1932

Abstract

The way in which a viral infection spreads within a host is a complex process that is not well understood. Different viruses, such as human immunodeficiency virus type 1 and hepatitis C virus, have evolved different strategies, including direct cell-to-cell transmission and cell-free transmission, to spread within a host. To what extent these two modes of transmission are exploited in vivo is still unknown. Mathematical modeling has been an essential tool to get a better systematic and quantitative understanding of viral processes that are difficult to discern through strictly experimental approaches. In this review, we discuss recent attempts that combine experimental data and mathematical modeling in order to determine and quantify viral transmission modes. We also discuss the current challenges for a systems-level understanding of viral spread, and we highlight the promises and challenges that novel experimental techniques and data will bring to the field.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-virology-110615-042249
2016-09-29
2024-04-23
Loading full text...

Full text loading...

/deliver/fulltext/virology/3/1/annurev-virology-110615-042249.html?itemId=/content/journals/10.1146/annurev-virology-110615-042249&mimeType=html&fmt=ahah

Literature Cited

  1. 1. Microbiology by numbers 2011. Nat. Rev. Microbiol. 9628
  2. Wilen CB, Tilton JC, Doms RW. 2.  2012. Molecular mechanisms of HIV entry. Viral Molecular Machines MG Rossmann, VB Rao, pp. 223–44 New York: Springer [Google Scholar]
  3. Zeisel MB, Koutsoudakis G, Schnober EK, Haberstroh A, Blum HE. 3.  et al. 2007. Scavenger receptor class B type I is a key host factor for hepatitis C virus infection required for an entry step closely linked to CD81. Hepatology 46:1722–31 [Google Scholar]
  4. Pileri P, Uematsu Y, Campagnoli S, Galli G, Falugi F. 4.  et al. 1998. Binding of hepatitis C virus to CD81. Science 282:938–41 [Google Scholar]
  5. Evans MJ, von Hahn T, Tscherne DM, Syder AJ, Panis M. 5.  et al. 2007. Claudin-1 is a hepatitis C virus co-receptor required for a late step in entry. Nature 446:801–5 [Google Scholar]
  6. Ploss A, Evans MJ, Gaysinskaya VA, Panis M, You H. 6.  et al. 2009. Human occludin is a hepatitis C virus entry factor required for infection of mouse cells. Nature 457:882–86 [Google Scholar]
  7. Sainz B Jr, Barretto N, Martin DN, Hiraga N, Imamura M. 7.  et al. 2012. Identification of the Niemann-Pick C1-like 1 cholesterol absorption receptor as a new hepatitis C virus entry factor. Nat. Med. 18:281–85 [Google Scholar]
  8. Verrier ER, Colpitts CC, Bach C, Heydmann L, Weiss A. 8.  et al. 2016. A targeted functional RNA interference screen uncovers glypican 5 as an entry factor for hepatitis B and D viruses. Hepatology 63:35–48 [Google Scholar]
  9. Yan H, Zhong G, Xu G, He W, Jing Z. 9.  et al. 2012. Sodium taurocholate cotransporting polypeptide is a functional receptor for human hepatitis B and D virus. eLife 1:e00049 [Google Scholar]
  10. Martin DN, Uprichard SL. 10.  2013. Identification of transferrin receptor 1 as a hepatitis C virus entry factor. PNAS 110:10777–82 [Google Scholar]
  11. Ujino S, Nishitsuji H, Hishiki T, Sugiyama K, Takaku H, Shimotohno K. 11.  2016. Hepatitis C virus utilizes VLDLR as a novel entry pathway. PNAS 113:188–93 [Google Scholar]
