also mitigates AWI sample damage.

Cryo-EM single-particle analysis of protein complexes with RvLEAMshort. a, d Display representative micrographs and CTFs-cropped up to the ice ring-out of the 1308 and 3896 collected respectively of the polymerase-primase complex (PP) and Polycomb repressive complex 2 (PRC2), each treated with RvLEAMshort at a molar ratio of 1:6. b, e Show 2D class averages, which demonstrate the structural homogeneity and quality of the sample with RvLEAMshort added. c, f Present the reconstructed cryo-EM maps of PP and PRC2, depicted in two orientations, achieving resolutions of 4.5 and 3.7 Å, respectively.

Samples with LEA protein addition distribute at vitrified ice surfaces

While our prediction that LEA proteins mitigate AWI damage was correct, our initial hypothesis about the mechanism of LEA-mediated AWI damage mitigation proved inaccurate. We speculated that once the LEA proteins formed a barrier at the AWI, which we termed the LEA-water interface (LWI), the sample particles would remain in the aqueous layer. When imaged in vitreous ice after plunge freezing, we expected the projected views of the frozen particles to be randomly distributed (Fig. 1). However, a major underlying assumption was that there was no interaction between the sample and the LWI. If such interactions exist, they would manifest as a bias in the particle orientation (view projection)6,17. Our particle orientation distribution analysis for the cryo-EM maps derived from the LEA protein datasets suggests this was the case (Fig. 4a and Supplementary Table 2). Calculations from the 3DFSC server14 indicated that the PP maps show a good isotropic distribution, approaching perfect isotropy with a sphericity of 0.98 for those with AavLEA1 and 0.83 with RvLEAMshort. Conversely, the PRC2 maps exhibited poorer particle orientation distribution, regardless of the LEA protein used; sphericity values were 0.77 and 0.79 for maps with AavLEA1 and RvLEAMshort, respectively. Overall, these results suggest that the samples interact with the LWI to varying degrees, dependent on the specific sample.Fig. 4 Samples with LEA protein addition distribute at vitrified ice surfaces.

Particle orientation distribution and cryo-electron tomography (cryo-ET) analysis for samples with LEA proteins addition. a Displays Mollweide projections that compare the particle distribution for the polymerase α-primase complex (PP) and Polycomb repressive complex 2 (PRC2) with AavLEA1 (1:40) and RvLEAMshort (1:6) added respectively. Corresponding sphericity values demonstrate the degree of isotropy achieved in the cryo-EM map under each condition. b, c Show cryo-ET cross-sectional analysis of the spatial distribution of PP and PRC2 particles within the grid holes, respectively. These plots highlight the location of particles relative to the edge of the holes and identify regions affected by ice contamination. The axes are expressed in pixels, with a scale of 4.4 Å per pixel.

If the samples are indeed interacting with the interface, the particles should be distributed as plane(s). To test this, we used fiducial-less cryo-electron tomography (cryo-ET) analysis to visualize the particle distribution of PP with AavLEA1 (1:40 molar ratio) and PRC2 with RvLEAMshort (1:6 molar ratio) in our grids (Fig. 4b, c and Supplementary Movies 1, 2). In both cases, we saw most of the particles were distributed within one or two planes in the vitrified ice, confirming that the samples were adsorbed to a surface in the presence of LEA proteins.

Due to the small sizes of LEA proteins, we were unable to visualize them in our cryo-EM images directly, preventing us from determining their empirical coverage at the AWI. Consequently, we cannot rule out the possibility of incomplete LEA protein coverage, and that the particle orientation bias could have resulted, in part or entirely, from interactions with exposed pockets of the AWI. If this is indeed the case, it is reassuring to note that these interactions with the AWI, in the presence of LEA proteins, did not significantly compromise the samples’ structural integrity, as demonstrated by the reconstructed high-resolution cryo-EM maps of the tested samples (Figs. 2, 3).

Biochemical strategies to improve particle orientation distribution of LEA datasets

Given that interactions between the sample and LEA proteins at the LWI can contribute to the observed particle orientation bias, we aimed to explore strategies that influenced these interactions to achieve a desirable particle orientation outcome. Both AavLEA1 and RvLEAMshort are predicted to form amphiphilic alpha-helical structures, with the hydrophobic face oriented towards the air at the AWI and the hydrophilic side (negatively charged) facing the aqueous solution49,50. Thus, the negatively charged, solution-facing side of the LWI could create a “sticky” surface that leads to the particle orientation bias observed in the LEA datasets.

Past studies have demonstrated that electrostatic charge on a surface, whether AWI or carbon film, can influence sample particle orientation51,52. Using PRC2 and RvLEAMshort as the model condition, we added a divalent cation, MgCl2, to the sample buffer to neutralize the negatively charged LWI surface, with the hope that this strategy would change the PRC2 particle orientation distribution. However, this approach did not improve the particle orientation distribution and instead made it worse with more limited views (Supplementary Fig. 9).

Next, we investigated the effect of mild glutaraldehyde crosslinking on PRC2 prior to freezing with RvLEAMshort to determine if this could improve particle orientation distribution. Our rationale was that the glutaraldehyde reaction would neutralize the positively charged groups on the surface of PRC2 and lead to particle orientation distribution changes, as has been demonstrated by past studies18,19,52. Chemical crosslinking also has the benefit of stabilizing the complex for improved structural homogeneity18,19. We collected cryo-EM datasets of crosslinked PRC2 with RvLEAMshort at a 1:6 sample:LEA molar ratio; the PRC2 samples were crosslinked with glutaraldehyde for 2 and 10 min (Supplementary Fig. 10).

Our analysis indicated that chemical crosslinking improved the orientation distribution of PRC2 particles (Fig. 5a and Supplementary Figs. 11, 12). The map sphericity increased from 0.79 in non-crosslinked samples to 0.83 after 2 min of crosslinking. Extending the crosslinking to 10 min further enhanced this value to 0.97 (Supplementary Table 2). This incremental improvement suggests that longer crosslinking durations may be slightly more effective. The 10 min crosslinked sample dataset enabled us to achieve a 3.1 Å global resolution cryo-EM map of the PRC2 complex (Fig. 5b). This map represents the highest resolution yet reported for the human PRC2 apo-state complex. Given that the map was reconstructed from a dataset collected on a 200 kV microscope, using a 300 kV microscope could potentially yield an even higher resolution. Our PRC2 model, built using this cryo-EM map, has a structure similar to that obtained through the streptavidin-biotin affinity EM grid approach25,44, with the RMSD between the two aligned structures being 0.89 Å (Supplementary Figs. 13, 14 and Supplementary Table 3).Fig. 5 Chemical crosslinking enhances the orientation distribution of PRC2 particles in the presence of RvLEAMshort.

a Displays Mollweide projections of the particle orientation distribution for the Polycomb repressive complex 2 (PRC2) treated with chemical crosslinking for 2 and 10 min, demonstrating improved isotropy as evidenced by the increased sphericity values of 0.83 and 0.97, respectively. b Shows the high-resolution cryo-EM maps of PRC2 crosslinked for 10 min, presented in two orientations to highlight the detailed structural features achieved, with a global resolution of 3.1 Å.

