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.

Keywords: Sparus aurata; Diet; Gills; Microalgae; Microbiota; Network; Skin.

Fig. 1

Relative abundance at the genus taxonomy category in the (A) gill and (B) skin microbiota of fish. NA indicates ASVs that were not taxonomically clustered at the genus level within the database. ETC < 1% indicates a relative abundance of less than 1%.

Fig. 2

Abundance correlation network of different types of microorganisms found in the gills. The graph is divided into three parts: one for the Control group (A); Raw group (B), and the Hydrolyzed group (C). Each circle represents a group of microorganisms, with different colors indicating how they are grouped together. The size of each circle depends on a value called Pi, and the lines connecting the circles show whether the microorganisms have a positive (green) or negative (red) relationship. Triangular shapes in the graph represent certain Pi values.

Fig. 3

Abundance correlation network of ASVs in skin, calculated for (A) Control, (B) Raw and (C) Hydrolyzed groups of study separately. Nodes are colored by community algorithm and sized by Pi value calculated. Edges are coloured by correlation type (green: positive; red: negative) and the triangular shape represents values of Pi < 0.62.

Fig. 4

ZiPi-plot showing distribution of ASVs based on their module-based topological roles to (A) gills and (B) skin of microbiota associated with Sparus aurata. Blue dots represent Control groups, orange to Raw and green to Hydrolyzed. The blue dotted line indicates the limit value of Pi (0.62), while the orange dotted line indicates the value of Zi (2.5).