# Early sensory responses to plant-based diets in rainbow trout (Oncorhynchus mykiss) alevins: Impact on feeding behavior

Maud Martinat, Marie Lasserre, Elodie Baranek, Anne Surget, Anthony

Lanuque, Terrier Frédéric, Cécile Heraud, Jérôme Roy

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Maud Martinat, Marie Lasserre, Elodie Baranek, Anne Surget, Anthony Lanuque, et al.. Early sensory responses to plant-based diets in rainbow trout (Oncorhynchus mykiss) alevins: Impact on feeding behavior. Aquaculture Reports, 2025, 43, pp.102943. 10.1016/j.aqrep.2025.102943. hal-05236906

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# Early sensory responses to plant-based diets in rainbow trout (*Oncorhynchus mykiss*) alevins: Impact on feeding behavior

Maud Martinat, Marie Lasserre, Elodie Baranek, Anne Surget, Anthony Lanuque, Frédéric Terrier, Cécile Heraud, Jérôme Roy*

Université de Pau et des Pays de l'Adour, INRAE, NUMEA, Aquapôle, Saint-Pée-sur-Nivelle, 64310, France

<figure><img src="image_2.png" /></figure>

## ARTICLE INFO

**Keywords:**

First feeding

Alternative diet

Farmed fish

Sensory system

Post-prandial kinetic

## ABSTRACT

Smell and taste are key sensory modalities involved in nutrient detection and feeding behavior in fish. In rainbow trout (*Oncorhynchus mykiss*), early growth can be compromised when fishmeal and fish oil are replaced by plant-based ingredients. However, the sensory mechanisms involved in feed detection at the alevin stage remain poorly understood. This study aimed to investigate how plant-based diets affect gustatory and olfactory responses during early development, and how these changes relate to feeding behavior. A postprandial kinetic experiment was conducted from first feeding to 30 days, using two diets: a commercial-like diet (C), composed of fishmeal, fish oil, and plant ingredients, and a fully plant-based diet (V). Fish were either fasted or sampled at 20 min, 2 h, 6 h, 10 h, and 24 h post-feeding. We measured the expression of genes involved in nutrient sensing (fatty acids, amino acids, sugars), taste modalities (sweet, salty, sour, acidic, bitter, umami), and calcium signaling in the olfactory rosette and tongue. We also analyzed neurotransmitter pathways (serotonin and dopamine), appetite-regulating neuropeptides in the brain, and intestinal hormones (CCK, ghrelin). Results showed that fish fed the V diet had significantly reduced growth performance (p < 0.01) and feed intake after 30 days (p < 0.01), associated with altered sensory gene expression. In C-fed fish, nutrient and taste receptors were mainly upregulated in the tongue, while in V-fed fish, expression shifted toward the olfactory rosette. C-fed fish also showed distinct calcium signaling patterns in the tongue and higher serotonin turnover. Expression of melanocortin 4 receptors (*mc4ra*, *mc4rb*) was elevated in V-fed fish (p < 0.05), suggesting central anorexigenic signaling. Together, these results indicate that V diets disrupt early feeding responses through changes in sensory perception and neuroendocrine regulation. This highlights the importance of considering sensory cues when formulating sustainable feeds for aquaculture.

## 1. Introduction

Today, aquatic systems are increasingly acknowledged as crucial for food and nutrition security (FAO, 2024). However, more can be done to address the needs of a growing and urbanizing population. With their remarkable diversity and ability to provide essential ecosystem services, aquatic food systems present a promising solution to enhance global food security and nutrition both now and for future generations. To maximize their potential for sustainable development, a transformation of these systems is essential. Given that aquafeeds account for 60–70% of total production costs in aquaculture and are the primary contributors to the environmental impact of these activities (FAO, 2024), optimizing fish feeding strategies is essential for fostering a more sustainable and economically viable industry. In this context, developing effective

aquaculture feed formulations poses a significant challenge. Reducing reliance on fish meal (FM) and fish oil (FO), traditionally considered the gold standard of aquaculture ingredients, is crucial. Efforts are being made to substitute these ingredients with readily available plant-based alternatives in the diets of aquatic species. Over the past two decades of research (Aragão et al., 2022), plants have emerged as a vital alternative to FM and FO, providing substantial sources of proteins and lipids. However, for rainbow trout (*Oncorhynchus mykiss*), which represents the most significant freshwater production in Europe, previous studies have shown that the complete replacement of FM/FO with a plant-based diet leads to noticeable changes early on specifically during the first months of feeding (Lazzarotto et al., 2018; Baranek et al., 2023). This includes early deterioration of survival rates and a decline in growth, in contrast to trout fed with commercial diets (Lazzarotto et al.,

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: jerome.roy@inrae.fr (J. Roy).</footnote>
2018). This disruption are primarily ascribed to alterations in feeding behavior (Baranek et al., 2023; Turchini et al., 2009) that exert a pro-found impact on fish throughout their entire life cycle which specifically exhibit often reduced food intake (Torstensen et al., 2008).

In general, fish exhibit feeding rhythms that can vary based on a range of factors. These fluctuations in appetite are of great interest to fish farmers, as they influence when food is consumed and when it is wasted. Therefore, optimizing food consumption is crucial for promot-ing growth, ensuring health, and maximizing survival rates in farmed fish, especially in aquaculture settings. Like other animals, farmed fish utilize universal mechanisms to regulate the key stages of food intake: initiation, consumption, and cessation. These processes are governed by central regulators located in the brain's feeding centers (Rønnestad et al., 2017). During life, this central nervous system will continuously shape the neural circuitry necessary to integrate sensory information and orchestrate an integrated feeding response. The acquisition of this feeding response originates from two sensing complex network systems of nutrient-sensing pathways: the olfactory (Kermen et al., 2013) and gustatory systems (Amodeo et al., 2018) which will transmit sensory signals in central system via sensory afferent nerve fibres. In mammals but also in fish, environmental factors that influence the establishment and functioning of food intake regulation, can come from a phenotypic trait that can be acquired during life. Indeed, the complex processes that govern taste and smell and hence the palatability of foodstuffs can be subject to adaptation acquired during early life experiences of the in-dividual (acquisition of knowledge of food and its reward value) (Ventura and Worobey, 2013; Birch, 1999). Moreover, the regulation of food intake in farmed fish can be affected by appetite-related factors such as cravings, hedonic perception, and the pleasurable sensations experienced after eating, all of which can be influenced by feed composition (Soengas et al., 1999). When alternative plant ingredients are incorporated into aquafeed formulations, one potential drawback is the alteration of the diet's nutrient profile, which can impact fish feeding behavior. Several studies have shown that dietary nutrient content significantly influences the feeding behavior of farmed fish, as high-lighted in a recent review (Soengas et al., 1999). In the current context, where minimizing the environmental impact of aquaculture is a top priority, it is essential to understand the mechanisms involved in nutrient detection that can affect the feeding behavior of farmed fish, particularly at early life stages during early life experiences of the in-dividual. This understanding is crucial for improving the composition and effectiveness of plant-based diets compared to those containing FM/FO. However, to the best of our knowledge, the characterization of nutrient detection mechanisms and their regulation concerning dietary composition at early stages has yet to be reported in trout.

Recently, we made an important discovery by showing that the absence of FM/FO in the diet for eight months (Baranek et al., 2023) or just after one single meal (Baranek et al., 2024) leads to notable changes in fatty acid detection in trout. This highlights the critical role of the nutrient detection mechanism as a complex system that regulates feeding behavior in farmed fish. However, it is important to emphasize that the observed results reflect the acute or chronic effects of this regimen (whether from a single meal or an eight-month diet) on the nutrient detection system of juvenile trout. Consequently, this limits our ability to fully understand how the early development of the nutrient detection system in alevins trout may influence long-term phenotypic traits, which in turn could affect their feeding behavior and breeding performance.

