The rainbow trout is a cold-water carnivorous species with high commercial value. In a commercial setting, the diet of this species consists of a high proportion of protein and oil from marine fish(Reference Tacon and Metian1). The supply of these traditional fish feed ingredients is economically and ecologically unsustainable due to high fishing pressure, which directly leads to the collapse of wild fish stocks(Reference Tacon and Metian1). As an alternative, a feed consisting exclusively of plant-based ingredients has been developed and extensively tested to meet all the nutritional requirements of rainbow trout(Reference Le Boucher, Quillet and Vandeputte2–Reference Lokesh, Ghislain and Reyrolle4). This next-generation sustainable diet formula is a major step towards achieving the Sustainable Development Goals (SDG14) set by the UN. However, these total plant-based diets are known to cause severe metabolic abnormalities such as glucose intolerance and high visceral fat when fed to rainbow trout(Reference Wacyk, Powell and Rodnick5,Reference Hua and Bureau6) .
To overcome this limitation, a genetic line (hereafter ‘line’) of fish that grow and survive better when fed a 100 % plant-based diet was developed through selective breeding (four generations)(Reference Callet, Médale and Larroquet3). This line of fish is able to digest and metabolise the total plant-based diet better than the naïve fish and maintain a similar growth profile to fish fed conventional ingredients(Reference Callet, Médale and Larroquet3). However, knowledge about metabolic adaptations, the intestinal microbiome and the interaction between diet, intestinal microbiome and host metabolism is unknown for the selected line (suave).
On the other hand, prebiotics such as inulin are potential modulators of various metabolic and immune processes in different animals, including fish(Reference Kolida, Tuohy and Gibson7). Inulin is known to affect energy metabolism, regulation of inflammation and immune homoeostasis in the intestine via its microbially derived metabolites (SCFA)(Reference Hu, Lin and Zheng8,Reference Schilderink, Verseijden and de Jonge9) . Systemically, these dietary fibre-derived metabolites are transported to the liver via the portal vein and are involved in the pathways of fatty acid synthesis, oxidation and fat storage(Reference He, Zhang and Shen10). In addition, SCFA are known to affect glucose uptake in muscle and adipose tissue(Reference Barrera, Sandoval and D’Alessio11). The members of the intestinal microbiome involved in the breakdown and utilisation of inulin in humans and livestock are well documented(Reference Rivière, Selak and Geirnaert12). The microbial species encoding inulin-degrading functions may vary, but the mechanism of inulin degradation and utilisation by the microbiota, as well as receptor-mediated uptake and utilisation of SCFA by the host, are conserved in humans and other mammals(Reference Lindberg13,Reference Gibson and Roberfroid14) .
The effect of inulin on growth, disease resistance, immune parameters, digestive enzymes and metabolism has been demonstrated in teleosts with a wide range of dietary habits(Reference Cerezuela, Cuesta and Meseguer15–Reference Eshaghzadeh, Hoseinifar and Vahabzadeh18). In rainbow trout, there are several studies demonstrating the beneficial effects of inulin on growth and immune status(Reference Hunt, Çetinkaya and Yılmaz19–Reference Ortiz, Rebolé and Velasco21). Recently, the involvement of inulin in metabolic processes in teleosts has also been demonstrated. Studies show that inulin can attenuate the negative metabolic syndrome caused by high-carbohydrate feeding in tilapia(Reference Wang, Zhang and Yu22) and alter the expression of genes involved in various metabolic pathways in rainbow trout(Reference Lokesh, Ghislain and Reyrolle4). Taken together, these results suggest that the mechanism of action of inulin in teleosts may be similar to that in mammals. Given the overwhelming interest in exploiting these beneficial aspects of the interaction between inulin and the gut microbiome for better health and nutritional management in teleosts, a more detailed investigation of this aspect is warranted.
Therefore, in this study, we investigate the effects of inulin and line on the metabolism (via microbially derived SCFA) and microbiome of rainbow trout fed a 100 % plant-based basal diet. To this end, two lines (temoin and suave) of rainbow trout (mean weight: 128·6 g ± 8·4) were fed a 100 % plant-based basal diet containing either 2 % inulin or devoid of it for a period of 120 days. In addition to growth and plasma parameters, host metabolic responses were measured by examining gene expression in various organs, including liver, intestine, muscle and adipose tissue. Since the established link between the inulin and the host is the microbially derived metabolites such as SCFA, we investigated the changes in the microbiome as well as the changes in the content of SCFA in the intestine. Changes in microvillar length are also reported, as inulin is known to affect these epithelial structures.
Materials and methods
Ethical approval
PEIMA INRAE facilities (Sizun, France) are authorised for animal experimentation under French regulation (D29–277–02). The fish handling and sampling were conducted in accordance with the guidelines of French and European legislation on the use and care of laboratory animals (Decree No. 2013–118 of 1 February 2013 and Directive 2010/63/EU, respectively). Experiments were conducted under the animal experimentation authorisation of Karine Brugirard Ricaud and Laurent Labbé.
Diet and experimental set-up
The feeding trial was conducted at the PEIMA fish breeding and rearing facility (INRAE, Sizun, France). Two genetic lines of rainbow trout (hereafter referred to as line) were used for the feeding trial, namely temoin (the INRAE synthetic strain; a domesticated strain maintained at the PEIMA facility with a large number of spawners and without artificial selection in order to maintain the genetic variability) and suave (a selected line from the synthetic strain obtained after four generations of selective breeding based on the ability to survive and grow when fed a 100 % plant-based diet). A two-factorial design was used, with line and inulin intake as the factors. A total plant-based diet (containing only plant ingredients and vegetable oils supplemented with free amino acids) with (2 %) or without (0 %) inulin was prepared at the feed manufacturing facility (INRAE Donzacq). The dosage of inulin was decided based on our previous study(Reference Lokesh, Ghislain and Reyrolle4). The diets were isoproteic (about 45 % crude protein), isolipidic (about 22 % crude fat) and isoenergetic (about 24 kJ/kg DM) and were prepared to meet the nutritional requirements of rainbow trout(23). The composition of the ingredients and the proximate composition of the diet are given in Table 1 and Supplementary Table 1, respectively.
