High-throughput super-resolution analysis of influenza virus pleomorphism reveals insights into viral spatial organization

  1. Andrew McMahon
  2. Rebecca Andrews
  3. Danielle Groves
  4. Sohail V. Ghani
  5. Thorben Cordes
  6. Achillefs N. Kapanidis
  7. Nicole C. Robb

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Abstract

Many viruses form highly pleomorphic particles. In influenza, virion structure is of interest not only in the context of virus assembly, but also because pleomorphic variations may correlate with infectivity and pathogenicity. We have used fluorescence super-resolution microscopy combined with a rapid automated analysis pipeline, a method well-suited to the study of large numbers of pleomorphic structures, to image many thousands of individual influenza virions; gaining information on their size, morphology and the distribution of membrane-embedded and internal proteins. We observed broad phenotypic variability in filament size, and Fourier transform analysis of super-resolution images demonstrated no generalized common spatial frequency patterning of HA or NA on the virion surface, suggesting a model of virus particle assembly where the release of progeny filaments from cells occurs in a stochastic way. We also showed that viral RNP complexes are located preferentially within Archetti bodies when these were observed at filament ends, suggesting that these structures may play a role in virus transmission. Our approach therefore offers exciting new insights into influenza virus morphology and represents a powerful technique that is easily extendable to the study of pleomorphism in other pathogenic viruses.

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  1. Version published to 10.1371/journal.ppat.1011484
  2. Version published to 10.1101/2021.09.23.461536v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.09.23.461536: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationAfter projecting the simulated filaments into 2D, localisations were randomly placed with a normal distribution about the protein location with a standard deviation of 7.4nm (derived from the localization precision of our data) and the image was coloured as a STORM image39.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    A/Udorn/72 virions were labelled with the mouse anti-HA primary antibody Hc83x (a kind gift from Stephen Wharton, Francis Crick Institute) and goat anti-NA and anti-M1 (a kind gift from Jeremy Rossman, University of Kent).
    anti-HA
    suggested: None
    anti-NA
    suggested: None
    anti-M1
    suggested: None
    SARS-CoV-2 virions were labelled with the human anti-spike antibody EY6A37 (a kind gift from Tiong Tan and Alain Townsend, University of Oxford) and a SARS-CoV-2 nucleocapsid antibody (GTX632269) from Genetex.
    anti-spike
    suggested: None
    GTX632269
    suggested: (GeneTex Cat# GTX632269, RRID:AB_2888304)
    Experimental Models: Cell Lines
    SentencesResources
    Virus strains: The influenza strain H3N2 A/Udorn/72 (Udorn) was grown in Madin-Darby Canine Kidney (MDCK) cells as described previously35.
    MDCK
    suggested: None
    SARS-CoV-2 was grown in Vero E6 cells and collected as above.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    Filament length analysis: Images were saved as .tif files, opened in ImageJ and each FOV was cropped so that just the single channel in which the HA protein was labelled was used.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    After iterating this over the skeleton, the calculated line profile of each filament were Fourier transformed using the MATLAB fft function and the resulting distributions across all filaments were summed to produce the average frequency spectrum for that surface protein38.
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)
    To create the intensity along the filament figures, movies recorded at 30 ms exposure with 1000 frames were projected in FIJI to make a single summation image.
    FIJI
    suggested: (Fiji, RRID:SCR_002285)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 13. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  4. Version published to 10.1101/2021.09.23.461536v1 on bioRxiv