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Multiple liquid crystalline geometries of highly compacted nucleic acid in a dsRNA virus

Nature volume 570, pages 252–256 (2019)Cite this article

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Abstract

Characterizing the genome of mature virions is pivotal to understanding the highly dynamic processes of virus assembly and infection. Owing to the different cellular fates of DNA and RNA, the life cycles of double-stranded (ds)DNA and dsRNA viruses are dissimilar. In terms of nucleic acid packing, dsDNA viruses, which lack genome segmentation and intra-capsid transcriptional machinery, predominantly display single-spooled genome organizations1,2,3,4,5,6,7,8. Because the release of dsRNA into the cytoplasm triggers host defence mechanisms9, dsRNA viruses retain their genomes within a core particle that contains the enzymes required for RNA replication and transcription10,11,12. The genomes of dsRNA viruses vary greatly in the degree of segmentation. In members of the Reoviridae family, genomes consist of 10–12 segments and exhibit a non-spooled arrangement mediated by RNA-dependent RNA polymerases11,12,13,14. However, whether this arrangement is a general feature of dsRNA viruses remains unknown. Here, using cryo-electron microscopy to resolve the dsRNA genome structure of the tri-segmented bacteriophage ɸ6 of the Cystoviridae family, we show that dsRNA viruses can adopt a dsDNA-like single-spooled genome organization. We find that in this group of viruses, RNA-dependent RNA polymerases do not direct genome ordering, and the dsRNA can adopt multiple conformations. We build a model that encompasses 90% of the genome, and use this to quantify variation in the packing density and to characterize the different liquid crystalline geometries that are exhibited by the tightly compacted nucleic acid. Our results demonstrate that the canonical model for the packing of dsDNA can be extended to dsRNA viruses.

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Fig. 1: Structure of the ɸ6 nucleocapsid and dsRNA genome.
Fig. 2: Organization of the dsRNA genome.
Fig. 3: Organizational heterogeneity in the genome.
Fig. 4: Putative interactions between RNA and the P1 shell.

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Data availability

Density maps and the model that support the findings of this study have been deposited in the Electron Microscopy Data Bank and in the Protein Data Bank (PDB) with the accession codes EMD-0299 and PDB 6HY0 (nucleocapsid, icosahedral symmetry); EMD-0300 (nucleocapsid, D3 symmetry); EMD-0301 (genome first-layer organization pD3); EMD-0302 (genome first-layer organization pD3′), EMD-0303 (genome first-layer organization pC2); EMD-0304 (genome first-layer sub-organization pD3′-1); EMD-0305 (genome first-layer sub-organization pD3′-2); and EMD-0306 (genome first-layer sub-organization pD3′-3). Maps from the layer-by-layer genome reconstruction have been submitted with the accession codes EMD-0294 (genome second layer), EMD-0295 (genome third layer) and EMD-0296 (genome fourth and fifth layers).

Code availability

Custom software code used in this study is available from the corresponding author upon request and from https://github.com/OPIC-Oxford.

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Acknowledgements

We thank R. Tarkiainen for technical assistance and Diamond Light Source for access to and support with the cryo-EM facilities (EM14856) at the UK national electron bio-imaging centre (eBIC), which is funded by the Wellcome Trust, MRC and BBSRC. We acknowledge the use of the Instruct-HiLIFE Biocomplex unit (University of Helsinki and Instruct-FI), and the support of the Academy of Finland (grant 1306833) for the unit. This work was supported by the European Research Council under the European Union’s Horizon 2020 research and innovation programme (649053 to J.T.H.); a Wellcome Trust administrative support grant (203141/Z/16/Z); a Wellcome Trust four-year PhD studentship (109135/Z/15/A to S.L.I.); the Academy of Finland (grant 272507 to M.M.P.); and the Sigrid Jusélius Foundation (to M.M.P).

Reviewer information

Nature thanks Alex Evilevitch and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Authors and Affiliations

  1. Division of Structural Biology, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK

    Serban L. Ilca, Abhay Kotecha, Jonathan M. Grimes, David I. Stuart & Juha T. Huiskonen

  2. Molecular and Integrative Biosciences Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland

    Xiaoyu Sun, Minna M. Poranen & Juha T. Huiskonen

  3. Diamond Light Source, Diamond House, Harwell Science and Innovation Campus, Didcot, UK

    Kamel El Omari, Jonathan M. Grimes & David I. Stuart

  4. Thermo Fisher Scientific, Eindhoven, The Netherlands

    Abhay Kotecha & Felix de Haas

  5. Department of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, USA

    Frank DiMaio

  6. Helsinki Institute of Life Science HiLIFE, University of Helsinki, Helsinki, Finland

    Juha T. Huiskonen

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Contributions

S.L.I. reconstructed the genome maps and built the genome models. X.S. prepared the virus sample. A.K. reconstructed the nucleocapsid map. F.d.H. assisted with data collection. F.D. provided custom tools and, together with J.M.G., gave advice for genome building. J.M.G., D.I.S., M.M.P. and J.T.H. provided supervision. K.E.O. analysed RNA–protein contacts. J.T.H. and S.L.I. analysed the data, prepared the figures and wrote the manuscript. All authors commented on the manuscript.