Table 1. Formulation of the diets used in the present study
Fifty juvenile rainbow trout with a stocking density of about 3·5 kg/m3 were introduced into each of the 1800-litre fibreglass circular tanks. The average initial weight of the fish in each group is given in Table 2. During subsequent growth, number of fish was reduced once by random elimination to keep a density below 15 kg/m3 in each tank. At the same time, early maturing males (at 1 year) were discarded. There was a total of four groups consisting of TVO: temoin-0 % inulin; TVI: temoin-2 % inulin; SVO: suave-0 % inulin; and SVI: suave-2 % inulin. Each group was allocated three tanks. Fish were reared under standard conditions during the experimental period, that is, water oxygen level of 9 mg/l, temperature between 6·0 and 18°C and pH of 6·5, water flow rate of 0·7 litre/s and natural photoperiod. The fish were fed by automatic feeder five times a day for 16 weeks. Total weight of fish in each tank was measured every 3 weeks to assess growth parameters. The amount of feed given was recorded daily to calculate the consumption index. The total amount of feed consumption increased steadily with growth and the feeding rate was adjusted accordingly.
Table 2. Growth parameters of rainbow trout (temoin and suave) fed with the control diet (O) and the diet supplemented with 2 % inulin (I)
The data are presented as the mean ± sd, n 3 tanks except for the final body weight (n 12) and hepatosomatic index (n 12). Means between the groups were compared using a two-way ANOVA. A P-value < 0·05 is considered as significant and is presented in bold.
* Feed efficiency = wet weight gain (g)/feed intake (g).
† Hepatosomatic index = 100 × (liver weight/total body weight).
‡ Specific growth rate = 100 × (Ln (final body weight, g)-Ln (initial body weight, g))/d.
§ Weight gain = final weight-initial weight (g).
Sampling
At the end of the feeding experiment, we randomly sampled twelve fish per group (four/tank). The fish were first anaesthetised with tricaine methane sulfonate; (MS-222) (50 mg/l) and then euthanised with a higher dose of MS-222 (100 mg/l). The fish were weighed, and then blood samples were collected using heparinised syringes and tubes and centrifuged at 3000 g for 10 min to isolate the plasma. Plasma samples were stored at −20°C until analysis of plasma parameters. The liver was dissected and weighed. Muscle samples were also taken. Then the viscera were dissected out, and the adipose tissue was removed. The mid-intestine was cut open, and the digestive contents were separated from the mucus. The mucus samples were obtained by scraping with a glass slide. The contents and mucus were kept in separate tubes for microbiome analysis. Part of the mid-intestinal tissue was also collected for gene expression analysis. From a separate group of fish, 2/tank (6/group) intestinal content samples were collected for SCFA analysis. All samples (except for electron microscopy) were frozen with liquid N2 and then stored at −80°C. Intestinal tissue (mid-intestine) was stored in 4 % formaldehyde for electron microscopy.
Diet and whole-body proximate composition
The same protocol was used to analyse the nutrient composition of the diet and the whole body. The nutrient composition of the feed was performed with fresh samples, while the nutrient composition of the whole body was derived from freeze-dried samples. The moisture content of the samples was measured by drying the samples at 105°C for 24 h. The weight of the post-dried samples was subtracted from the weight of the pre-dried samples. The ash content of the samples was measured by burning the samples at 550°C for 16 h and subtracting the weight of the post-combusted samples from that of the pre-combusted samples. The energy content of the samples was measured using the adiabatic bomb calorimeter (IKA). Total lipids were measured by petroleum ether extraction using the Soxtherm system (Gerhardt analytical systems). Crude protein content was measured by the Kjeldahl method using the Kjeltek™ 8400 system (FOSS) after acid extraction.
Measurement of the plasma biochemical parameters
Plasma parameters were measured using commercial kits in combination with a microplate reader. Various biochemical plasma parameters such as glucose (Glucose RTU, bioMérieux)(Reference Trinder24), TAG (PAP 150, bioMérieux)(Reference Rifai, Warnick and Dominiczak25), cholesterol (Cholesterol RTU, bioMérieux)(Reference Amundson and Zhou26) and free fatty acids (NEFA C Kit, Wako Chemicals)(Reference Mulder, Schouten and Popp-Snijders27) were measured. Total free amino acid was quantified according to the method of Moore(Reference Moore28), with glycine as standard.
Microbiome analysis
DNA extraction
DNA from the intestinal contents and mucus samples was extracted using the QIAamp fast DNA stool kit (Qiagen) according to the manufacturer’s instructions. Some modifications were made to the protocol to achieve a better yield from the difficult-to-lyse bacterial cells(Reference Lokesh and Kiron29). The purity and integrity of the extracted DNA were assessed using the NanoDrop 2000c (Thermo) and an agarose gel, respectively.
Preparation of the 16s rRNA (V3–V4) sequencing libraries
The sequencing libraries were prepared according to the standard protocol recommended by Illumina® (Illumina) and as described elsewhere(Reference Lokesh, Ghislain and Reyrolle4,30) . Briefly, the V3 and V4 regions of the bacterial 16s rRNA gene were amplified using the recommended set of primers(Reference Klindworth, Pruesse and Schweer31) linked to the Illumina® adaptor overhangs. The final primer pairs were as follows: Forward 5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3' and Reverse 5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3'. The preparation of the library involved two stages of PCR. In the first stage, the PCR mix (25 µl) contained 12·5 µl of KAPA HiFi Master Mix (Roche) together with 5 µl each of forward and reverse primers (1 µM each) and 2·5 µl of DNA (about 100 ng). Reactions were performed in duplicate. Thermocycling conditions included pre-incubation for 3 min at 95°C, followed by thirty cycles of denaturation at 95°C for 30 s, annealing at 55°C for 30 s and extension at 72°C for 30 s. A final extension was performed at 72°C for 5 min. After PCR, duplicate reactions belonging to one sample were pooled and an aliquot was run on the agarose gel to confirm a positive reaction (about 550 bp). The positive control with a mock bacterial DNA (ZymoBIOMICS Microbial Community DNA Standard, Zymo Research Irvine) and a negative control with water were also included. The negative PCR control showed no visible band on the agarose gel after PCR. The PCR products were transported to La Plateforme Génome Transcriptome de Bordeaux (PGTB) to perform the second-stage PCR. In the second stage, index PCR was performed to add sample-specific barcodes to the PCR products using the Nextera XT index kit according to the manufacturer’s protocol (Illumina). The PCR set-up was the same as in stage 1 except that only eight cycles were used. PCR products were purified using AMPure XP beads (Beckman Coulter) and quantified using the KAPA library quantification kit for Illumina platforms (Roche) according to the manufacturer’s instructions. The sequencing libraries were pooled equimolarly (4 nM) and sequenced using a 250-bp Paired-End Sequencing Kit v2 (Illumina).
