The hidden costs of resistance: Contrasting the energetics of successfully and unsuccessfully fighting infection

Abstract

Abstract Exposure to a pathogen is predicted to lead to increased energy use as hosts attempt to activate a costly immune system and repair damaged tissue. To meet this demand, metabolic rates, which capture the rate at which a host can use, transform and expend energy, are expected to increase. Yet for many host–pathogen systems, metabolic rates after encountering a pathogen are just as likely to decrease as increase, suggesting that increased energy expenditure may not always be best for fighting infection. Diverging metabolic trajectories have been previously attributed to the different pathways that specific pathogen classes, such as bacteria or viruses, induce in a host. Here, we test how the magnitude and direction of metabolic change following pathogen exposure might also depend on whether a host has cleared infection or is instead fighting to reduce pathogen burden, as well as interactions between host and pathogen genotypes of a single host–pathogen system. Using a model system, Daphnia magna and its bacterial pathogen, we quantified changes in mass‐independent metabolic rates over a 30‐day period for multiple host and pathogen genotypes. We found that the metabolic trajectory of an exposed host diverged quickly during the infection process. For hosts that were exposed to a pathogen and resisted infection, their mass‐independent metabolic rates remained suppressed long after exposure, leading to a sustained reduction in total energy use compared to unexposed animals. The reverse was true for hosts in which the pathogen was able to establish an infection. Underlying these changes were differences in the energetic burden that each pathogen genotype imposed on its host, as well as changes in the way host genotype and the outcome of infection shaped underlying scaling relationships between host body mass and metabolic rates. Our results demonstrate how variation in an organism's metabolic rate and overall energy use can arise from within a single host–pathogen encounter and depend on the likelihood of pathogen clearance, as well as the within‐species genetic variability of both hosts and pathogens. Read the free Plain Language Summary for this article on the Journal blog.