Corresponding author

Correspondence to Juha T. Huiskonen.

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F.d.H. and A.K. are both employees of Thermo Fisher Scientific.

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Extended data figures and tables

Extended Data Fig. 1 Asymmetric reconstruction of the ɸ6 genome.

a, The icosahedral symmetry (I1) in the ɸ6 nucleocapsid reconstruction, calculated from the original cryo-EM single particles (particle images), was relaxed to allow asymmetric reconstruction. The protein shells were subtracted, and the resulting genome-only particle images were used to calculate a D3 genome reconstruction in addition to asymmetric reconstructions that had either pD3 or pC2 symmetry. Three sub-conformations of the pD3′ reconstruction (pD3′-1, pD3′-2 and pD3′-3) are shown, rotated as indicated to reveal their differences in RNA organization. The names of the reconstructions that were used to model the layers of the dsRNA genome and dsRNA–P1 interactions are in bold and are indicated with dotted lines. b–f, The Fourier shell correlation (FSC) is plotted for the reconstructions that are included in further analysis, namely I1, D3, pD3, pC2 and pD3′-1. Volume masking (blue line) was used to focus the FSC test on the area used in further modelling and this increased the estimated resolution compared to the original unmasked reconstruction (grey line). Possible effects of the masking were compensated for by noise randomization (red line), to create the final FSC curve (black line). The resolution at which the correlation drops below the FSC = 0.143 threshold is indicated.

Source data

Extended Data Fig. 2 Model of the ɸ6 genome.

The cryo-EM asymmetric reconstruction (Density) and the model built into the same density (Model) are shown for each of the genome layers. The layers are coloured as in Fig. 1. The density shown for layer 1 is from the pD3′-1 map and the density for layers 2–5 is from the pD3 map.

Extended Data Fig. 3 Modes of dsRNA packing in ɸ6.

A histogram with the relative fractions of base pairs that are located in hexagonal, cubic and undefined packing regions. The total number of base pairs defined for each layer is provided.

Source data

Extended Data Fig. 4 Distances between different types of P1 residues and RNA.

a, b, The fractions of different P1 amino acid residue types (hydrophobic, polar, positively charged and negatively charged) at different distances from the RNA are shown for the pD3 (a) and pC2 (b) models.

Source data

Extended Data Fig. 5 P1–RNA distances in the first genome layer with pD3 symmetry.

The frequency of P1 residues in the pD3 conformation that have non-hydrogen atoms located at a shorter distance than 14 Å from non-hydrogen atoms in the dsRNA model is given in each distance bin (1–14 Å) for the P1 chains A and B together and separately. The total number of residues with an atom or atoms closer than the cut-off distance is given for each table. The frequencies are colour coded so that higher frequencies are in a lighter shade of orange and lower frequencies are darker. The difference in the total numbers between chains A and B is given (Comparison) as a log2 ratio (that is, the base-2 logarithm of the ratio of total frequencies for chains A and B). For example, a value of 1 means that chain A has 2 times as many included residues as chain B, and a value of 2 means that chain A has 4 times as many included residues as chain B (negative values mean that chain B had more included residues). Positive values are in red and negative values in blue. Those cases in which an included residue was present only in one of the two chains are indicated.

Source data

Extended Data Fig. 6 P1–RNA distances in the first genome layer with pC2 symmetry.

The frequency of P1 residues in the pC2 conformation that have non-hydrogen atoms located at a shorter distance than 14 Å from non-hydrogen atoms in the dsRNA model is given in each distance bin (1–14 Å) for P1 chains A and B together and separately. The annotations are as in Extended Data Fig. 5.

Source data

Extended Data Table 1 Cryo-EM data collection and nucleocapsid model
Full size table
Extended Data Table 2 Cryo-EM reconstruction parameters
Full size table

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Ilca, S.L., Sun, X., El Omari, K. et al. Multiple liquid crystalline geometries of highly compacted nucleic acid in a dsRNA virus. Nature 570, 252–256 (2019). https://doi.org/10.1038/s41586-019-1229-9

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