COMPARTMENT-SPECIFIC MICROBIOTA RESPONSES TO CYCLIC TEMPERATURE AND SALINITY CHANGES IN GILTHEAD SEA BREAM

Introduction

Aquaculture is one of the fastest-growing food production sectors worldwide, yet its long-term sustainability is threatened by climate change. This challenge is particularly relevant in the Mediterranean basin, where its semi-enclosed nature amplifies warming trends which include salinity and oxygen fluctuations (Dayan et al., 2023). Aquatic organisms respond to environmental stress through a complex set of physiological, cellular, and molecular mechanisms. Within this framework, the microbiota emerges as a potential marker of stress response and as a key component of the host's adaptive capacity (Domingo-Bretón et al., 2025). In fact, the gut, skin, and surrounding water harbor interconnected microbial communities that, along with the host, form the holobiont, an integrated biological unit which reacts in a coordinated manner to environmental change. Despite this importance, relatively limited and sometimes contradictory information is available on how changes in temperature and salinity reshape microbiota in farmed species. Accordingly, the present study aimed to characterize gilthead sea bream microbiota changes in the intestinal tract, skin, and rearing water in response to shifts in temperature and salinity. Understanding these dynamics is essential to identify whether specific environmental perturbations induce transient dysbiosis, functional reorganization, or recovery to the original state in the sea bream holobiont system.

Materials and methods

A total of 120 gilthead sea bream (Sparus aurata) juveniles (~13.4g) were randomly distributed into six 90-L tanks (20 fish/ tank) connected to two independent RAS. Three tanks were allocated to the salinity challenge and three tanks to the temperature challenge, performing a closed-loop trials, characterized by a decrease in salinity and an increase in temperature from as illustrated in Figure 1a. Before the start of the trial, fish were acclimated for two weeks under common conditions (20 °C, seawater, natural photoperiod, DO> 75%) and were fed manually to visual satiation with a commercial diet. The experimental program included three sampling points (t0, t1, t2), used to collect skin, intestinal and farm water microbiota samples. Microbiota samples were processed for DNA extraction and sequenced using Oxford Nanopore Technologies (16S rRNA regions V1-V9) for skin and water samples, and Illumina MiSeq (16S rRNA region V3-V4) for gut microbiota samples. For both platforms, sequences identified as ASVs were taxonomical assigned using Minimap2 v2.17-r941 with SILVA v138.1 as reference database. Temporal and between-branch differences were assessed using alpha and beta diversity metrics. In addition, partial least squares discriminant analysis (PLS-DA) and Bayesian network analysis was applied to identify bacterial clusters associated with environmental changes, whereas MaAsLin2 was used to model longitudinal microbial trajectories and associations across time and experimental conditions.

Results and discussion

The results indicate that the water microbiota responded more strongly to environmental perturbations than the gut microbiota, both under temperature-driven and salinity-driven changes. In particular, alpha diversity exhibited a temporal patterns in water samples, whereas gut samples showed a more homogeneous profile across sampling times or experimental branches (Figure 1b). This trend was further supported by beta diversity and discriminant analyses, which consistently identified environmental changes as the main driver of shifts in the water microbiota. In contrast, the intestinal compartment appeared to be more stable and buffered, likely reflecting the role of the host in maintaining gut homeostasis, as previously reported (Naya-Català et al., 2026). At the taxon level, LEfSe and MaAsLin2 identified multiple bacterial markers associated with environmental change in the rearing water, including taxa that responded similarly, as common stress-related signature, regardless of the perturbation. Further analyses are ongoing to evaluate whether analogous patterns extend to the skin microbiota and to a more integrative, with the aim of defining the broader physiological response of the holobiont to environmental stress. Overall, these findings support the view that the water microbiota acts as a highly responsive environmental sensor, whereas the gut microbiota behaves as a more constrained and host-filtered compartment, thereby contributing to the maintenance of holobiont stability under fluctuating conditions.

Figure 1. Experimental design (a). Alpha diversity metrics for water and gut microbiota (b).

Funding

This study is part of the ThinkInAzul program and was funded by the MCIN with funds from the NextGenerationEU program (PRTR-C17.I1) and the Valencian Government THINKINAZUL/2021/024, AICO 2025 (CIAICO/2024/281) and APOSTD 2024 (CIAPOS/2024/092).

References

Dayan, H., et al. (2023). Marine heat waves in the Mediterranean Sea: An assessment from the surface to the subsurface to meet national needs. Front Mar Sci. 10:1045138.

Domingo‑Bretón, R., et al. (2025). Intestinal microbiota shifts by dietary intervention during extreme heat summer episodes in farmed gilthead sea bream (Sparus aurata). Aquac Rep. 40:102566.

Naya-Català, F., et al. (2026). Dietary rayon microfibers differentially reshape rearing water and host associated microbiomes of farmed European sea bass (Dicentrarchus labrax). Environmental Microbiome 21, 30.