In this way, the aim of the present study was to evaluate the impact of the first month of feeding with a plant-based diet (referred as V diet), in comparison to a commercially formulated diet (containing FM, FO and alternative plant ingredient, referred as C diet) on alevins trout nutrition detection mechanism. To achieve this, one month after examining the breeding parameters, we conducted a post-prandial kinetic experiment to investigate the expression patterns of several nutrient receptors, including those for fatty acids, amino acids, carbohydrates, and flavor

receptors (acid, bitter, sour, sweet, and umami). We also explored their associated signaling pathways, including in the trout's olfactory rosette (calcium pathways) and tongue (calcium and indolamine/catechol-amine pathways) following a single meal (C or V diet). The experiment covered several time points, encompassing measurements before the meal (after a 3 days fasting period), as well as 20 min, 2, 6, 10 and 24 h after the meal. Additionally, we characterized the expression patterns of genes encoding neuropeptides that regulate appetite in the brain, as well as selected intestinal hormones in the gut that also influence feeding behavior. This comprehensive analysis of the critical first feeding stage in alevin trout will provide valuable insights into the regulatory mechanisms governing food detection in farmed fish.

## 2. Materials and methods

### 2.1. Ethics statement

The trial was conducted according to the guidelines of the National Legislation on Animal Care of the French Ministry of Research (decree no. 2013-118, 1 February 2013) and in accordance with European Union legal frameworks relating to the protection of animals used for scientific purposes (i.e. Directive 2010/63/EU). The trial was conducted at the INRAE's NuMeA facilities (https://doi.org/10.15454/GPYD-AM38) and approved by the ethical committee (C2EA-73) of INRAE "Comité d'éthique Aquitaine poissons oiseaux" (INRAE agreement no. 21699, 19 December 2019). All efforts were made to minimize the number of fish used and their suffering. The scientists in charge of the trial received training and personal authorization.

### 2.2. Experimental diets design

Diets were manufactured at INRAE's experimental facilities at Don-zacq (permit no. A40-228.1, Landes, France) using a twinscrew extruder (BC 45, Clextral, Firminy, France) after formulated using Allix® software (A-Systems, City, France). The pellets had a diameter of 1 mm and a length of 1 mm. Details about the ingredients and composition of the experimental diets are given in Table 1 and the proportions of the main fatty acid and amino acid in the diets in Tables 2 and 3 respectively. The experiment was conducted with two different experimental diets: a commercial-like diet (C diet) containing a mix of FM (32%), FO (11.4%) and plant ingredients, and a plant-based diet (V diet), completely free from FM and FO, which were replaced by a blend of plant ingredients 23.3% of soybean meal and 25.5% of peas and corn gluten to replace FM and 8% of palm oil and 4% of linseed oil to replace FO). This vegetal oil blend in V diet was chosen in order to achieve a similar proportion of fatty acid classes as found in C diet. For V diet, DHA and EPA (present in FO for C diet) was replaced to the benefit of ALA by adding linseed oil (4%).

Diets were isoenergetic (c. 24.37 and 24.33 $kJg^{-1}$ for C and V diet respectively) and were formulated to cover the nutritional requirements of the trout (The National Research Council NRC, 2011). Diets were also isoproteic (53.4% ± 1.59% dry matter) and close to be isolipidic (18.82% ± 2.53% dry matter). The ω-3 PUFA content was standardized between diets in terms of total proportion (23.8% for the C diet and 26.6% for the V diet, Table 2). In terms of the overall composition of the diets, these percentages corresponded to 4.05% and 4.53% of the total diet, respectively, but consisted mainly of EPA, ALA and DHA in the C diet and ALA in the V diet. This amount of ω-3 FA class was chosen in order to be close to the proportions of ω-3 FA classes found in traditional diet of trout rich in FM/FO (more than 80% of aquafeed composition) (Lazzarotto et al., 2018) in line with our recent findings on the topic (Martinat et al., 2025; Fernández-Maestú et al., 2025). In order to avoid exceeding anti-nutrient threshold levels, we used a blend of wheat gluten, soybean meal and whole wheat, corn gluten meal, soy protein and peas as protein sources. L-lysine, L-methionine, dicalciumphosphate and soy-lecithin were added to all diets to correct the deficiency in
<table><caption>**Table 1**
Ingredients and composition of the experimental diets.</caption><thead><tr><th rowspan="2">Ingredient (%)</th><th colspan="2">DIET</th></tr><tr><th>Commercial-like (C) diet</th><th>Plant-based (V) diet</th></tr></thead><tbody><tr><td>Fish meal</td><td>32.0</td><td>0.0</td></tr><tr><td>Soybean meal</td><td>9.0</td><td>23.3</td></tr><tr><td>Peas Lysamine protein concentrate</td><td>17.7</td><td>25.5</td></tr><tr><td>Corn gluten</td><td>11.9</td><td>25.6</td></tr><tr><td>Extruded whole wheat</td><td>8.6</td><td>2.0</td></tr><tr><td>Gelatinized wheat starch</td><td>2.2</td><td>0.0</td></tr><tr><td>Sunflower lecithin</td><td>0.0</td><td>3.0</td></tr><tr><td>L-Lysine</td><td>0.0</td><td>1.0</td></tr><tr><td>L-methionine</td><td>0.4</td><td>1.0</td></tr><tr><td>CaHPO<sub>4</sub>·2H<sub>2</sub>O</td><td>0.0</td><td>1.5</td></tr><tr><td>Mineral premix<sup>a</sup></td><td>1.5</td><td>1.5</td></tr><tr><td>Vitamin premix<sup>b</sup></td><td>1.5</td><td>1.5</td></tr><tr><td>Fish oil</td><td>11.40</td><td>0.0</td></tr><tr><td>Rapeseed oil</td><td>3.80</td><td>1.80</td></tr><tr><td>Palm oil</td><td>0.0</td><td>8.30</td></tr><tr><td>Linseed oil</td><td>0.0</td><td>4.00</td></tr><tr><td>Composition (% of dry matter)</td><td></td><td></td></tr><tr><td>Dry matter (in % of diet)</td><td>94.47</td><td>96.03</td></tr><tr><td>Crude protein</td><td>54.54</td><td>52.29</td></tr><tr><td>Crude lipid</td><td>17.03</td><td>20.61</td></tr><tr><td>Ash</td><td>9.96</td><td>7.24</td></tr><tr><td>Energy (kJ·g<sup>-1</sup>, DM)</td><td>24.37</td><td>24.33</td></tr></tbody></table>

<sup>a</sup> Mineral premix: (g or mg kg<sup>-1</sup> diet): calcium carbonate (40 % Ca), 2.15 g; magnesium oxide (60 % Mg), 1.24 g; ferric citrate, 0.2 g; potassium iodide (75 % I), 0.4 mg; zinc sulphate (36 % Zn), 0.4 g; copper sulphate (25 % Cu), 0.3 g; manganese sulphate (33 % Mn), 0.3 g; dibasic calcium phosphate (20 % Ca, 18 % P), 5 g; cobalt sulphate, 2 mg; sodium selenite (30 % Se), 3 mg; KCl, 0.9 g; NaCl, 0.4 g (UPAE, INRAE).

<sup>b</sup> Vitamin premix (IU or mg kg<sup>-1</sup> diet): retinol acetate, 55,000 IU; cholecalciferol, 2500 IU; DL-α-tocopherol acetate, 50 IU; sodium menadione bisulfate, 10 mg; thiamin-HCl, 1 mg; riboflavin, 4 mg; niacin, 10 mg; D-calcium pantothenate, 20 mg; pyridoxine-HCl, 3 mg; D-biotin, 0.2 mg; folic acid, 1 mg; cyanocobalamin, 10 µg; L-ascorbyl-2-polyphosphate, 50 mg; myo-inositol, 0.3 g; choline, 1 g (UPAE, INRAE).

essential amino acids, phosphorous and phospholipids. Mineral and vitamin premix were also added to each diet.

## 2.3. Proximate Composition

Nutrient compositions of the diets, crude protein and lipids, gross energy, ash and starch content and fatty acid profiles were analyzed as previously described (Baranek et al., 2023) and following Official Methods of Analysis of AOAC INTERNATIONAL (Latimer et al., 2023). Briefly, the nutrient composition of the diets was analyzed after 24 h of drying at 105°C. Gross energy was determined using an adiabatic bomb calorimeter (IKA, Heitersheim Grißheimer, Germany). Ash content was measured by combustion in a muffle furnace (550°C for 8 h). Crude protein was quantified using the Kjeldahl method (Kjeldahl, 1883) and crude lipids using the Soxhlet method. Fatty acid profiles were measured gravimetrically according to the Folch method (Folch et al., 1957) using dichloromethane/methanol mixture (2/1).

