Maintenance of the latent reservoir by pyroptosis and superinfection in a fractional order HIV transmission model
Maintenance of the latent reservoir by pyroptosis and superinfection in a fractional order HIV transmission model
We focus on the importance of pyroptosis and superinfection on the maintenance of the human immunodeficiency virus (HIV) latent reservoir on infectedpatients. The latent reservoir has been found to be crucial to the persistenceof low levels of viral loads found in HIV-infected patients, after many yearsof successfully suppressive anti-retroviral therapy (ART). This reservoir seemsto act as an archive for strains of HIV no longer dominant in the blood, suchas wild-type virus. When a patient decides to quit therapy there is a rapidturnover and the wild-type virus re-emerges. Thus, it is extremely importantto understand the mechanisms behind the maintenance of this reservoir. Forthat, we propose a fractional order model for the dynamics of HIV, wherepyroptosis and superinfection are considered. The model is simulated for biological meaningful parameters and interesting patterns are found. Our resultsare interpreted for clinical appreciation.
___
- [1] Perelson, A.S., Kirschner, D.E & De Boer, R. (1993). Dynamic of HIV infection of CD4+ T cells. Mathematical Biosciences, 112, 81-125.
- [2] Chavez, L., Calvanese, V & Verdin, E. (2015). HIV latency is established directly and early in both resting and activated primary CD4 T cells. PLOS Pathogens, 11(6), e1004955.
- [3] Doitsh, G., Galloway, N.L.K., Geng, X., Yang, Z., Monroe, K.M., Zepeda, O., Hunt, P.W., Hatano, H., Sowinski, S., Muoz-Arias, I. & Greene, W.C. (2014). Pyroptosis drives CD4 T-cell depletion in HIV-1 infection. Nature, 505(7484), 509–514.
- [4] Kim, H. & Perelson, A.S. (2006). Viral and latent reservoir persistence in HIV-1infected patients on therapy. PLOS Computational Biology, 2(10), e135.
- [5] Rong, L. & Perelson, A.S. (2009). Modeling HIV persistence, the latent reservoir, and viral blips. Journal of Theoretical Biology, 260, 308–331.
- [6] Wang, S., Hottz, P., Schechter, M. & Rong, L. (2015). Modeling the slow CD4+ T cell decline in HIV-infected individuals. PLOS Computational Biology, 11(12), e1004665.
- [7] Conway, J.M. & Perelson, A.S. (2015). Posttreatment control of HIV infection. Proceedings of the National Academy of Sciences, 112(17), 5467–5472.
- [8] Wodarz, D., Levy, D.N., Pyroptosis, superinfection, and the maintenance of the latent reservoir in HIV-1 infection. Nature - Scientific Reports, 7(1), 1-10 (2017).
- [9] Samko, S., Kilbas, A. & Marichev, O. (1993). Fractional Integrals and Derivatives: Theory and Applications. London: Gordon and Breach Science Publishers.
- [10] Diethelm, K. (2013). A fractional calculus based model for the simulation of an outbreak of dengue fever. Nonlinear Dynamics, 71, 613–619.
- [11] Pinto, C.M.A. & Carvalho, A.R.M. (2017). A latency fractional order model for HIV dynamics. Journal of Computational and Applied Mathematics, 312, 240–256.
- [12] T´ejado, I., Val´erio, D., P´erez, E. & Val´erio, N. (2017). Fractional calculus in economic growth modelling: the Spanish and Portuguese cases. International Journal of Dynamics and Control, 5(1), 208–222.
- [13] Arshad, S., Baleanu, D., Bu, W., Tang, Y., Effects of HIV infection on CD4+ T-cell population based on a fractional-order model. Advances in Difference Equations, 2017(92), 1–14 (2017).
- [14] Carvalho, A.R.M., Pinto, C.M.A. & Baleanu, D. (2018). HIV/HCV coinfection model: a fractional-order perspective for the effect of the HIV viral load. Advances in Difference Equations, 2018(1), 1–22.
- [15] Driessche, P. & Watmough, P. (2002). Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Mathematical Biosciences, 180, 29-48.
- [16] Tavazoei, M.S. & Haeri, M. (2008). Chaotic attractors in incommensurate fractional order systems. Physica D, 237, 2628–2637.
- [17] Chitnis, N., Hyman, J.M. & Cushing, J.M. (2008). Determining important parameters in the spread of malaria through the sensitivity analysis of a mathematical model. Bulletin of Mathematical Biology, 70, 1272–1296.