Analyzing bacterial networks and interactions in skin and gills of Sparus aurata with microalgae-based additive feeding

Abstract

The inclusion of microalgae in functional fish diets has a notable impact on the welfare, metabolism and physiology of the organism. The microbial communities associated with the fish are directly influenced by the host’s diet, and further understanding the impact on mucosal microbiota is needed. This study aimed to analyze the microbiota associated with the skin and gills of Sparus aurata fed a diet containing 10% microalgae. Sequencing of the V3-V4 variable region of 16S rDNA molecules was employed to determine the composition of the microbial communities. The study employed bioinformatics tools to explore the taxonomic composition and interactions of the microbiota, emphasizing the integration of taxonomic analysis and abundance correlation networks as crucial for understanding microbial community dynamics and the impact of functional diets. The results indicated that there were not changes in the composition of the skin and gill microbiota. However, notable differences were observed in the bacterial interaction networks. The skin and gill networks exhibited distinct overall patterns influenced by their respective environments and functions. The gill network showed a highly connected and redundant structure, increasing its resilience, while the skin network showed a more fragmented structure, suggesting a potentially greater vulnerability to perturbations. Key taxa, such as Acinetobacter and Polaribacter, were identified as critical for maintaining the stability and functionality of these microbial ecosystems. Polaribacter could demonstrate potential protection against pathogens through negative interactions. These tentative studies open up an additional avenue to consider, such as the interactions among bacterial communities, as well as new proposals to corroborate these findings. These observations underline the importance of understanding the composition and interactions within bacterial groups to fully grasp the dynamics of microbial communities.