Optimal resource allocation to biochemical defense and counter-counter defense in trophic and parasitic interactions

Stefan Schuster , Department of Bioinformatics, Matthias Schleiden Institute, Friedrich Schiller University Jena
In antagonistic interactions among organisms, often one organism “defends” itself by some toxic compound and the counterpart, in turn, responds by producing an enzyme that inactivates that compound [1]. In some cases, the former organism can respond by producing an inhibitor of that enzyme (counter-counter defence) [2,3]. An example is provided by cephalosporins, \beta-lactamases and clavulanic acid (an inhibitor of \beta-lactamases). We tackle the question under which conditions it pays, during evolution, to establish a counter-counter defence rather than to intensify or widen the defence mechanisms. We establish a mathematical model describing this phenomenon, based on enzyme kinetics for competitive inhibition [3]. The optimal allocation of defence and counter-counter defence can be calculated in an analytical way despite the nonlinearity in the underlying differential equation. The calculation predicts that only if the inhibition constant is below a threshold, it pays to have a counter-counter defence. This prediction accounts for the observation that not for all defence mechanisms, a counter-counter defence exists. Our results should be of interest for computing optimal mixtures of \beta-lactam antibiotics and \beta-lactamase inhibitors, as well as for plant-herbivore and other molecular-ecological interactions. References [1] S. Dühring, …, S. Schuster: Host-pathogen interactions between the human innate immune system and Candida albicans - Understanding and modeling defense and evasion strategies. Front. Microbiol. 6 (2015) 625. [2] J. Ewald, …, S. Schuster, B. Ibrahim: Trends in mathematical modeling of host-pathogen interactions. Cell. Mol. Life Sci. 77 (2020) 467–480. [3] S. Schuster, …, S. Dühring: Optimizing defence, counter-defence and counter-counter defence in parasitic and trophic interactions - A modelling study. arXiv: 1907.04820 (2019)
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18 Jun 2024, 16:00
Institut für Theoretische Physik, BioQuant, SR 41

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