Sequence data analysis
The paired-end sequencing data were analysed using the UPARSE pipeline(Reference Edgar32) as described elsewhere(Reference Lokesh, Kiron and Sipkema33). The paired-end sequences were merged, and the primer binding sites were removed. Sequences were then quality-filtered using the maximum error rate strategy (threshold = 1)(Reference Edgar and Flyvbjerg34). The sequences from different samples were merged after being uniquely labelled, the dataset was dereplicated and the singletons were removed. Operational taxonomic unit (OTU) clustering was performed at 97 % similarity. The raw reads were mapped to the OTU to create the OTU abundance table. Taxonomies were assigned using the SINTAX algorithm(Reference Edgar35). Assignments with < 0·8 confidence value were filtered out. A phylogenetic tree in Newick format was created. The OTU table, taxonomy table and phylogenetic tree were exported to the phyloseq package for downstream analysis(Reference McMurdie and Holmes36).
SCFA measurement
The SCFA measurements are performed as previously described(Reference Lokesh, Ghislain and Reyrolle4). Briefly, frozen intestinal content samples (1 g) were placed in glass bottles filled with clean air zero supplied by an F-DGS air zero generator (Evry). These bottles were connected to heated inlet line (100°C) of the SIFT-MS instrument via the sample inlet. To compensate for the dispersion in the bottle during SIFT-MS sampling, a Tedlar bag (Zefon International Inc.) filled with dry and clean zero air was connected to the bottle inlet. The closed bottle was incubated at 60°C ± 2 for 2 h before SIFT-MS analysis.
Full-scan mass spectra were recorded for each positive precursor ion (H3O+, O2 &x25CF;+ and NO+) in a m/z range from 15 to 250 with an integration time of 60 s. Quantification was performed using the NO+ precursor ion as described before(Reference Ghislain, Costarramone and Sotiropoulos37,Reference Ghislain, Costarramone and Pigot38) .
Electron microscopy
Electron microscopic examinations were carried out at the Bordeaux Imaging Centre – University of Bordeaux, a core facility of the French network ‘France Bio Imaging’. The processing and sectioning of the samples have been described in detail previously(Reference Lokesh, Ghislain and Reyrolle4). Mid-intestinal tissue samples were fixed with 2·5 % (v/v) glutaraldehyde in 0·1 M phosphate buffer (pH = 7·4) for 2 h before being stored at 4°C. Samples were then washed in phosphate buffer and fixed in 1 % (v/v) osmium tetroxide in 0·1M phosphate buffer for 2 h in the dark (RT) and then washed. Then the samples were dehydrated and embedded in epoxy resin using the automated microwave tissue processor for electron microscopy (Leica EM AMW; Leica Microsystems). After polymerisation, the samples were cut with a diamond knife (Diatome) on an ultramicrotome (EM UCT, Leica Microsystems). After localisation of the regions of interest, ultrathin sections (70 nm) were picked up on copper grids and subsequently stained with UranyLess and lead citrate. The grids were examined with a transmission electron microscope (H7650, Hitachi) at 80 kV.
Gene expression analysis
RNA from liver, intestine and muscle was extracted using the TRIzol reagent method (Invitrogen) according to the manufacturer’s protocol. RNA from the adipose tissue was extracted using the RNeasy lipid tissue mini kit according to the manufacturer’s instructions (Qiagen). The quality and quantity of the RNA were checked on a 1 % agarose gel and a nanodrop (Thermo scientific), respectively. Two µg of RNA was converted to cDNA using the enzyme superscript III reverse transcriptase and random hexamers (Invitrogen). After reverse transcription, the cDNA was diluted 50-fold before being used in RT-qPCR.
RT-qPCR was performed on a LightCycler® 384 system (Roche Diagnostics) according to the protocol described previously (including primer details)(Reference Lokesh, Ghislain and Reyrolle4). The data normalisation was performed using geNorm(Reference Vandesompele, De Preter and Pattyn39). The reference genes eef1a and rna18s were used to calculate the normalisation factor in liver and intestine, while a combination of actb and gapdh was used in muscle and actb and eef1a in adipose tissue.
Statistical analysis
Feeding efficiency, bulk fish weight and specific growth rate were measured per tank (n 3 per group). For SCFA and electron microscopy, two fish were sampled per tank (n 6 per group). All other parameters were measured on four individual fish per tank (n 12 per group).
All statistical analyses were performed using R software (version 3.6.3)(40) in combination with phyloseq (Reference McMurdie and Holmes36). The heat map was created with heatmapper (Reference Babicki, Arndt and Marcu41). All data subjected to either one-way ANOVA or two-way ANOVA were tested for normal distribution and homogeneity of variances. If the data did not meet any of these assumptions, a non-parametric Kruskal–Wallis test or a non-parametric equivalent of the factorial ANOVA (aligned rank transform ANOVA) was used.
α-diversity (observed OTU and Shannon index), β-diversity (Bray–Curtis dissimilarity index) and OTU compositions were calculated using the phyloseq package. The effects of two factors (inulin and line) on α-diversity were calculated separately for the two sample types (i.e. contents and mucus) using two-way ANOVA. For the β-diversity measures, the homogeneity of sample dispersions between groups was checked using the betadisper function of the vegan package(Reference Oksanen, Blanchet and Friendly42). Permutative multivariate analysis of variance (PERMANOVA) was used to test the significance of Bray–Curtis distance between samples belonging to different sample types (content and mucus) and to analyse the effect of the factors (inulin or line) on β-diversity in contents and mucus.
The effect of two factors (inulin and line) on the expression levels of each gene was analysed using two-way ANOVA. A similar approach was used to test the effect of experimental factors on microvilli length and SCFA levels. Based on the relative expression of the genes, a Bray–Curtis distance matrix was calculated and a group-wise comparison was performed using two-way PERMANOVA after checking the homogeneity of dispersions.
LEfSe (linear discriminant analysis effect size) was performed to identify the significant features (OTU) belonging to specific groups(Reference Segata, Izard and Waldron43). The p-values and linear discriminant analysis (LDA) score thresholds were set at 0·05 and 4, respectively. Regularised canonical correlation analysis was performed using the mixOmics package to understand the correlations between relative gene expression in different tissues and OTU abundances in content and mucus samples(Reference Rohart, Gautier and Singh44). Zero-inflated OTU data were transformed using centred log transformation (clr) before analysis. Correlations with a value above 0·45 are shown.
