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Capturing the start point of the virus–cell interaction with high-speed 3D single-virus tracking

Nature Methods volume 19, pages 1642–1652 (2022)Cite this article

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Abstract

The early stages of the virus–cell interaction have long evaded observation by existing microscopy methods due to the rapid diffusion of virions in the extracellular space and the large three-dimensional cellular structures involved. Here we present an active-feedback single-particle tracking method with simultaneous volumetric imaging of the live cell environment called 3D-TrIm to address this knowledge gap. 3D-TrIm captures the extracellular phase of the infectious cycle in what we believe is unprecedented detail. We report what are, to our knowledge, previously unobserved phenomena in the early stages of the virus–cell interaction, including skimming contact events at the millisecond timescale, orders of magnitude change in diffusion coefficient upon binding and cylindrical and linear diffusion modes along cellular protrusions. Finally, we demonstrate how this method can move single-particle tracking from simple monolayer culture toward more tissue-like conditions by tracking single virions in tightly packed epithelial cells. This multiresolution method presents opportunities for capturing fast, three-dimensional processes in biological systems.

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Fig. 1: 3D tracking and imaging (3D-TrIm).
Fig. 2: Minute-long high-resolution 3D tracking and volumetric live cell imaging reveals transient VSV-G VLP contacts with the cell surface.
Fig. 3: VSV-G VLP binding.
Fig. 4: Virus interaction with cellular protrusions.
Fig. 5: VSV-G VLP diffusing through multi-layered epithelial cells.
Fig. 6: Internalized viral trafficking.

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Data availability

Raw data files for 3D-TrIm trajectories in all main text figures can be found at the Duke University Research Data Repository at https://doi.org/10.7924/r4bp07h15.

Code availability

Code to analyze single virus trajectories (MATLAB) and render them (Amira) is available at https://github.com/welsherlab/3dtrim.

References

  1. Baos, S. C., Phillips, D. B., Wildling, L., McMaster, T. J. & Berry, M. Distribution of sialic acids on mucins and gels: a defense mechanism. Biophys. J. 102, 176–184 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Kesimer, M. et al. Molecular organization of the mucins and glycocalyx underlying mucus transport over mucosal surfaces of the airways. Mucosal Immunol. 6, 379–392 (2013).

    Article  CAS  PubMed  Google Scholar 

  3. Linden, S. K., Sutton, P., Karlsson, N. G., Korolik, V. & McGuckin, M. A. Mucins in the mucosal barrier to infection. Mucosal Immunol. 1, 183–197 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Ridley, C. & Thornton, D. J. Mucins: the frontline defence of the lung. Biochem. Soc. Trans. 46, 1099–1106 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Thornton, D. J., Rousseau, K. & McGuckin, M. A. Structure and function of the polymeric mucins in airways mucus. Annu. Rev. Physiol. 70, 459–486 (2008).

    Article  CAS  PubMed  Google Scholar 

  6. Tomlin, H. & Piccinini, A. M. A complex interplay between the extracellular matrix and the innate immune response to microbial pathogens. Immunology 155, 186–201 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Pais-Correia, A.-M. et al. Biofilm-like extracellular viral assemblies mediate HTLV-1 cell-to-cell transmission at virological synapses. Nat. Med. 16, 83–89 (2010).

    Article  CAS  PubMed  Google Scholar 

  8. Brandenburg, B. & Zhuang, X. Virus trafficking—learning from single-virus tracking. Nat. Rev. Microbiol. 5, 197–208 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Liu, S. L. et al. Single-virus tracking: from imaging methodologies to virological applications. Chem. Rev. 120, 1936–1979 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Parveen, N., Borrenberghs, D., Rocha, S. & Hendrix, J. Single viruses on the fluorescence microscope: imaging molecular mobility, interactions and structure sheds new light on viral replication. Viruses 10, 250 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bhagwat, A. R. et al. Quantitative live cell imaging reveals influenza virus manipulation of Rab11A transport through reduced dynein association. Nat. Commun. 11, 23 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Lakdawala, S. S. et al. Influenza A virus assembly intermediates fuse in the cytoplasm. PLoS Pathog. 10, e1003971 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Endress, T. et al. HIV-1-cellular interactions analyzed by single virus tracing. Eur. Biophys. J. 37, 1291–1301 (2008).