  12. Sigal A, Kim JT, Balazs AB, Dekel E, Mayo A. 12.  et al. 2011. Cell-to-cell spread of HIV permits ongoing replication despite antiretroviral therapy. Nature 477:95–98 [Google Scholar]
  13. Brimacombe CL, Grove J, Meredith LW, Hu K, Syder AJ. 13.  et al. 2011. Neutralizing antibody-resistant hepatitis C virus cell-to-cell transmission. J. Virol. 85:596–605 [Google Scholar]
  14. Abela IA, Berlinger L, Schanz M, Reynell L, Gunthard HF. 14.  et al. 2012. Cell-cell transmission enables HIV-1 to evade inhibition by potent CD4bs directed antibodies. PLOS Pathog 8:e1002634 [Google Scholar]
  15. Sattentau Q. 15.  2008. Avoiding the void: cell-to-cell spread of human viruses. Nat. Rev. Microbiol. 6:815–26 [Google Scholar]
  16. Mothes W, Sherer NM, Jin J, Zhong P. 16.  2010. Virus cell-to-cell transmission. J. Virol. 84:8360–68 [Google Scholar]
  17. Alvarez RA, Barria MI, Chen BK. 17.  2014. Unique features of HIV-1 spread through T cell virological synapses. PLOS Pathog 10:e1004513 [Google Scholar]
  18. Chen P, Hubner W, Spinelli MA, Chen BK. 18.  2007. Predominant mode of human immunodeficiency virus transfer between T cells is mediated by sustained Env-dependent neutralization-resistant virological synapses. J. Virol. 81:12582–95 [Google Scholar]
  19. Martin N, Welsch S, Jolly C, Briggs JA, Vaux D, Sattentau QJ. 19.  2010. Virological synapse-mediated spread of human immunodeficiency virus type 1 between T cells is sensitive to entry inhibition. J. Virol. 84:3516–27 [Google Scholar]
  20. Sourisseau M, Sol-Foulon N, Porrot F, Blanchet F, Schwartz O. 20.  2007. Inefficient human immunodeficiency virus replication in mobile lymphocytes. J. Virol. 81:1000–12 [Google Scholar]
  21. Hubner W, McNerney GP, Chen P, Dale BM, Gordon RE. 21.  et al. 2009. Quantitative 3D video microscopy of HIV transfer across T cell virological synapses. Science 323:1743–47 [Google Scholar]
  22. Agosto LM, Zhong P, Munro J, Mothes W. 22.  2014. Highly active antiretroviral therapies are effective against HIV-1 cell-to-cell transmission. PLOS Pathog 10:e1003982 [Google Scholar]
  23. Agosto LM, Uchil PD, Mothes W. 23.  2015. HIV cell-to-cell transmission: effects on pathogenesis and antiretroviral therapy. Trends Microbiol 23:289–95 [Google Scholar]
  24. Komarova NL, Levy DN, Wodarz D. 24.  2013. Synaptic transmission and the susceptibility of HIV infection to anti-viral drugs. Sci. Rep. 3:2103 [Google Scholar]
  25. Barretto N, Sainz B Jr, Hussain S, Uprichard SL. 25.  2014. Determining the involvement and therapeutic implications of host cellular factors in hepatitis C virus cell-to-cell spread. J. Virol. 88:5050–61 [Google Scholar]
  26. Galloway NLK, Doitsh G, Monroe KM, Yang Z, Muñoz-Arias I. 26.  et al. 2016. Cell-to-cell transmission of HIV-1 is required to trigger pyroptotic death of lymphoid-tissue-derived CD4 T cells. Cell Rep. 12:1555–63 [Google Scholar]
  27. Perelson AS. 27.  2002. Modelling viral and immune system dynamics. Nat. Rev. Immunol. 2:28–36 [Google Scholar]
  28. Perelson AS, Neumann AU, Markowitz M, Leonard JM, Ho DD. 28.  1996. HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science 271:1582–86 [Google Scholar]
  29. Ho DD, Neumann AU, Perelson AS, Chen W, Leonard JM, Markowitz M. 29.  1995. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature 373:123–26 [Google Scholar]
