Pesticides reaching aquatic ecosystems can affect organisms either directly or indirectly, the latter by interacting, for example, with gut bacteria. In vertebrates, the gut microbiome and the implications of its composition for the immune status and health of the host organism have become increasingly important in recent years, even though causal relationships are far from being fully understood. In this context, the term "holobiont" was coined to describe the entity of a host (biont) and its microbiome. For mammals, it has already been demonstrated that a holobiont can be negatively affected by chemicals that are not explicitly directed against metabolic pathways of the host organism, but induce a dysbiosis of the gut microbiome and thereby promote e.g. pathogens and their gene products. In the proposed project, the effect of a model pesticide, the widely used systemic broad-spectrum herbicide glyphosate, one of its formulations (Roundup®) and its main metabolite aminomethylphosphonic acid (AMPA) on the gut microbiome and health status of the brown trout, a fish species with high ecological relevance, will be investigated. Effects at the microbiome level will be mechanistically linked to biomarkers characterising the health and immune status of the fish host. The two main objectives are (1) to establish a comprehensive, statistically validated and plausible link between biomarker-based effect concentrations and gut-microbiome responses (shifts in microbiome composition with a particular focus on fish pathogens), and (2) to establish causality for these relationships using an experimental approach in which the influence of the herbicide on the primary molecular target is gradually manipulated. Since our project explicitly focuses on mechanistic links between the exposure of a holobiont to glyphosate, Roundup or AMPA, i.e. the health of the biont and the reactions of its microbiome, it aims to contribute to a differentiated discussion on the potential hazards of this herbicide for humans and the environment with scientifically sound data.