    Article  CAS  PubMed  Google Scholar 

  14. Seisenberger, G. et al. Real-time single-molecule imaging of the infection pathway of an adeno-associated virus. Science 294, 1929–1932 (2001).

    Article  CAS  PubMed  Google Scholar 

  15. Rust, M. J., Lakadamyali, M., Zhang, F. & Zhuang, X. Assembly of endocytic machinery around individual influenza viruses during viral entry. Nat. Struct. Mol. Biol. 11, 567–573 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Pelkmans, L., Kartenbeck, J. & Helenius, A. Caveolar endocytosis of simian virus 40 reveals a new two-step vesicular-transport pathway to the ER. Nat. Cell Biol. 3, 473–483 (2001).

    Article  CAS  PubMed  Google Scholar 

  17. Cureton, D. K., Harbison, C. E., Cocucci, E., Parrish, C. R. & Kirchhausen, T. Limited transferrin receptor clustering allows rapid diffusion of canine parvovirus into clathrin endocytic structures. J. Virol. 86, 5330–5340 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Sun, E. Z. et al. Real-time dissection of distinct dynamin-dependent endocytic routes of influenza A virus by quantum dot-based single-virus tracking. ACS Nano 11, 4395–4406 (2017).

    Article  CAS  PubMed  Google Scholar 

  19. Xu, H. et al. Real-time imaging of rabies virus entry into living vero cells. Sci. Rep. 5, 11753 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lakadamyali, M., Rust, M. J., Babcock, H. P. & Zhuang, X. Visualizing infection of individual influenza viruses. Proc. Natl Acad. Sci. USA 100, 9280–9285 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. van der Schaar, H. M. et al. Dissecting the cell entry pathway of dengue virus by single-particle tracking in living cells. PLoS Pathog. 4, e1000244 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  22. van der Schaar, H. M. et al. Characterization of the early events in dengue virus cell entry by biochemical assays and single-virus tracking. J. Virol. 81, 12019–12028 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Coller, K. E. et al. RNA interference and single particle tracking analysis of hepatitis C virus endocytosis. PLoS Pathog. 5, e1000702 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Qin, C. et al. Real-time dissection of dynamic uncoating of individual influenza viruses. Proc. Natl Acad. Sci. USA 116, 2577–2582 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Li, Q. et al. Single-particle tracking of human immunodeficiency virus type 1 productive entry into human primary macrophages. ACS Nano 11, 3890–3903 (2017).

    Article  CAS  PubMed  Google Scholar 

  26. Ewers, H. et al. Single-particle tracking of murine polyoma virus-like particles on live cells and artificial membranes. Proc. Natl Acad. Sci. USA 102, 15110–15115 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Suomalainen, M. et al. Microtubule-dependent plus- and minus end-directed motilities are competing processes for nuclear targeting of adenovirus. J. Cell Biol. 144, 657–672 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. McDonald, D. et al. Visualization of the intracellular behavior of HIV in living cells. J. Cell Biol. 159, 441–452 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Bailey, C. J., Crystal, R. G. & Leopold, P. L. Association of adenovirus with the microtubule organizing center. J. Virol. 77, 13275–13287 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Arhel, N. et al. Quantitative four-dimensional tracking of cytoplasmic and nuclear HIV-1 complexes. Nat. Methods 3, 817–824 (2006).

    Article  CAS  PubMed  Google Scholar 

  31. Liu, S. L. et al. Effectively and efficiently dissecting the infection of influenza virus by quantum-dot-based single-particle tracking. ACS Nano 6, 141–150 (2012).