A control 10 min crosslinked PRC2 cryo-EM dataset without RvLEAMshort was also collected to determine the effect of adding LEA proteins crosslinked samples. While discernable and somewhat homogeneous particles were observed, the subsequent single-particle analysis revealed that most particles were broken subcomplexes of PRC2 (Supplementary Fig. 15), a result consistent with a previous study47. Nonetheless, we obtained a 4.3 Å cryo-EM map of an intact PRC2 complex (Supplementary Fig. 15), although the efficiency was modest; from 3274 movies, ~1.7 million particles were picked, but only about ~3% contributed to the final cryo-EM map reconstruction (Supplementary Fig. 15). In contrast, with the addition of RvLEAMshort, ~14% of initially picked particles (~2.5 million particles) were utilized in the final reconstruction (Supplementary Fig. 12). Furthermore, particles from the crosslinked control dataset suffered from biased particle orientation, with a 3DFSC calculated sphericity value of 0.66. The inclusion of RvLEAMshort improved the sphericity value to 0.97 (Supplementary Table 2). Overall, the above comparison suggests the addition of RvLEAMshort enhanced the stability and particle orientation distribution of crosslinked PRC2 complexes.

Comparative analysis of LEA proteins and CHAPSO as AWI damage mitigation strategies

CHAPSO, a zwitterionic detergent, can mitigate AWI damage to protein samples during plunge freezing17,53. In our hands, it is an effective strategy for determining the high-resolution cryo-EM structures of PP-related complexes40,54. Hence, we wanted to compare LEA protein’s efficiency in obtaining a high-resolution cryo-EM structure against that of CHAPSO. To this end, we determined a 3.4 Å cryo-EM map of apo-state PP using CHAPSO (Fig. 6a and Supplementary Fig. 16). By visual inspection, we found no discernable differences between the two cryo-EM maps or modeled structures (compared to the 40:1 AavLEA1:PP cryo-EM map, Supplementary Figs. 17, 18 and Table 1). However, three separate empirical analyses, Reslog55 (Fig. 6b), per-particle spectral signal-to-noise (ppSSNR)56 (Fig. 6c), and Rosenthal–Henderson57 (Supplementary Fig. 19) plots, all pointed to the AavLEA1 dataset having the better particle image quality. It is possible that thicker ice in the CHAPSO dataset impacted particle image quality, explaining the observed differences. Nonetheless, our results demonstrate that AavLEA1, when used as a sample additive, can achieve cryo-EM map quality comparable to, or even better than, that obtained with detergents.Fig. 6 Comparative evaluation of LEA Proteins and CHAPSO as AWI damage mitigation strategies.

a Showcases the reconstructed cryo-EM map of the polymerase α-primase complex, visualized in two orientations, achieving a global resolution of 3.4 Å. b, c Detail the ResLog and per-particle spectra SNR (ppSSNR) analyses respectively, comparing the effects of AavLEA1 and CHAPSO addition on particle image data and map reconstruction quality. The ResLog analysis in panel (b) illustrates the spatial frequency improvements associated with each additive, plotted against batch size on a logarithmic scale, indicating that AavLEA1 outperforms CHAPSO at higher spatial frequencies. c Displays the logarithm of ppSSNR, demonstrating that AavLEA1 maintains higher SNR values across the majority of the spatial frequencies tested. Source data are provided as a Source Data file.

A major advantage of using AavLEA1 over CHAPSO, or other detergents, is its effectiveness when cryo-EM samples are limited or unstable at high concentrations. CHAPSO and similar detergents typically require high sample concentrations51,58—over 4 mg/mL or ~13 μM for a 300 kDa protein sample—which can be challenging for precious samples. In contrast, with AavLEA1, we used only 1–1.5 μM of sample protein, which is more than ten times less than that required for CHAPSO or detergents in general. While the application of LEA proteins can lead to an anisotropic distribution of particle orientations (see Result section: Samples with LEA proteins addition distribute at vitrified ice surfaces and Fig. 4b, c), this issue does not arise with the use of CHAPSO. The particles in the CHAPSO dataset have an even distribution of particle orientations (Supplementary Fig. 16 and Table 2). Consequently, the calculated sphericity value of the PP cryo-EM map from the CHAPSO dataset is 0.99.

Discussion

In summary, we have shown that two group three LEA proteins, AavLEA1 from nematodes and RvLEAM (truncated) from tardigrades, can mitigate sample damage caused by sample interaction with the AWI during cryo-EM plunge freezing. We demonstrated the effects on two model multi-subunit protein complexes, human PP and PRC2, in the apo-state, both challenging targets for cryo-EM analysis. By simply adding AavLEA1 or RvLEAMshort to the samples before plunge freezing, we determined the cryo-EM structures of both PP and PRC2 at comparable, or better resolution than those previously reported using more challenging and complicated anti-AWI damage strategies20,42–44,47. It is important to note that these fragile samples did not yield any discernable monodisperse particles using standard plunge freezing methods. Therefore, our results underscore the effectiveness of LEA proteins in revitalizing cryo-EM projects that would otherwise be deemed unfeasible. While our study demonstrates the effectiveness of LEA proteins in mitigating AWI damage for PP and PRC2 complexes, further investigation is needed to determine their applicability to other macromolecular assemblies, membrane proteins, or smaller protein complexes.

The LEA proteins require lower sample concentration compared to other AWI mitigation solutions, such as Spotiton31–33 or detergents51,58,59, offering a significant advantage when working with limited samples or those prone to aggregation at high concentrations. Another common solution for accommodating low sample concentrations is the use of cryo-EM grids with support films. However, the quality of these specialized EM grids can vary due to production batch reproducibility, and they can be technically challenging to produce in research laboratories. Unlike these methods, the application of LEA proteins does not require specialized grids and is compatible with standard cryo-EM holey grids. While the utilization of LEA proteins can lead to preferred particle orientation problems and varying degrees of anisotropy depending on the sample, this issue is not insurmountable. It can be mitigated by employing chemical crosslinking18 or tilted-stage data collection strategies14. Additionally, given that the proteins adhere to LEA-water interfaces, the molar ratio between the sample and LEA proteins may not be a key optimization parameter for sample grid plunge freezing. Rather, the concentration of LEA proteins used is important. In our hands, a minimum of 6 µM LEA proteins was sufficient to mitigate AWI damage to fragile samples.

We believe that LEA proteins represent a promising avenue for structural biologists to revisit cryo-EM projects previously hindered by AWI issues, particularly those that have exhausted conventional AWI mitigation strategies. These proteins can be produced in large quantities using standard bacterial expression systems and purification schemes, providing a sustainable and cost-effective alternative to methods that rely on more expensive and perishable materials and reagents. Most importantly, the accessibility and economic benefits of LEA proteins enable any structural biology laboratory or cryo-EM facility to readily adopt this method, potentially revolutionizing their approach to cryo-EM structure determination.

Methods

Expression and purification of AavLEA1 and RvLEAMshort

The expression plasmid for HIS-tagged AavLEA1 was sourced from the Addgene plasmid repository [pET15b-AavLEA1, a gift from Claude Férec (Addgene plasmid # 53093)]60. The expression plasmid for HIS-tagged RvLEAMshort was constructed by inserting a truncated cDNA from pEThT-RvLEAM [pEThT-RvLEAM was a gift from Takekazu Kunieda (Addgene plasmid # 90033)]49 into a pET15b vector. RvLEAMshort encodes residues 58-181 of RvLEAM (A0A0E4AVP3.1). Both recombinant AavLEA1 and RvLEAMshort were expressed in Escherichia coli BL21 (DE3) cells. A single bacterial colony containing the transformed plasmid was cultured overnight in 2 mL of Luria Bertani broth (LB) with 100 µg mL−1 carbenicillin at 37 °C. This starter culture was then used to inoculate 1 L of LB supplemented with the same antibiotic. At an optical density (A600) of 0.6, gene expression was induced using 0.1 mM isopropyl-β-d-thiogalactopyranoside (IPTG) for 16 h at 12 °C and shaken at 230 rpm.

