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The shape of pleomorphic virions determines resistance to cell-entry pressure

Nature Microbiology volume 6, pages 617–629 (2021)Cite this article

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Abstract

Many enveloped animal viruses produce a variety of particle shapes, ranging from small spherical to long filamentous types. Characterization of how the shape of the virion affects infectivity has been difficult because the shape is only partially genetically encoded, and most pleomorphic virus structures have no selective advantage in vitro. Here, we apply virus fractionation using low-force sedimentation, as well as antibody neutralization coupled with RNAScope, single-particle membrane fusion experiments and stochastic simulations to evaluate the effects of differently shaped influenza A viruses and influenza viruses pseudotyped with Ebola glycoprotein on the infection of cells. Our results reveal that the shape of the virus particles determines the probability of both virus attachment and membrane fusion when viral glycoprotein activity is compromised. The larger contact interface between a cell and a larger particle offers a greater probability that several active glycoproteins are adjacent to each other and can cooperate to induce membrane merger. Particles with a length of tens of micrometres can fuse even when 95% of the glycoproteins are inactivated. We hypothesize that non-genetically encoded variable particle shapes enable pleomorphic viruses to overcome selective pressure and may enable adaptation to infection of cells by emerging viruses such as Ebola. Our results suggest that therapeutics targeting filamentous virus particles could overcome antiviral drug resistance and immune evasion in pleomorphic viruses.

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Fig. 1: Particle fractions.
Fig. 2: Filamentous virus particles have an infectivity advantage when HA functions in receptor attachment or membrane fusion are inhibited.
Fig. 3: Filamentous particles fuse more rapidly and/or more efficiently depending on the extent of HA inactivation.
Fig. 4: Filamentous particles are resistant to extreme HA inactivation.
Fig. 5: Endosomal fusion is insensitive to rate changes that result from HA inhibition.
Fig. 6: The lower sensitivity of filamentous particles to neutralizing antibodies is a general property of pleomorphic viruses.

Data availability

All manuscript data are provided within the paper and its Supplementary Information. There are no restrictions on data availability. Source data are provided with this paper.

Code availability

The MATLAB code for stochastic simulations is available at https://doi.org/10.7554/eLife.11009. The MATLAB codes for fusion data analysis were previously described (https://doi.org/10.1073/pnas.0807771105, https://doi.org/10.7554/eLife.00333 and https://doi.org/10.7554/eLife.11009). The new MATLAB codes used for fluorescence-intensity analysis are included in the Supplementary Information. All codes are deposited at GitHub (https://doi.org/10.5281/zenodo.3883000, https://github.com/tivanovic/Ivanovic-lab-analysis-codes).

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Acknowledgements

We thank G. Bajic (Harvard Medical School) for help with Fab expression and purification; M. Popovic (Boston University) for help with analysis codes; and S. C. Harrison (Harvard Medical School), B. L. Goode (Brandeis University), P. L. Yang (Stanford University) and A. S. Y. Lee (Brandeis University) for comments on the manuscript. We acknowledge support from the NIH Director’s New Innovator Award 1DP2GM128204 (to T.I.), the NSF MRSEC DMR-1420382 (to T.I.) and the NIH grant R01AI134824 (to K.C.).

Author information

Authors and Affiliations

  1. Biochemistry Department, Brandeis University, Waltham, MA, USA

    Tian Li, Zhenyu Li, Erin E. Deans, Meisui Liu & Tijana Ivanovic

  2. Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA

    Eva Mittler & Kartik Chandran

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  1. Tian Li
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Contributions

T.L.: experiment design, acquisition of data, analysis and interpretation of data. Z.L., M.L. and E.E.D.: acquisition of data, analysis and interpretation of data. E.M. and K.C.: EBOV expertise, reagents and DNA constructs. T.I.: conception and design, experiment design, acquisition of data, analysis and interpretation of data, and writing of the manuscript. All of the authors contributed to the revision of the manuscript.

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Correspondence to Tijana Ivanovic.

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K.C. is a member of the Scientific Advisory Board of Integrum Scientific, LLC. The remaining authors declare no competing interests.

Additional information

Peer review information: Nature Microbiology thanks Michael Vahey and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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

Extended data

Extended Data Fig. 1 A full scTCID50 dataset used to calculate fold-inhibition of infectivity by HC19 IgG and M-Fab.

a, HC19 inhibition panel. b, M-Fab inhibition panel. The no-inhibitor baselines for the PEL and SUP fractions from which the infectivity shifts are measured in Fig. 2c,f are shown on all plots along with the corresponding curves at each inhibitor concentration.