    Article  CAS  PubMed  Google Scholar 

  32. Zhang, L. J. et al. A ‘driver switchover’ mechanism of influenza virus transport from microfilaments to microtubules. ACS Nano 12, 474–484 (2018).

    Article  CAS  PubMed  Google Scholar 

  33. Wu, Q. M. et al. Uncovering the Rab5-independent autophagic trafficking of influenza A virus by quantum-dot-based single-virus tracking. Small 14, e1702841 (2018).

    Article  PubMed  Google Scholar 

  34. Sherer, N. M. et al. Retroviruses can establish filopodial bridges for efficient cell-to-cell transmission. Nat. Cell Biol. 9, 310–315 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Dixit, R., Tiwari, V. & Shukla, D. Herpes simplex virus type 1 induces filopodia in differentiated P19 neural cells to facilitate viral spread. Neurosci. Lett. 440, 113–118 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Schelhaas, M. et al. Human papillomavirus type 16 entry: retrograde cell surface transport along actin-rich protrusions. PLoS Pathog. 4, e1000148 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Sowinski, S. et al. Membrane nanotubes physically connect T cells over long distances presenting a novel route for HIV-1 transmission. Nat. Cell Biol. 10, 211–219 (2008).

    Article  CAS  PubMed  Google Scholar 

  38. Mercer, J. & Helenius, A. Vaccinia virus uses macropinocytosis and apoptotic mimicry to enter host cells. Science 320, 531–535 (2008).

    Article  CAS  PubMed  Google Scholar 

  39. Jose, J., Tang, J., Taylor, A. B., Baker, T. S. & Kuhn, R. J. Fluorescent protein-tagged Sindbis virus E2 glycoprotein allows single particle analysis of virus budding from live cells. Viruses 7, 6182–6199 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Gao, L., Shao, L., Chen, B.-C. & Betzig, E. 3D live fluorescence imaging of cellular dynamics using Bessel beam plane illumination microscopy. Nat. Protoc. 9, 1083–1101 (2014).

    Article  CAS  PubMed  Google Scholar 

  41. Planchon, T. A. et al. Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination. Nat. Methods 8, 417 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Hou, S., Johnson, C. & Welsher, K. Real-time 3D single particle tracking: towards active feedback single molecule spectroscopy in live cells. Molecules 24, 2826 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Hou, S., Exell, J. & Welsher, K. Real-time 3D single molecule tracking. Nat. Commun. 11, 3607 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Hou, S., Lang, X. & Welsher, K. Robust real-time 3D single-particle tracking using a dynamically moving laser spot. Opt. Lett. 42, 2390–2393 (2017).

    Article  CAS  PubMed  Google Scholar 

  45. Hou, S. & Welsher, K. An adaptive real-time 3D single particle tracking method for monitoring viral first contacts. Small 15, e1903039 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Johnson, C., Exell, J., Kuo, J. & Welsher, K. Continuous focal translation enhances rate of point-scan volumetric microscopy. Opt. Express 27, 36241–36258 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Finkelshtein, D., Werman, A., Novick, D., Barak, S. & Rubinstein, M. LDL receptor and its family members serve as the cellular receptors for vesicular stomatitis virus. Proc. Natl Acad. Sci. USA 110, 7306–7311 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Naldini, L. et al. In vivo gene delivery and stable transduction of nondividing cells by a lentiviral vector. Science 272, 263–267 (1996).

    Article  CAS  PubMed  Google Scholar 

  49. Desai, T. M. et al. Fluorescent protein-tagged Vpr dissociates from HIV-1 core after viral fusion and rapidly enters the cell nucleus. Retrovirology 12, 88 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Montiel, D., Cang, H. & Yang, H. Quantitative characterization of changes in dynamical behavior for single-particle tracking studies. J. Phys. Chem. B 110, 19763–19770 (2006).

