Genetic selection for growth drives differences in intestinal microbiota composition and parasite disease resistance in gilthead sea bream

Abstract

Background: The key effects of intestinal microbiota in animal health has led to an increasing interest in manipulating these bacterial populations to improve animal welfare. The aquaculture sector is no exception and in the last years many studies have described these populations in different fish species. However, this is not an easy task, as intestinal microbiota is composed of very dynamic populations that are influenced by different factors, such as diet, environment, host age and genetics. In the current study, we aimed to determine whether the genetic background of gilthead sea bream (Sparus aurata) influences the intestinal microbial composition, how these bacterial populations are modulated by dietary changes, and the effect of selection by growth on intestinal disease resistance. To that aim, three different groups of five families of gilthead sea bream that were selected during two generations for fast, intermediate or slow growth (F3 generation) were kept together in the same open-flow tanks and fed a control or a well-balanced plant-based diet during nine months. Six animals per family and dietary treatment were sacrificed and the adherent bacteria from the anterior intestinal portion were sequenced. In parallel, fish of the fast- and slow-growth groups were infected with the intestinal parasite Enteromyxum leei and the disease signs, prevalence, intensity and parasite abundance were evaluated. Results: No differences were detected in alpha diversity indexes among families, and the core bacterial architecture was the prototypical composition of gilthead sea bream intestinal microbiota, indicating no dysbiosis in any of the groups. The plant-based diet significantly changed the microbiota in the intermediate- and slow-growth families, with a much lower effect on the fast-growth group. Interestingly, the smaller changes detected in the fast-growth families potentially accounted for more changes at the metabolic level when compared to the other families. Upon parasitic infection, the fast-growth group showed significantly lower disease signs and parasite intensity and abundance than the slow-growth animals. Conclusions: These results show a clear genome-metagenome interaction indicating that the fast-growth families harbor a microbiota that is more flexible upon dietary changes. These animals also showed a better ability to cope with intestinal infections.

Review on alternative meals for gilthead seabream, Sparus aurata

“…There is a limited number of studies defining the effects of the host genome on intestinal microbiota composition in fish, but it has been demonstrated that there is a clear correlation between fish genotype and intestinal microbial communities. As reported by Piazzon et al (2017, 2020), the genetic background influences the structure of the commensal bacterial communities and their fluctuations upon differences in diet. Moreover, the authors showed that the genetic background, microbiota composition, and dietary and physiological plasticity are intricately linked (Piazzon et al, 2020).…”

“…As reported by Piazzon et al (2017, 2020), the genetic background influences the structure of the commensal bacterial communities and their fluctuations upon differences in diet. Moreover, the authors showed that the genetic background, microbiota composition, and dietary and physiological plasticity are intricately linked (Piazzon et al, 2020). Results obtained in this trial suggest that genetic background of GSB influences the structure of the commensal bacterial communities and that the typical microbial architecture of the anterior intestine of the three different groups of families of GSB selected by growth fed two different diets do not differ significantly in their overall core composition.…”

“…The aim of this review was to report the effects of use of alternative sources on GSB. Data of different works (Adamidou et al, 2011; Alexis, 1997; Baeza‐Ariño et al, 2016; Benedito‐Palos et al, 2008, 2016; Bonaldo et al, 2008; Caballero et al, 2003; Castro, Couto, et al, 2019; Dimitroglou et al, 2010; Estensoro et al, 2016; Estruch et al, 2018; Fontinha et al, 2021; Fountoulaki et al, 2009; Gil‐Solsona et al, 2019; Gisbert et al, 2017; Guerreiro et al, 2016; Kokou et al, 2012; Martinez‐Llorens et al, 2012; Moutinho et al, 2017; Perera et al, 2019; Piazzon et al, 2017, 2020; Saleh et al, 2022; Sales et al, 2021; Sánchez‐Lozano et al, 2009; Santigosa et al, 2010; Simó‐Mirabet et al, 2018; Sitjà‐Bobadilla et al, 2005; Wassef et al, 2007; Wassef et al, 2015; Wassef et al, 2014; Wassef et al, 2009; Wassef et al, 2012) are summarized in Tables 1 and 2. Table 1 shows the major effects of alternative diets to FM/FO; Table 2 shows composition of experimental diets and the composition of GSB’s carcasses after trials.…”