## 2.4. Experimental design

The female (genetically all female) alevins trout came from the same parental stock (INRAE Fish Farm of Lees-Athas, permit no. A64.104.1, Aspe valley, France). Swimming fry with an initial body weight of 108 ± 0.1 mg were transferred in a raceway system at the INRAE's facilities of Donzacq (permit no. A40-228-1, Landes, France) for the feeding trial. Fingerlings were randomly allocated to five tanks per dietary treatment, with 150 fish per tank, this number to minimise the influence of tank size on feeding behaviour. Water flow was set to ensure

<table><caption>**Table 2**
Fatty acid composition of experimental diets (% of total fatty acids).</caption><thead><tr><th rowspan="2"></th><th colspan="2">Diet</th></tr><tr><th>Commercial-like (C) diet</th><th>Plant-based (V) diet</th></tr></thead><tbody><tr><td>C14:0</td><td>4.8</td><td>0.3</td></tr><tr><td>C15:0</td><td>0.5</td><td>0.1</td></tr><tr><td>C16:0</td><td>15.7</td><td>15.5</td></tr><tr><td>C17:0</td><td>0.5</td><td>0.1</td></tr><tr><td>C18:0</td><td>3.4</td><td>3.9</td></tr><tr><td>C20:0</td><td>0.3</td><td>0.3</td></tr><tr><td>C22:0</td><td>0.0</td><td>0.2</td></tr><tr><td>C24:0</td><td>0.0</td><td>0.0</td></tr><tr><td><strong>Sum of saturated fatty acids</strong></td><td><strong>25.1</strong></td><td><strong>20.3</strong></td></tr><tr><td>C16:1 ω-7</td><td>5.7</td><td>0.2</td></tr><tr><td>C18:1 ω-9</td><td>27.6</td><td>28.8</td></tr><tr><td>C20:1 ω-9</td><td>2.2</td><td>0.3</td></tr><tr><td>C22:1 ω-9</td><td>1.6</td><td>0.0</td></tr><tr><td><strong>Sum of MUFAs</strong></td><td><strong>37.1</strong></td><td><strong>29.2</strong></td></tr><tr><td>C18:2 ω-6 (LA)</td><td>10.5</td><td>23.8</td></tr><tr><td>C18:3 ω-6</td><td>0.2</td><td>0.0</td></tr><tr><td>C20:2 ω-6</td><td>0.1</td><td>0.0</td></tr><tr><td>C20:4 ω-6 (ARA)</td><td>0.7</td><td>0.0</td></tr><tr><td><strong>Sum of ω-6 LC-PUFAs</strong></td><td><strong>11.6</strong></td><td><strong>23.8</strong></td></tr><tr><td>C16:4 ω-3</td><td>1.2</td><td>0.0</td></tr><tr><td>C18:3 ω-3 (ALA)</td><td>3.7</td><td>26.6</td></tr><tr><td>C18:4 ω-3</td><td>1.5</td><td>0.0</td></tr><tr><td>C20:4 ω-3</td><td>0.3</td><td>0.0</td></tr><tr><td>C20:5 ω-3 (EPA)</td><td>6.4</td><td>0.0</td></tr><tr><td>C21:5 ω-3</td><td>0.1</td><td>0.0</td></tr><tr><td>C22:5 ω-3</td><td>0.8</td><td>0.0</td></tr><tr><td>C22:6 ω-3 (DHA)</td><td>9.4</td><td>0.0</td></tr><tr><td><strong>Sum of ω-3 LC-PUFAs</strong></td><td><strong>23.8</strong></td><td><strong>26.6</strong></td></tr><tr><td><strong>Sum of ω-3 (EPA + DHA)</strong></td><td><strong>15.8</strong></td><td><strong>0.0</strong></td></tr><tr><td>ω-3 (DHA + EPA) / ω-6</td><td>1.4</td><td>0.0</td></tr></tbody></table>

<table><caption>**Table 3**
Amino acid composition of experimental diets (% of dry matter).</caption><thead><tr><th>Amino acids</th><th>Commercial-like (C) diet</th><th>Plant-based (V) diet</th></tr></thead><tbody><tr><td>Alanine</td><td>2.84</td><td>2.67</td></tr><tr><td>Arginine</td><td>3.12</td><td>3.06</td></tr><tr><td>Aspartatic acid</td><td>4.43</td><td>4.18</td></tr><tr><td>Cysteine</td><td>0.52</td><td>0.61</td></tr><tr><td>Glutamatic acid</td><td>7.87</td><td>8.76</td></tr><tr><td>Glycine</td><td>2.23</td><td>1.66</td></tr><tr><td>Histidine</td><td>1.16</td><td>1.1</td></tr><tr><td>Isoleucine</td><td>2.3</td><td>2.3</td></tr><tr><td>Leucine</td><td>4.33</td><td>5.01</td></tr><tr><td>Lysine</td><td>3.14</td><td>3.21</td></tr><tr><td>Methionine</td><td>1.43</td><td>1.71</td></tr><tr><td>Phenylalanine</td><td>2.34</td><td>2.61</td></tr><tr><td>Proline</td><td>2.5</td><td>2.92</td></tr><tr><td>Serine</td><td>2.16</td><td>2.3</td></tr><tr><td>Threonine</td><td>1.91</td><td>1.72</td></tr><tr><td>Tryptophane</td><td>0.47</td><td>0.42</td></tr><tr><td>Tyrosine</td><td>1.66</td><td>1.8</td></tr><tr><td>Valine</td><td>2.45</td><td>2.29</td></tr></tbody></table>

a dissolved oxygen concentration greater than 90 % of saturation. Fish were exposed to natural photoperiod condition and the water temperature was set at 17 ± 1°C. During the trial, the water conditions were as follows: dissolved oxygen was measured at 9 mg L<sup>-1</sup>, ammonia levels were below 0.01 mg L<sup>-1</sup>, nitrite levels below 0.04 mg L<sup>-1</sup> and nitrate concentration was approximately 17 ppm. The flow rate in each tank was 0.3 L/s, resulting in a complete water renewal of each tank 6 times per hour. During 30 days, all fish were fed by hand eight a day with C or V diet, until apparent satiety. After this, fish were starved during 3 days to obtain control condition (exclude feeding effect) and observe the postprandial regulation of feed intake by a meal. Afterwards, the trout were fed once either the C diet or the V diet.

At the end of the trial fish biomass and the quantity of feed distributed per tank were measured to calculate mean body weight and mor-
tality rates (%), estimated daily food intake (in units per day), and estimated feed efficiency, as calculated below. For food intake, due to the difference in body weight between the two diets throughout the trial (Fig. 1), these values were expressed per kg metabolic body weight (MBW) per day. MBW was calculated as the geometric mean body weight, as previously described (Baranek et al., 2023; Saravanan et al., 2012).

$$Growth = \frac{Wf}{NBf}$$

$$Feed intake = \frac{Feed distributed}{\left(\frac{Biomass+Wi}{2}\right)} 0.75/1000*30(days)$$

$$Feed efficiency = \frac{(Biomass + Wd) - Wi}{Feed distributed}$$

Wf: Final weightNBf: Final number of fishWi: Initial weightWd: Death weight

For tissue sampling, fish were first anesthetized by immersing them in a benzocaine solution (30 mg/l) and euthanized in a bath containing 60 mg/l of benzocaine. tongue, olfactory rosette, brain and gut were sampled before the single meal (T0) as well as 20 min (T20'), 2 h (T2), 6 h (T6), 10 h (T10), and 24 h after the single meal (T24). To minimize stress on the fish during sampling, we employed all five tanks per diet, thus avoiding the need to repeatedly sample the same tank six times for each timing point.