    Article  CAS  PubMed  Google Scholar 

  51. Welsher, K. & Yang, H. Multi-resolution 3D visualization of the early stages of cellular uptake of peptide-coated nanoparticles. Nat. Nanotechnol. 9, 198–203 (2014).

    Article  CAS  PubMed  Google Scholar 

  52. Jensen, C. & Teng, Y. Is it time to start transitioning from 2D to 3D cell culture? Front. Mol. Biosci. 7, 33 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Button, B. et al. A periciliary brush promotes the lung health by separating the mucus layer from airway epithelia. Science 337, 937–941 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Perillo, E. P. et al. Deep and high-resolution three-dimensional tracking of single particles using nonlinear and multiplexed illumination. Nat. Commun. 6, 7874 (2015).

    Article  CAS  PubMed  Google Scholar 

  55. Nasir, W., Bally, M., Zhdanov, V. P., Larson, G. & Höök, F. Interaction of virus-like particles with vesicles containing glycolipids: kinetics of detachment. J. Phys. Chem. B 119, 11466–11472 (2015).

    Article  CAS  PubMed  Google Scholar 

  56. Zhang, C. & Welsher, K. Information-efficient, off-center sampling results in improved precision in 3D single-particle tracking microscopy. Entropy (Basel) 23, 498 (2021).

    Article  PubMed  Google Scholar 

  57. Hamming, P. H. E., Overeem, N. J. & Huskens, J. Influenza as a molecular walker. Chem. Sci. 11, 27–36 (2020).

    Article  CAS  PubMed  Google Scholar 

  58. Peacock, T. P. et al. The furin cleavage site in the SARS-CoV-2 spike protein is required for transmission in ferrets. Nat. Microbiol. 6, 899–909 (2021).

    Article  CAS  PubMed  Google Scholar 

  59. Bobba, C. M. et al. Nanoparticle delivery of microRNA-146a regulates mechanotransduction in lung macrophages and mitigates injury during mechanical ventilation. Nat. Commun. 12, 289 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Sun, D., Zhou, S. & Gao, W. What went wrong with anticancer nanomedicine design and how to make it right. ACS Nano 14, 12281–12290 (2020).

    Article  CAS  PubMed  Google Scholar 

  61. Wang, Q. & Moerner, W. E. Optimal strategy for trapping single fluorescent molecules in solution using the ABEL trap. Appl. Phys. B 99, 23–30 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Mermillod-Blondin, A., McLeod, E. & Arnold, C. B. High-speed varifocal imaging with a tunable acoustic gradient index of refraction lens. Opt. Lett. 33, 2146–2148 (2008).

    Article  PubMed  Google Scholar 

  63. Fields, A. P. & Cohen, A. E. Optimal tracking of a Brownian particle. Opt. Express 20, 22585–22601 (2012).

    Article  PubMed  Google Scholar 

  64. Garcia, D. Robust smoothing of gridded data in one and higher dimensions with missing values. Comput. Stat. Data Anal. 54, 1167–1178 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Wakabayashi, Y., Chua, J., Larkin, J. M., Lippincott-Schwartz, J. & Arias, I. M. Four-dimensional imaging of filter-grown polarized epithelial cells. Histochem. Cell Biol. 127, 463–472 (2007).

    Article  CAS  PubMed  Google Scholar 

  66. Ortinski, P. I., O’Donovan, B., Dong, X. & Kantor, B. Integrase-deficient lentiviral vector as an all-in-one platform for highly efficient CRISPR/Cas9-mediated gene editing. Mol. Ther. Methods Clin. Dev. 5, 153–164 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We acknowledge financial support from the National Institute of General Medical Sciences of the National Institutes of Health under award number R35GM124868 (K.D.W.). We also acknowledge the Duke Viral Vector Core for assistance with virus-like particle generation and the Duke Cell Culture Facility for access to cell lines used in this study. We further thank LSM Tech for help customizing the laser scanning microscope for integration into the 3D-TrIm setup. We are also grateful to Duke Office of Information Technology (OIT) and Duke Research Computing for facilitating access to Amira 3D 2021.1 for data rendering.

