The discovery and design of biologically important RNA molecules is outpacing three-dimensional structural characterization. Here, we demonstrate that cryo-electron microscopy can routinely resolve maps of RNA-only systems and that these maps enable subnanometer-resolution coordinate estimation when complemented with multidimensional chemical mapping and Rosetta DRRAFTER computational modeling. This hybrid ‘Ribosolve’ pipeline detects and falsifies homologies and conformational rearrangements in 11 previously unknown 119- to 338-nucleotide protein-free RNA structures: full-length Tetrahymena ribozyme, hc16 ligase with and without substrate, full-length Vibrio cholerae and Fusobacterium nucleatum glycine riboswitch aptamers with and without glycine, Mycobacterium SAM-IV riboswitch with and without S-adenosylmethionine, and the computer-designed ATP-TTR-3 aptamer with and without AMP. Simulation benchmarks, blind challenges, compensatory mutagenesis, cross-RNA homologies and internal controls demonstrate that Ribosolve can accurately resolve the global architectures of RNA molecules but does not resolve atomic details. These tests offer guidelines for making inferences in future RNA structural studies with similarly accelerated throughput.
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Cryo-EM maps are available in the EMDB with accession codes EMD-21831, EMD-21832, EMD-21833, EMD-21834, EMD-21835, EMD-21836, EMD-21838, EMD-21839, EMD-21840, EMD-21841 and EMD-21842. Models (best-case) are available in the PDB with accession codes 6WLJ, 6WLK, 6WLL, 6WLM, 6WLN, 6WLO, 6WLQ, 6WLR, 6WLS, 6WLT and 6WLU. Fully automated models are available in the Supplementary Data. M2-seq and mutate-map-rescue data are available in the RMDB with accession codes RB1UTR_DMS_0000, 243RNA_DMS_0000, ATPAPO_DMS_0000, ATPAMP_DMS_0000, U1SNRNA_DMS_0000, SCARNA6_DMS_0000, VCKTAPO_DMS_0000, VCKTGLY_DMS_0000, DPRGLN_DMS_0000, ETERNA3_DMS_0000, SPINACH_DMS_0000, FNKTAPO_DMS_0000, FNKTGLY_DMS_0000, HC16APO_DMS_0000, HC16PRO_DMS_0000, SAM4APO_DMS_0000, SAM4SAM_DMS_0000, L21RNA_DMS_0000, HC16M2R_1M7_0001, HC16M2R_1M7_0002 and HC16M2R_1M7_0003. The raw particle image data that support the findings of this study are available from the corresponding author upon request.
The auto-DRRAFTER software is freely available to academic users as part of the Rosetta software package. Documentation is available at https://www.rosettacommons.org/docs/latest/application_documentation/rna/auto-drrafter and a demo is available at https://www.rosettacommons.org/demos/latest/public/auto-drrafter/README. A limited version of the software is also freely available through an online ROSIE server at https://rosie.rosettacommons.org/auto-drrafter.
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We thank members of the Das laboratory for useful discussions; members of the Rosetta community for discussions and code sharing; M. Summers for permission to perform the HIV-1 DIS blind modeling challenge; V. Kosaraju and J. Nicol for helping to develop the Eterna3D interface; and Eterna participant J.R. for designing the eterna3D-JR_1 construct through the Eterna3D interface. Calculations were performed on the Stanford Sherlock cluster. Molecular graphics and analyses were performed with UCSF Chimera, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from NIH grant no. P41-GM103311. This work was supported by a Gabilan Stanford Graduate Fellowship (K.K.), the National Science Foundation (GRFP to K.K. and R.R.) and the National Institutes of Health (grant nos. P41GM103832, R01GM079429, P01AI120943, U54GM103297 and S10 OD021600 to W.C.; grant nos. R35 GM112579 and R21 AI145647 to R.D.).
The authors declare no competing interests.