Results
Diet and whole-body composition, growth and plasma parameters
In the present study, the composition of the various macronutrients did not differ between the control and experimental diets (P > 0·05; online Supplementary Table 1). We also did not detect any effect of either factor (line and inulin) or the interaction between them on the proximate composition of the whole body (P > 0·05; online Supplementary Table 2). The final bulk body weight and weight gain were significantly higher (10·77 %) in suave (P < 0·05, Table 2). Similarly, there was a significant effect of line on plasma glucose (P = 0·0012) and TAG (P = 0·0026; Table 3).
Table 3. Plasma parameters in rainbow trout (temoin and suave) fed with the control diet (O) and the diet supplemented with 2 % inulin (I)
The data are presented as the mean ± sd, n 12. Means between the groups were compared using a two-way ANOVA. A P-value < 0·05 is considered as significant and is presented in bold.
Expression of different genes involved in metabolism
We investigated the expression of several genes involved in amino acid metabolism, energy metabolism, fatty acid oxidation, fatty acid conversion, gluconeogenesis, glucose transport, glycolysis, lipogenesis and SCFA uptake in different tissues.
Liver
The hepatic gene expression profile is shown in Fig. 1(a). The overall (group-wise) expression was significantly affected by line (PERMANOVA, P = 0·016) and the interaction between line and inulin (PERMANOVA, P = 0·030). Effect of factors and interaction (P < 0·05) on expression of genes in different pathways is given below.
Fig. 1. Heat map showing the relative expression of different genes involved in metabolism in (a) liver and (b) intestine of two lines (temoin and suave) of rainbow trout fed 0 % and 2 % inulin. The different feeding groups are symbolised as follows: TVO: temoin-0 % inulin; TVI: temoin-2 % inulin; SVO: suave-0 % inulin; and SVI: suave-2 % inulin. The effect of line and inulin on the expression of each gene was evaluated using two-way ANOVA. Significant effects (P < 0·05) of either factor (line or inulin) or interaction are indicated on the left panel (I: effect of inulin; L: effect of line; I × L: interaction effect). The gene names and the pathways to which they belong are shown on the right panel. Group-wise differences in expression levels of all genes were statistically tested using PERMANOVA (liver P-value: I > 0·05, L = 0·016, I × L > 0·030; intestine P-value: I = 0·001, L = 0·001, I × L > 0·05) based on the Bray–Curtis dissimilarity matrix derived using the relative expression levels and shown in the top panel.
Line: Expression of genes of amino acid metabolism (asat2 and asat3), gluconeogenesis (fbp1b1, g6pca, g6pcb1b, and g6pcb2a) and glycolysis (pfkla) was down-regulated in suave.
Inulin: Inulin-fed groups were showing an up-regulation of amino acid metabolism (alat2 and gdh3), energy metabolism (atp5a and cox4) and fatty acid oxidation (cpt1c and hoad).
Interaction: The expression of genes in amino acid metabolism (asat1), energy metabolism (cox4 and cs), gluconeogenesis (g6pcb2a) and lipogenesis (acly and g6pdh) were up-regulated in inulin-fed groups only in the suave. On the contrary, the expression of a fatty acid oxidation gene (cpt1b) was down-regulated in the suave when fed with inulin.
Intestine
The intestinal gene expression profile is shown in Fig. 1(b). The group-wise expression was significantly affected by both factors, line (PERMANOVA, P = 0·001) and inulin (PERMANOVA, P = 0·001). Effect of factors and interaction (P < 0·05) on expression of genes in different pathways is given below.
Line: The expression of genes in amino acid metabolism (asat1, asat2, asat3 and gdh2), energy metabolism (cox2, cox4, cs, qcr2 and sdhb) and glycolysis (pfkla and pfklb) were significantly down-regulated in suave.
Inulin: The expression of genes involved in amino acid metabolism (asat1, asat2, asat3, gdh2 and gdh3), energy metabolism (atp5a, cox2, cox4, cs, qcr2 and sdhb) and glucose transport (glut1ba and glut1bb) were significantly down-regulated in the inulin-fed group.
Interaction: No significant interaction effect between the inulin and the line was found.
Muscle
The gene expression profile of muscle is shown in Fig. 2(a). The overall (group-wise) expression pattern was significantly affected by line (PERMANOVA, P = 0·004). Effect of factors and interaction (P < 0·05) on expression of genes in different pathways is given below.
Fig. 2. Heat map showing the relative expression of different genes involved in metabolism in the muscle (a) and adipose (b) of two lines (temoin and suave) of rainbow trout fed 0 % and 2 % inulin. The different feeding groups are symbolised as follows: TVO: temoin-0 % inulin; TVI: temoin-2 % inulin; SVO: suave-0 % inulin; and SVI: suave-2 % inulin. The effect of line and inulin on the expression of each gene was evaluated using two-way ANOVA. Significant effects (P < 0·05) of either factor (line or inulin) or interaction are indicated on the left panel (I: effect of inulin; L: effect of line; I × L: interaction effect). The gene names and the pathways to which they belong are shown on the right panel. Group-wise differences in expression levels of all genes were statistically tested using PERMANOVA (P-value: I > 0·05, L = 0·004, I × L > 0·05) based on the Bray–Curtis dissimilarity matrix derived using the relative expression levels and shown in the top panel.
Line: The expression levels of genes in amino acid metabolism (alat2, asat3, gdh2 and gdh3), energy metabolism (atp5a, cox2, cs and qcr2), fatty acid oxidation (cpt1a and cpt1d), glucose transport (glut1bb and glut4a) and lipogenesis (fas) were significantly down-regulated in suave.
Inulin: The expression of alat2 (amino acid metabolism), cpt1a (fatty acid oxidation) and g6pdh (lipogenesis) was up-regulated in inulin-fed groups. On the other hand, the expression of a gene in glycolytic pathway (hk1) was down-regulated in inulin-fed group.
Interaction: The levels of cpt1a and cpt1b (fatty acid oxidation) was higher in inulin-fed group only in the temoin. On the other hand, fas (lipogenesis) was up-regulated in the inulin-fed suave.
Adipose
The gene expression profile of adipose tissue is shown in Fig. 2(b). Group-wise expression profile was not affected by any of the factors. Effect of factors and interaction (P < 0·05) on expression of genes in different pathways is given below.
Line: The expression of gdh2 (amino acid metabolism) was lower in suave, and the expression of cox2 (energy metabolism) and fbp1b1 (gluconeogenesis) was up-regulated in suave.
Inulin: The expression of g6pcb1a (gluconeogenesis) was down-regulated when fed inulin.
Interaction: The expression of genes of energy metabolism (atp5, cox4 and qcr2), fatty acid oxidation and conversion (hoad and fad), gluconeogenesis (fbp1b1) and lipogenesis (acly and g6pdh) was up-regulated only in inulin-fed suave.
