Increased T cell trafficking as adjunct therapy for HIV-1

Spatial Lymphocyte Dynamics in Lymph Nodes Predicts the Cytotoxic T Cell Frequency Needed for HIV Infection Control

The surveillance of host body tissues by immune cells is central for mediating their defense function. In vivo imaging technologies have been used to quantitatively characterize target cell scanning and migration of lymphocytes within lymph nodes (LNs). The translation of these quantitative insights into a predictive understanding of immune system functioning in response to various perturbations critically depends on computational tools linking the individual immune cell properties with the emergent behavior of the immune system. By choosing the Newtonian second law for the governing equations, we developed a broadly applicable mathematical model linking individual and coordinated T-cell behaviors. The spatial cell dynamics is described by a superposition of autonomous locomotion, intercellular interaction, and viscous damping processes. The model is calibrated using in vivo data on T-cell motility metrics in LNs such as the translational speeds, turning angle speeds, and meandering indices. The model is applied to predict the impact of T-cell motility on protection against HIV infection, i.e., to estimate the threshold frequency of HIV-specific cytotoxic T cells (CTLs) that is required to detect productively infected cells before the release of viral particles starts. With this, it provides guidance for HIV vaccine studies allowing for the migration of cells in fibrotic LNs.

Modeling HIV persistence and cure studies

PURPOSE OF REVIEW

To provide a summary of the contributions of mathematical modeling to understanding of HIV persistence during antiretroviral therapy.

RECENT FINDINGS

Although HIV persistence during therapy could be caused by continual viral replication or slow-decaying latent infection, most evidence points toward the latter mechanism. The latent reservoir is maintained by a balance of cell death, proliferation, and reactivation, and new methods to estimate the relative contributions of these rates use a wide range of experimental data. This has led to new quantitative predictions about the potential benefit of therapies such as latency-reversing agents or antiproliferative drugs.

SUMMARY

Results of these mathematical modeling studies can be used to design and interpret future trials of new therapies targeting HIV persistence.