## 2.5. Total RNA isolation and real-time quantitative PCR

Total RNA was isolated from the tongue, olfactory rosette, whole brain and gut (n = 8 per dietary treatment) using the TRIzol® reagent (Invitrogen, Carlsbad, CA, USA) with Precellys® 24 (Bertin Technologies, Montigny-le-Bretonneux, France) in accordance with the instructions of the manufacturer, as previously described (Roy et al., 2023). The quantities of extracted RNA were measured using a spectrophotometer (ND-1000, Nanodrop, Thermo), and the quality of extracted RNAs was estimated using the 260 nm:280 nm OD ratio (purity of DNA and RNA) and 260 nm:230 nm OD ratio (purity of solution, to avoid phenol contamination). For gene-expression analysis, only total RNA with a 260 nm:280 nm OD ratio exceeding 1.8 and a 260 nm:230 nm OD ratio exceeding 2.0 were utilised. Two micrograms of total RNA were reverse-transcribed into cDNA using the Super-Script III RNAse H-Reverse transcriptase kit (Invitrogen) and random primers (Promega, Chartonniéres-les-Bains) (Table 3) according to the manufacturer's recommendations. The LightCycler® 480 system (Roche Diagnostics) was used to measure mRNA levels via real-time quantitative PCR (RT-qPCR). The reaction mixture was 6 µl and consisted of 2 µl of diluted cDNA (1:10), 0.24 µl of each primer (10 µmol/l), 3 µl of Light-Cycler® 480 SYBR Green I Master mix and 0.52 µl of DNAse/RNAse-free water (5 Prime GmbH). Thermal cycling was initiated with incubation at 95°C for 10 min for the initial denaturation of the cDNA and hot-start Taq-polymerase activation, followed by 45 cycles of a two-step amplification program (15 s at 95°C; 10 s at 60°C). Cycle thresholds greater than 32 cycles were not considered. Melting curves were controlled systematically (temperature gradient: 1.1°C/15 s from 65°C to 97°C) at

<figure><img src="image_3.png" /><figcaption>Fig. 1. Zootechnical parameters of rainbow trout fed a commercial-like (C) or plant-based (V) diet from first feeding to one month. Comparison of body weight (g), mortality rate (%), feed intake (g feed/kg$^{0.8}$ d$^{-1}$), and feed efficiency (g of BW/g of feed) for trout fed the C or V diet from first feeding to 30 days. An asterisk indicates a significant difference between the dietary treatments as determined by Welch Two Sample t-test (p < 0.05). Results are expressed in g as means ± SEM (n = 5 tanks).</figcaption></figure>
the end of the last amplification cycle to ensure that only one fragment was amplified. During a run, each sample was deposited twice, and two negative controls were added: a pool of samples without reverse transcriptase and a pool of samples without cDNA. The sequences of amplicons had been previously assessed via sequencing (Baranek et al., 2023, 2024).

Data were extrapolated from standard curves and normalized to the housekeeping elongation factor 1α gene (eef1α) for data from olfactory rosette, brain, and gut, and keratin 8b gene (krt8b) for data from tongue. Relative expression of the target genes was determined using the