Intestinal microbial diversity and composition
Effect of sample type on the microbial diversity and composition
We analysed the microbial diversity and composition in the two sample types, namely mucus and digestive contents (contents), separately. There was a significant effect of sample type on microbial diversity and composition. The α-diversity of the contents was significantly higher than that of the mucus (P = 0·0002). We found no significant effect of line or the inulin on α-diversity measures (observed OTU and Shannon index) in the mucus or digestive contents (P > 0·05) (Fig. 3(a)).
Fig. 3. Plot of α- and β-diversity, OTU composition and the discriminant features in the intestine of two lines (temoin and suave) of rainbow trout fed 0 % and 2 % inulin (Mycoplasma and Streptophyta OTU are filtered out). Feeding groups are symbolised as TVO: temoin-0 % inulin; TVI: temoin-2 % inulin; SVO: suave-0 % inulin; and SVI: suave-2 % inulin. (a) α-diversity measures (observed OTU and Shannon index) in different feeding groups. Measurements were performed separately for the content (C) and mucus (M) samples. There was no statistically significant effect of inulin or line on the α diversity measurement (two-way ANOVA; P > 0·05). The differences between the mucus and content samples were significant for both the observed and Shannon indexes (one-way ANOVA; P = 0·0001). (b) β-diversity calculated using the Bray–Curtis dissimilarity matrix is shown in an non-metric multidimensional scaling (NMDS) plot. Sample types (content and mucus) are colour-coded. Feeding groups are represented by different shapes (0 % inulin: sphere; 2 % inulin: triangle). There was a significant effect of sample type (mucus and contents) on sample dispersion (PERMANOVA: P = 0·0002). (c) Composition of the twenty most abundant OTU in the content (C) and mucus (M) samples. Taxonomies assigned to OTU are colour-coded (at genus level). OTU with grey colour indicate non-assignment of the taxonomy at the genus level. (d) LEfSe analysis showing the discriminant genera between the content and mucus samples (LDA score > 4). OUT, operational taxonomic unit.
PERMANOVA of Bray–Curtis distances between samples shows a significant effect of sample type (P = 0·0001), with the mucus and contents samples forming separate clusters. The individual samples are plotted in a two-dimensional space using NMDS (Fig. 3(b)).
The top twenty OTU in terms of total abundance (after removal of the genera Mycoplasma and Streptophyta) are shown in Fig. 3(c). These OTU include Bacillus, Janthinobacterium, Lactobacillus, Moraxella, Pseudomonas, Ralstonia, Singulisphaera, Sphingomonas, Streptococcus, Weissella and others. The different abundances of OTU between the mucus and the contents were analysed using LEfSe (Fig. 3(d)). The relative abundance of Firmicutes was significantly higher in the contents than in the mucus. Among this phylum, the families Lactobacillaceae (genus: Lactobacillus), Leuconostocaceae (genus: Weissella) and Streptococcaceae were the most important representatives. Phylum Planctomycetes was also a significant feature in the content, which comprised of one significant OTU in the genus Singulisphaera. On the other hand, Proteobacteria was the most abundant phylum in the mucus samples. Among this phylum, Alphaproteobacteria (genus: Sphingomonas), Betaproteobacteria and Gammaproteobacteria (genus: Pseudomonas) were found in significantly higher amounts compared with the content. In the Betaproteobacteria class, there were two significantly abundant families, including Burkholderiaceae (two OTU belonging to the genus Ralstonia) and Oxalobacteriaceae (genus: Janthinobacterium).
Effect of inulin and line on the microbial β-diversity and composition
Two-way PERMANOVA revealed that there was a significant effect of inulin and the interaction between inulin and the line on the β-diversity of the content samples (P: I = 0·026; P: I × L = 0·025) (Fig. 4(a)). In contrast, mucus samples showed no such responses (P > 0·05) (Fig. 4(b)).
Fig. 4. NMDS and bar plot showing the dispersion of the samples in a multivariate space and the discriminating features belonging to different groups in the contents. β-diversity of the (a) content samples and (b) mucus samples calculated based on the Bray–Curtis dissimilarity index are shown using NMDS plot. Feeding groups are symbolised as TVO: temoin-0 % inulin; TVI: temoin-2 % inulin; SVO: suave-0 % inulin; and SVI: suave-2 % inulin. Groups fed with different levels of inulin are colour-coded, and the lines are represented by different shapes (temoin: triangle; suave: sphere). Statistical significance of group dispersion was analysed using two-way PERMANOVA (contents P-value: I = 0·026, L > 0·05, I × L = 0·025; mucus P-value: I > 0·05, L > 0·05, I × L > 0·05). LEfSe analysis showing the discriminant genera (c) between the fish fed with either control diet (0 % inulin) or diet containing 2 % inulin and (d) between the two lines of fish (LDA score > 4).
LEfSe analysis to identify the differentially abundant groups between two dietary conditions revealed thirteen features, nine of which belonged to the control group and four to the inulin-fed group. Two phyla were significantly abundant in the control group, including Proteobacteria and Actinobacteria. Among the Proteobacteria, two families, namely Enterobacteriaceae and Pseudomonadaceae (genus: Pseudomonas), were significantly abundant (Fig. 4(c)). Significant OTU in the inulin-fed group included Weissella and Streptococcus (Fig. 4(c)). Comparison between the two lines revealed four features, three of which belonged to the temoin (genus: Pseudomonas and Brevundimonas) and one to the suave (family: Ruminococcaceae) (Fig. 4(d)).
Correlation between the operational taxonomic unit abundance and gene expression
Liver v. content OTU: The OTU belonging to Lactobacillus, Weissella and Ruminococcaceae showed a strong negative correlation with the genes involved in glycolysis, gluconeogenesis and fatty acid oxidation. Moraxella and Bacillus were showing a negative correlation with genes involved in lipogenesis, amino acid metabolism and energy metabolism (Fig. 5(a)). In contrast to the OTU belonging to Lactobacillus, Bacillus showed a positive correlation with some genes involved in glycolysis and fatty acid oxidation (Fig. 5(a)).
Fig. 5. Correlation between relative abundance of OTU found in intestinal content samples (Y-axis) and expression levels of different genes in the (a) liver and (b) intestine. (c) Correlation between relative abundance of OTU found in intestinal mucus samples (Y-axis) and expression levels of different genes in the intestine. The correlations were computed with rCCA (regularised canonical correlation analysis). Colour key shows the strength of the correlation. OUT, operational taxonomic unit.
