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Resumen del trabajo presentado en Aquaculture Europe, celebrado en Rimini (Italia) del 27 al 30 de septiembre de 2022., [Introduction]: The AquaIMPACT H2020 EU project aims to integrate selective breeding and nutrition for producing more sustainable marine fish with a higher phenotypic plasticity to deal with environmental challenges. At this interplay between diet and genetics, gut microbiota emerge as a reliable criterion to assess the selection practices. However, the influence of the host genome on the composition and activity of gut microbiota is still scarcely investigated in gilthead sea bream (Piazzon et al., 2020). Thus, the aim of this study was to unravel the main effects of alternative diet formulations along the production cycle of gilthead sea bream selected for high growth (HG) compared to reference (REF) fish, establishing correlations between intestinal gene expression and gut microbiota abundance., [Methods]: HG and REF gilthead sea bream were fed CTRL (15% FM; 6-8% FO) and FUTURE (7.5% FM; 12% poultry sub-products and 3% DHA-rich algae oil) diets during 12 months at the experimental facilities of ECOAQUA, at ULPGC, under natural photoperiod and temperature conditions. Initial (t0; Nov-19; 10 g body weight; 18 fish), intermediate (Jul-20; t1; 200 g; 36 fish) and final (Nov-20; t2; 350 g; 40 fish) sampling points were established to assess the dynamics of anterior intestine (AI) mucosal adherent microbiota composition across the production cycle. As the most prominent differences in gut microbiota among groups were found in t1, fish of this sampling point were selected for RNA-sequencing. V3-V4 region of the 16S rRNA of each sample was amplified and sequenced by Illumina MiSeq, and taxonomy was assigned using the RDP database. RNA-seq libraries were sequenced by Illumina NovaSeq6000. Good-quality reads were mapped against CSIC gilthead sea bream genome and differential expressed transcripts (DET) were retrieved using DESeq2 (FDR < 0.05). Overrepresentation analyses of GO and KEGG terms were implemented in goseq and protein-protein association networks were retrieved using STRING (FDR < 0.05). DET expression and OTUs abundances of the equivalent fish of t1 were correlated using Spearman correlation tests (P < 0.001)., [Results]: Illumina sequencing and taxonomic assignment of the 94 samples allowed the identification of 1,897 OTUs at 97% identity threshold along the gilthead sea bream production cycle. Taking into account the entire population, Chao1 richness index progressively decreased with age, whereas the α-diversity Simpson index was significantly higher in t1 and t2 than in t0. Proteobacteria was the most abundant phylum (64-78%) in all the sampling times, followed by Firmicutes (13-15%), Actinobacteria (6-12%), and Bacteroidetes (~2%). The core microbiota of gilthead sea bream along the production cycle was constituted by 25 OTUs (>1% in at least one of the three sampling times). A validated PLS-DA (Figure 1A) rendered the separation of the three experimental time points. The FUTURE diet induced a shift in the gut microbiota composition of REF fish, validated by PLS-DA, but not in HG fish. The influence of the genetic background was already evidenced at t0, when discriminant analyses separated HG from REF fish. The magnitude of this separation and the number of discriminant taxa persisted along time, but progressively decreased in t1 and t2 in fish were fed CTRL diet. By contrast, HG and REF fish microbiota was not distinguished when fed the FUTURE diet. In t1, RNA-seq mapped reads were associated to 41,582 AI transcripts, with 1,429 DET (1,218 unique descriptions). Group comparisons displayed 1,057 and 459 DET differentially regulated between HG-CTRL and REF-CTRL fish, and between HG-FUTURE and HG-CTRL, respectively. A total of 1,025 significant associations were established between the abundance of 96 OTUs and the expression of 476 DET. A total of 35 correlations between 20 abundant (>1%) OTUs and 25 DET were stablished (Figure 1B). The 60% of the correlated OTUs were associated to DET related with immune system, with a clear presence of Bacilli linked to anti-inflammatory responses. The microbiota-independent list of DET (953) showed the over-representation of transcripts involved in β-oxidative processes of very long chain fatty acids (up-regulated in HG-CTRL) and smooth muscle contraction (upregulated in HG-FUTURE)., [Conclusions]: These results highlight the plasticity of gilthead sea bream gut microbiota along its production cycle, showing the effects of size and season. As in previous studies (Naya-Català et al., 2022), the genetic background strongly influenced the gut microbial composition and the intestinal response of this species, as selected fish exhibited a more plastic microbiota and more changes at the transcriptomic level, when facing dietary changes. Genes related with cell membrane fluency were up-regulated in HG-CTRL fish, whereas FUTURE diet boosted genes involved in intestinal motility in both fish groups. Correlation studies denoted the close link between immune system genes and the intestinal microbiota. Altogether, these results show how diet and genetics can affect the microbiota and the digestive process, and highlight that certain taxa could be interacting with the gilthead sea bream transcriptome., AquaIMPACT (H2020; #818367). RYC2018-024049-I & ESF.

Resumen del trabajo presentado en 6th International Symposium on Genomics in Aquaculture, celebrado en Granada (España) del 04 al 06 de mayo de 2022., The use of feed additives has expanded rapidly as an alternative for antibiotics and chemotherapeutics, with also the capacity to modify the composition of gut microbiota. In farmed fish, and in gilthead sea bream in particular, there is evidence that the host genetic background has a major impact on gut microbiota. Thus, families selected for fast growth have a more flexible microbiota capable of exerting a wider nutritionallymediated response with less microbial community changes. However, nutrition and genetic interactions remain poorly explored in fish, and the aim of this study was to unravel how the microbiota of fish selected (GS) and unselected (NGS) for growth is differentially regulated by oil-coated feed additives. The basal diet (CTRL, no feed additives) was a low fish meal/fish containing algae oil, poultry by-products, and plant ingredients. Experimental diets were oil-coated with the additives: organic acids (OA), Bacillus-species probiotics (PROB), or natural plant extracts (PHYTO). Fish were fed to visual satiety with the CTRL diet during two weeks. After this adaptation period, the different supplemented diets were used with a high additive dose (7.5-10 g/kg) during 2 weeks, decreasing thereafter to 2-5 g/kg until the end of the trial (97 days). Then, adherent microbiota was obtained from the anterior intestine. Illumina sequencing of microbiota yielded a mean of 62,594 reads per sample, which were assigned to 1,156 OTUs at 97% identity threshold. A significant lower richness and diversity was found in the GS fish, which was mainly evidenced by a higher abundance of Actinobacteria in GS-PROB. To study in more detail the observed differences on gut microbial populations, supervised partial least-squares discriminant analyses (PLS-DA) were used. When all populations were analysed as a whole (GS vs NGS), dispersal was markedly lower in GS fish. This pattern was further evidenced for fish fed the CTRL, PROB and OA diets but not for the PHYTO additive, explaining the statistically validated PLS-DA models more than 80% of the total variance. This genetically-guided group differentiation was driven by a total of 104 OTUs. Regarding diet and genetic interactions: i) no effect was detected with the PHYTO additive, ii) the OA reshaped the gut microbiota in NGS with a decrease of Photobacterium damselae sp. and an increase of Paracoccus and Acinetobacter genera, and iii) the PROB diet modified the gut microbiota of both GS and NGS fish, with a higher abundance of Kocuria and Bacillus genera, which reflected the establishment of the probiotic bacteria in the mucosal adherent surface, favouring long-term health promoting probiotic effects., AquaIMPACT (H2020 #818367), RYC2018-024049-I & ESF