Cells were harvested by centrifugation, resuspended in lysis buffer (50 mM HEPES pH 7.5, 300 mM NaCl, 10 mM imidazole, 1 mM DTT or TCEP, 1 mM PMSF), and lysed via sonication. The cell debris was then removed by centrifugation. The clarified lysate was incubated with pre-equilibrated nickel-NTA resin (Qiagen, Germany) and stirred for 1 h at 4 °C. The protein-bound resin was washed three times with 50 mL of lysis buffer. Proteins were eluted with 10 mL of elution buffer (wash buffer supplemented with 250 mM imidazole) using a gravity flow column. The proteins were then concentrated to ~500 μL using a 3 kDa MWCO spin column and further purified on a Superdex 75 10/300 size-exclusion chromatography (SEC) column (Cytiva, USA) pre-equilibrated with SEC buffer (50 mM HEPES pH 7.5, 300 mM NaCl, 1 mM TCEP, 10% glycerol). Eluted fractions were analyzed by SDS-PAGE. Chosen fractions were pooled, concentrated, snap-frozen in 5–10 µL aliquots, and stored at −80 °C until use. The protein concentration of the aliquots was determined using the Beer–Lambert equation, with absorbance measurements obtained from a NanoDrop spectrophotometer (Thermo Fisher, USA) and extinction coefficients calculated based on their protein sequences.

Production of recombinant human DNA polymerase alpha-primase

Recombinant human Polα–primase was expressed and purified as previously described54. Briefly, Trichoplusia ni (T.ni) cells (Expression System) were infected with four baculoviruses (POLA1, POLA2, PRIM1, and PRIM2) for the co-expression of human Polα–primase. The infected T.ni cells were collected for protein purification after 66–68 h post-infection. The human Polα–primase was obtained using a tandem affinity approach. First, His-tagged POLA2, PRIM1, and PRIM2 were captured using Ni-NTA agarose resin (Qiagen). The elute was then subjected to a second pull-down using Strep-Tactin XT 4Flow-resin (IBA LifeScience) for strep-tagged POLA1. The purified Polα–primase complex was verified using SDS-PAGE analysis.

Production of recombinant human polycomb repressive complex 2

Purified recombinant human polycomb repressive complex 2 (PRC2) protein complexes were generously provided by Dr. Tom Cech at the University of Colorado Boulder44.

PRC2 cryo-EM sample glutaraldehyde crosslinking

Approximately 2 µM of PRC2 was incubated with a 0.1% (v/v) final concentration of glutaraldehyde for 2- and 10-min intervals. After each interval, an aliquot was removed and quenched with 80 mM Tris-HCl to stop the reaction. SDS-PAGE was then used to assess the crosslinking efficiency of the PRC2 samples at each incubation time point.

All samples were thawed just prior to cryo-EM grid preparation. Holey carbon cryo-EM grids, either Quantifoil R 1.2/1.3 300 mesh Au or C-flat R 1.2/1.3 300 mesh Au, were glow discharged using a PELCO EasiGlow glow-discharge unit (15 mA for 30 s with a 10-s hold). These treated grids were used within 30 minutes. Protein samples were diluted to the working concentration immediately before application to the grid. Where indicated, the sample (~3.5 μL) was supplemented with LEA proteins, CHAPSO, or MgCl2 just before being applied to the glow-discharged grid. Typically, the high-concentration LEA protein stock was first diluted to an intermediate working solution using the sample buffer and then mixed with the sample (e.g., 2 μL of LEA with 2 μL of the sample). The grid was then blotted for 4 to 6 s at 4 °C and 95% humidity before being plunged frozen into liquid ethane using a Vitrobot Mark IV (Thermo Fisher, USA).

For all conditions except those specified, 1–1.5 μM of PP or PRC2 were used with the indicated molar ratio of AavLEA1 or RvLEAMshort. For conditions with PP and 4 mM CHAPSO, 13.8 μM of PP was utilized.

Cryo-EM data collection

All data collections and screenings were conducted on a Talos Arctica 200 kV TEM (Thermo Fisher Scientific, USA) equipped with a Gatan BioQuantum K3 direct electron detector (Gatan, USA). Data screening and acquisition were managed using either EPU (Thermo Fisher, USA) or SerialEM61. All cryo-EM datasets were collected at a pixel size of 1.064 Å/pixel, with a total dose of 50 e− Å−2 distributed across 40 frames. The CDS counting mode was utilized along with a 20 eV energy filter slit. The defocus range was set between −1 and −2.5 μm in 0.25-μm intervals.

Cryo-EM data processing

For all datasets, image processing was carried out using cryoSPARC62. In brief, movies were subjected to patch motion correction, and the aligned micrographs had their contrast transfer function (CTF) estimated. The CTF values were utilized to select a subset of micrographs deemed suitable for high-resolution single-particle analysis. Detailed procedures for subsequent image processing steps specific to each dataset are outlined below:

1.5 μM PP, 12 μM AavLEA1 (1:8) dataset

A total of 2764 movies were collected. After micrograph curation 2112 movies remained and 1,724,984 particles were extracted and binned 4x binning (4.3 Å/pixel). After 2D classification, 785,653 particles proceeded to ab initio reconstruction and were sorted into four separated reference-free 3D classes. Particles underwent another round of ab initio modeling and separated into two classes. The intact complex was re-extracted at 1.1 Å/pixel and was sorted into one of the two classes (239,029 particles, 75%). Non-uniform refinement of this class with per-particle CTF refinement resulted in a global resolution (reported at Fourier shell correlation of 0.143) of 3.6 Å.

1.5 μM PP, 60 μM AavLEA1 (1:40) dataset

A total of 4403 movies were collected. After micrograph curation, 500 movies were initially used, with a total of 340,430 particles extracted at 4x binning. From 2D classification, 201,337 particles were selected and re-extracted at the original pixel size. Particles then proceeded to ab initio reconstruction and were sorted into four separated reference-free 3D classes. Two of the four classes resulted in intact particles, which were verified through non-uniform refinement of the combined classes using 165,472 particles, resulting in a 3.8 Å structure. Particles were extracted from the remaining 3771 movies and binned 4x, resulting in 2,668,602 particles. These particles were then sorted into 2D classes, and the selected 1,438,074 particles underwent ab initio modeling. Selected particles underwent another round of ab initio modeling with two classes. One of the two classes showed intact particles, and those 1,009,026 particles were sent to non-uniform refinement yielding a 3.4 Å global resolution. CryoSparc global and local CTF refinement jobs were run, followed by further filtering, resulting in 988,417 particles. These particles were then extracted at the original pixel size, 1.1 Å/pixel. All resulting particles underwent non-uniform refinement, reference motion correction, and heterogeneous refinement. 856,205 particles were used for a final non-uniform refinement, with a final global resolution of 3.0 Å.

1 µM PP, 6 µM RvLEAMshort (1:6) dataset

A total of 1308 movies were collected. Following micrograph curation, 335,907 particles were extracted from 1076 micrographs and binned 4x. About 125,231 particles were extracted with 2D classification. These particles then proceeded to ab initio reconstruction and split into 3D classes. The selected 74,198 particles were re-extracted at the original pixel size (1.1 Å/pixel) from 1071 micrographs. Particles underwent another round of 2D classification and ab initio 3D reconstruction. Selected particles underwent non-uniform refinement and had a final global resolution of 4.5 Å. The final resolution of this dataset is lower than our other PP datasets which is likely because this data collection contains only 1308 movies while other PP datasets have 2700 or more movies.