Source data

Extended Data Fig. 2 Flow cytometry analysis of influenza virus binding to cells.

MDCK-siat7e cells were incubated with the equal input HAU of PEL or SUP fractions, and the cell-associated virus-specific epitopes were detected using antibodies against either the M1 (HB-64 IgG) or NP (HB-65 IgG). a, The singlet-cell population analyzed in b, and c. The same gating was applied to all samples (Supplementary Fig. 1). b, Sample histograms showing cell-associated M1 or NP intensities of the Mock, SUP, and PEL samples. c, The median intensity data for M1 and NP were normalized to SUP signals. Data are mean ± s.d. of three independent experiments. Individual measurements are overlaid as dot plots.

Source data

Extended Data Fig. 3 Sample RNAscope images of a complete HC19-concentration dataset.

a, Sample RNAscope images at t0 detecting viral (-)RNA (red), and its overlays with DAPI (blue) and DIC (grey) for a range of HC19 IgG concentrations. Scale bar, 20 µm. n = 10 images or greater were processed per experiment to yield quantification in Fig. 2h,i. b, (+)RNA detection (green) at t12 with a range of HC19 IgG concentrations. Scale bar, 50 µm. n = 5–40 images were scored per experiment.

Extended Data Fig. 4 HC19 IgG is more effective at inhibiting haemagglutination by the SUP than PEL particles.

An assay measuring the agglutination of red-blood cells by the SUP and PEL fractions via HA-receptor interactions in the presence of HC19 IgG. HAI was calculated relative to a no-HC19 control. Mean ± s.d. of three independent experiments is shown. Statistical analysis was performed using one-sided Student’s t-tests comparing SUP and PEL datasets; P=0.40 (1.25nM), P=0.0096 (2.5nM), P=0.0012 (5nM), P=0.054 (10nM), and P=0.0027 (20nM); NS, P>0.05, *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001).

Source data

Extended Data Fig. 5 The filamentous PEL particles are less sensitive to M-Fab than the spherical PEL particles.

Sample scTCID50 experiment (top), and the mean±s.d. of three independent scTCID50 experiments (bottom) with individual measurements overlaid as dot plots. The extent of inhibition (fold-increase in scTCID50) is expressed either relative to untreated (M-Fab or EIPA alone) or relative to EIPA-treated samples (M-Fab and EIPA together). Statistical analysis was performed using one-sided Student’s t-tests comparing SUP and PEL datasets; P=0.00011 (M-Fab/Unt), P=0.28 (EIPA/Unt), and P=0.081 (M-Fab/EIPA); NS, P>0.05, ***P<0.001).

Source data

Extended Data Fig. 6 Quantification of M-Fabfl binding to unlabeled particles.

Glass coverslips were passivated with a mixture of polyethylene glycol (PEG) and PEG-biotin. Biotinylated antibody targeting HA1 is specifically captured with neutravidin, and it recruits virus particles for imaging. Virus particles were pre-incubated with 134 nM M-Fabfl before capture, and unbound M-Fabfl was washed away after capture. a, Representative particle-images (left), and the particle fluorescence-intensity quantification at neutral pH (middle), or after 20 minutes at pH 4.8 (right). Data were pooled from n=4 videos taken in the same flow-cell chamber. The number of particles (n) represented by the histograms is indicated on the plots. Scale bar, 5 µm. b, Median±s.e. fluorescence intensity from the data plotted in histograms in (a). Wilcoxon rank sum and the two-sample Kolmogorov-Smirnov tests (both one-sided) were performed on each pair of SUP and PEL distributions, or on each pH7.4 and pH4.8 pair: pH7.4, P (RS)=1.52e-7 and P (KS)=5.66e-7; pH4.8, P (RS)=8.41e-7 and P (KS)=1.9e-9; SUP, P (RS)=0.45 and P (KS)=0.49; PEL, P (RS)=0.42 and P (KS)=0.29; NS, P>0.05, ****P<0.0001). c, The fluorescence-intensity quantification for the short WT, D1122A, and H171Y particles after 20 minutes at pH 4.8. Histograms of the entire data sets and the corresponding bar plot of the medians±s.e. are shown and derive from n=4 videos each taken in the same flow-cell chamber. Wilcoxon rank sum and the two-sample Kolmogorov-Smirnov tests (both one-sided) reveal statistically significant differences between the M-Fabfl distributions for the WT and each of the mutants: D1122A, P (RS)=0.0027 and P (KS)=0.0072; H171Y, P (RS)=0.00052 and P (KS)=0.00012; **P<0.01, ***P<0.001, but the overall differences are small (medians are within 25% of each other in each case).

