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Multi-omics characterisation of Daphnia magna exposed to PFAS and microplastics: transcriptome and gut microbiome datasets
Summary
Researchers generated a multi-omics dataset from Daphnia magna exposed to environmentally relevant concentrations of PFOS, PFOA, and PET microplastics, integrating gut microbiome 16S rRNA profiling and whole-organism transcriptomes to enable systems-level investigation of host-microbiome interactions under complex contaminant stress.
Abstract Per-and polyfluoroalkyl substances (PFAS) and microplastics (MPs) are highly persistent, mobile contaminants that are increasingly recognized as threats to freshwater ecosystems. Their ubiquity, resistance to degradation, and potential for bioaccumulation raise concern over sub-lethal impacts on aquatic organisms, including keystone species central to food-web dynamics. Daphnia magna, a keystone species in freshwater ecosystems and a widely used model in ecotoxicology and evolutionary biology, provides a powerful system to investigate these effects. Here, we present a multi-omics dataset from D. magna exposed to environmentally relevant concentrations of perfluorooctane sulfonate (PFOS, 7 ng/L), perfluorooctanoic acid (PFOA, 70 ng/L), and polyethylene terephthalate (PET) microplastics (50 mg/L), both individually and in combination. The dataset integrates 16S rRNA metabarcoding profiles of the gut microbiome with whole-organism transcriptomes generated by RNA sequencing. This combined design enables systems-level exploration of host–microbiome interactions and gene regulatory responses under chemical stress. By providing high-resolution molecular data on a sentinel species, this resource fills a critical gap in ecotoxicological data for complex contaminant mixtures and offers a foundation for predictive modelling, mechanistic inference, and next-generation environmental risk assessment in freshwater ecosystems.
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