Electron cryo-microscopy of Bacteriophage PR772 reveals the elusive vertex complex and the capsid architecture

  1. Hemanth KN Reddy  Is a corresponding author
  2. Janos Hajdu
  3. Marta Carroni
  4. Martin Svenda  Is a corresponding author
  1. Uppsala University, Sweden
  2. Stockholm University, Sweden

Abstract

Bacteriophage PR772, a member of the Tectiviridae family, has a 70-nm diameter icosahedral protein capsid that encapsulates a lipid membrane, dsDNA, and various internal proteins. An icosahedrally averaged CryoEM reconstruction of the wild-type virion and a localized reconstruction of the vertex region reveal the composition and the structure of the vertex complex along with new protein conformations that play a vital role in maintaining the capsid architecture of the virion. The overall resolution of the virion is 2.75 Å, while the resolution of the protein capsid is 2.3 Å. The conventional penta-symmetron formed by the capsomeres is replaced by a large vertex complex in the pseudo T=25 capsid. All the vertices contain the host-recognition protein, P5; two of these vertices show the presence of the receptor-binding protein, P2. The 3D structure of the vertex complex shows interactions with the viral membrane, indicating a possible mechanism for viral infection.

Data availability

CryoEM Density maps and atomic models that support the findings of this study have been deposited in the Electron Microscopy Database and the Protein Databank with the accession codes EMD-4461 (Whole particle reconstruction), EMD-4462 (Vertex Complex), EMD-10237 (Localized reconstruction of the penton region), EMD-10238 (Focused Classification of the penton region) and PDB ID 6Q5U (Atomic model of the asymmetric unit).

The following data sets were generated

Article and author information

Author details

  1. Hemanth KN Reddy

    Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
    For correspondence
    hemanth.kumar@icm.uu.se
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4698-8005
  2. Janos Hajdu

    Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
    Competing interests
    The authors declare that no competing interests exist.
  3. Marta Carroni

    Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7697-6427
  4. Martin Svenda

    Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
    For correspondence
    Martin.Svenda@icm.uu.se
    Competing interests
    The authors declare that no competing interests exist.

Funding

Vetenskapsrådet (828-2012-108)

  • Janos Hajdu

Vetenskapsrådet (628-2008-1109)

  • Janos Hajdu

Vetenskapsrådet (822-2010-6157)

  • Janos Hajdu

Vetenskapsrådet (822-2012-5260)

  • Janos Hajdu

Knut och Alice Wallenbergs Stiftelse (KAW-2011.081)

  • Janos Hajdu

European Research Council (ERC-291602)

  • Janos Hajdu

Vetenskapsrådet (349-2011-6488)

  • Janos Hajdu

Vetenskapsrådet (2015-06107)

  • Janos Hajdu

European Structural and Investment Funds (CZ.02.1.01/0.0/0.0/15_003/0000447)

  • Janos Hajdu

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Sjors HW Scheres, MRC Laboratory of Molecular Biology, United Kingdom

Publication history

  1. Received: May 15, 2019
  2. Accepted: September 9, 2019
  3. Accepted Manuscript published: September 12, 2019 (version 1)
  4. Version of Record published: September 18, 2019 (version 2)

Copyright

© 2019, Reddy et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Hemanth KN Reddy
  2. Janos Hajdu
  3. Marta Carroni
  4. Martin Svenda
(2019)
Electron cryo-microscopy of Bacteriophage PR772 reveals the elusive vertex complex and the capsid architecture
eLife 8:e48496.
https://doi.org/10.7554/eLife.48496

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    Results:

    The nonlaboratory scorecard model achieved an area under the receiver operating curve (auROC) of 0.81 (95% confidence interval [CI] 0.77–0.84) and an odds ratio (OR) between the upper and fifth prevalence deciles of 17.2 (95% CI 5–66). Using this model, we classified three risk groups, a group with 1% (0.8–1%), 5% (3–6%), and the third group with a 9% (7–12%) risk of developing T2D. We further analyzed the contribution of the laboratory-based model and devised a blood test model based on age, sex, and the four common blood tests noted above. In this scorecard model, we included age, sex, glycated hemoglobin (HbA1c%), gamma glutamyl-transferase, triglycerides, and HDL cholesterol. Using this model, we achieved an auROC of 0.87 (95% CI 0.85–0.90) and a deciles' OR of ×48 (95% CI 12–109). Using this model, we classified the cohort into four risk groups with the following risks: 0.5% (0.4–7%); 3% (2–4%); 10% (8–12%); and a high-risk group of 23% (10–37%) of developing T2D. When applying the blood tests model using the external validation cohort (Clalit), we achieved an auROC of 0.75 (95% CI 0.74–0.75). We analyzed several additional comprehensive models, which included genotyping data and other environmental factors. We found that these models did not provide cost-efficient benefits over the four blood test model. The commonly used German Diabetes Risk Score (GDRS) and Finnish Diabetes Risk Score (FINDRISC) models, trained using our data, achieved an auROC of 0.73 (0.69–0.76) and 0.66 (0.62–0.70), respectively, inferior to the results achieved by the four blood test model and by the anthropometry models.

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    The four blood test and anthropometric models outperformed the commonly used nonlaboratory models, the FINDRISC and the GDRS. We suggest that our models be used as tools for decision-makers to assess populations at elevated T2D risk and thus improve medical strategies. These models might also provide a personal catalyst for changing lifestyle, diet, or medication modifications to lower the risk of T2D onset.

    Funding:

    The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.