  30. Neumann AU, Lam NP, Dahari H, Gretch DR, Wiley TE. 30.  et al. 1998. Hepatitis C viral dynamics in vivo and the antiviral efficacy of interferon-α therapy. Science 282:103–7 [Google Scholar]
  31. Ramratnam B, Bonhoeffer S, Binley J, Hurley A, Zhang L. 31.  et al. 1999. Rapid production and clearance of HIV-1 and hepatitis C virus assessed by large volume plasma apheresis. Lancet 354:1782–85 [Google Scholar]
  32. Guedj J, Dahari H, Rong L, Sansone ND, Nettles RE. 32.  et al. 2013. Modeling shows that the NS5A inhibitor daclatasvir has two modes of action and yields a shorter estimate of the hepatitis C virus half-life. PNAS 110:3991–96 [Google Scholar]
  33. Chatterjee A, Guedj J, Perelson AS. 33.  2012. Mathematical modelling of HCV infection: What can it teach us in the era of direct-acting antiviral agents?. Antivir. Ther. 17:1171–82 [Google Scholar]
  34. Dixit NM, Layden-Almer JE, Layden TJ, Perelson AS. 34.  2004. Modelling how ribavirin improves interferon response rates in hepatitis C virus infection. Nature 432:922–24 [Google Scholar]
  35. Guedj J, Dahari H, Pohl RT, Ferenci P, Perelson AS. 35.  2012. Understanding silibinin's modes of action against HCV using viral kinetic modeling. J. Hepatol. 56:1019–24 [Google Scholar]
  36. Perelson AS. 36.  2016. Mathematical modeling. In Viral Pathogenesis: From Basics to Systems Biology MG Katze, MJ Korth, GL Law, N Nathanson 199–211 Amsterdam: Academic [Google Scholar]
  37. Nowak M, May R. 37.  2000. Virus Dynamics: Mathematical Principles of Immunology and Virology Oxford, UK: Oxford Univ. Press
  38. Perelson AS, Ribeiro RM. 38.  2013. Modeling the within-host dynamics of HIV infection. BMC Biol. 11:96 [Google Scholar]
  39. Zhang C, Zhou S, Groppelli E, Pellegrino P, Williams I. 39.  et al. 2015. Hybrid spreading mechanisms and T cell activation shape the dynamics of HIV-1 infection. PLOS Comput. Biol. 11:e1004179 [Google Scholar]
  40. Komarova NL, Levy DN, Wodarz D. 40.  2012. Effect of synaptic transmission on viral fitness in HIV infection. PLOS ONE 7:e48361 [Google Scholar]
  41. Komarova NL, Wodarz D. 41.  2013. Virus dynamics in the presence of synaptic transmission. Math. Biosci. 242:161–71 [Google Scholar]
  42. Iwami S, Takeuchi JS, Nakaoka S, Mammano F, Clavel F. 42.  et al. 2015. Cell-to-cell infection by HIV contributes over half of virus infection. eLife 4:e08150 [Google Scholar]
  43. Murooka TT, Deruaz M, Marangoni F, Vrbanac VD, Seung E. 43.  et al. 2012. HIV-infected T cells are migratory vehicles for viral dissemination. Nature 490:283–87 [Google Scholar]
  44. Dixit NM, Perelson AS. 44.  2004. Multiplicity of human immunodeficiency virus infections in lymphoid tissue. J. Virol. 78:8942–45 [Google Scholar]
  45. Vasiliver-Shamis G, Dustin ML, Hioe CE. 45.  2010. HIV-1 virological synapse is not simply a copycat of the immunological synapse. Viruses 2:1239–60 [Google Scholar]
  46. Jolly C, Kashefi K, Hollinshead M, Sattentau QJ. 46.  2004. HIV-1 cell to cell transfer across an Env-induced, actin-dependent synapse. J. Exp. Med. 199:283–93 [Google Scholar]
  47. Jolly C, Mitar I, Sattentau QJ. 47.  2007. Adhesion molecule interactions facilitate human immunodeficiency virus type 1-induced virological synapse formation between T cells. J. Virol. 81:13916–21 [Google Scholar]