<table><caption>**Table 4**

Nucleotide sequences of the PCR primers used to evaluate mRNA abundance of transcripts by real-time quantitative PCR.</caption><thead><tr><th>Transcript</th><th>Forward Primer</th><th>Reverse Primer</th><th>Accession Number</th><th>Efficiency (R<sup>2</sup>)</th></tr></thead><tbody><tr><td><strong>Reference</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>eef1a1</td><td>TCCTCTTGGTCGTTTCGCTG</td><td>ACCCGAGGGACATCCTGTG</td><td>ENSOMYG00000038328</td><td>1.91</td></tr><tr><td>krt8b</td><td>TGGCTACTCCAGTGGTTTCG</td><td>CCGCTACCGGAGCTGTAGTT</td><td>ENSOMYG00000057091</td><td>1.87</td></tr><tr><td><strong>fatty acid receptors</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>ffar1</td><td>ACTGTTGCACCTGAGTCTGG</td><td>GCTGGTCCTGGGTGAAGTTC</td><td>ENSOMYG00000041396</td><td>1.76</td></tr><tr><td>ffar2a1a</td><td>CCGAGTTCCTCTGCTCCATC</td><td>TAGGTGATGGGGAAGGCAAC</td><td>ENSOMYG00000004986</td><td>1.76</td></tr><tr><td>ffar2a2</td><td>GACAACTTCACCCAGGAGCA</td><td>AGCAGAACACACAGGCCAG</td><td>ENSOMYG00000030315</td><td>1.86</td></tr><tr><td>ffar2b1.1</td><td>TTTTCCACACACAGTTGGCC</td><td>AGGTAGTGTTGTCGGCATCT</td><td>ENSOMYG00000041393</td><td>1.95</td></tr><tr><td>ffar2b1.2</td><td>GTGTGGCCTTCCTCCTATCAGA</td><td>GCAGGGCACAATGTACACAA</td><td>ENSOMYG00000041387</td><td>1.77</td></tr><tr><td>ffar2b2a</td><td>CCCATCCAACACTCGCTGAA</td><td>GTGATGACGACGATGCTCAGG</td><td>ENSOMYG00000030493</td><td>2.21</td></tr><tr><td>ffar2b2b1</td><td>TGACCGCAATCAGTGTCGAA</td><td>CCCAGAAGAAGACGCTAGCC</td><td>ENSOMYG00000030500</td><td>1.85</td></tr><tr><td>ffar2b2b2</td><td>GTCCAGTACCATCAACGCCA</td><td>CTGCACACTCTCCAACAGGGT</td><td>ENSOMYG00000005604</td><td>1.75</td></tr><tr><td>cd36</td><td>CCTGCTCTCCAAAATCCACG</td><td>TATAGTCCCGTTTCGCCAGTC</td><td>ENSOMYG00000030873</td><td>2.04</td></tr><tr><td>slc27a1</td><td>GGGCTACATGTACTTCCGGG</td><td>CCAGCAGACCACTCAGTGTT</td><td>ENSOMYG00000012230</td><td>2.04</td></tr><tr><td>slc27a4a</td><td>GAAACATTGTTGGCGTGGGG</td><td>TCGTGCAGTTGTACTTGCA</td><td>ENSOMYT00000042886.1</td><td>2.01</td></tr><tr><td>slc27a4b</td><td>CACCATTTCCAACGCCAAGG</td><td>GTCCCCTGAACACAGCATCT</td><td>ENSOMYG00000030841</td><td>1.94</td></tr><tr><td>gpr84</td><td>CTCCTCCACCACCTCTTCAG</td><td>TCAGCAATGTTCAGCAGCAG</td><td>ENSOMYG00000019195</td><td>2.14</td></tr><tr><td>gpr119</td><td>TCAGTTGATGCGCAGGAAGG</td><td>GTGCATCAGGAGTAGCGGTT</td><td>ENSOMYG00000030815</td><td>1.91</td></tr><tr><td><strong>amino acid / sweet receptors</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>casr</td><td>CCTCATCGCCAAACCAGAGT</td><td>TGGTCTGAAACTGGTGCTCC</td><td>ENSOMYG00000047418</td><td>1.89</td></tr><tr><td>gprc6a</td><td>AGTGCAAGTTCCCCTCGTTT</td><td>CGTCACTGCCTATCACTCCC</td><td>ENSOMYG00000014183</td><td>1.88</td></tr><tr><td>lpar5</td><td>TGTGGCTGCTTGTGATCAAC</td><td>GGGAACTGGGATTGAAGGA</td><td>ENSOMYG00000007169</td><td>1.8</td></tr><tr><td>t1r1-1</td><td>GCTGGTGCGTTTTAACTGGA</td><td>GGCGATGCAGATGTCAAAGT</td><td>ENSOMYG000000023953</td><td>1.92</td></tr><tr><td>t1r1-2</td><td>ATCCCTCATTCTCCTGCGAAC</td><td>TCATCACCGCTGCTGACAAA</td><td>ENSOMYG00000021237</td><td>1.96</td></tr><tr><td>t1r2-a</td><td>CTGTCGCCATCACACTCATG</td><td>GCAGACTTAACAACCGGCTT</td><td>ENSOMYG00000021237</td><td>1.93</td></tr><tr><td>t1r3</td><td>CCAGATACAGAGCCAACCCA</td><td>GACCCTGAAAGCTGACCTCT</td><td>ENSOMYG00000012034</td><td>1.88</td></tr><tr><td><strong>flavours receptors</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>tasr2r4</td><td>TGTTTTCCTGCACCTCTCCA</td><td>ACTGCTCAGCCACACATACA</td><td>ENSOMYG00000012237</td><td>1.96</td></tr><tr><td>otop1</td><td>GAGACCCCGAGCAAGAAGAG</td><td>GTTCATGGGCACGGCAAAAT</td><td>ENSOMYG00000046532</td><td>1.88</td></tr><tr><td>asic1a</td><td>GAGCAGCTCTGAGTCTGGAG</td><td>TGTGCTGGATGGTGAGGAAG</td><td>ENSOMYG000000062884</td><td>2.05</td></tr><tr><td>grm4a</td><td>CCATTTCATCTGGGTGGGCT</td><td>CCTCTGATGGACTGGCGTTT</td><td>ENSOMYG00000030638</td><td>1.88</td></tr><tr><td>grm4b</td><td>GCCGACACCTACAGCTGTAA</td><td>AACTCCACTCCAGCTTGACG</td><td>ENSOMYG00000042365</td><td>1.89</td></tr><tr><td><strong>calcium signaling pathways</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>cpla2a</td><td>CGTGGCTGGACTTTCTGGAT</td><td>GCTCACACACCTCATCAGCT</td><td>ENSOMYT00000110702.1</td><td>1.91</td></tr><tr><td>plcb3</td><td>ATAGTGGACGGCATCGTAGC</td><td>TGTGTCAGCAGGAAGTCCAA</td><td>ENSOMYG00000038153</td><td>2.13</td></tr><tr><td>plcb4</td><td>CCGAGGCGTCTGAGGATAAC</td><td>GTAGGGGTGGATGTTGGTGG</td><td>ENSOMYG000000018058</td><td>2.2</td></tr><tr><td>itpr3</td><td>TACCTGCGACTACTCTGCCT</td><td>AATGATGATTGCAGGGCCCA</td><td>ENSOMYT00000051670.1</td><td>2.03</td></tr><tr><td>stim1a</td><td>GAACCTTGACCCCAGCATCA</td><td>GGAGATTGCAGAGTACCGGG</td><td>ENSOMYG00000038250</td><td>2.01</td></tr><tr><td>stim1b</td><td>CGGACGTGTACAACTGGACA</td><td>CCTTCCGTCCAGATTGTGCT</td><td>ENSOMYG00000011142</td><td>2.08</td></tr><tr><td>oral1a</td><td>CTATGGTGAGGTGCAGCTG</td><td>TCATCAGGGCGAAAAGGTGC</td><td>ENSOMYG00000005009</td><td>2.13</td></tr><tr><td>oral1b</td><td>TGAAGGCTTCCAGTCGAACG</td><td>GGCACTGAAGGCAATGAGGA</td><td>ENSOMYT00000069145</td><td>1.99</td></tr><tr><td>oral2a</td><td>TGCTGCTCTGCTGGATCAAG</td><td>GGGGCCACTACAGTTCACCTT</td><td>ENSOMYG00000041809</td><td>1.96</td></tr><tr><td>atp2a3a (SERCA3a)</td><td>GCTGTTATCACCACTGCCT</td><td>AGATGACAGAAGTGCGAGCCC</td><td>ENSOMYT00000017316</td><td>1.99</td></tr><tr><td>calmh1</td><td>CTACGGGATTGGACTGCTGG</td><td>TCTTCCCGTCGGTCTTTTC</td><td>ENSOMYT00000065284.1</td><td>2.09</td></tr><tr><td><strong>Neuropeptide</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>npya</td><td>AAGGCAGAGGTGAGTGCTGT</td><td>AGCCTGTGGCTCACTAATC AA</td><td>ENSOMYG00000006572</td><td>2.04</td></tr><tr><td>npyb</td><td>CGTATTTGTTAGCGCCTTTTC</td><td>TCATTCGATTTCTTCACTT CCA</td><td>ENSOMYG00000013012</td><td>1.9</td></tr><tr><td>agrp1</td><td>ACCAGCAGTCCTGTCTGGGTAA</td><td>AGTAGCAGATGGAGCCGAACA</td><td>ENSOMYG00000068541</td><td>2.03</td></tr><tr><td>agrp2</td><td>CCAGGAGACGGATTTTGCCAA</td><td>GAGGGGCACAGCTATCCATC</td><td>ENSOMYG00000066626</td><td>1.99</td></tr><tr><td>pomca</td><td>ACAAGATGAACCACTTCCGCT</td><td>TGAACAACGTGAGCAGTGGT</td><td>ENSOMYG00000014502</td><td>1.88</td></tr><tr><td>pomcb</td><td>AGAGCTCCACCATCTCGT</td><td>GCGCCCCCATCAAAGTCTAT</td><td>ENSOMYG0000002756</td><td>1.92</td></tr><tr><td>cartpt</td><td>ACCATGGAGAGCTCCAG</td><td>GCGCACTGCTCTCCAA</td><td>ENSOMYG00000036163</td><td>1.88</td></tr><tr><td>mc4ra</td><td>CCACAACATCATGACCACGC</td><td>AGGCAGATGAGGACGGTAGT</td><td>ENSOMYG00000010233</td><td>1.91</td></tr><tr><td>mc4rb</td><td>CGGTCCTCATCTGCCTCATC</td><td>TCCTCTTTATGTGCAGGCGG</td><td>ENSOMYG00000012402</td><td>1.98</td></tr><tr><td><strong>Intestinal hormone</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>cck</td><td>GGGTCCCGAGCCACAAGATAA</td><td>TGGATTTAGTGGTGGTGCGT</td><td>ENSOMYT00000059759.2</td><td>1.96</td></tr><tr><td>pyy</td><td>GGCTCCCGAAGAGCTGGCCAAATA</td><td>CCTCCTGGGTGGACCTCTTTCCA</td><td>ENSOMYT000000096954.2</td><td>1.93</td></tr><tr><td>lepa1</td><td>TTGCTCAAACCATGGTGATTAGGA</td><td>GTCATGCCCTCGATCAGGTTA</td><td>ENSOMYT00000056091</td><td>1.87</td></tr><tr><td>ghrl</td><td>GGTCCCTTCCACCAGGAAGAC</td><td>GGTGATGCCCATCTCAAAGG</td><td>ENSOMYG00000008000</td><td>1.94</td></tr></tbody></table>

agrp (1 and 2), agouti-related-peptide; *asic1a*, acid-sensing ion channel 1a; *atp2a3* (a), sarcoendoplasmic reticulum calcium transport ATPase (SERCA); *calmh1*, calcium homeostasis modulator 1; *cartpt*, amphetamine-related transcript; *csp*, calcium sensing receptor; *cd36*, cluster of differentiation 36; *cck*, cholecystokinin; *cpla2a*, Phospholipase A2; *ef1a*, elongation factor 1α; *ffar*, (1, 21a1, 2a2, 2b1.1, 2b1.2, 2b2a, 2b2b1, 2b2b2), free fatty acid; *ghrl*, ghrelin and obestatin prepropeptide; *gpr84*, G-protein coupled receptor 84; *gpr119*, G-protein coupled receptor 119; *gprc6a*, G protein-coupled receptor family C group 6 member A; *gmr4* (a/b), glutamate metabotropic receptor 4; *itpr3*, inositol 1,4,5-triphosphate receptor 3; *krt8b*, keratin 8b; *lepa1*, leptin 1a; *lpar5*, lysophosphatidic acid receptor 5; *pyy*, peptide YY; *mc4r* (a/b), melanocortin 4 receptor; *npy* (a, b), neuropeptide Y; *oral* (1a, 1b), *otop1*, otopetin 1; calcium release-activated calcium modulator; *plcb* (Lazzarotto et al., 2018; Baranek et al., 2023), phospholipase C-β; *stim* [1a, 1b, 2a], stromal interaction molecule; *pomc* (a, b), proopiomelanocortin; *slc27a1*, fatty acid transporter 1; *slc27a4* (a/b), fatty acid transporter 4; *t1r* (t1r1-1, t1r1-2, t1r2-a, t1r3), taste receptor type 1 (member 1, 2 and 3); *tasr2r4*, taste 2 receptor member 4;
ΔΔCT method (Pfaffl, 2001). The values for each group were expressed in fold changes relative to the T0 and presented as means ± 1 standard error of the mean (SEM) for all genes. Primer sequences used to amplify all paralog genes were previsouly validated and their accession numbers are presented in Table 3.

