"Analyzing the dynamics in defense/counter-defense games among hosts and pathogens"Dwivedi, ShaluIn the dynamic interplay between hosts and pathogens, hosts may produce a defense compound that acts as toxin to deter pathogen attack. Conversely, pathogens may evolve to produce a counter-defense enzyme, neutralizing the host’s toxin. This evolutionary arms race incurs costs for both parties, prompting adaptations and strategic shifts. We conceptualize this interaction as an asymmetric game, with hosts and pathogens as players, and their potential responses - defense, counter-defense, or inaction- as their strategic options [1]. This scenario presents a paradox: if the pathogen’s counter-defense enzyme is entirely effective, then the host’s toxin is rendered obsolete. However, should the host cease toxin production, the pathogen's enzyme becomes redundant, ironically reinstating the toxin's utility. This paradox raises a critical question: does this interaction leads to an oscillatory change in strategies or to a steady state, reflecting a balanced, optimal production of toxin and enzymes by hosts and parasites, respectively? To explore this, we introduce a game-theoretical model incorporating replicator dynamics [2] to examine temporal shifts in strategy from active defense to non-defense and back. Our findings suggest that producing a moderate amount of toxin and enzyme represents the most advantageous strategy for both organisms. Extending our model to population dynamics reveals potential oscillations in defense and counter-defense strategies under certain conditions. In addition, we frame these adaptive strategies as forms of bet-hedging, providing host and pathogens with a survival advantage in unpredictable environments. In conclusion, our analysis supports the notion of a continual strategic flux in host-pathogen interactions, characterized by periodic adjustments in the levels of defensive and counter-defensive measures. [1] Ewald J, Sieber P, Garde R, Lang SN, Schuster S, Ibrahim B. Trends in mathematical modeling of host-pathogen interactions. Cell Mol Life Sci. (2020) 77:467-480. doi: 10.1007/s00018-019-03382-0. [2] Hofbauer J, Sigmund K. Evolutionary games and population dynamics. Cambridge: Cambridge University Press; 1998. Authors: Shalu Dwivedi^1, Leonardo Oña^2 and Stefan Schuster^1 1^Dept. of Bioinformatics, Matthias Schleiden Institute, University of Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany 2^Dept. of Ecology, University of Osnabrück, Germany |
« back