Throughout the project, we successfully implemented a series of experiments aimed at understanding the molecular mechanisms underlying vibriosis in sole (Solea senegalensis) and identifying key biomarkers for early disease detection. Our work involved a combination of metabolomics, proteomics, and microbiome analyses, which were performed across various stages of infection.
We performed laboratory infection experiments in collaboration with the Aquatic One Health Research Centre at the University of Santiago de Compostela (AHRCUS). Initially, an established Vibrio anguillarum virulence assay was conducted via direct intraperitoneal injection and key immune organs, including the spleen and kidney, were sampled. Additionally, an indirect bath-infection model was established to study natural infection dynamics in aquaculture settings. Fish were sampled from various tissues such as mucus, gills, spleen, kidney, and intestine, providing an extensive dataset for downstream molecular analyses.
The virulence assay dataset was used to refine the analytical protocols to optimise the chelOMICS approach. This involved streamlining sample processing, LC-MS/MS method development, and siderophore detection, creating a robust workflow. To complement metabolomics analysis, we incorporated proteomics to gain more insight into the infection’s effect of infection on fish metabolism. We integrated open-source bioinformatics tools such as MZmine, DIA-NN, MetaboAnalyst, clusterProfiler, and MixOmics, to improve reproducibility of data analysis and scalability of the approach.
A key achievement was the successful detection and identification of the Vibrio anguillarum-specific siderophore, piscibactin. As we chelated metabolomics extracts, obtained from sole immune organs, with iron chloride (FeCl3), we were able to detect iron-bound siderophores by searching for the characteristic iron isotopic pattern in LC-MS spectra. Furthermore, the presence of ferri-piscibactin was quantified in high-infection samples using multiple reaction monitoring (MRM).
The integration of multi-omics data revealed significant alterations in metabolite and protein profiles, particularly those related to energy production, nucleotide synthesis, and protein regulation during infection. We identified several metabolite and protein biomarkers, including ferri-piscibactin and the STEAP4-like metalloreductase, emphasising the important role of iron metabolism in infection dynamics. These findings provide novel insights into how Vibrio anguillarum exploits host iron resources to support its virulence.
While the metabolome and microbiome analysis via 16S rRNA sequencing was performed on samples from the bath-infection experiment, the results were inconclusive in linking microbiome alterations to the infection process. Nevertheless, the overall project has significantly advanced our understanding of the molecular responses of Solea senegalensis to vibriosis and has set the stage for future diagnostic tools targeting siderophores as infection markers.
