Mathematical modeling of antigenicity for HIV dynamics
MathematicS In Action, Tome 3 (2010) no. 1, pp. 1-35.

This contribution is devoted to a new model of HIV multiplication motivated by the patent of one of the authors. We take into account the antigenic diversity through what we define “antigenicity”, whether of the virus or of the adapted lymphocytes. We model the interaction of the immune system and the viral strains by two processes. On the one hand, the presence of a given viral quasi-species generates antigenically adapted lymphocytes. On the other hand, the lymphocytes kill only viruses for which they have been designed. We consider also the mutation and multiplication of the virus. An original infection term is derived.

So as to compare our system of differential equations with well-known models, we study some of them and compare their predictions to ours in the reduced case of only one antigenicity. In this particular case, our model does not yield any major qualitative difference. We prove mathematically that, in this case, our model is biologically consistent (positive fields) and has a unique continuous solution for long time evolution. In conclusion, this model improves the ability to simulate more advanced phases of the disease.

Publié le :
DOI : 10.5802/msia.3
Classification : 34-99, 65-05, 65Z05, 92B99, 92C50
Mots clés : HIV modeling, antigenic variation, mutation, immune response
François Dubois 1 ; Hervé V.J. Le Meur 2 ; Claude Reiss 3

1 Conservatoire National des Arts et Métiers, EA 3196, Paris, France ; univ Paris-Sud, Orsay cedex, F-91405.
2 CNRS, Laboratoire de Mathématiques d’Orsay, Orsay cedex, F-91405; univ Paris-Sud, Orsay cedex, F-91405.
3 Vigilent Technologies, 38160 Chevrières, France.
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François Dubois; Hervé V.J. Le Meur; Claude Reiss. Mathematical modeling of antigenicity for HIV dynamics. MathematicS In Action, Tome 3 (2010) no. 1, pp. 1-35. doi : 10.5802/msia.3. https://msia.centre-mersenne.org/articles/10.5802/msia.3/

[1] Christian L. Althaus; Rob J. De Boer Dynamics of Immune Escape during HIV/SIV Infection, PLoS Comput. Biol., Volume 4 (2008) no. 7, e1000103 pages ( http://dx.plos.org/10.1371/journal.pcbi.1000103 ) | MR

[2] JP. Anderson; R. Daifuku; LA. Loeb Viral error catastrophe by mutagenic nucleosides, Annu. Rev. Microbiol., Volume 58 (2004), pp. 183-205 | DOI

[3] VI. Arnold Ordinary Differential Equations, The MIT Press., Massachusetts, 1978

[4] K. Bebenek; J. Abbotts; SH. Wilson; TA. Kunkel Error-prone polymerization by HIV-1 reverse transcriptase. Contribution of template-primer misalignment, miscoding, and termination probability to mutational hot spots., J. Biol. Chem., Volume 268(14) (1993), p. 10324-34 | DOI

[5] CK. Biebricher; M. Eigen The error threshold, Virus Res., Volume 107 (1993) no. 2, pp. 117-127 | DOI

[6] D.M. Bortz; P. W. Nelson Model Selection and Mixed-Effects Modeling of HIV Infection Dynamics., Bull. Math. Biol., Volume 68 (2006) no. 8, pp. 2005-2025 | DOI | MR | Zbl

[7] AL. Brass; DM. Dykxhoorn; Y. Benita; N. Yan; A. Engelman; RJ. Xavier; J. Lieberman; Elledge SJ. Identification of host proteins required for HIV infection through a functional genomic screen., Science, Volume 319 (2008) no. 5865, p. 921-6 | DOI

[8] DS. Callaway; AS. Perelson HIV-1 Infection and Low Steady State Viral Loads., Bull. Math. Biol., Volume 64 (2002), pp. 29-64 | DOI | Zbl

[9] RJ. De Boer Understanding the Failure of CD8+ T-Cell Vaccination against Simian/Human Immunodeficiency Virus, J. Virol., Volume 81 (2007) no. 6, pp. 2838-2848 | DOI

[10] RJ. De Boer; AS. Perelson Target Cell Limited and Immune Control Models of HIV Infection: A Comparison, J. Theor. Biol., Volume 190 (1998), pp. 201-214 | DOI

