Abstract
Simulation code for a model of the adaptive immune response seen in flavivirus infections is used to explain the immunopathological consequences seen in West Nile Virus virus (WNV) infections. We use a model that specifically handles the differences in how the virus infects resting cells, the G0 state, versus dividing cells, the G1 state, which includes vastly increased MHC-I upregulation for resting cells over dividing cells. The simulation suggests how the infection progresses in a one host model and the results shed insight into the unusual survival curve data obtained for this infection: there is an increase in health even though viral load has increased.
Highlights
The code for the general simulation framework has been discussed in [1] with results in [2], and the reader is referred to those works for the background details
We show the decoy hypothesis is a reasonable way to explain collateral damage and the existing survival data measured in West Nile Virus virus (WNV) infections
In addition to the simulation results, we have included simple arguments based on approximations that show we can expect some sorts of oscillatory behavior in the level of healthy cells versus viral load
Summary
The code for the general simulation framework has been discussed in [1] with results in [2], and the reader is referred to those works for the background details. Increases in MHC-I concentration on infected cells enhance the avidity of interaction of virus-specific CTL with the infected target cell. The increased avidity enables the interaction of infected cells with CTL clones previously below the recognition threshold because of their low affinity for MHC-virus peptide ligand. Due to the increased avidity of their interaction, these low-affinity, self-reactive clones can lyse both infected and uninfected target cells that express high cell surface MHC-I concentrations [8]. The mortality associated with intervening doses is unpredictable over several log dilutions of virus dose Explain the ragged dose survival curves seen in these infections
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