Diversity of immune strategies explained by adaptation to pathogen statistics

TL;DR

This paper introduces a mathematical framework to understand how different immune strategies evolve based on pathogen dynamics, revealing that pathogen frequency and timescale shape immune diversity.

Contribution

It provides a novel quantitative model linking pathogen statistics to the evolution of diverse immune strategies in biological populations.

Findings

Different immune strategies are optimal depending on pathogen frequency and timescale.

The framework recapitulates the diversity of natural immune systems.

Identifies key parameters influencing immune system evolution.

Abstract

Biological organisms have evolved a wide range of immune mechanisms to defend themselves against pathogens. Beyond molecular details, these mechanisms differ in how protection is acquired, processed and passed on to subsequent generations -- differences that may be essential to long-term survival. Here, we introduce a mathematical framework to compare the long-term adaptation of populations as a function of the pathogen dynamics that they experience and of the immune strategy that they adopt. We find that the two key determinants of an optimal immune strategy are the frequency and the characteristic timescale of the pathogens. Depending on these two parameters, our framework identifies distinct modes of immunity, including adaptive, innate, bet-hedging and CRISPR-like immunities, which recapitulate the diversity of natural immune systems.