Intestine v. content OTU: The OTU belonging to Pseudomonas was positively correlated with genes involved in many pathways, notably glycolysis, amino acid metabolism and energy metabolism. On the other hand, Streptococcus was negatively correlated with several pathways, most notable being the glucose transport, lipogenesis and amino acid metabolism (Fig. 5(b)). Planctomycetaceae, was negatively correlated with all genes, especially those involved in glycolysis (pfklb), amino acid metabolism (asat1 and asat2) and energy metabolism (cox4, cs, atp5a and sdhb) (Fig. 5(b)).
Intestine v. mucus OTU: Ralstonia, Janthinobacterium, Pseudomonas and Sphingomonas were negatively correlated with genes involved in energy metabolism, amino acid metabolism, lipogenesis, glycolysis, fatty acid oxidation, fatty acid conversion and glucose transport (Fig. 5(c)). There was a positive correlation between these OTU and one of the fatty acid oxidation genes (cpt1d) (Fig. 5(c)).
SCFA levels and microvilli length
The SCFA acetic acid, butyric acid, caproic acid, propionic acid and valeric acid were measured in the intestinal contents (Fig. 6(a)). There was a significant effect of line on the level of propionic acid (P = 0·034). In general, the level of all SCFA was higher in temoin. Within the temoin line, the levels of all SCFA were generally higher in the inulin-fed group, except for butyric acid.
Fig. 6. (a) Levels of different SCFA including acetic acid, butyric acid, caproic acid, propionic acid and valeric acid in the mid-intestinal contents of two lines (temoin and suave) of rainbow trout fed 0 % and 2 % inulin. (b) Length of intestinal epithelial microvilli (µm) in two lines (suave and temoin) of rainbow trout fed 0 % and 2 % inulin.
We observed a significant effect of both inulin and line on microvilli length (Fig. 6(b)). Microvilli were significantly longer in suave (P = 1·47e-15). On the other hand, they were significantly shorter in fish fed inulin (P = 2·22e-16).
Discussion
In the last decade, much research has been done on the diet–microbiome–host (metabolism) axis in mammals. One of the main focuses has been on the benefits of fibre-utilising bacteria and their metabolites (SCFA). In humans and livestock, a direct link has been established between dietary fibres and various metabolic processes in liver, skeletal muscle, intestine and adipose tissue(Reference Den Besten, Van Eunen and Groen45). Although there is great interest in harnessing the beneficial effects of prebiotic-derived microbial metabolites to improve aquatic animal health and metabolism, the prebiotic–microbiome–host axis is not well understood. Prebiotics such as inulin have been used in the diets of teleosts for decades, although not much is known about whether inulin has the same effect on host metabolism (via SCFA) in teleosts as it does in mammals. In addition, there is a lack of knowledge about the effects of genotype on inulin degradation and utilisation and the bacterial groups that respond to inulin in teleosts. To address this, in the present study, we investigated the metabolic effects of feeding inulin (2 %) for 16 weeks to two different lines (temoin and suave) of rainbow trout.
Growth and plasma parameters
Final body weight was significantly higher in fish selected for better utilisation of the 100 % plant-based diet (suave), as previously observed(Reference Callet, Médale and Larroquet3). The lower growth rate in naïve lines of rainbow trout fed an all-plant diet has been attributed to a combination of factors, including lower feed intake and feed efficiency(Reference Callet, Médale and Larroquet3). However, in the present study, feed acceptance and feed efficiency did not differ significantly between the two lines. It should be noted that there was a significant weight difference between the two lines before the start of the experiment. And this difference remained throughout the experiment. It was important to keep the age of the two lines the same at the beginning of the experiment, so the weight difference had to be accepted(Reference Callet, Médale and Larroquet3,Reference Le Boucher, Dupont-Nivet and Vandeputte46) . Moreover, the significant difference between the lines in weight gain also underscores the fact that these two lines naturally grow at different rates(Reference Le Boucher, Dupont-Nivet and Vandeputte46).
Inulin had no effect on growth parameters. This is interesting because inulin is known to positively affect the growth of many teleosts, including rainbow trout(Reference Ortiz, Rebolé and Velasco21,Reference Ibrahem, Fathi and Mesalhy47) . The source of inulin, the genetic background of the fish used in the experiment and the differences in basal diet could be the plausible reason for the discrepancies(Reference Song, Beck and Kim48). In addition, the species-specific microbiota and the intra-species differences in the intestinal microbial communities (observed in trout) could also lead to such discrepancies(Reference Lokesh, Ghislain and Reyrolle4,Reference Pérez-Pascual, Pérez-Cobas and Rigaudeau49) .
We found a significant difference in plasma glucose and TAG levels between the two lines. It is likely that glucose uptake is not as efficient in the suave because of its adaptation to a plant-based diet, which is generally rich in dietary fibre. Glucose uptake from the high-fibre diet is relatively slow compared with the low-fibre diet(Reference Huang, Zhao and Mao50). On the other hand, the higher TAG in temoin could be due to increased lipolysis, because carnitine palmitoyltransferase 1 was generally more highly expressed in liver and muscle of the temoin line.
Effect on the hepatic metabolism
In the liver, total group-wise gene expression was affected by line. Most of the tested genes in the different metabolic pathways showed lower expression in the suave compared with the temoin. Interestingly, selection of the fish on a plant-based diet resulted in decreased glycolysis. A higher plasma glucose level in the suave also suggests a lower availability of glucose for hepatic glycolysis. Amino acid catabolism is one of the major metabolic pathways in rainbow trout, providing substrates necessary for energy metabolism(Reference Polakof, Panserat and Soengas51). In the present study, the expression of genes responsible for amino acid catabolism was also lower in the suave. In addition, genes involved in gluconeogenesis were also less expressed in suave. Taken together, these results could possibly indicate the use of prebiotic-derived substrates (SCFA) (instead of amino acids and glucose) for energy metabolism in suave. The involvement of SCFA (acetate) instead of glucose in the production of acetyl-CoA, which is required for the tricarboxylic acid cycle, has been reported previously(Reference Shi and Tu52). Indeed, some genes (cox4 and cs) involved in energy metabolism were affected by the interaction between line and inulin (higher expression only in inulin-fed suave), further supporting this assumption.
