title: Quantifying the Protection of Activating and Inhibiting NK Cell Receptors during Infection with a CMV-Like Virus.
abstract: The responsiveness of natural killer (NK) cells is controlled by balancing signals from activating and inhibitory receptors. The most important ligands of inhibitory NK cell receptors are the highly polymorphic major histocompatibility complex (MHC) class I molecules, which allow NK cells to screen the cellular health of target cells. Although these inhibitory receptor-ligand interactions have been well characterized, the ligands for most activating receptors are still unknown. The mouse cytomegalovirus (MCMV) represents a helpful model to study NK cell-driven immune responses. Many studies have demonstrated that CMV infection can be controlled by NK cells via their activating receptors, but the exact contribution of the different signaling potential (i.e., activating vs. inhibiting) remains puzzling. In this study, we have developed a probabilistic model, which predicts the optimal specificity of inhibitory and activating NK cell receptors needed to offer the best protection against a CMV-like virus. We confirm our analytical predictions with an agent-based model of an evolving host population. Our analysis quantifies the degree of protection of each receptor type, revealing that mixed haplotypes (i.e., haplotypes composed of activating and inhibiting receptors) are most protective against CMV-like viruses, and that the protective effect depends on the number of MHC loci per individual.
authors: Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University , Utrecht , Netherlands.
authors: Paola
authors: P
authors: Carrillo-Bustamante
authors: Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University , Utrecht , Netherlands.
authors: Can
authors: C
authors: Keşmir
authors: Theoretical Biology and Bioinformatics, Department of Biology, Utrecht University , Utrecht , Netherlands.
authors: Rob J
authors: RJ
authors: de Boer
keywords: CMV infection; NK cell receptors; agent-based modeling; evolution; models; theoretical