  48. Rudnicka D, Feldmann J, Porrot F, Wietgrefe S, Guadagnini S. 48.  et al. 2009. Simultaneous cell-to-cell transmission of human immunodeficiency virus to multiple targets through polysynapses. J. Virol. 83:6234–46 [Google Scholar]
  49. Vasiliver-Shamis G, Tuen M, Wu TW, Starr T, Cameron TO. 49.  et al. 2008. Human immunodeficiency virus type 1 envelope gp120 induces a stop signal and virological synapse formation in noninfected CD4+ T cells. J. Virol. 82:9445–57 [Google Scholar]
  50. McDonald D, Wu L, Bohks SM, KewalRamani VN, Unutmaz D, Hope TJ. 50.  2003. Recruitment of HIV and its receptors to dendritic cell-T cell junctions. Science 300:1295–97 [Google Scholar]
  51. Cameron PU, Freudenthal PS, Barker JM, Gezelter S, Inaba K, Steinman RM. 51.  1992. Dendritic cells exposed to human immunodeficiency virus type-1 transmit a vigorous cytopathic infection to CD4+ T cells. Science 257:383–87 [Google Scholar]
  52. Brandenberg OF, Magnus C, Regoes RR, Trkola A. 52.  2015. The HIV-1 entry process: a stoichiometric view. Trends Microbiol. 23:763–74 [Google Scholar]
  53. Del Portillo A, Tripodi J, Najfeld V, Wodarz D, Levy DN, Chen BK. 53.  2011. Multiploid inheritance of HIV-1 during cell-to-cell infection. J. Virol. 85:7169–76 [Google Scholar]
  54. Russell RA, Martin N, Mitar I, Jones E, Sattentau QJ. 54.  2013. Multiple proviral integration events after virological synapse-mediated HIV-1 spread. Virology 443:143–49 [Google Scholar]
  55. Jung A, Maier R, Vartanian JP, Bocharov G, Jung V. 55.  et al. 2002. Recombination: multiply infected spleen cells in HIV patients. Nature 418:144 [Google Scholar]
  56. Josefsson L, King MS, Makitalo B, Brannstrom J, Shao W. 56.  et al. 2011. Majority of CD4+ T cells from peripheral blood of HIV-1-infected individuals contain only one HIV DNA molecule. PNAS 108:11199–204 [Google Scholar]
  57. Piguet V, Gu F, Foti M, Demaurex N, Gruenberg J. 57.  et al. 1999. Nef-induced CD4 degradation: A diacidic-based motif in Nef functions as a lysosomal targeting signal through the binding of β-COP in endosomes. Cell 97:63–73 [Google Scholar]
  58. Miyashita S, Ishibashi K, Kishino H, Ishikawa M. 58.  2015. Viruses roll the dice: The stochastic behavior of viral genome molecules accelerates viral adaptation at the cell and tissue levels. PLOS Biol. 13:e1002094 [Google Scholar]
  59. Richardson LA. 59.  2015. Viral cell-to-cell transmission—why less is more. PLOS Biol. 13:e1002095 [Google Scholar]
  60. Guedj J, Pang PS, Denning J, Rodriguez-Torres M, Lawitz E. 60.  et al. 2014. Analysis of hepatitis C viral kinetics during administration of two nucleotide analogues: sofosbuvir (GS-7977) and GS-0938. Antivir. Ther. 19:211–20 [Google Scholar]
  61. Ribeiro RM, Li H, Wang S, Stoddard MB, Learn GH. 61.  et al. 2012. Quantifying the diversification of hepatitis C virus (HCV) during primary infection: estimates of the in vivo mutation rate. PLOS Pathog. 8:e1002881 [Google Scholar]
  62. Rong L, Dahari H, Ribeiro RM, Perelson AS. 62.  2010. Rapid emergence of protease inhibitor resistance in hepatitis C virus. Sci. Transl. Med. 2:30ra32 [Google Scholar]
  63. Perelson AS, Guedj J. 63.  2015. Modelling hepatitis C therapy—predicting effects of treatment. Nat. Rev. Gastroenterol. Hepatol. 12:437–45 [Google Scholar]
