Computer Analysis Models Immune Response to HIV

Researchers recently demonstrated, via a computational perspective, how the innate immune system and human immunodeficiency virus (HIV-1) interact. The study was published on PLOS One, on March 24, 2016, and was conducted by Edward P. Browne, PhD, of the Koch Institute for Integrative Cancer Research at Massachusetts Institute of Technology in Massachusetts in the United States.

In describing the reason the undertook this study the researchers said “Since the the structure of the IFNa inhibitory network, as well as the parameters that regulate its activity, are poorly understood, a better understanding of the underlying dynamics of this response may lead to improved and more effective IFNa-based therapies.” They created a dynamic model, which, they said, “simulated the inhibition of HIV-1 by IFNa” and that they “tested this model in a well-defined experimental system.”

The researchers said they “performed experiments with a tissue culture model of spreading HIV-1 infection.” In order learn more about the interaction of HIV-1 and the immune system, they said they “constructed a dynamical system that models the dynamics of CD4 T cells and their interaction with both IHV-1 and IFNa.” They tested the model and determined that it “could be useful for the design of novel therapies for HIV-1 that target the IFNa pathway.”

Additionally, the researchers say “The application of this model to clinical data from HIV-1 patients could yield valuable insights into HIV-1 immunity and pathogenesis.” For example, the model may help clinicians derive parameter values for individual patients.

There are some limitations to the uses of the model including, the fact that the “model relies on mass-action interactions to simulate the innate immune response to infection,” according to the researchers, who add, “it may not be applicable to immune responses in solid tissues such as lymph nodes or mucosal surfaces.” Additionally the model does not take into account the contribution of endogenous IFNa.

Despite the limitations of the model, the researchers conclude, “this study represents the first attempt to analyze the interaction of the innate immune system with HIV-1 from a computational perspective, and demonstrates that quantitative estimates for the parameters that regulate IFNa’s potency can be derived from experimental data.” They believe that the model provides a starting point for future studies.