13.8 μM PP, 4 mM CHAPSO dataset

A total of 4567 movies were collected. Following micrograph curation, 1,832,455 particles were extracted from 4510 micrographs and binned 4x. Particles underwent 2D classification where and ab initio reconstruction. Selected particles were re-extracted at the original pixel size of 1.1 Å/pixel (744,824 particles). Extracted particles were then sorted into 2D classes and underwent non-uniform refinement with per-particle CTF refinement and reference motion correction, with a final global resolution of 3.4 Å with 674,793 particles.

1.5 μM PRC2, 60 μM AavLEA1 (1:40) dataset

A total of 2843 movies were collected. Following micrograph curation, 687,121 particles were extracted from 1642 micrographs and binned 4x. Particles underwent 2D classification and ab initio reconstruction. Selected classes were re-extracted at the original pixel size, 1.1 Å/pixel, yielding 150,359 particles. The re-extracted particles underwent non-uniform refinement with per-particle CTF refinement and resulted in a global resolution of 3.8 Å.

1 μM PRC2, 6.7 μM RvLEAMshort (~1:6) dataset

A total of 3896 movies were collected. Following micrograph curation, 1,766,944 particles were extracted from 3637 micrographs and binned 4x. Particles were sorted into 2D classes followed by 3D classes via ab initio reconstruction. The selected 547,610 particles were re-extracted at 1.1 Å/pixel and subjected to ab initio 3D reconstruction. The final 206,807 particles underwent non-uniform refinement with per-particle CTF refinement, resulting in a global resolution of 3.7 Å.

1 μM PRC2, 6.7 μM RvLEAMshort (~1:6) 10 mM MgCl2 dataset

A total of 4333 movies were collected. Following micrograph curation, 1,755,138 particles were extracted from 3759 micrographs and binned 4x. Particles underwent two rounds of 2D classification. From here, 408,373 particles were selected and proceeded to ab initio 3D reconstruction. The resulting 406,148 particles were re-extracted from 3746 movies at the original pixel size (1.1 Å/pixel) and underwent another round of ab initio reconstruction. The final 102,181 particles proceeded to non-uniform refinement with a final global resolution was 4.2 Å.

1 μM PRC2 crosslinked 2 min, 6.7 μM RvLEAMshort (~1:6) dataset

A total of 2981 movies were collected. Following micrograph curation, 982,264 particles were extracted from 2189 movies and binned 4x. Particles were sorted into 2D classes followed by 3D classes via ab initio reconstruction. Selected particles were re-extracted at the original pixel size (1.1 Å/pixel) and underwent ab initio reconstruction again. The resulting 534,068 particles were subjected to non-uniform refinement with per-particle CTF refinement, resulting in a global resolution of 3.5 Å.

1 μM PRC2 crosslinked 10 min, 6.7 μM RvLEAMshort (~1:6) dataset

A total of 3432 movies were collected. Following micrograph curation, 2,084,816 particles were extracted from 3295 movies and binned 4x. Particles underwent 2D classification followed by ab initio 3D reconstruction. Selected particles were re-extracted at the original pixel size (1.1 Å/pixel). Particles underwent non-uniform refinement, resulting in a global resolution of 3.3 Å. Global CTF refinement, reference-based motion correction, and heterogeneous refinement jobs were run. 366,459 particles were used in this final round of non-uniform refinement, resulting in a global resolution of 3.1 Å.

1 μM PRC2 crosslinked 10 min dataset

A total of 3274 movies were collected. Following micrograph curation, 1,231,903 particles were extracted from 3274 movies and binned 4x. Particles underwent 2D classification followed by ab initio 3D reconstruction. Selected particles were re-extracted at the original pixel size (1.1 Å/pixel) and underwent a second batch of ab initio 3D reconstruction, reference-based motion correction non-uniform refinement. The final 51,494 particles resulted in a global resolution of 4.3 Å.

Cryo-EM structure modeling and refinement

The published apo-state models of Polymerase alpha-primase (PP, PDB: 5EXR)46 and Polycomb Repressive Complex 2 (PRC2, PDB: 8FYH)44 were used as initial models for real-space refinement against their respective cryo-EM maps using Phenix63. Structural alignments between the published models and the refined models were performed using the MatchMaker module in ChimeraX64. Refinement statistics and validation reports are provided in Supplementary Tables 1, 3 for PP and PRC2, respectively. Q-score65 analysis was conducted for each refined model and reported in the abovementioned tables.

Particle image quality and orientation distribution analysis

ResLog plots were generated using the ResLog job in cryoSPARC62. Rosenthal–Henderson plots were derived from the data utilized in the ResLog plot, following the method described by Rosenthal and Henderson57. The per-particle spectral signal-to-noise ratio (ppSSNR) plots were produced using the FSC_noisesub data from the ResLog Analysis job in cryoSPARC. Particles were segmented into stacks of 30,000, 60,000, 90,000, 120,000, and 150,000 for analysis. The ppSSNR calculations are performed as described by ref. 66. Cryo-EM map sphericity values are calculated using the 3DFSC server14. The conical FSC area ratio (cFAR) and sampling compensation factor (SCF)56,67 were computed using CryoSPARC62.

Tilt-series collection

Tilt series were collected on a Titan Krios (Thermo Fisher Scientific, USA) operating at 300 kV, equipped with a K3 summit direct electron detector and a Quantum energy filter (Gatan, USA), controlled by SerialEM61. Images were collected with an exposure of 8 e-/pixel/s on the detector, with the camera operating in CDS mode, with a calibrated pixel size of 1.1 Å per pixel. Tilt series were collected using a dose-symmetric tilt scheme from −45° to 45° with a tilt increment of 3° and nominal defocus between 2 and 4 μm68. Each tilt angle was collected as a five-frame movie, with an exposure of 5 e–/Å2 per tilt, and, therefore, a total exposure of 150 e–/Å2 per tilt series.

Tilt-series data processing

Each movie was whole frame aligned using the Unblur package in cisTEM69. Tilt series were aligned and reconstructed at a binning factor 4 using AreTomo70. To further enhance the contrast of protein particles for better localization, the reconstructed tomograms were denoised using IsoNet71. The reconstructions are shown in Supplementary Movies 1, 2. These movies were created using 3dmod from the IMOD package72 and ImageJ73.

Particle localization and ice surface estimation

Particles in the tomograms were picked manually with Dynamo74. The surfaces of vitrified ice were determined via three markers: crystalline ice contaminations above the ice, carbon edges, and the protein layers, which are assumed to be close to the surface.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Supplementary information

Supplementary Information

Peer Review File

Supplementary Video 1

Supplementary Video 2

Description of Additional Supplementary Files

Reporting Summary

Source data

Source data

Supplementary information

The online version contains supplementary material available at 10.1038/s41467-024-52091-1.

