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Published on: December 17, 2013
Saturated lysing efficiency of CD8+ cells induced monostable, bistable and oscillatory HIV kinetics
Shilian Xu1,2
1Department of Environment and Genetics, School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, VIC 3086, Australia.
Insights
Human leukocyte antigen (HLA) alleles influence human immunodeficiency virus (HIV) dynamics by affecting CD8+ T-cell killing rates. Mathematical modeling reveals how HLA variations lead to diverse HIV infection outcomes, from high viral loads to oscillations.
Area of Science:
- Immunology
- Mathematical Biology
- Virology
Background:
- Effector CD8+ T-cells are crucial for clearing human immunodeficiency virus (HIV)-infected CD4+ T-cells.
- Human leukocyte antigen (HLA) alleles present viral peptides, influencing CD8+ T-cell recognition and lysis efficiency.
- Variability in HIV infection outcomes suggests underlying host genetic factors, such as HLA type.
Purpose of the Study:
- To develop a mathematical model investigating HIV dynamics based on CD8+ T-cell lysing rates influenced by different HLA alleles.
- To explore the complex interactions between CD4+ T-cells, HIV, and CD8+ T-cells under varying lysis parameters.
- To elucidate how HLA-driven variations in CD8+ T-cell activity contribute to the spectrum of HIV infection control.
Main Methods:
- Utilized a mathematical model incorporating semi-saturated CD8+ T-cell lysing efficiency.
- Employed local stability analysis and bifurcation plots to analyze system dynamics.
- Investigated the interplay of CD8+ T-cell lysing rate, CD8+ T-cell count, and saturation effects on HIV kinetics.
Main Results:
- The model demonstrated complex behaviors including monostability, periodic oscillations, and bistability.
- Low CD8+ T-cell lysing rates with high saturation effects resulted in high viral loads (monostability).
- Low lysing rates with low saturation effects led to periodic oscillations, explaining poor control in non-protective HLA allele carriers.
- High lysing rates resulted in bistability or monostability to low viral titers, explaining variable outcomes even with protective HLA alleles.
Conclusions:
- Differences in HLA alleles significantly impact HIV infection dynamics by modulating CD8+ T-cell killing efficiency.
- Mathematical modeling provides insights into the mechanisms underlying inter-individual variability in HIV disease progression.
- The study highlights the critical role of HLA-specific CD8+ T-cell responses in determining HIV control outcomes.
Abstract:
Effector CD8+ cells lyse human immunodeficiency viruses (HIV)-infected CD4+ cells by recognizing a viral peptide presented by human leukocyte antigens (HLA) on the CD4+ cell surface, which plays an irreplaceable role in within-host HIV clearance. Using a semi-saturated lysing efficiency of a CD8+ cell, we discuss a model that captures HIV dynamics with different magnitudes of lysing rate induced by different HLA alleles. With the aid of local stability analysis and bifurcation plots, exponential interactions among CD4+ cells, HIV, and CD8+ cells were investigated. The system exhibited unexpectedly complex behaviors that were both mathematically and biologically interesting, for example monostability, periodic oscillations, and bistability. The CD8+ cell lysing rate, the CD8+ cell count, and the saturation effect were combined to determine the HIV kinetics. For a given CD8+ cell count, a low CD8+ cell lysing rate and a high saturation effect led to monostability to a high viral titre, and a low CD8+ cell lysing rate and a low saturation effect triggered periodic oscillations; this explained why patients with a non-protective HLA allele were always associated with a high viral titer and exhibited bad infection control. On the other hand, a high CD8+ cell lysing rate led to bistability and monostability to a low viral titer; this explained why protective HLA alleles are not always associated with good HIV infection outcomes. These mathematical results explain how differences in HLA alleles determine the variability in viral infection.
