A quantitative model for the regulation of innate immune activation

Abstract

The immune system employs a wide variety of strategies to protect the body from infection. Cells such as natural killer (NK) cells and macrophages can recognize and eliminate targets with aberrant surface ligand expression in a manner that is not antigen-specific. This innate mechanism of activation must be tightly regulated to prevent autoimmunity. Here we introduce a quantitative model of the regulation of nonspecific activation inspired by Bayesian inference. Our model captures known behaviors of innate immune cells, including adaptation to changing environments and the development of hyposensitivity after prolonged exposure to activating signals. Our analysis also reveals a tradeoff between precision and adaptation. Maintaining the ability to adapt to different environments leads to heterogeneous responses, even for hypothetical populations of immune cells and targets that have identical surface receptor and ligand expression. Collectively, our results describe an adaptive algorithm for self/nonself discrimination that functions even in the absence of antigen restriction. The same model could also apply more broadly to the adaptive regulation of activation for other immune cell types.