[11] P. De Leenheer; HL. Smith Virus dynamics: a global analysis., SIAM J. Appl. Math., Volume 63 (2003) no. 4, pp. 1313-1327 | MR | Zbl

[12] K. Dern; H. Rübsamen-Waigmann; RE. Unger Inhibition of HIV type 1 replication by simultaneous infection of peripheral blood lymphocytes with human immunodeficiency virus types 1 and 2., AIDS Res. Hum. Retroviruses, Volume 17 (2001) no. 4, pp. 295-309 | DOI

[13] V. Derrien Fidelity and termination of polymerization by reverse transcriptases in vitro., Paris-Sud University (1998) (Ph. D. Thesis)

[14] WC. Drosopoulos; LF. Rezende; MA. Wainberg; VR. Prasad Virtues of being faithful: can we limit the genetic variation in human immunodeficiency virus?, J. Mol. Med., Volume 76 (1998) no. 9, p. 604-12 | DOI

[15] F. Dubois; HVJ. Le Meur; C. Reiss; Congrès d’Analyse NUMérique Modélisation de la multiplication du virus HIV. (2007)

[16] D. Finzi; RF. Silliciano Viral dynamics in HIV-1 infection., Cell, Volume 93 (1998) no. 5, p. 665-71 | DOI

[17] H. Frid; P-E. Jabin; B. Perthame Global stability of steady solutions for a model in virus dynamics., Math. Model. Numer. Anal., Volume 37 (2003) no. 4, pp. 709-723 | DOI | MR | Zbl

[18] K. Fujii; JH. Hurley; EO. Freed Beyond Tsg101: the role of Alix in ’ESCRTing’ HIV-1., Nat. Rev. Microbiol., Volume 5 (2007) no. 12, p. 912-6 | DOI

[19] J. Guedj; R. Thiebaut; D. Commenges Practical Identifiability of HIV Dynamics Models., Bull. Math. Biol., Volume 69 (2007) no. 8, p. 2493-513 | DOI | MR | Zbl

[20] KS. Harris; W. Brabant; S. Styrchak; A. Gall; R. Daifuku KP-1212/1461, a nucleoside designed for the treatment of HIV by viral mutagenesis., Antivir. Res, Volume 67 (2005), pp. 1-9 | DOI

[21] P. Henrici Applied and Computational Complex Analysis, John Wiley, New-York, 1974

[22] AV. Herz; S. Bonhoeffer; RM. Anderson; RM. May; MA. Nowak Viral dynamics in vivo: limitations on estimates of intracellular delay and virus decay., Proc. Natl. Acad. Sci. USA, Volume 93 (1996), pp. 7247-7251 | DOI

[23] J. Ji; LA. Loeb Fidelity of HIV-1 reverse transcriptase copying a hypervariable region of the HIV-1 env gene., Virology, Volume 199 (1994) no. 2, p. 323-30 | DOI

[24] E. Kashkina; M. Anikin; F. Brueckner; RT. Pomerantz; WT. McAllister; P. Cramer; D. Temiakov Template misalignment in multisubunit RNA polymerases and transcription fidelity., Mol. Cell., Volume 24 (2006) no. 2, p. 257-66 | DOI

[25] DL. Kothe; Y. Li; JM. Decker; F. Bibollet-Ruche; KP. Zammit; MG. Salazar; Y. Chen; Z. Weng; EA. Weaver; F. Gao; BF. Haynes; GM. Shaw; BT. Korber; BH. Hahn Ancestral and consensus envelope immunogens for HIV-1 subtype C., Virology, Volume 352 (2006) no. 2, p. 438-49 | DOI

[26] S. Mueller; D. Papamichail; JR. Coleman; S. Skiena; E. Wimmer Reduction of the rate of poliovirus protein synthesis through large-scale codon deoptimization causes attenuation of viral virulence by lowering specific infectivity., J. Virol., Volume 80 (2006) no. 19, p. 9687-96 | DOI

[27] E. Murakami; A. Basavapathruni; WD. Bradley; KS. Anderson Mechanism of action of a novel viral mutagenic covert nucleotide: molecular interaction with HIV-1 reverse transcriptase and host cell DNA polymerases., Antivir. Res., Volume 67 (2005), pp. 10-17 | DOI