The overall gene expression was not significantly affected by inulin, although two genes of the fatty acid oxidation pathway showed high expression in the inulin groups. Inulin (via the action of various SCFA) has been shown to increase fatty acid oxidation in humans and other animals(Reference Delzenne, Daubioul and Neyrinck53). It is known that these metabolic changes in the liver are due to the activity of acetate and propionate, because butyrate is generally preferentially taken up by intestinal cells(Reference Den Besten, Van Eunen and Groen45,Reference Frampton, Murphy and Frost54,Reference Liu, Fu and Li55) . Although we did not measure the amount of the various SCFA in plasma or liver, the amount of SCFA in the intestine was generally higher in the inulin-fed groups, suggesting a possible relationship between inulin and fatty acid oxidation. Moreover, two genes of lipogenic metabolism were induced to a higher extent in the inulin-fed fish only in suave. This suave-specific induction contradicts the anti-lipogenic effect of inulin in mammals and needs further investigation(Reference Den Besten, Van Eunen and Groen45,Reference Liu, Fu and Li55) .
Metabolic changes in the intestine
Regarding the collective expression of all tested genes in the intestine, we observed a significant effect of line and inulin. In particular, there was a strong decrease in the expression of several genes involved in amino acid catabolism and energy metabolism in suave. Rainbow trout is a carnivorous teleost. The efficient use of amino acids compared with glucose and fatty acids to meet energy requirements is already well established in this species(Reference Zhang and Davies56). The lower expression of energy metabolism genes in the suave suggests that selection on a purely plant-based diet results in changes in the mechanisms of energy homoeostasis due to reduced amino acid degradation and glycolysis. This observation contradicts what has been documented in mammals. SCFA are known to positively affect intestinal energy metabolism by introducing SCFA into the β-oxidation pathway, leading to the production of acetyl-CoA, which is used in energy metabolism(Reference Den Besten, Van Eunen and Groen45). Moreover, most of the metabolic effects in the intestine are mediated by butyrate, and intestinal butyrate levels were relatively low compared with other SCFA, suggesting that the dynamics of SCFA production and utilisation in the trout intestine may be different from those in mammals and need further investigation.
Metabolic changes in the muscle
The overall gene expression in muscle was significantly affected by line, and expression was significantly lower in suave. The major groups of genes that were down-regulated in suave include amino acid catabolism, energy metabolism and glucose transporters. Suave is reported to gain 35·3 % weight within one generation when fed a plant-based diet. Also, in the present study, weight gain was higher (10 %) in suave than in temoin, and these advantages in weight gain may be due to the sensory, morphological and metabolic changes that the selected line undergoes(Reference Le Boucher, Dupont-Nivet and Vandeputte46,Reference Luca, Perry and Di Rienzo57) . The expression pattern in the present study may be indicative of the metabolic changes undergone by this line. In contrast, the control line (temoin) fed a plant-based diet appears to metabolise the diet poorly. It is likely that energy metabolism in this group is subject to regulatory mechanisms involving molecules from fatty acid oxidation and amino acid catabolism(Reference Véron, Panserat and Le Boucher58). In addition, the higher expression of genes for fatty acid oxidation and lower lipogenesis when fed inulin may again indicate the inability of the temoin group to efficiently utilise inulin.
Inulin had no significant effect on gene expression in muscle. An essential role of prebiotics and their derivatives (SCFA) in skeletal muscle metabolism has been demonstrated in humans by increased uptake and oxidation of fatty acids and decreased lipogenesis(Reference Frampton, Murphy and Frost54). In addition, an increase in glucose uptake and retention of nitrogen (protein metabolism) has been suggested(Reference Frampton, Murphy and Frost54). In the present study, the effect of inulin on the expression of genes for fatty acid oxidation, lipogenesis and glycolysis was not evident. This counterintuitive finding may be due to the fact that muscle is not the primary site of action for SCFA in carnivorous rainbow trout. Moreover, in addition to the direct effects of SCFA, metabolites released after hepatic assimilation of SCFA are known to have effects on metabolic processes in muscle(Reference Frampton, Murphy and Frost54).
Metabolic changes in adipose tissue
There were no drastic group-wise changes in the expression of metabolic genes in adipose tissue. It should be noted that most of the genes that showed a change responded to the interaction effect of line and inulin. As observed in liver, lipogenic genes are up-regulated only in the inulin-fed group of suave. The effect of SCFA on lipogenic pathways in the adipose tissue is uncertain, as there are some studies showing a lipogenic effect of SCFA, whereas others show the opposite(Reference May and den Hartigh59–Reference Li, Yao and Jiang61). However, regardless of the effect on lipogenesis, higher levels of the fatty oxidation and energy metabolism are consistently observed(Reference den Besten, Bleeker and Gerding62,Reference Gao, Yin and Zhang63) . These observations are very similar to those observed in the present study, in which genes were up-regulated in both the lipogenic pathway and fatty acid oxidation. It is likely that the higher fatty acid oxidation is in turn related to the higher energy metabolism observed in the same group of fish. This relationship between fatty acid oxidation and energy metabolism has been documented previously(Reference Gao, Yin and Zhang63). As for adipose tissue, only the suave appears to have adapted to utilise inulin, as has been described in mammals, which may be indicative of the metabolic changes experienced by the suave as a result of selection.
Microbial mediation of prebiotic digestion
The effect of prebiotics (or dietary fibre) is mainly mediated by the intestinal microbiome via the production of metabolites such as SCFA. These microbial processes are carried out in mammals by different groups of microbes belonging to the phyla Bacteroidetes and Firmicutes(Reference Kaoutari, Armougom and Gordon64). The intestinal microbiome of rainbow trout is dominated by Mycoplasma (Reference Lokesh, Ghislain and Reyrolle4,Reference Rasmussen, Villumsen and Duchêne65) and is abundant in the mucus/epithelial samples(Reference Cheaib, Yang and Kazlauskaite66). Therefore, we separated the mucus and digestive content samples in the present study. As expected, Mycoplasma was a common group in the mucus samples, while the contents were abundant with Streptophyta (most likely of dietary origin), as the diet was entirely plant-based (online Supplementary Fig. 1). β-diversity indicated significantly different clustering of the samples depending on the sample type (either mucus or contents). Interestingly, these clusters persisted despite the removal of Mycoplasma and Streptophyta OTU, with high abundance of Ralstonia, Pseudomonas, Janthinobacterium and Sphingomonas (all belonging to Proteobacteria) in the mucus, while members belonging to Firmicutes (Lactobacillus and Streptococcaceae) and Planctomycetes (Singulisphaera) were a significant feature in the contents, indicating the adaptation of the microbes to the specific microenvironment (either mucus or contents). Together with these results, the significantly lower α diversity in the mucus compared with the contents suggests that the contents may offer a nutrient-rich niche (high fibre) and harbour a higher diversity of bacterial populations compared with the mucus. In support of this idea, a prevalence of Firmicutes in high-fibre diets has already been described in many animals(Reference Kaoutari, Armougom and Gordon64,Reference Terry, Badhan and Wang67) . Although Planctomycetes are not a known species in the intestinal microbiome of animals, this group is known to contain an enzyme repertoire required for the degradation of polysaccharides(Reference Kim, Brawley and Prochnik68), suggesting their potential role in dietary fibre utilisation.