Peer review information Arunima Singh and Allison Doerr were the primary editors on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Gel images for (1) and (2) RB1 5′ UTR, (3) and (4) scaRNA6, (5) and (6) U1 snRNA, (7) and (8) SAM-IV riboswitch (apo), (9) and (10) 24-3, (11) V. cholerae glycine riboswitch (apo), (12) hc16, (13) Tetrahymena ribozyme, (14) F. nucleatum glycine riboswitch (apo), (15) and (16) Eterna3D-JR_1, (17) and (18) spinach-TTR-3, (19) F. nucleatum glycine riboswitch (apo), (20) ATP-TTR-3 (apo), (21) Eterna3D-JR_1, (22) SAM-IV riboswitch (apo), (23) downstream peptide riboswitch, (24) hc16, and (25) hc16 product. Samples 1-13, 24, 25 were run on an 8% polyacrylamide gel. Samples 14-23 were run on a 12% polyacrylamide gel. All samples were run in 10 mM MgCl2, 67 mM HEPES, 33 mM Tris, pH 7.2. All gels that were run are shown here (experiments were not repeated beyond results shown here).
Micrographs shown in (a), (b), (c), (g), (h), (i), (j), (k), (l), (o), (q), and (r) were taken with the Talos Arctica. All others were taken with the Titan Krios. A Volta phase plate was used for (a), (b), (c), (g), (h), (i), (j), (k), (l), (o), and (q). The total numbers of micrographs collected are listed in Supplementary Table 1.
Shown here for the V. cholerae glycine riboswitch without glycine.
Extended Data Fig. 4 Cryo-EM 2D class averages and 3D reconstructions for all RNA systems in this study.
One dataset was collected for all RNAs except for the SAM-IV riboswitch without SAM and V. cholerae glycine riboswitch without glycine, for which smaller preliminary datasets were initially collected (see Methods). Results from these preliminary datasets were similar, though map resolution was lower. The numbers of particles used for the 3D reconstructions are listed in Supplementary Table 1.
Calculated with ResMap48 for (a) Tetrahymena ribozyme, (b) hc16 product, (c) hc16, (d) V. cholerae glycine riboswitch with glycine, (e) V. cholerae glycine riboswitch without glycine, (f) F. nucleatum glycine riboswitch with glycine, (g) F. nucleatum glycine riboswitch without glycine, (h) ATP-TTR-3 with AMP, (i) ATP-TTR-3 without AMP, (j) SAM-IV riboswitch with SAM, and (k) SAM-IV riboswitch without SAM.
The F. nucleatum glycine riboswitch is shown here as an example. a, Secondary structure elements that connect to just one other helix or junction (‘end nodes’) are circled. b, The cryo-EM density map is low-pass filtered to 20 Å and points are placed (spheres) throughout the map to identify possible placements for ‘end nodes’ in the map (red spheres). The circled end node was randomly selected for initial helix placement. A probe helix (black) was then fit into the density map. The location of the probe helix was optimized, while the distances between the C1’ atom of nucleotide 6 (nucleotides 1-6 labeled) of the probe helix (black sphere) and the end node and the neighboring map node were monitored (see Supplementary Note 4). c, 3D models are built for each of the elements circled in (a) and fit into the density map in the location of the circled point in (b). These elements are kept fixed while the rest of the RNA is built into the density map. d, The top ten best scoring models after round 1. The overall convergence of these models is above the 10 Å threshold (convergence = 20.2 Å), so another round of modeling is performed. e, For the second round of modeling, regions that have converged are extracted from the top scoring models and kept fixed while the rest of the RNA is built into the density map. f, The top ten scoring models after round 2. The convergence is below the 10 Å threshold (convergence = 6.2 Å), so there is only one initial model for the third round of modeling, composed of converged regions from the top ten scoring models from round 2 g,. These regions are allowed to move from their initial positions during this modeling round. h, The best scoring models from round 3. i, Again, converged regions are extracted from top scoring models to form the initial model for the final round of modeling. These regions are kept fixed during the fragment assembly stage of auto-DRRAFTER modeling, but allowed to move during final refinement. j, The top ten scoring models built independently into each half map. Helical regions are depicted with bright colors in (c)-(j) and match colors in the secondary structure diagram (A). Non-helical regions are colored gray.