  64. Lau G, Benhamou Y, Chen G, Li J, Shao Q. 64.  et al. 2016. Efficacy and safety of three week response-guided direct-acting antiviral therapy: a phase 2, proof-of-concept study. Lancet Gastroenterol. Hepatol. In press [Google Scholar]
  65. Bauer AL, Beauchemin CA, Perelson AS. 65.  2009. Agent-based modeling of host-pathogen systems: the successes and challenges. Inf. Sci. 179:1379–89 [Google Scholar]
  66. Beauchemin C, Samuel J, Tuszynski J. 66.  2005. A simple cellular automaton model for influenza A viral infections. J. Theor. Biol. 232:223–34 [Google Scholar]
  67. Zorzenon dos Santos RM, Coutinho S. 67.  2001. Dynamics of HIV infection: a cellular automata approach. Phys. Rev. Lett. 87:168102 [Google Scholar]
  68. Funk GA, Jansen VA, Bonhoeffer S, Killingback T. 68.  2005. Spatial models of virus-immune dynamics. J. Theor. Biol. 233:221–36 [Google Scholar]
  69. Frank SA. 69.  2000. Within-host spatial dynamics of viruses and defective interfering particles. J. Theor. Biol. 206:279–90 [Google Scholar]
  70. Graziano FM, Kettoola SY, Munshower JM, Stapleton JT, Towfic GJ. 70.  2008. Effect of spatial distribution of T-cells and HIV load on HIV progression. Bioinformatics 24:855–60 [Google Scholar]
  71. Strain MC, Richman DD, Wong JK, Levine H. 71.  2002. Spatiotemporal dynamics of HIV propagation. J. Theor. Biol. 218:85–96 [Google Scholar]
  72. Kandathil AJ, Graw F, Quinn J, Hwang HS, Torbenson M. 72.  et al. 2013. Use of laser capture microdissection to map hepatitis C virus-positive hepatocytes in human liver. Gastroenterology 145:1404–13 [Google Scholar]
  73. Wieland S, Makowska Z, Campana B, Calabrese D, Dill MT. 73.  et al. 2014. Simultaneous detection of hepatitis C virus and interferon stimulated gene expression in infected human liver. Hepatology 59:2121–30 [Google Scholar]
  74. Shulla A, Randall G. 74.  2015. Spatiotemporal analysis of hepatitis C virus infection. PLOS Pathog. 11:e1004758 [Google Scholar]
  75. Binder M, Sulaimanov N, Clausznitzer D, Schulze M, Huber CM. 75.  et al. 2013. Replication vesicles are load- and choke-points in the hepatitis C virus lifecycle. PLOS Pathog 9:e1003561 [Google Scholar]
  76. Dahari H, Ribeiro RM, Rice CM, Perelson AS. 76.  2007. Mathematical modeling of subgenomic hepatitis C virus replication in Huh-7 cells. J. Virol. 81:750–60 [Google Scholar]
  77. Graw F, Balagopal A, Kandathil AJ, Ray SC, Thomas DL. 77.  et al. 2014. Inferring viral dynamics in chronically HCV infected patients from the spatial distribution of infected hepatocytes. PLOS Comput. Biol. 10:e1003934 [Google Scholar]
  78. Liang Y, Shilagard T, Xiao SY, Snyder N, Lau D. 78.  et al. 2009. Visualizing hepatitis C virus infections in human liver by two-photon microscopy. Gastroenterology 137:1448–58 [Google Scholar]
  79. Stiffler JD, Nguyen M, Sohn JA, Liu C, Kaplan D, Seeger C. 79.  2009. Focal distribution of hepatitis C virus RNA in infected livers. PLOS ONE 4:e6661 [Google Scholar]
  80. Graw F, Martin DN, Perelson AS, Uprichard SL, Dahari H. 80.  2015. Quantification of hepatitis C virus cell-to-cell spread using a stochastic modeling approach. J. Virol. 89:6551–61 [Google Scholar]
  81. Quinkert D, Bartenschlager R, Lohmann V. 81.  2005. Quantitative analysis of the hepatitis C virus replication complex. J. Virol. 79:13594–605 [Google Scholar]