We also analysed the effect of inulin and line on the β-diversity of the mucosal microbiome and content separately. There was no effect of line on the β-diversity of the microbiome, but an OTU belonging to the Ruminococcaceae was a significant feature in suave, indicating the adaptability of this OTU to the intestinal environment of suave. A relationship between genotype and microbial population has been described in many species, including teleosts(Reference Ahern, Whittaker and Williams69–Reference Li, Liu and Tan71). In addition, several species of Ruminococcus have been described as one of the most efficient fibre-degrading groups in ruminants(Reference Terry, Badhan and Wang67).
The significant effect of inulin was observed only in the contents further supporting the hypothesis that fibre-degrading bacteria are more abundant in the contents and that they respond more readily to dietary inulin compared with the mucosal microbiome. This type of differentiation between the mucosal and content microbiome in terms of response to dietary components has been observed previously in Atlantic salmon(Reference Li, Bruni and Jaramillo-Torres72).
Correlation between the gene expression and microbial abundance
There were negative correlations between several genes (hepatic glycolysis and gluconeogenesis) and OTU belonging to Lactobacillus. On the other hand, a positive correlation of these pathways with Bacillus OTU was observed. A similar finding has been previously reported in rainbow trout(Reference Lokesh, Ghislain and Reyrolle4). It needs to be investigated whether the abundance of Lactobacillus and Bacillus is related to the high plasma glucose levels observed in suave. Interestingly, the most abundant bacterial groups in the contents (OTU among Firmicutes) were not correlated with the expression of genes in the intestine. The OTU that were predominant in the mucosa were negatively correlated with the genes down-regulated in intestine (energy metabolism and amino acid catabolism) of suave fed with inulin. This counterintuitive down-regulation of energy metabolism genes in the intestine could be due to the uptake of SCFA by the mucosal microbiota, resulting in reduced availability of these metabolites to epithelial cells(Reference Rios-Covian, Gueimonde and Duncan73).
SCFA in intestine
It was evident that the levels of all the SCFA in general were higher in the intestinal content of temoin (especially in the inulin-fed group). This difference was significant in the case of propionic acid. It has been previously shown that the SCFA are absorbed by the intestinal cells quite rapidly after their release from the intestinal microbiome(Reference Den Besten, Van Eunen and Groen45). Presumably, the rate of absorption of the SCFA in the intestine of suave is higher due to their adaptation to a plant-based diet through selection (which is generally rich in SCFA). Measuring SCFA levels in multiple organs such as intestine, liver and blood simultaneously in the future studies would be more insightful.
SCFA receptor expression levels were not drastically modulated in any of the tissues studied. This underscores the need for a detailed study of the mechanisms involved in SCFA production, uptake by host cells and metabolism in the various organs of teleosts. Moreover, in the present study, no direct relationship can be established between the content of SCFA and their biological effect, because the measurement of SCFA in the intestine is complicated due to (1) complex molecular cross-feeding mechanisms, which in turn depend on the microbial composition(Reference Zhang and Davies56) and (2) different SCFA have different sensitivities to different SCFA receptors and are therefore preferentially utilised by different organs(Reference Priyadarshini, Kotlo and Dudeja74).
The length of the intestinal microvilli was higher in suave, and apparently this is an adaptation of the selected lineage to better nutrient absorption. This adaptation has been noted previously in several animals(Reference Caspary75). The relationship between the higher villus length and the higher weight gain in suave needs further investigation. However, we observed a decrease in microvillus length in the groups fed inulin. Although the reason for this decrease is not clear, a similar effect was observed in another carnivorous teleost, the gilthead seabream(Reference Cerezuela, Fumanal and Tapia-Paniagua76).
Conclusions and future perspectives
In summary, feeding 2 % inulin to different lines of rainbow trout has a strong effect on the expression of several metabolic genes depending on the tissue. In the liver, the expression of several metabolic pathways is influenced by the line and the interaction between line and inulin, while in the intestine, both inulin and line influence the expression of metabolic genes. The overall expression in muscle was also influenced by line. From the present study, microbial communities differed drastically in mucus and contents and line-specific and inulin-specific abundance profiles were observed only in contents. The high abundance of specific genera among Proteobacteria (in mucus) and Firmicutes (in contents) indicates their metabolic adaptation to the specific intestinal microenvironment. The high abundance of OTU among Firmicutes in fish fed 2 % inulin may indicate their ability to degrade inulin, and the genomes of these groups need to be further studied. The association of an OTU belonging to the Ruminococcaceae with the selected line (suave) is interesting, and its involvement in the better utilisation of plant ingredients in suave needs further investigation. The correlation between several members of the Firmicutes and Proteobacteria and the expression of genes involved in different metabolic pathways in both the liver and the intestine (especially gluconeogenesis in the liver and amino acid metabolism and energy metabolism in the intestine) could be indicative of the diet–microbiome–host axis and should be a focus of future research.
Acknowledgements
Imaging was performed at the Bordeaux Imaging Centre, a member of the National Infrastructure for Bioimaging in France (ANR-10-INBS-04). The authors thank Sabrina Lacomme for her TEM work on this project. The authors also thank the PEIMA fish experimental facility, Sizun, for the experimental set-up, monitoring of the experiment and sampling. The authors also thank Marianne Houssier and Michael Marchand for their help with sampling. The authors also thank Anne Surget for her help with whole-body composition analysis.
The current study was supported by the European Maritime and Fisheries Fund (FEAMP) AntiOB Grant to KR (22001230–00002811).
J. L. designed and performed the wet lab experiments and data analysis and drafted the first version of the manuscript. M. D. and R. D. performed the RNA. extraction and qPCR experiments. M. L. B. and T. P. performed the SCFA quantification. M. D-N. designed the selection and maintenance of the selected line suave. T. K., L. L. and L. G. oversaw the feeding experiments and organised the sampling. F. T. formulated and manufactured the feed. K. B-R. and S. P. conceived and coordinated the study. All authors contributed to the review of the manuscript. All authors read and approved the final manuscript.
The authors declare no conflict of interest.
Supplementary material
For supplementary material/s referred to in this article, please visit https://doi.org/10.1017/S0007114523000120
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