Diversity of immune strategies explained by adaptation to pathogen statistics

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.immune systems | CRISPR immunity | adaptive immunity | bet hedging | evolution of immunity

Transitions in optimal adaptive strategies for populations in fluctuating environments

“…Our work extends the growing literature investigating transitions between optimal adaptive strategies [13,[15][16][17][18] and generalizes some of our previous results on the adaptation of immune strategies to pathogen statistics [19]. In particular, we derive exact expressions for the transitions between different modes of immunity in memoryless environments when the strategy includes an adjustable investment into immunity.…”

“…3), generalizing previous results [1,15,20,[23][24][25]. Extending the method to phenotypes constrained by a trade-off function, we constructed graphically and calculated analytically the transitions between optimal strategies of diversification and adaptability in a simple model of evolution of immunity [19] (Fig. 5).…”

“…Possible extensions of our results include the influence of non-random environmental changes, such as periodic environments [14,18,21,27], constraints on relative switching rates [16,17,27], active sensing mechanisms [3] and heritable plasticity [13,19], or finite population size effects [28]. Some of these factors are known to lead to transitions between adaptive strategies, e.g.…”

“…Such a constraint on switching rates can induce discontinuous transitions, or cause the co-existence of multiple locally optimal solutions, as we now illustrate in a simple model of evolution of immunity. Our illustrative example is a model that we proposed to explain the diversity of immune strategies observed across the tree of life [19]. The purpose is to show how different strategies are associated with different statistics of pathogen dynamics.…”

Invasions of Host-Associated Microbiome Networks

“…While there are parallels of generalists and specialists to innate effectors and adaptive effector cells, respectively, these effectors engage in collective behaviours that go beyond free-living systems, which we discuss in the following two paragraphs. Studying the population dynamics and evolution of this system is itself a growing field to which ecology and evolutionary biology have been applied (Alizon and van Baalen 2008;Mayer et al 2016;Murall et al 2012;Pilyugin and Antia 2000;Sadd and Schmid-Hempel 2009;Wodarz 2006). To close the section, we discuss the ways in which the WH community coordinates with the immune system in countering a pathogen invasion.…”