Microbiome mediated tolerance to biotic stressors: a case study of the interaction between a toxic cyanobacterium and an oomycete-like infection in Daphnia magna

Organisms are increasingly facing multiple, potentially interacting stressors in natural populations. The ability of populations coping with combined stressors depends on their tolerance to individual stressors and how stressors interact, which may not be correctly captured in controlled laboratory settings. One largely unexplored reason for this is that the microbial communities in laboratory settings often differ from the natural environment, which could result in different stressor responses and interaction patterns. In this study, we investigated the impact of single and combined exposure to a toxic cyanobacterium and an oomycete-like parasite on the performance of three Daphnia magna genotypes. Daphnia individuals were first sterilized and then experimentally given a natural or a laboratory-derived microbial inoculum. Survival, reproduction and body size were monitored for three weeks and gut microbiomes were characterized at the end of the experiment. Our study confirmed that natural and laboratory microbial inocula and gut microbiomes are differently structured with natural microbiomes being more diverse than laboratory microbiomes. Our results showed that exposure to the stressors reduced D. magna performance compared to the D. magna not exposed to any stressor. An antagonistic interaction between the two biotic stressors was revealed with respect to D. magna survival when Daphnia individuals were exposed to the laboratory microbial inoculum. This effect was consistent across all three genotypes. In Daphnia exposed to a natural microbial inoculum this antagonistic interaction could not be detected and the genotype x exposure interaction was genotype-dependent. Our results indicate that host-stressor interactions depend on the microbial inoculum and that the gut microbiome potentially has a strong role in this, thereby providing a largely unexplored dimension to multiple-stressor research.