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Author notes

  1. These authors contributed equally: Courtney Johnson, Jack Exell.

Authors and Affiliations

  1. Department of Chemistry, Duke University, Durham, NC, USA

    Courtney Johnson, Jack Exell, Yuxin Lin, Jonathan Aguilar & Kevin D. Welsher

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  1. Courtney Johnson
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Contributions

C.J., J.E. and K.D.W. conceptualized the study. C.J., J.E. and K.D.W. were responsible for the methodology. C.J., J.E. and Y.L. performed investigations. C.J., J.E., Y.L., J.A. and K.D.W. curated the data. C.J., J.E., Y.L., J.A. and K.D.W. performed visualizations. K.D.W. was responsible for funding acquisition. C.J., J.E. and K.D.W. wrote the original draft and reviewed and edited the manuscript.

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Correspondence to Kevin D. Welsher.

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Nature Methods thanks Hari Shroff and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Madhura Mukhopadhyay, in collaboration with the Nature Methods team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Instrument Diagram.

3D-TrIm Instrument Diagram. The 3D-TrIm microscope consists of two excitation sources: one for single-particle tracking and one for imaging. The tracking laser position is modulated using two electro-optic deflectors (EOD) and tunable acoustic gradient (TAG) lens. The imaging laser focus is modulated by an electrically tunable lens (ETL) and the beam is sampled by beam-splitters (BS) and evaluated using a system of photodiodes (PD). This focus is relayed using two lenses (IL). The tracking laser enters the underside of the LSM410 through a dichroic mirror (DCM2) where it ultimately couples with the imaging laser through DCM1 toward the shared objective lens and piezoelectric stage. After exciting the sample, the fluorescence emission pathway is shared between tracking and imaging until separated by DCM3.

Extended Data Fig. 2 Comparison of image-based tracking and imaging (spinning disk confocal) with active-feedback tracking and complementary 3D imaging (3D-TrIm).

Fluorescently-labeled virus-like particles (eGFP-Vpr VSVG) were introduced to cultures of live HeLa cells stained with SiR650-actin (100 nm). a-e, Data collected on Andor Dragon fly spinning disk confocal microscope. The same area was sampled continuously. Each volume has a depth of 8 μm split into 16 z planes. Virus particles and cells were imaged simultaneously with a camera exposure time of 40 msec. f-j, Data collected on 3D-TrIm microscope. A single virus particle was tracked continuously (1 msec sampling shown) and the surrounding area was imaged 5 μm below the particle and 3 μm above, to give an approximate 8 μm volume. The resulting trajectories over the entire acquisition period are shown and color-coded by time. Gray box in XZ projections shows the size of the spinning disk imaging volume for comparison. Experiments were performed in live-cell image solution with 2% FBS and maintained at 37 °C.

Extended Data Fig. 3 High resolution tracking and 3D imaging data, related to Fig. 2.

a, Local Volume MIPs. b, Tracking intensity trace. Both a and b are associated with VSV-G/HeLa tracking and imaging render, Fig. 2c–g. c, Local Volume MIPs, local volumes from 138-162 sec have been omitted as trajectory diffuses a greater distance above the cells than the axial range of the ETL. Note in volume 2 from 17-34s there is a noted absence of intensity due to transit in Z of the particle away from the cells. This can appear as striping due to unsampled voxels and is a feature of local volumes, especially when displayed as MIPs. d, Tracking intensity trace. Both c and d are associated VSV-G/GM701 tracking and imaging render, Fig. 2h-j.