Acknowledgements

We are grateful to Tom Cech, Anne Gooding, and Jiarui Song at the University of Colorado Boulder for their generous gift of purified recombinant human PRC2. We also extend our thanks to members of the Lim and Grant laboratories for their valuable suggestions. Our appreciation goes to Kliment Verba and his lab members at the University of California San Francisco for their assistance with our ppSSNR calculations. We thank Lori Passmore and her lab members at MRC LMB for providing insightful feedback on our preprint. We also like to thank Tom Terwilliger at the Los Alamos National Lab for his help in model refinement using the Phenix software. Lastly, we are thankful to our colleagues Elizabeth Wright and Robert Kirchdoerfer for their helpful feedback and suggestions. Some of this work was performed in the Cryo-EM Research Center (CEMRC) in the Department of Biochemistry at the University of Wisconsin–Madison. We thank the staff at CEMRC for their support and assistance in cryo-EM data collection. The Lim lab is a member of the SBGrid consortium (www.sbgrid.org) and some of the analyses were performed using software compiled by SBGrid. Support for this research was provided to C.L. by the National Institutes of Health (NIH), the National Institute of General Medical Sciences (R00GM131023 and DP2GM150023), and the University of Wisconsin–Madison, Office of the Vice-Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation and the Department of Biochemistry. In addition, K.M.A. is supported by an NIH T32 predoctoral fellowship (T32GM130550). T.G. is an Investigator of The Morgridge Institute for Research.

Author contributions

C.L. conceived the study. K.M.A. and Q.H. made the recombinant proteins. K.M.A made the cryo-EM grids, and performed data collection and image processing with C.L. in support. C.L. and K.M.A. collected the cryo-EM tilt-series datasets with T.G. in support. G.L. and T.G. reconstructed the cryo-EM tomograms and performed related analyses. K.M.A. performed the crosslinking experiments and analysis. K.M.A., G.L., T.G., and C.L. wrote the manuscript and prepared the figures.

Peer review

Peer review information

Nature Communications thanks Alex Noble and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Data availability

The described cryo-EM maps and coordinate files have been deposited in the Electron Microscopy Data Bank and the Protein Data Bank (PDB) under the following accession codes: Polymerase alpha-primase (PP)–AavLEA1, 1:8 molar ratio under code EMD-43619, PP–AavLEA1, 1:40 molar ratio under codes PDB-ID 8VY3 and EMD-43628, PP–RvLEAMshort, 1:6 molar ratio under code EMD-43626, PP–CHAPSO 4 mM under codes PDB-ID 9C8V and EMD-43627, Polycomb repressive complex 2 (PRC2)–AavLEA1, 1:40 molar ratio under code EMD-43620, PRC2–RvLEAMshort, 1:6 molar ratio under code EMD-43621, PRC2–RvLEAMshort, 1:6 molar ratio, 10 mM MgCl2 under code EMD-43622, PRC2–RvLEAMshort, 1:6 molar ratio, 2 min crosslink under code EMD-43623, PRC2–RvLEAMshort, 1:6 molar ratio, 10 min crosslink under codes PDB-ID 9C8U and EMD-43625, and PRC2, 10 min crosslink under code EMD-45273 [https://www.ebi.ac.uk/emdb/EMD-45723]. Raw datasets (movies) and their respective gain references were deposited in the Electron Microscopy Public Image Archive (EMPIAR): PP–AavLEA1, 1:8 molar ratio under accession code EMPIAR-11963, PP–AavLEA1, 1:40 molar ratio under accession code EMPIAR-11964, PP–RvLEAMshort, 1:6 molar ratio under accession code EMPIAR-11965, PP–CHAPSO 4 mM under accession code EMPIAR-11966, PRC2–AavLEA1, 1:40 molar ratio under accession code EMPIAR-11975, PRC2–RvLEAMshort, 1:6 molar ratio under accession code EMPIAR-11976, PRC2–RvLEAMshort, 1:6 molar ratio, 2 min crosslink under accession code EMPIAR-11978, PRC2–RvLEAMshort, 1:6 molar ratio, 10 min crosslink under accession code EMPIAR-11979, and PRC2, 10 min crosslink under accession code EMPIAR-12125. The PRC2–RvLEAMshort, 1:6 molar ratio with 10 mM MgCl2 dataset is uploaded as aligned micrographs, under accession code EMPIAR-12140. Reconstructed tomograms for PP–AavLEA1, 1:8 molar ratio are included in EMD-43619 and PRC2–RvLEAMshort, 1:6 molar ratio in EMD-43621. The following previously published PDB depositions were used in this study: PDB-ID 8FYH and PDB-ID 5EXR. Source data are provided with this paper.