## 2.6. Indolamine and catecholamine release measurement using UHPLC-FL

Indolamine and catecholamine in tongue (n = 10) from standard mixtures and polar metabolite extracts were separated using UHPLC (ACQUITY H-Class PLUS System, Waters, Milford, MA, USA), equipped with a thermostatted autosampler (4°C). Metabolites were detected through a fluorescence detector (ACQUITY FLR, Waters). Waters® Empower™ Pro software was used to obtain and quantify results Table 4.

All reagents and standards were purchased from Merck KGaA (Darmstadt, Germany). All organic solvents used were gradient MS grade (ADL & Prochilab, Lormont, France). Each tongue was homogenized with Precellys® 24 (Bertin Technologies, Montigny-le-Bretonneux, France) in accordance with the instructions of the manufacturer, in 20 mM phosphate and 1 mM EDTA buffer (pH = 6.5 ± 0.05) with 1/5 (m/v) ratio. After first centrifugation (14,000 × g, 20 min, 4 °C), deproteinization of the supernatant was performed with a volume-to-volume 10% metaphosphoric acid solution. After second centrifugation (14,000 × g, 5 min, 4 °C), the supernatant was filtered with a 0.22 µm poly-vinylidene di-fluoride unit through a third and last centrifugation (14,000 × g, 5 min, 4 °C). Metabolite mixtures were stored at -20°C until analysis. Chromatographic separation was performed on a HPLC column (150 mm × 4.6 mm, i.d. 3 µm) at 30°C (Luna PFP (Aragão et al., 2022), Phenomenex, Torrance, CA, USA). The injection volume was 10 µL, and the flow rate was set at 0.4 mL/min. A quaternary solvent system was used, which consisted of (A) a 10 mM phosphate buffer (pH 4.3 ± 0.05), (B) methanol and (C) ultrapure water. The mobile phase was filtered through in-line 0.2 µm membrane filters. The following linear gradient elution was used: 0 min: 85 % A, 15 % B; 11 min: 80 % A, 20 % B; 11-14 min: 80 % A, 20 % B; 17 min: 70 % A, 30 % B; 17.1 min: 40 % A, 60 % B; 17.1-22 min: 40 % A, 60 % B; 22.1 min: 85 % A, 15 % C; 22.1-25 min: 85 % A, 15 % C; 25.1 min: 85 % A, 15 % B and 25.1-30 min: 85 % A, 15 % B. The eluate was monitored for identification and quantification using 2 sets of wavelengths. The first one, 285 nm (excitation)/355 nm (emission), was for indoles namely serotonine (5-HT) and 5-hydroxyindolacetic Acid (5-HIAA). The second one, 280 nm (excitation)/330 nm (emission), was for catecolamines namely 3,4-dihydroxyphénylalanine (L-DOPA) and homovanillic acid (HVA). Metabolites of interest were identified by comparing retention times to standards. Quantification was based on integrating peak areas and comparing them to standard calibration curves (R² > 0.995) of each metabolite of interest. Calibration curves were linear from 0.05-55 pmol per injection for each standard. Normalization was made using the total protein quantification using the bicinchoninic acid method (#BCA1-1KT, Sigma-Aldrich).

## 2.7. Statistical analysis

All statistical analyses were performed using R software (version 3.6.1; R Core Team) (R, 2023). The tank was the experimental unit for data on growth parameters and Welch Two Sample t-test was used for statistical analysis of growth parameters. In comparison individual fish were the experimental unit for data on gene expression and indolamine/catecholamine release. The sample size of eight individuals per group was selected based on previous studies on gene expression and metabolite profiling in early-stage fish (Martinat et al., 2025; Fernández-Maestú et al., 2025), and represents a balance between statistical power (using G\*Power 3.1: a statistical power of 0.89 to detect a small effect size (Cohen's d = 0.2) at a significance level of α = 0.05) and

ethical considerations for animal use. The results were calculated as means ± 1 standard error of the mean (SEM). Analyses were carried out on untransformed data as criteria for normality of distribution and homeogeneity of variances were fulfilled (Shapiro-Wilk and Levene's test, respectively). The interaction between the two factors, diets and time, were assessed using a two-way analysis of variance (ANOVA). When a significant interaction was observed, a one-way analysis of variance (ANOVA) was conducted to assess the individual effects of time after feeding between the two diets. This allowed us to specifically examine the impact of each factor in isolation and determine their respective contributions to the observed results. When appropriate, analysis was followed by Tukey's post-hoc test. All statistical analysis were presented in supplemental information 1–6 and selected results in Figs. 2–9. Differences were considered significant at p < 0.05.

# 3. Results

## 3.1. Zootechnical parameters

Fig. 1 shows the body weight, mortality rates and food intake and feed efficiency of rainbow trout fry fed with either a commercial-like diet or a completely plant-based diet, during a period of 30 days from the first feeding. At the end of the trial, the difference in mean body weight between fish fed the C vs. V diet was nearly 37% (p < 0.05): 597 mg and 493 mg, respectively. The mortality did not differ between alevins fed the C vs. V diet (2.10% ± 0.50% vs. 2.54% ± 0.30%, respectively). Food intake was significantly lower (-9.7%) for fish fed the V diet after 30 days of feeding where as feed efficiency was not different between two diets proposed.

## 3.2. Kinetic influence of the V diet on changes in fatty acid receptor gene expression in tongue and olfactory rosette in trout

The mRNA levels of free fatty acid receptor (ffar) 1 and the seven paralogs of ffar2 (Roy et al., 2023) in the tongue and olfactory rosette of trout before meal, 20 min, 2, 6, 10 and 24 h after meal varied (Fig. 2 and supplemental information 1 and 2 for tongue and olfactory rosette tissue respectively). For tongue tissue, the mRNA levels of ffar1 and ffar2a1, ffar2b1.1, ffar2b2a presented the same patterns of gene expression with up-regulation after meal (timing effect), a diet effect with up-regulation for C diet before meal and 6 h for these 4 selected ffar genes, at 20 min for ffar1 and ffar2b1.1 and 10 h for ffar1 and ffar2a2. The mRNA level of these 4 selected ffar genes were up-regulated 2 h after meal for V diet and 24 h after meal for ffar1 and ffar2a2.

For olfactory tissue, whereas no diet effect was observed for these 4 selected ffar genes, a timing effect were observed for the mRNA levels of ffar, ffar2a2 and ffar2b1.1. The mRNA level of ffar1 was up-regulated 2 h and 24 h after meal for V diet and for C diet 6 h after meal. For ffar2a2 and ffar2b1.1 the mRNA level was up-regulated 2 h after meal for C diet.

The mRNA levels of others selected fatty acid receptor in the tongue and olfactory rosette of trout before meal, 20 min, 2, 6, 10 and 24 h after meal are presented in supplemental information 2 and Fig. 3 for selected fatty acid receptor (cd36, slc27a1, slc27a4b, gpr84).

In tongue tissue, the mRNA levels of cd36, slc27a1, slc27a4b, gpr84 were up-regulated after meal (timing effect) and for V diet for slc27a4b. cd36, slc27a1, slc27a4b, gpr84 were up-regulated 2 h after meal in fish fed the V, and 10 h for slc27a. The mRNA level of cd36 and gpr84 were up-regulated for C diet before meal and 6 h after meal in fish fed the C diet respectively.

In olfactory rosette tissue, the mRNA levels of cd36, slc27a1, slc27a4b, gpr84 were up-regulated after meal (timing effect) and for V diet for cd36 and slc27a1. slc27a4b and gpr84 were up-regulated 2 h after meal in fish fed the C, and 24 h for slc27a4b for V diet.
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Relative expression of mRNA encoding free fatty acid receptors (ffar) of genes after meal in tongue and olfactory tissue. Relative gene expression measured by RT-PCR of selected free fatty acid receptors (ffar1, ffar2a1, ffar2b1.1, ffar2b2a) genes in tongue (left panel) and olfactory rosette (right panel) tissue of trout fed the C or V diet 20 min, 2, 6, 10 or 24 h after meal. Datas are expressed as group mean ± SEM; fold change 2⁻⁰⁻⁰⁵ vs before meal (T0) for all genes. Two-way ANOVA following by one-way ANOVA when the interaction is significant, Tukey's post-hoc test when appropriate; different letters indicate a significant difference (P < 0.05) between diet and time (n = 8).</figcaption></figure>
<figure><img src="image_5.png" /></figure>

(caption on next page)
**Fig. 3.** Relative expression of mRNA encoding fatty acid receptors of genes after meal in tongue and olfactory tissue. Relative gene expression measured by RT-PCR of selected fatty acid receptors (cd36, slc27a1, slc27a4b gpr84, gpr119) genes in tongue (left panel) and olfactory rosette (right panel) tissue of trout fed the C or V diet 20 min, 2, 6, 10 or 24 h after meal. Datas are expressed as group mean ± SEM; fold change 2⁻⁰·⁰⁵ vs before meal (T0) for all genes. Two-way ANOVA following by one-way ANOVA when the interaction is significant, Tukey's post-hoc test when appropriate; different letters indicate a significant difference (P < 0·05) between diet and time (n = 8).