Extended Data Fig. 4 Virus-to-cell distance map calculation.

a and b, The full trajectory is shown in white. Using the top-hat-generated isosurface (gray, see Supplementary Information 3.4) from 3D-FASTR imaging data the distance from each trajectory point to each surface vertex is calculated as describe in Supplementary Information Section 3.5. The minimum distance is then assigned to each data point (purple lines, only every 50th data point is shown for clarity and every 10th data point in the insert). The vectors from the vertex to the data point corresponding to the minimum distance are also shown as spheres on the cellular contour. a is related to trajectory shown in Fig. 2c-g, b is related to trajectory shown in Fig. 2h-j.

Extended Data Fig. 5 Additional example 1 of VSV-G VLP freely diffusing in the extracellular space.

a, Top-down view of virus trajectory pincering live HeLa cell. b, Virus-to-cell distance representation of trajectory in a. a and b share the same axes and scale bar. c,d, Different view of the trajectory shown in a, b. Circular insets shows close-up views of virus in close contact with the cell surface. c and d share the same axes and scale bar. e, Cross-section with slice along x and y axis, overlaid with trajectory color-coded by diffusion coefficient. a, c, and e are color-coded by image intensity, while b and d display virus-to-cell distance map on surface of cell. f, Top, correlation between diffusivity and distance from the cell surface of VSV-G VLP, close-approaches (below 0.5 µm) are color patched purple. Dashed purple line, 0.5 µm from cell surface. Below left, enlarged view of data between 14.5-25.5 sec, associated with trajectory segment displayed in circular inset of d. Below right, enlarged view of data between 43.25-56 sec, associated with trajectory segment displayed in circular inset of d. g, Visual representation of virus-to-cell distance calculation. Isosurface volume render of cell image (gray) overlayed with trajectory sampled at 3 msec (white). Distance vectors are calculated from each trajectory timepoint to the isosurface (generated by top-hat transform) and displayed as color-coded spheres on the cell surface.

Extended Data Fig. 6 Additional example of VSV-G VLP Binding Event.

a, 3D-TrIm render of BJ Fibroblast cells stained with SiR-650 (f-Actin). b, Distance-diffusivity trace of viral trajectory. This trajectory begins with rapid extracellular diffusion before binding to the surface. A small ~1 second detachment occurs before re-binding for several seconds and detaching again where skimming is observed with inhibited diffusivity compared to the initial free diffusion, followed by free diffusion that has greater diffusivity than observed while skimming, but lower than the initial free diffusion.

Extended Data Fig. 7 Additional example 1 of VLP-protrusion interaction.

a, Top-down view of VSV-G VLP landing on protrusion from the surface of a live cell. 3D volume rendering of live HeLa cells (stained with SYTO61) co-registered with high resolution virus trajectory from 4D tracking and imaging data. b, c Alternate views of the trajectory shown in a. d, Magnified views showing cylindrical nature of trajectory and proximity to cell surface. e, Top-down view, with trajectory colored by diffusion coefficient, free portion with D > 1.5 × 10−2 μm2/s colored gray. f, Color-coded trajectory, showing free diffusion (D > 1.5 × 10−2 μm2/s, gray) and bound diffusion (green-yellow). g, Cylindrical fitting of the bound portion of the trajectory in a-f (28-120 sec), fitted cylinder (magenta) has a radius of 122 ± 8.4 nm after taking into consideration the tracked particle diameter. h, View of trajectory along the cylinder axis. i, Intensity trace of tracked VLP.

Extended Data Fig. 8 High resolution tracking and simultaneous 3D imaging localizes VSV-G VLP diffusion along fibroblast protrusion.

a, Left, top-down view of VSV-G VLP ‘surfing’ on actin-stained protrusion of BJ fibroblast. Trajectory colored by time. The lower, brighter, z-planes have been omitted to help visualize the protrusion the VLP is localized to. Right, same view but trajectory color-coded by diffusivity. b, Snapshots of 3D reconstruction. The sustained linear motion correlates with the lateral surface of the protrusion, large changes in diffusivity where detected. c, (left) XY MIP, (middle) magnified, and (right) YZ MIP of viral diffusion on actin-rich protrusion.