Competing interests

A provisional patent has been filed by C.L. for this technology with the Wisconsin Alumni Research Foundation (WARF). The remaining authors declare no competing interests.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. Kühlbrandt W The resolution revolution Science 2014 343 1443 1444 10.1126/science.1251652 24675944
Kühlbrandt, W. The resolution revolution. Science 343, 1443–1444 (2014).24675944 10.1126/science.1251652
2. Han B-G Avila-Sakar A Remis J Glaeser RM Challenges in making ideal cryo-EM samples Curr. Opin. Struct. Biol. 2023 81 102646 10.1016/j.sbi.2023.102646 37392555
Han, B.-G., Avila-Sakar, A., Remis, J. & Glaeser, R. M. Challenges in making ideal cryo-EM samples. Curr. Opin. Struct. Biol. 81, 102646 (2023).37392555 10.1016/j.sbi.2023.102646
3. Xu Y Dang S Recent technical advances in sample preparation for single-particle cryo-EM Front. Mol. Biosci. 2022 9 892459 10.3389/fmolb.2022.892459 35813814
Xu, Y. & Dang, S. Recent technical advances in sample preparation for single-particle cryo-EM. Front. Mol. Biosci. 9, 892459 (2022).35813814 10.3389/fmolb.2022.892459
4. D’Imprima E Protein denaturation at the air-water interface and how to prevent it Elife 2019 8 e42747 10.7554/eLife.42747 30932812
D’Imprima, E. et al. Protein denaturation at the air-water interface and how to prevent it. Elife 8, e42747 (2019).30932812 10.7554/eLife.42747
5. Noble AJ Reducing effects of particle adsorption to the air–water interface in cryo-EM Nat. Methods 2018 15 793 795 10.1038/s41592-018-0139-3 30250056
Noble, A. J. et al. Reducing effects of particle adsorption to the air–water interface in cryo-EM. Nat. Methods 15, 793–795 (2018).30250056 10.1038/s41592-018-0139-3
6. Noble AJ Routine single particle CryoEM sample and grid characterization by tomography Elife 2018 7 e34257 10.7554/eLife.34257 29809143
Noble, A. J. et al. Routine single particle CryoEM sample and grid characterization by tomography. Elife 7, e34257 (2018).29809143 10.7554/eLife.34257
7. Glaeser RM Proteins, interfaces, and cryo-EM grids Curr. Opin. Colloid Interface Sci. 2018 34 1 8 10.1016/j.cocis.2017.12.009 29867291
Glaeser, R. M. Proteins, interfaces, and cryo-EM grids. Curr. Opin. Colloid Interface Sci. 34, 1–8 (2018).29867291 10.1016/j.cocis.2017.12.009
8. Glaeser RM Han B-G Opinion: hazards faced by macromolecules when confined to thin aqueous films Biophys. Rep. 2017 3 1 7 10.1007/s41048-016-0026-3 28781996
Glaeser, R. M. & Han, B.-G. Opinion: hazards faced by macromolecules when confined to thin aqueous films. Biophys. Rep. 3, 1–7 (2017).28781996 10.1007/s41048-016-0026-3
9. Taylor KA Glaeser RM Retrospective on the early development of cryoelectron microscopy of macromolecules and a prospective on opportunities for the future J. Struct. Biol. 2008 163 214 223 10.1016/j.jsb.2008.06.004 18606231
Taylor, K. A. & Glaeser, R. M. Retrospective on the early development of cryoelectron microscopy of macromolecules and a prospective on opportunities for the future. J. Struct. Biol. 163, 214–223 (2008).18606231 10.1016/j.jsb.2008.06.004
10. Kim, L. Y. et al. Benchmarking cryo-EM single particle analysis workflow. Front. Mol. Biosci. 5, 50 (2018).
11. Adrian M Dubochet J Lepault J McDowall AW Cryo-electron microscopy of viruses Nature 1984 308 32 36 10.1038/308032a0 6322001
Adrian, M., Dubochet, J., Lepault, J. & McDowall, A. W. Cryo-electron microscopy of viruses. Nature 308, 32–36 (1984).6322001 10.1038/308032a0
12. Dubochet J Chang J-J Freeman R Lepault J McDowall AW Frozen aqueous suspensions Ultramicroscopy 1982 10 55 61 10.1016/0304-3991(82)90187-5
Dubochet, J., Chang, J.-J., Freeman, R., Lepault, J. & McDowall, A. W. Frozen aqueous suspensions. Ultramicroscopy 10, 55–61 (1982).10.1016/0304-3991(82)90187-5
13. Glaeser, R. M. Preparing better samples for cryo-electron microscopy: biochemical challenges do not end with isolation and purification. Ann. Rev. Biochem. 90, 451–474 (2021).
14. Tan YZ Addressing preferred specimen orientation in single-particle cryo-EM through tilting Nat. Methods 2017 14 793 796 10.1038/nmeth.4347 28671674
Tan, Y. Z. et al. Addressing preferred specimen orientation in single-particle cryo-EM through tilting. Nat. Methods 14, 793–796 (2017).28671674 10.1038/nmeth.4347
15. Naydenova K Russo CJ Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy Nat. Commun. 2017 8 629 10.1038/s41467-017-00782-3 28931821
Naydenova, K. & Russo, C. J. Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy. Nat. Commun. 8, 629 (2017).28931821 10.1038/s41467-017-00782-3
16. Liu, N. & Wang, H.-W. Better cryo-EM specimen preparation: how to deal with the air–water interface? J. Mol. Biol.10.1016/j.jmb.2022.167926 (2022).
17. Chen, J., Noble, A. J., Kang, J. Y. & Darst, S. A. Eliminating effects of particle adsorption to the air/water interface in single-particle cryo-electron microscopy: bacterial RNA polymerase and CHAPSO. J. Struct. Biol. X 1, 100005 (2019).
18. Stark, H. GraFix: stabilization of fragile macromolecular complexes for single particle cryo-EM. Methods Enzymol. 481, 109–126 (2010).
19. Kastner B GraFix: sample preparation for single-particle electron cryomicroscopy Nat. Methods 2008 5 53 55 10.1038/nmeth1139 18157137
Kastner, B. et al. GraFix: sample preparation for single-particle electron cryomicroscopy. Nat. Methods 5, 53–55 (2008).18157137 10.1038/nmeth1139
20. Kasinath, V. et al. Structures of human PRC2 with its cofactors AEBP2 and JARID2. Science 359, 940–944 (2018).
21. Adamus, K., Le, S. N., Elmlund, H., Boudes, M. & Elmlund, D. AgarFix: simple and accessible stabilization of challenging single-particle cryo-EM specimens through crosslinking in a matrix of agar. J. Struct. Biol. 207, 327–331 (2019).
22. Wang F General and robust covalently linked graphene oxide affinity grids for high-resolution cryo-EM Proc. Natl Acad. Sci. USA 2020 117 24269 24273 10.1073/pnas.2009707117 32913054
Wang, F. et al. General and robust covalently linked graphene oxide affinity grids for high-resolution cryo-EM. Proc. Natl Acad. Sci. USA 117, 24269–24273 (2020).32913054 10.1073/pnas.2009707117
23. Wang F Amino and PEG-amino graphene oxide grids enrich and protect samples for high-resolution single particle cryo-electron microscopy J. Struct. Biol. 2020 209 107437 10.1016/j.jsb.2019.107437 31866389
Wang, F. et al. Amino and PEG-amino graphene oxide grids enrich and protect samples for high-resolution single particle cryo-electron microscopy. J. Struct. Biol. 209, 107437 (2020).31866389 10.1016/j.jsb.2019.107437
24. Liu N Bioactive functionalized monolayer graphene for high-resolution cryo-electron microscopy J. Am. Chem. Soc. 2019 141 4016 4025 10.1021/jacs.8b13038 30724081
Liu, N. et al. Bioactive functionalized monolayer graphene for high-resolution cryo-electron microscopy. J. Am. Chem. Soc. 141, 4016–4025 (2019).30724081 10.1021/jacs.8b13038
25. Glaeser RM Han B-G Streptavidin affinity grids for single-particle cryo-EM Microsc. Microanal. 2019 25 990 991 10.1017/S1431927619005683
Glaeser, R. M. & Han, B.-G. Streptavidin affinity grids for single-particle cryo-EM. Microsc. Microanal. 25, 990–991 (2019).10.1017/S1431927619005683
26. Palovcak E A simple and robust procedure for preparing graphene-oxide cryo-EM grids J. Struct. Biol. 2018 204 80 84 10.1016/j.jsb.2018.07.007 30017701
