Parallel processing in immune networks

TL;DR

This paper models the adaptive immune system as a bipartite spin-glass, revealing how link sparsity enables parallel pathogen response and providing insights into lymphocyte behavior and autoimmunity through statistical mechanics analysis.

Contribution

It introduces a novel bipartite spin-glass model for immune networks, demonstrating how link dilution facilitates multitasking and analyzing lymphocyte dynamics with analytical and simulation methods.

Findings

Link sparsity enables parallel pathogen response.

Model's analytical results agree with simulations.

Provides a systemic explanation for lymphocytosis-autoimmunity correlation.

Abstract

In this work we adopt a statistical mechanics approach to investigate basic, systemic features exhibited by adaptive immune systems. The lymphocyte network made by B-cells and T-cells is modeled by a bipartite spin-glass, where, following biological prescriptions, links connecting B-cells and T-cells are sparse. Interestingly, the dilution performed on links is shown to make the system able to orchestrate parallel strategies to fight several pathogens at the same time; this multitasking capability constitutes a remarkable, key property of immune systems as multiple antigens are always present within the host. We also define the stochastic process ruling the temporal evolution of lymphocyte activity, and show its relaxation toward an equilibrium measure allowing statistical mechanics investigations. Analytical results are compared with Monte Carlo simulations and signal-to-noise outcomes showing overall excellent agreement. Finally, within our model, a rationale for the experimentally well-evidenced correlation between lymphocytosis and autoimmunity is achieved; this sheds further light on the systemic features exhibited by immune networks.