Extended Data Fig. 9 Additional example of VSV-G VLP circumnavigating HT29-MTX cells.

a, 3D reconstruction from a 4D data set covering 3 local volumes, at 16 FPV of suspended HT29-MTX cells grown on inverted matrix stained with SiR650-actin with high resolution trajectory. Below, axial view. b, Magnified view. c, Cell boundary reconstruction highlighting sample density. d, XY MIP. e, 3D reconstruction of cellular imaging data in a with trajectory split into unique segments of diffusion behavior via change-point analysis. f, VLP intensity trace.

Extended Data Fig. 10 Multi-trajectory acquisition.

a, Left: 10 VSV-G VLP trajectories collected in the same area of live HeLa cells stained with SYTO61 (see also: Supplementary Fig. 29 and Supplementary Video 8). Right: top-down (xy) MIP with multiple co-registered VLP trajectories. Colorbar represents trajectory number, with each trajectory uniquely colored. b, The dwell time of 27 VSV-G VLP trajectories (starting from free diffusion) collected in the same area as a were binned into voxels and represented as spheres, color-mapped by diffusivity. This correlated analysis reveals commonly visited regions and highlights the slower diffusion experienced by the VLP population nearer the cell surface. Inset: two different VLPs land in close proximity on the same cell. c, Exploded views showing multiple VLPs contact the same cell.

Supplementary information

Supplementary Information

Supplementary methods and Figs. 1–30, and description of Supplementary Videos.

Reporting Summary

Peer Review File

Supplementary Video 1

3D-TrIm method animation, related to Fig. 1. Demonstration of 3D-TrIm operating principle. Animation sequence begins with overview of experimental setup in which a heated sample containing virus-like particles (VLP) and live cells are mounted on a piezoelectric stage with an objective lens shared by both tracking and imaging microscope sources. This overview is followed by an animation of 3D-SMART real-time tracking, demonstrating how a pair of Electro-Optic Deflectors (EOD) create a lateral Knight’s Tour grid pattern, followed by the use of a Tunable Acoustic Gradient (TAG lens) to scan a focal range above and below the center of the focal volume. A final animation demonstrates the principle of 3D-FASTR point-scan imaging.

Supplementary Video 2

VSV-G exploring the extracellular matrix, related to Fig. 2a,b. 3D reconstruction of real-time VSV-G VLP trajectory in extracellular matrix of live GM701 cells (stained with F-actin label SiR650-actin), from a 4D dataset covering 10 local volumes, at 16 FPV. Trajectory (~162 s) is segmented into 25 segments per second (25 frames per second when playback rate is 1×) and color mapped by time. The progress bar shows how the trajectory is further categorized: (1) Free diffusion period (playback rate: 2×): 0–14 s, 18–38 s, 44–62 s, 70–108 s. (2) Skimming period (playback rate: 1×): 14–18 s, 38–44 s, 62–70 s, 108–122 s. (3) Detachment (playback rate: 2×): 122–162 s. Sphere represents the VLP position in the current frame (refreshing rate is consistent with the trajectory, that is, 25 FPS at 1× playback rate). Image volumes formed from maximum intensity projection over time from local volumes acquired over 16 frame-times. In a, cells are color-coded by imaging intensity, while in b, cells are color-coded depending on distance of the virus from the cell surface. Panels a and b share the same trajectory color scale, camera angle and camera path; however, a is magnified compared with b.

Supplementary Video 3

VSV-G VLP skimming and binding, related to Fig. 3a–c. 3D reconstruction of live HeLa cells (stained with nucleic acid label SYTO61) corendered with virus trajectory. Trajectory (~123 s) is segmented into 25 segments per second (25 frames per second when playback rate is 1×) and color mapped by time. The progress bar shows how the trajectory is further categorized: (1) Free diffusion period (playback rate: 2×): 14–30 s, 41–70 s. (2) Skimming period (playback rate: 1×): 0–14 s, 30–41 s. (3) Immobilized period (playback rate: 4×): 70–123 s. The end points of trajectory segments are labeled with spheres (refreshing rate is consistent with the trajectory, that is, 25 FPS at 1× playback rate), representing the position of the viral particle. The diffusional status of viral particle is further illustrated by the color change of the sphere (gray, free motion; cyan, skimming behavior; purple, immobilization). Image volumes formed from maximum intensity projection over time from local volumes acquired over 16 frame-times. Cells are color-coded by image intensity.