Palovcak, E. et al. A simple and robust procedure for preparing graphene-oxide cryo-EM grids. J. Struct. Biol. 204, 80–84 (2018).30017701 10.1016/j.jsb.2018.07.007
27. Lu Y Functionalized graphene grids with various charges for single-particle cryo-EM Nat. Commun. 2022 13 6718 10.1038/s41467-022-34579-w 36344519
Lu, Y. et al. Functionalized graphene grids with various charges for single-particle cryo-EM. Nat. Commun. 13, 6718 (2022).36344519 10.1038/s41467-022-34579-w
28. Zheng L Uniform thin ice on ultraflat graphene for high-resolution cryo-EM Nat. Methods 2023 20 123 130 10.1038/s41592-022-01693-y 36522503
Zheng, L. et al. Uniform thin ice on ultraflat graphene for high-resolution cryo-EM. Nat. Methods 20, 123–130 (2023).36522503 10.1038/s41592-022-01693-y
29. Han Y High-yield monolayer graphene grids for near-atomic resolution cryoelectron microscopy Proc. Natl Acad. Sci. USA 2020 117 1009 1014 10.1073/pnas.1919114117 31879346
Han, Y. et al. High-yield monolayer graphene grids for near-atomic resolution cryoelectron microscopy. Proc. Natl Acad. Sci. USA 117, 1009–1014 (2020).31879346 10.1073/pnas.1919114117
30. Esfahani, B. G. et al. SPOT-RASTR—a cryo-EM specimen preparation technique that overcomes problems with preferred orientation and the air/water interface. Biophys. J. 123 (2024).
31. Jain T Sheehan P Crum J Carragher B Potter CS Spotiton: a prototype for an integrated inkjet dispense and vitrification system for cryo-TEM J. Struct. Biol. 2012 179 68 75 10.1016/j.jsb.2012.04.020 22569522
Jain, T., Sheehan, P., Crum, J., Carragher, B. & Potter, C. S. Spotiton: a prototype for an integrated inkjet dispense and vitrification system for cryo-TEM. J. Struct. Biol. 179, 68–75 (2012).22569522 10.1016/j.jsb.2012.04.020
32. Darrow MC Moore JP Walker RJ Doering K King RS Chameleon: next generation sample preparation for cryoEM based on Spotiton Microsc. Microanal. 2019 25 994 995 10.1017/S1431927619005701
Darrow, M. C., Moore, J. P., Walker, R. J., Doering, K. & King, R. S. Chameleon: next generation sample preparation for cryoEM based on Spotiton. Microsc. Microanal. 25, 994–995 (2019).10.1017/S1431927619005701
33. Dandey VP Time-resolved cryo-EM using Spotiton Nat. Methods 2020 17 897 900 10.1038/s41592-020-0925-6 32778833
Dandey, V. P. et al. Time-resolved cryo-EM using Spotiton. Nat. Methods 17, 897–900 (2020).32778833 10.1038/s41592-020-0925-6
34. Rubinstein JL Shake-it-off: a simple ultrasonic cryo-EM specimen-preparation device Acta Crystallogr. D. Struct. Biol. 2019 75 1063 1070 10.1107/S2059798319014372 31793900
Rubinstein, J. L. et al. Shake-it-off: a simple ultrasonic cryo-EM specimen-preparation device. Acta Crystallogr. D. Struct. Biol. 75, 1063–1070 (2019).31793900 10.1107/S2059798319014372
35. Tan YZ Rubinstein JL Through-grid wicking enables high-speed cryoEM specimen preparation Acta Crystallogr. D. Struct. Biol. 2020 76 1092 1103 10.1107/S2059798320012474 33135680
Tan, Y. Z. & Rubinstein, J. L. Through-grid wicking enables high-speed cryoEM specimen preparation. Acta Crystallogr. D. Struct. Biol. 76, 1092–1103 (2020).33135680 10.1107/S2059798320012474
36. Hernández-Sánchez, I. E. et al. LEAfing through literature: late embryogenesis abundant proteins coming of age - achievements and perspectives. J. Exp. Bot. 73, 6525–6546 (2022).
37. Hibshman JD Goldstein B LEA motifs promote desiccation tolerance in vivo BMC Biol. 2021 19 263 10.1186/s12915-021-01176-0 34903234
Hibshman, J. D. & Goldstein, B. LEA motifs promote desiccation tolerance in vivo. BMC Biol. 19, 263 (2021).34903234 10.1186/s12915-021-01176-0
38. Hibshman JD Clegg JS Goldstein B Mechanisms of desiccation tolerance: themes and variations in brine shrimp, roundworms, and tardigrades Front. Physiol. 2020 11 592016 10.3389/fphys.2020.592016 33192606
Hibshman, J. D., Clegg, J. S. & Goldstein, B. Mechanisms of desiccation tolerance: themes and variations in brine shrimp, roundworms, and tardigrades. Front. Physiol. 11, 592016 (2020).33192606 10.3389/fphys.2020.592016
39. Goyal, K., Walton, L. J. & Tunnacliffe, A. LEA proteins prevent protein aggregation due to water stress. Biochem. J. 388, 151–157 (2005).
40. He Q Structures of human primosome elongation complexes Nat. Struct. Mol. Biol. 2023 30 579 583 10.1038/s41594-023-00971-3 37069376
He, Q. et al. Structures of human primosome elongation complexes. Nat. Struct. Mol. Biol. 30, 579–583 (2023).37069376 10.1038/s41594-023-00971-3
41. Yin, Z., Kilkenny, M. L., Ker, D. S. & Pellegrini, L. CryoEM insights into RNA primer synthesis by the human primosome. FEBS J. 291, 1813–1829 (2024).
42. Kilkenny, M. L. et al. Structural basis for the interaction of SARS-CoV-2 virulence factor nsp1 with DNA polymerase α–primase. Protein Sci. 31, 333–344 (2022).
43. Kasinath V JARID2 and AEBP2 regulate PRC2 in the presence of H2AK119ub1 and other histone modifications Science 2021 371 eabc3393 10.1126/science.abc3393 33479123
Kasinath, V. et al. JARID2 and AEBP2 regulate PRC2 in the presence of H2AK119ub1 and other histone modifications. Science 371, eabc3393 (2021).33479123 10.1126/science.abc3393
44. Song J Structural basis for inactivation of PRC2 by G-quadruplex RNA Science 2023 381 1331 1337 10.1126/science.adh0059 37733873
Song, J. et al. Structural basis for inactivation of PRC2 by G-quadruplex RNA. Science 381, 1331–1337 (2023).37733873 10.1126/science.adh0059
45. Grau D Structures of monomeric and dimeric PRC2:EZH1 reveal flexible modules involved in chromatin compaction Nat. Commun. 2021 12 714 10.1038/s41467-020-20775-z 33514705
Grau, D. et al. Structures of monomeric and dimeric PRC2:EZH1 reveal flexible modules involved in chromatin compaction. Nat. Commun. 12, 714 (2021).33514705 10.1038/s41467-020-20775-z
46. Baranovskiy AG Mechanism of concerted RNA-DNA primer synthesis by the human primosome J. Biol. Chem. 2016 291 10006 10020 10.1074/jbc.M116.717405 26975377
Baranovskiy, A. G. et al. Mechanism of concerted RNA-DNA primer synthesis by the human primosome. J. Biol. Chem. 291, 10006–10020 (2016).26975377 10.1074/jbc.M116.717405
47. Lipscomb, D. M. Electron Microscopy Methods to Overcome the Challenges of Structural Heterogeneity and Preferred Orientations in Small (sub-500 kDa) Macromolecular Complexes. Ph.D thesis, California Univ. (2017).
48. Møbjerg, N. et al. Survival in extreme environments - on the current knowledge of adaptations in tardigrades. Acta Physiol. 202, 409–420 (2011).
49. Tanaka S Novel mitochondria-targeted heat-soluble proteins identified in the anhydrobiotic tardigrade improve osmotic tolerance of human cells PLoS ONE 2015 10 e0118272 10.1371/journal.pone.0118272 25675104
Tanaka, S. et al. Novel mitochondria-targeted heat-soluble proteins identified in the anhydrobiotic tardigrade improve osmotic tolerance of human cells. PLoS ONE 10, e0118272 (2015).25675104 10.1371/journal.pone.0118272
50. Li, D. & He, X. Desiccation dependent structure and stability of an anhydrobiotic nematode late embryogenesis abundant (LEA) protein. In ASME 2009 Summer Bioengineering Conference, Parts A and B 213–214 (American Society of Mechanical Engineers, 2009).
51. Li B Zhu D Shi H Zhang X Effect of charge on protein preferred orientation at the air–water interface in cryo-electron microscopy J. Struct. Biol. 2021 213 107783 10.1016/j.jsb.2021.107783 34454014