### 3.3. Kinetic influence of the V diet on changes in amino acid receptor gene expression in tongue and olfactory rosette in trout

The mRNA levels of selected amino acid receptor in the tongue and olfactory rosette of trout before meal, 20 min, 2, 6, 10 and 24 h after meal are presented in supplemental information 1 and 2 for tongue and olfactory rosette tissue respectively and Fig. 4.

In tongue tissue, the mRNA levels of *lpar5*, *t1r1-1*, *t1r1-2*, *t1r2-a* and *t1r3* were all up-regulated after meal (timing effect) and for C diet. The mRNA levels of *lpar5*, *t1r1-1*, *t1r1-2*, *t1r2-a* and *t1r3* were all up-regulated 6 and 10 h after meal for C diet, 20 min after meal for *t1r1-2*, *t1r2-a* for C diet, before meal for *t1r2-a* for C diet and 20 min and 24 h after meal for *lpar5* for V diet.

In olfactory rosette tissue, the mRNA levels of *lpar5*, *t1r1-1*, *t1r1-2* and *t1r3* were up-regulated after meal (timing effect) and for C diet for *lpar5*, *t1r1-1* and *t1r3*. The mRNA levels of *lpar5*, *t1r1-1*, *t1r1-2*, *t1r2-a* and *t1r3* were all up-regulated 6 and 10 h after meal for C diet, 20 min after meal for *t1r1-2*, *t1r2-a* for C diet, before meal for *t1r2-a* for C diet and 20 min and 24 h after meal for *lpar5* for V diet.

### 3.4. Kinetic influence of the V diet on changes in flavour receptor gene expression in tongue and olfactory rosette in trout

The mRNA levels of selected flavour receptor in the tongue and olfactory rosette of trout before meal, 20 min, 2, 6, 10 and 24 h after meal are presented in supplemental information 1 and 2 for tongue and olfactory rosette tissue respectively and Fig. 5.

In tongue tissue, the mRNA levels of *tasr2a4* (bitter), *otop1* (sour), *grm4a* (umami), and *asic1a* (acid) were all up-regulated after meal (timing effect) and for C diet for *tasr2a4*, *otop1* and *grm4a*. The mRNA levels of *tasr2a4*, *otop1*, *grm4a* and *asic1a* were all up-regulated 6 h after meal for C diet, before meal and 20 min after meal for *tasr2a4* and *grm4*, and 20 min and 2 h after meal for *otop1*. The mRNA levels of *tasr2a4* and *asic1a* were up-regulated 2 h after meal for V diet, and 24 min after meal for *otop1*.

In olfactory rosette tissue, the mRNA levels of *tasr2a4*, *otop1*, *grm4a*, and *asic1a* were all up-regulated after meal (timing effect). The mRNA levels of *tasr2a4*, *asic1a* were up-regulated 2 h after meal for C diet. The mRNA levels of *asic1a* were up-regulated 20 min after meal for V diet and 2 h after meal for *otop1*.

### 3.5. Calcium-signaling pathway gene expression in tongue and olfactory rosette tissues

The mRNA levels of selected calcium-signaling pathway markers in the tongue and olfactory rosette of alevins trouts before meal, 20 min, 2, 6, 10 and 24 h after meal are presented in supplemental information 3 and 4 for tongue and olfactory rosette tissue respectively and Fig. 6.

For tongue tissue, the mRNA level of the two isoforms of phospholipase C β (*plcb3* and 4), *orai1a* and *stim1a* were up-regulated after meal but also for C diet. When comparing the two diets, mRNA level of *plcb3*, *plcb4* and *stim1a* gene were up-regulated in fish fed the C diet before meal, 20 min after meal for *plcb3* and *orai1a*, and 6 and 10 h after meal for *plcb4* and *orai1a*. The mRNA level of *plcb3*, *plcb4* and *stim1a* gene were up-regulated in fish fed the V diet 2 houts after meal.

For olfactory rosette tissue, the mRNA level of the *plcb3* and 4, *orai1a* and *stim1a* were up-regulated after meal but also for V diet (except for *orai1a*).

### 3.6. Indolamine and catecholamine metabolites quantification in tongue tissue

The metabolites levels of indolamine and catecholamine turnover in the tongue of trout before meal, 20 min, 2, 6, 10 and 24 h after meal are presented in Fig. 7.

For indolamine pathway metabolites, the 5-HT (serotonin) was increased after meal (timing effect) and by C diet. When comparing the two diets, fish fed the C diet had more 5-HT in tongue than fish fed the V diet before meal, 20 min and 6 h after meal. For 5-HIAA, the direct degradation product of 5-HT, the metabolite level was less quantify after meal (timing effect) and less quantify for C diet. The ratio 5-HIAA/5-HT ratio was lower after meal (timing effect) and for fish fed the C diet. When comparing the two diets, fish fed the V diet had a higher 5-HIAA/5-HT ratio than fish fed the C diet before meal until 24 h.

For catecholamine pathway metabolites, the L-DOPA (dopamine precursor) was increased after meal (timing effect) and by V diet. When comparing the two diets, fish fed the C diet had more L-DOPA in tongue than fish fed the V diet before meal and 24 h after meal where as L-DOPA was higher for fish fed the V diet 20 min and 2 h after meal. For HVA, one of the direct degradation products of L-DOPA, only a timing effect was observed (decrease). The ratio HVA/L-DOPA ratio was lower after meal (timing effect) and for fish fed the V diet. When comparing the two diets, fish fed the V diet had a higher HVA/L-DOPA ratio than fish fed the C diet before meal and 24 h after meal where as L-DOPA was higher for fish fed the C diet 20 min and 2 h after meal.

### 3.7. Neuropeptide gene expression profile in brain tissue

The mRNA levels of neuropeptide gene in the brain of trout before meal, 20 min, 2, 6, 10 and 24 h after meal are presented in supplemental information 5 and Fig. 8.

For orexigenic markers, the mRNA level of *npya* and *b* were up-regulated after meal (timing effect) and for fish fed V diet. The mRNA level of *agrp1* and 2 was up and down-regulated after meal respectively (timing effect).

For anorexigenic markers, the mRNA levels of *pomca1* and 2 and *cartpt* were up-regulated after meal (timing effect) and by V diet for *pomca1*.

For melanocortin 4 receptor, the mRNA levels of *mc4ra* and *b* were up-regulated after meal (timing effect) and by V diet. The mRNA levels of *mc4ra* were up-regulated 20 min, 10 and 24 h after meal for fish fed the V diet.

### 3.8. Intestinal hormone gene expression profile in gut tissue of trout

The mRNA levels of selected intestinal hormones gene in the gut of trout before meal, 20 min, 2, 6, 10 and 24 h after meal are presented in supplemental information 6 and Fig. 9.

The mRNA level of *cck* was up-regulated after meal and down-regulated for *lepa1* (leptin) and *ghrl* (ghrelin) (timing effect). The mRNA level of *cck* was up-regulated for C diet, and 24 h after meal compared to V diet. The mRNA level of *ghrl* was up-regulated for V diet.

