Network-based integration of omics, physiological and environmental data in real-world Elbe estuarine Zander

Coastal and estuarine environments are under endogenic and exogenic pressures jeopardizing survival and diversity of inhabiting biota. Information of possible synergistic effects of multiple (a)biotic stressors and holobiont interaction are largely missing in estuaries like the Elbe but are of importance to estimate unforeseen effects on animals' physiology. Here, we seek to leverage host-transcriptional RNA-seq and gill mucus microbial 16S rRNA metabarcoding data coupled with physiological and abiotic measurements in a network analysis approach to decipher the impact of multiple stressors on the health of juvenile Sander lucioperca along one of the largest European estuaries. We find mesohaline areas characterized by gill tissue specific transcriptional responses matching osmosensing and tissue remodeling. Liver transcriptomes instead emphasized that zander from highly turbid areas were undergoing starvation which was supported by compromised body condition. Potential pathogenic bacteria, including Shewanella, Acinetobacter, Aeromonas and Chryseobacterium, dominated the gill microbiome along the freshwater transition and oxygen minimum zone. Their occurrence coincided with a strong adaptive and innate transcriptional immune response in host gill and enhanced energy demand in liver tissue supporting their potential pathogenicity. Taken together, we show physiological responses of a fish species and its microbiome to abiotic factors whose impact is expected to increase with consequences of climate change. We further present a method for the close-meshed detection of the main stressors and bacterial species with disease potential in a highly productive ecosystem.