(a) Tetrahymena ribozyme (n = 65041 sequences), (b) hc16 product (n = 459852 sequences), (c) hc16 (n = 451568 sequences), (d) human scaRNA6 (n = 866158 seqeunces), (e) V. cholerae glycine riboswitch with glycine (n = 928767 sequences), (f) V. cholerae glycine riboswitch without glycine (n = 974343 sequences), (g) human RB1 5′ UTR (n = 889700 sequences), (h) 24-3 (n = 515486 sequences), (i) human U1 snRNA (n = 1185187), (j) F. nucleatum glycine riboswitch with glycine (n = 803254 sequences), (k) F. nucleatum glycine riboswitch without glycine (n = 670301 sequences), (l) eterna3D-JR_1 (n = 994048 sequences), (m) spinach-TTR-3 (n = 1090666 sequences), (n) ATP-TTR-3 with AMP (n = 914892 sequences), (o) ATP-TTR-3 without AMP (n = 712801 sequences), (p) SAM IV riboswitch with SAM (n = 131464 sequences), (q) SAM IV riboswitch without SAM (n = 991972 sequences), and (r) downstream peptide riboswitch (n = 1012081 sequences).
Extended Data Fig. 8 Secondary structures automatically derived from M2-seq data and revisions for best-case auto-DRRAFTER modeling based on sequence covariation and previously solved crystal structures.
(a) Tetrahymena ribozyme, (b) hc16 product, (c) hc16, (d) V. cholerae glycine riboswitch with glycine, (e) V. cholerae glycine riboswitch without glycine, (f) F. nucleatum glycine riboswitch with glycine, (g) F. nucleatum glycine riboswitch without glycine, (h) ATP-TTR-3 with AMP (I) ATP-TTR-3 without AMP, (j) SAM-IV riboswitch with SAM, and (k) SAM-IV riboswitch without SAM. (a-k) Blue lines indicate base pairs that are present in the best-case, but not automated secondary structures. Red lines indicate base pairs that are present in the automated, but not best-case secondary structures. (l) The previously proposed hc16 secondary structure4. (m) M2-seq and mutate-map-rescue experiments suggest that hc16 contains alt-P4 rather than P4. (n) Additional modeling and experiments suggest further modifications to the hc16 secondary structure: alt-P4 is extended, a pseudoknot is formed between the hairpin loops of P5c and P1, P5 is not formed, and P10 is formed. Helical regions are depicted with bright colors that match those shown in Fig. 3. Non-helical regions are colored black.
(a) Tetrahymena ribozyme, (b) hc16 product, (c) hc16, (d) V. cholerae glycine riboswitch with glycine, (e) V. cholerae glycine riboswitch without glycine, (f) F. nucleatum glycine riboswitch with glycine, (g) F. nucleatum glycine riboswitch without glycine, (h) eterna3D-JR_1 (see Fig. 6), (i) spinach-TTR-3 (discussed in ‘Limitations of the Ribosolve pipeline’ in the main text), (j) ATP-TTR-3 with AMP (k) ATP-TTR-3 without AMP, (l) SAM-IV riboswitch with SAM, and (m) SAM-IV riboswitch without SAM. Helical regions are depicted with bright colors that match those shown in Fig. 3. Non-helical regions are colored black.
(a–h) The top ten scoring auto-DRRAFTER models (models #2-10 are transparent) built into 10 Å simulated density maps (left) and the corresponding crystal structures (right) for (a) THF riboswitch, (b) c-di-AMP riboswitch, (c) bacterial SRP Alu domain, (d) FMN riboswitch, (e) SAM-I riboswitch, (f) Tetrahymena ribozyme P4-P6 domain, (g) lysine riboswitch, and (h) lariat capping ribozyme. (i) Ribosolve models for THF riboswitch built into the previously solved 2.9 Å crystallographic density map (left) and the crystal structure (right). (j) Ribosolve models for the B. subtilis T-box-tRNA complex built into a 4.9 Å cryo-EM map (left) and previously modeled coordinates (right) based on high-resolution crystal structures30. Helical regions are depicted with bright colors. Non-helical regions are colored gray.
Supplementary Results, Notes 1–7, Figs. 1–8, Tables 1–4, 6 and 7, and captions for Supplementary Table 5 and Supplementary Video 1.
DNA and RNA sequences used in this study.
RNA structures determined by the Ribosolve pipeline.
Auto-DRRAFTER models built using the fully automated procedure.
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Kappel, K., Zhang, K., Su, Z. et al. Accelerated cryo-EM-guided determination of three-dimensional RNA-only structures. Nat Methods 17, 699–707 (2020). https://doi.org/10.1038/s41592-020-0878-9
Nature Methods (2020)