  82. Chang M, Williams O, Mittler J, Quintanilla A, Carithers RL Jr. 82.  2003. Dynamics of hepatitis C virus replication in human liver. Am. J. Pathol. 163:433–44 [Google Scholar]
  83. Canini L, Perelson AS. 83.  2014. Viral kinetic modeling: state of the art. J. Pharmacokinet. Pharmacodyn. 41:431–43 [Google Scholar]
  84. Fletcher CV, Staskus K, Wietgrefe S, Bedford T, Rotherberger M. 84.  et al. 2015. Persistent HIV-1 replication is associated with lower antiretroviral drug concentrations in lymphatic tissues. PNAS 111:2307–12 [Google Scholar]
  85. Lorenzo-Redondo R, Fryer HR, Bedford T, Kim EY, Archer J. 85.  et al. 2016. Persistent HIV-1 replication maintains the tissue reservoir during therapy. Nature 530:51–56 [Google Scholar]
  86. Metz P, Dazert E, Ruggieri A, Mazur J, Kaderali L. 86.  et al. 2012. Identification of type I and type II interferon-induced effectors controlling hepatitis C virus replication. Hepatology 56:2082–93 [Google Scholar]
  87. Takahashi K, Asabe S, Wieland S, Garaigorta U, Gastaminza P. 87.  et al. 2010. Plasmacytoid dendritic cells sense hepatitis C virus-infected cells, produce interferon, and inhibit infection. PNAS 107:7431–36 [Google Scholar]
  88. Schmid B, Rinas M, Ruggieri A, Acosta EG, Bartenschlager M. 88.  et al. 2015. Live cell analysis and mathematical modeling identify determinants of attenuation of dengue virus 2′-O-methylation mutant. PLOS Pathog. 11:e1005345 [Google Scholar]
  89. Howat TJ, Barreca C, O'Hare P, Gog JR, Grenfell BT. 89.  2006. Modelling dynamics of the type I interferon response to in vitro viral infection. J. R. Soc. Interface 3:699–709 [Google Scholar]
  90. McDonald D, Vodicka MA, Lucero G, Svitkina TM, Borisy GG. 90.  et al. 2002. Visualization of the intracellular behavior of HIV in living cells. J. Cell Biol. 159:441–52 [Google Scholar]
  91. Swick A, Baltes A, Yin J. 91.  2014. Visualizing infection spread: dual-color fluorescent reporting of virus-host interactions. Biotechnol. Bioeng. 111:1200–9 [Google Scholar]
  92. Voigt EA, Swick A, Yin J. 92.  2016. Rapid induction and persistence of paracrine-induced cellular antiviral states arrest viral infection spread in A549 cells. Virology In press [Google Scholar]
  93. Fackler OT, Murooka TT, Imle A, Mempel TR. 93.  2014. Adding new dimensions: towards an integrative understanding of HIV-1 spread. Nat. Rev. Microbiol. 12:563–74 [Google Scholar]
  94. Dinh MH, Anderson MR, McRaven MD, Cianci GC, McCoombe SG. 94.  et al. 2015. Visualization of HIV-1 interactions with penile and foreskin epithelia: clues for female-to-male HIV transmission. PLOS Pathog. 11:e1004729 [Google Scholar]
  95. Koch P, Lampe M, Godinez WJ, Muller B, Rohr K. 95.  et al. 2009. Visualizing fusion of pseudotyped HIV-1 particles in real time by live cell microscopy. Retrovirology 6:84 [Google Scholar]
  96. Di Primio C, Quercioli V, Allouch A, Gijsbers R, Christ F. 96.  et al. 2013. Single-cell imaging of HIV-1 provirus (SCIP). PNAS 110:5636–41 [Google Scholar]
  97. Coombes JL, Robey EA. 97.  2010. Dynamic imaging of host-pathogen interactions in vivo. Nat. Rev. Immunol. 10:353–64 [Google Scholar]
/content/journals/10.1146/annurev-virology-110615-042249
Loading
/content/journals/10.1146/annurev-virology-110615-042249
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error