Li, B., Zhu, D., Shi, H. & Zhang, X. Effect of charge on protein preferred orientation at the air–water interface in cryo-electron microscopy. J. Struct. Biol. 213, 107783 (2021).34454014 10.1016/j.jsb.2021.107783
52. Patel, A. B. et al. Structure of human TFIID and mechanism of TBP loading onto promoter DNA. Science 362, eaau8872 (2018).
53. Chen S Li J Vinothkumar KR Henderson R Interaction of human erythrocyte catalase with air – water interface in cryoEM Microscopy 2022 71 i51 i59 10.1093/jmicro/dfab037 35275189
Chen, S., Li, J., Vinothkumar, K. R. & Henderson, R. Interaction of human erythrocyte catalase with air – water interface in cryoEM. Microscopy 71, i51–i59 (2022).35275189 10.1093/jmicro/dfab037
54. He Q Structures of the human CST-Polα–primase complex bound to telomere templates Nature 2022 608 826 832 10.1038/s41586-022-05040-1 35830881
He, Q. et al. Structures of the human CST-Polα–primase complex bound to telomere templates. Nature 608, 826–832 (2022).35830881 10.1038/s41586-022-05040-1
55. Stagg SM Noble AJ Spilman M Chapman MS ResLog plots as an empirical metric of the quality of cryo-EM reconstructions J. Struct. Biol. 2014 185 418 426 10.1016/j.jsb.2013.12.010 24384117
Stagg, S. M., Noble, A. J., Spilman, M. & Chapman, M. S. ResLog plots as an empirical metric of the quality of cryo-EM reconstructions. J. Struct. Biol. 185, 418–426 (2014).24384117 10.1016/j.jsb.2013.12.010
56. Baldwin PR Lyumkis D Non-uniformity of projection distributions attenuates resolution in Cryo-EM Prog. Biophys. Mol. Biol. 2020 150 160 183 10.1016/j.pbiomolbio.2019.09.002 31525386
Baldwin, P. R. & Lyumkis, D. Non-uniformity of projection distributions attenuates resolution in Cryo-EM. Prog. Biophys. Mol. Biol. 150, 160–183 (2020).31525386 10.1016/j.pbiomolbio.2019.09.002
57. Rosenthal PB Henderson R Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy J. Mol. Biol. 2003 333 721 745 10.1016/j.jmb.2003.07.013 14568533
Rosenthal, P. B. & Henderson, R. Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy. J. Mol. Biol. 333, 721–745 (2003).14568533 10.1016/j.jmb.2003.07.013
58. Snijder J Vitrification after multiple rounds of sample application and blotting improves particle density on cryo-electron microscopy grids J. Struct. Biol. 2017 198 38 42 10.1016/j.jsb.2017.02.008 28254381
Snijder, J. et al. Vitrification after multiple rounds of sample application and blotting improves particle density on cryo-electron microscopy grids. J. Struct. Biol. 198, 38–42 (2017).28254381 10.1016/j.jsb.2017.02.008
59. Kampjut D Steiner J Sazanov LA Cryo-EM grid optimization for membrane proteins iScience 2021 24 102139 10.1016/j.isci.2021.102139 33665558
Kampjut, D., Steiner, J. & Sazanov, L. A. Cryo-EM grid optimization for membrane proteins. iScience 24, 102139 (2021).33665558 10.1016/j.isci.2021.102139
60. Tripathi R Benz N Culleton B Trouvé P Férec C Biophysical characterisation of calumenin as a charged F508del-CFTR folding modulator PLoS ONE 2014 9 e104970 10.1371/journal.pone.0104970 25120007
Tripathi, R., Benz, N., Culleton, B., Trouvé, P. & Férec, C. Biophysical characterisation of calumenin as a charged F508del-CFTR folding modulator. PLoS ONE 9, e104970 (2014).25120007 10.1371/journal.pone.0104970
61. Mastronarde DN Automated electron microscope tomography using robust prediction of specimen movements J. Struct. Biol. 2005 152 36 51 10.1016/j.jsb.2005.07.007 16182563
Mastronarde, D. N. Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152, 36–51 (2005).16182563 10.1016/j.jsb.2005.07.007
62. Punjani A Rubinstein JL Fleet DJ Brubaker M A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination Nat. Methods 2017 14 290 296 10.1038/nmeth.4169 28165473
Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017).28165473 10.1038/nmeth.4169
63. Adams PD PHENIX: a comprehensive Python-based system for macromolecular structure solution Acta Crystallogr. D. Biol. Crystallogr. 2010 66 213 221 10.1107/S0907444909052925 20124702
Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D. Biol. Crystallogr. 66, 213–221 (2010).20124702 10.1107/S0907444909052925
64. Meng EC UCSF ChimeraX: tools for structure building and analysis Protein Sci. 2023 32 e4792 10.1002/pro.4792 37774136
Meng, E. C. et al. UCSF ChimeraX: tools for structure building and analysis. Protein Sci. 32, e4792 (2023).37774136 10.1002/pro.4792
65. Pintilie G Measurement of atom resolvability in cryo-EM maps with Q-scores Nat. Methods 2020 17 328 334 10.1038/s41592-020-0731-1 32042190
Pintilie, G. et al. Measurement of atom resolvability in cryo-EM maps with Q-scores. Nat. Methods 17, 328–334 (2020).32042190 10.1038/s41592-020-0731-1
66. Chan, L. M. et al. High-resolution single-particle imaging at 100-200 keV with the Gatan Alpine direct electron detector. J. Struct. Biol. 216, 108108 (2024).
67. Baldwin PR Lyumkis D Tools for visualizing and analyzing Fourier space sampling in Cryo-EM Prog. Biophys. Mol. Biol. 2021 160 53 65 10.1016/j.pbiomolbio.2020.06.003 32645314
Baldwin, P. R. & Lyumkis, D. Tools for visualizing and analyzing Fourier space sampling in Cryo-EM. Prog. Biophys. Mol. Biol. 160, 53–65 (2021).32645314 10.1016/j.pbiomolbio.2020.06.003
68. Hagen WJH Wan W Briggs JAG Implementation of a cryo-electron tomography tilt-scheme optimized for high resolution subtomogram averaging J. Struct. Biol. 2017 197 191 198 10.1016/j.jsb.2016.06.007 27313000
Hagen, W. J. H., Wan, W. & Briggs, J. A. G. Implementation of a cryo-electron tomography tilt-scheme optimized for high resolution subtomogram averaging. J. Struct. Biol. 197, 191–198 (2017).27313000 10.1016/j.jsb.2016.06.007
69. Grant T Rohou A Grigorieff N CisTEM, user-friendly software for single-particle image processing Elife 2018 7 e35383 10.7554/eLife.35383 29513216
Grant, T., Rohou, A. & Grigorieff, N. CisTEM, user-friendly software for single-particle image processing. Elife 7, e35383 (2018).29513216 10.7554/eLife.35383
70. Zheng S AreTomo: an integrated software package for automated marker-free, motion-corrected cryo-electron tomographic alignment and reconstruction J. Struct. Biol. X 2022 6 100068 35601683
Zheng, S. et al. AreTomo: an integrated software package for automated marker-free, motion-corrected cryo-electron tomographic alignment and reconstruction. J. Struct. Biol. X 6, 100068 (2022).35601683
71. Liu YT Isotropic reconstruction for electron tomography with deep learning Nat. Commun. 2022 13 6482 10.1038/s41467-022-33957-8 36309499
Liu, Y. T. et al. Isotropic reconstruction for electron tomography with deep learning. Nat. Commun. 13, 6482 (2022).36309499 10.1038/s41467-022-33957-8
72. Kremer JR Mastronarde DN McIntosh JR Computer visualization of three-dimensional image data using IMOD J. Struct. Biol. 1996 116 71 76 10.1006/jsbi.1996.0013 8742726
Kremer, J. R., Mastronarde, D. N. & McIntosh, J. R. Computer visualization of three-dimensional image data using IMOD. J. Struct. Biol. 116, 71–76 (1996).8742726 10.1006/jsbi.1996.0013
73. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).
74. Castaño-Díez, D., Kudryashev, M., Arheit, M. & Stahlberg, H. Dynamo: a flexible, user-friendly development tool for subtomogram averaging of cryo-EM data in high-performance computing environments. J. Struct. Biol. 178, 139–151 (2012).