[28] PW. Nelson; JE. Mittler; AS. Perelson Effect of drug efficacy and the eclipse phase of the viral life cycle on estimates of HIV viral dynamic parameters., J. Acquir. Immune Defic. Syndr., Volume 26 (2001) no. 5, pp. 405-412 | DOI

[29] MA Nowak; Bangham. CRM Population dynamics of immune responses to persistent viruses., Science, Volume 272 (1996), pp. 74-79 | DOI

[30] MA. Nowak; RM. May Virus dynamics. Mathematical Principles of Immunology and Virology, Oxford University Press, 2000 | Zbl

[31] DH. Pastore; JP. Zubelli; Mauricio Peixoto Alberto Adrego Pinto; David Rand On the dynamics of certain models describing the HIV infection., Dynamics and Games in Science, in honour of Mauricio Peixoto and David Rand, Springer-Verlag, 2010

[32] AS. Perelson Modelling viral and immune system dynamics, Nature Rev. Immunol., Volume 2 (2002), pp. 28-36 | DOI

[33] AS. Perelson; P. Nelson Mathematical analysis of HIV-1 dynamics in vivo., SIAM Review, Volume 41 (1999) no. 1, pp. 3-44 | DOI | MR | Zbl

[34] AS. Perelson; AU. Neumann; M. Markowitz; JM. Leonard; DD. Ho HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time., Science, Volume 271 (1996) no. 5255, p. 1582-6 | DOI

[35] J. Petravic; L. Loh; SJ. Kent; MP. Davenport CD4+ Target cell availability determines the dynamics of immune escape and reversion in vivo., J. Virol., Volume 82 (2008) no. 8, p. 4091-101 | DOI

[36] M. Recher; KS. Lang; A. Navarini; L. Hunziker; PA. Lang; K. Fink; S. Freigang; P. Georgiev; L. Hangartner; R. Zellweger; A. Bergthaler; AN. Hegazy; B. Eschli; A. Theocharides; LT. Jeker; D. Merkler; B. Odermatt; M. Hersberger; H. Hengartner; RM. Zinkernagel Extralymphatic virus sanctuaries as a consequence of potent T-cell activation., Nat. Med., Volume 13 (2007) no. 11, p. 1316-23 | DOI

[37] N. Sachsenberg; AS. Perelson; S. Yerly; GA. Schockmel; D. Leduc; B. Hirschel; L. Perrin Turnover of CD4 + and CD8 + lymphocytes in HIV-1 infection as measured by Ki-67 antigen, J. Exp. Medecine, Volume 187 (1998) no. 8, pp. 1295-1303 | DOI

[38] A. Samson; M. Lavielle; F. Mentré The SAEM algorithm for group comparison tests in longitudinal data analysis based on non-linear mixed-effects model., Stat Med., Volume 26 (2007) no. 27, p. 4860-75 | DOI | MR

[39] SJ. Snedecor Comparison of three kinetic models of HIV-1 implications for optimization of treatment., J. Theor. Biol., Volume 221 (2003), pp. 519-541 | DOI | MR | Zbl

[40] JA. Thomas; DE. Ott; RJ. Gorelick Efficiency of human immunodeficiency virus type 1 postentry infection processes: evidence against disproportionate numbers of defective virions., J. Virol., Volume 81 (2007) no. 8, p. 4367-70 | DOI

[41] HC. Tuckwell; E. Le Corfec A stochastic model for early HIV-1 population dynamics., J. Theor. Biol., Volume 195 (1998) no. 4, p. 451-63 | DOI

[42] L. Wang; M.Y. Li Mathematical analysis of the global dynamics of a model for HIV infection of CD 4 + T cells., Math. Biosci., Volume 200 (2006) no. 1, pp. 44-57 | DOI | MR

[43] D. Warrilow; L. Meredith; A. Davis; C. Burrell; P. Li; D. Harrich Cell factors stimulate human immunodeficiency virus type 1 reverse transcription in vitro., J. Virol., Volume 82 (2008) no. 3, p. 1425-37 | DOI

[44] D. Wodarz; D.H. Hamer Infection dynamics in HIV-specific CD4 T cells: does a CD4 T cell boost benefit the host or the virus?, Math. Biosci., Volume 209 (2007) no. 1, pp. 14-29 | DOI | MR | Zbl

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