Source data

Extended Data Fig. 7 Single-particle measurements of membrane fusion for the D1122A and H171Y particles.

Hemifusion lag times with a gamma-distribution fit (red line). Data from several experiments were pooled where each condition was represented on each day. The total number of particles (n) represented by each histogram is indicated. a, Short WT and D1122A particles, pH 5.2 b, Short WT and H171Y particles, pH 4.8.

Source data

Extended Data Fig. 8 D1122A and H171Y particle fractionation and scTCID50 measurements.

a and b, Particle-length distributions derived from the electron micrographs as shown in Fig. 1a. Length data were normalized such that the total area under the bars is equal to 1 for all of the plots. The dotted vertical lines mark 0.25 µm length cutoff, and the percentage of particles longer than 0.25 µm is indicated above. Insets: the mean particle length for the entire population (black bar), or the subset of the population longer than 0.25 µm (grey bar). c and d, Sample D1122A (c) and H171Y (d) cell-death data plotted in Fig. 5c–e. The no-inhibitor baseline values (shown on all plots) were used in Fig. 5c or as values from which to calculate the infectivity shifts in the presence of M-Fab in Fig. 5d,e.

Source data

Extended Data Fig. 9 Model for the role of filamentous particles in viral adaptation and persistence.

Viral progeny is pleomorphic independent of the initiating-virus morphology. Circles, spherical particles; ellipses, filamentous particles. Random mutations arise during virus replication. Blue, WT particles; other colours, mutant particles. a, Under low pressures on the cell-entry machinery, infections by spherical particles dominate. Spherical particles might become internalized via clathrin-mediated endocytosis (CME) as in the case of influenza virus, or macropinocytosis as in the case of EBOV28,41. Filamentous particles invariably require macropinocytosis for internalization.. b, Under high pressures on the cell-entry machinery, filamentous particles can enter cells permitting some level of replication when spherical particles are unable, and can by random chance lead to adaptive mutations (red). c, Preventing filamentous particle assembly or internalization (for example by using macropinocytosis inhibitors) might avert viral adaptation to an immune pressure or man-made inhibitors. The same strategy might apply to preventing zoonotic adaptations that can lead to viral pandemics.

Extended Data Fig. 10 Influenza and reovirus EM images.

Sample EM images of mixtures of WT influenza SUP or PEL particles and reovirus particles. Small arrows point to reovirus particles. Influenza virus particles are readily distinguishable by the characteristic glycoprotein layer coating the particles of various sizes including some comparable in size to reovirus particles. Scale bar, 500 nM.

Supplementary information

Supplementary Information

Supplementary Fig. 1 and Table 1.

Reporting Summary

Supplementary Video 1

A sample video of SUP-fraction hemifusion at pH 5.2 and no M-Fab. The exposure time is 0.5 s and the video is at 80 frames per second (f.p.s.).

Supplementary Video 2

A sample video of the PEL-fraction hemifusion at pH 5.2 and no M-Fab. The exposure time is 0.5 s and the video is at 80 f.p.s.

Supplementary Video 3

A sample video of the SUP-fraction hemifusion at pH 5.2 and 134 nM M-Fab. The exposure time is 0.8 s and the video is at 50 f.p.s.

Supplementary Video 4

A sample video of the PEL-fraction hemifusion at pH 5.2 and 134 nM M-Fab. The exposure time is 0.8 s and the video is at 50 f.p.s.

Supplementary Software 1

See the ‘Particle fluorescence-intensity measurements’ section in the Methods.

Supplementary Software 2

See the ‘Particle fluorescence-intensity measurements’ section in the Methods.

Supplementary Software 3

See the ‘Particle fluorescence-intensity measurements’ section in the Methods.

Peer Review File

Source data

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Unprocessed western blot for Fig. 4c.

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Li, T., Li, Z., Deans, E.E. et al. The shape of pleomorphic virions determines resistance to cell-entry pressure. Nat Microbiol 6, 617–629 (2021). https://doi.org/10.1038/s41564-021-00877-0

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