Supplementary Video 4

VSV-G VLP transient binding, related to Fig. 3e–g. 3D reconstruction of live GM701 cells (stained with F-actin label SiR650-actin) corendered with virus trajectory. Trajectory (~54 s) is segmented into 25 segments per second and color mapped by diffusivity. The playback rate is constant 1×. Image volumes formed from maximum intensity projection over time from local volumes acquired over 16 frame-times. Cells are color-coded by image intensity. We observed the VLP repeatedly landing and detaching.

Supplementary Video 5

VSV-G VLP interaction with cell surface protrusion, related to Fig. 4. 3D reconstruction of live HeLa cells (stained with nucleic acid label SYTO61) corendered with virus trajectory. Trajectory (~133 s) is segmented into 25 segments per second (25 frames per second when playback rate is 1×) and color mapped by time. Image volumes formed from maximum intensity projection over time from local volumes acquired over 16 frame-times. Cells are color-coded by image intensity. Shown in the progress bar, the trajectory is further categorized into two segments: (1) Free diffusion (playback rate: 1×): 0–16 s. (2) Membrane-bound diffusion on protrusion: 16–133 s.

Supplementary Video 6

VSV-G VLP diffusing through multi-layered epithelial cells, related to Fig. 5. 3D reconstruction of suspended HT29-MTX cells grown on inverted matrix support (stained with F-actin label SiR650-actin) corendered with virus trajectory. Trajectory (~166 s) is segmented into 25 segments per second (25 frames per second) and color mapped by time. The playback rate is constant 4×. This video shows how the global volume intensity is accumulated from local volumes acquired over four frame-times. Cells are color-coded by image intensity. Axes grid represents approximate position of matrix support on which the cells are suspended.

Supplementary Video 7

Internalized viral trafficking, related to Fig. 6. 3D reconstruction of live HeLa cells (stained with F-actin label SiR650) corendered with virus trajectory. Trajectory (~325 s) color mapped by time. Global image volume formed from maximum intensity projection over time from local volumes acquired over 16 frame-times. Cells are color-coded by image intensity. Initially, the cells are opaque and the trajectory is not visible; a cut-through reveals the complete internalized trajectory. Viewing this embedded trajectory from above reveals high-intensity, actin-rich regions which the trajectory appears to navigate. Finally, the camera is rotated to a lateral view to show the position of the trajectory within the 3D cell.

Supplementary Video 8

Multi-trajectory overlay, related to Extended Data Fig. 10. 3D reconstruction of a single assembled area containing live HeLa cells (stained with nucleic acid label SYTO61) corendered with ten virus trajectories. The total imaging data were acquired during the ten trajectories and coregistered to form a single common area. Image volumes formed from maximum intensity projection over time from the assembled volumes acquired over 16 frame-times. Cells are color-coded by image intensity. Ten trajectories combined (~490 s in total) are segmented into 25 segments per second (25 frames per second when playback rate is 1×). The trajectories are color mapped with respect to trajectory number (the color legend in lower left indicates the initial color of each trajectory). Each trajectory is further color mapped by time, as indicated in the progress bar. Trajectory no. 5 is related to Supplementary Video 3.

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Johnson, C., Exell, J., Lin, Y. et al. Capturing the start point of the virus–cell interaction with high-speed 3D single-virus tracking. Nat Methods 19, 1642–1652 (2022). https://doi.org/10.1038/s41592-022-01672-3

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