## 4. Discussion

The nutrient sensing system plays a critical role in enabling individuals to differentiate between various food sources, facilitating the selection of nutritious feeds and maintaining energy homeostasis. While
<figure><img src="image_6.png" /></figure>

(caption on next page)
<caption>**Fig. 4.** Relative expression of mRNA encoding amino acid receptors of genes after meal in tongue and olfactory tissue. Relative gene expression measured by RT-PCR of selected *amino acid receptors* (*lpar5*, *tlr1r-1*, *tlr1r-2*, *tlr2a*, *tlr3*) genes in tongue (left panel) and olfactory rosette (right panel) tissue of trout fed the C or V diet 20 min, 2, 6, 10 or 24 h after meal. Datas are expressed as group mean ± SEM; fold change 2<sup>-ΔΔCt</sup> vs before meal (TO) for all genes. Two-way ANOVA following by one-way ANOVA when the interaction is significant, Tukey's post-hoc test when appropriate; different letters indicate a significant difference (P < 0.05) between diet and time (n = 8).</caption>

factors such as population density, social hierarchy, temperature, and species-specific traits can influence diet selection, the immediate attraction driven by taste remains the primary determinant of food preference in both mammals and fish (Lall and Tibbetts, 2009). In fish, this sensing system is crucial for detecting the taste of substances, which, in turn, triggers different feeding behaviors (Soengas et al., 1999). Moreover, the complex processes that govern sensing perception, and consequently the acceptance of food, can undergo adaptations based on early life experiences, such as the acquisition of knowledge about food and its reward value (Ventura and Worobey, 2013; Birch, 1999). The early developmental stages in fish are particularly critical, as they undergo significant morphological and physiological changes, including the regulation of feeding habits (Gatesoupe et al., 2001). In rainbow trout, we have previously demonstrated that nutrient detection, especially for fatty acids, is modulated after eight months of feeding on diets without fish meal FM/FO, starting from the first meal. Although these findings are groundbreaking, they reflect long-term chronic effects of the diet and do not provide in-depth insights into the early stages of nutrient detection (Baranek et al., 2024). A second study explored the nutrient detection mechanisms after a single meal in juvenile rainbow trout using kinetic experiments (Baranek et al., 2023). However, these studies primarily focus on juvenile fish, overlooking the critical early stages of feeding in alevins, which is a key phase for feed acceptance. To our knowledge, this study is the first to evaluate the impact of alternative diets to FM/FO on the nutrient sensing and signaling pathways in rainbow trout alevins during the first month of feeding.

After one month of feeding, a nearly 20 % reduction in growth was observed in fish fed the V diet, accompanied by a more than 10 % decrease in food intake. These results are consistent with our previous study, which demonstrated a reduction in final body weight after 20 and 41 days on a plant-based diet (Baranek et al., 2023). In contrast, another study reported no significant weight differences during the first month of life (Lazzarotto et al., 2018). Interestingly, while that study observed a sharp decline in survival, up to 35 % after nine weeks, beginning in the first month, we did not observe any such effects on survival in either our current or previous experiments. A key factor behind the survival differences between the studies likely stems from diet composition. As highlighted by FAO reports (FAO, 2024, 2022), ongoing improvements in alternative ingredients to FM and FO have made plant-based diets more acceptable to fish over time. The nearly 10-year gap between studies likely accounts for the improved acceptance of plant-based diets by alevins today. Advances in plant oils and raw materials have reduced anti-nutritional factors, enhancing feed quality and performance in farmed fish (FAO, 2024, 2022). Our data suggest that reduced feed intake may account for the growth deficit observed after one month and potentially over the long term, as shown in our previous studies (Lazzarotto et al., 2018, 2015; Baranek et al., 2023; Panserat et al., 2008). Examining the two main sensory pathways involved in nutrient detection and regulating feed intake reveals a link between decreased intake and impaired growth. The gustatory and olfactory sensory systems, which are among the first to detect nutrients, play a vital role in regulating feeding behavior and energy balance in fish (Kermen et al., 2013; Morais, 2017). Certain stimuli promote feed acceptance, while others trigger rejection. These sensory signals are processed and translated into specific behavioral responses, such as adjustments in feed intake (Laberge and Hara, 2001; Kasumyan, 2019). For over twenty years, it has been understood that nutrient perception by fish often precedes the discovery and grasping of food, leading to increased feeding activity (Pavlov and Kasumyan, 1998). Although the structure of

olfactory and taste organs, along with their receptors, has been studied in detail in fish (Døving and Kasumyan, 2008), there is currently no information on the functional development of the common chemical sense during the ontogeny of these species (Kasumyan, 2011). Moreover, it remains unclear whether the stimulation of nutrient-sensing receptors and their signaling pathways affects food properties perception and, consequently, the recognition and consumption of food by fish, particularly during early developmental stages. Firstly, our data reveal that the fatty acid receptors, selected in this study and recently characterized in the trout genome through phylogenetic and syntenic analysis (Roy et al., 2023), including tissue distribution for the FFAR family (Roy et al., 2022) and their postprandial regulation (Baranek et al., 2024), were all influenced by meal intake 30 days after the first feeding, both in the gustatory and olfactory systems. These findings are consistent with previous studies in rodents (Hichami et al., 2022) and humans (Ozdener et al., 2014), which showed an increased expression of the *ffar4* or *cd36* genes immediately after a meal. This aligns with our earlier long-term studies on trout, which also demonstrated a role for nutrient detection systems in regulating feeding behavior (Baranek et al., 2024; Heraud et al., 2022). Interestingly, these new results suggest that fatty acid receptors may play a key role in fat recognition in food from the first month of life in rainbow trout. When comparing the olfactory and gustatory systems between the two diets, FFAR family receptors seem more sensitive in the tongue and olfactory rosette of alevins fed a C diet, whereas other fat receptors selected (*cd36*, *gpr84*, *gpr119 fatp1a*, *fatp4*) in this study are notably more sensitive in the nose and tongue of alevins fed a V diet.

These effects may be explained by the differences in fatty acid composition between the diets. The main distinction lies in the omega-3 content. While DHA and EPA are abundantly present in the C diet (15.8 %), they are completely absent in the V diet, which compensates with over 26 % ALA. Linoleic acid (omega-6, C18:2) levels also differ significantly, with 2.26 times more omega-6 in the V diet (23.8 %) compared to the C one (10.5 %). Saturated or monosaturated fatty acids like myristic acid (C14:0) and palmetoleic acid (C16:1), which is 16 and 28.5 times more prevalent in the commercial diet (4.8 %, 5.8 %) than in the plant-based diet (0.3 %, 0.2 %) respectively, may also contribute to the receptor sensitivity observed in our analysis. In mammals, FFARs respond to fatty acids based on the length of their aliphatic chains (Kimura et al., 2020). FFAR1 and FFAR4 detect medium and long-chain fatty acids with carbon chain lengths ranging from 6 to 12 and 13–21, respectively (Hirasawa, 2015). Meanwhile, FFAR2 and FFAR3 specifically detect short-chain fatty acids, such as acetate, butyrate, or propanionate, which have less than 6 carbon atoms (Kimura et al., 2020). The heightened sensitivity in fish fed the C diet could be explained by the higher presence of medium-chain fatty acids and numerous long-chain omega-3s more than ALA alone. In trout, it has been shown that FFAR agonists reduce feed intake, an effect that is blocked by FFAR antagonists and long-chain fatty acids like oleic acid (C18:1) (Velasco et al., 2020). This underscores the importance of FFARs as regulators of feed intake in trout. Although evidence is limited regarding GPR84 (Huang et al., 2014) and GPR119 (Fredriksson et al., 2003) in fish, a study on trout revealed that their agonists also influence feed intake. GPR84 responds to medium-chain fatty acids (6–12 carbons) (Luscombe et al., 2020), while GPR119 is linked to oleoylethanolamide and other endogenous lipids containing oleic acid but is qualified as fat sensor in mammals (Hansen et al., 2012). In addition, trout studies showed that *cd36* and *FATP* (1 and 4) lipid transporters may detected fatty acids of various lengths (Calo et al., 2023), in contrast to the more restricted
<figure><img src="image_7.png" /><figcaption>**Fig. 5.** Relative expression of mRNA encoding flavours receptors of genes after meal in tongue and olfactory tissue. Relative gene expression measured by RT-PCR of selected *flavours receptors* (*tas2r4*, *otop1*, *gmr4a*, *asic1a*) genes in tongue (left panel) and olfactory rosette (right panel) tissue of trout fed the C or V diet 20 min, 2, 6, 10 or 24 h after meal. Datas are expressed as group mean ± SEM; fold change $2^{-\Delta\Delta Ct}$ vs before meal (T0) for all genes. Two-way ANOVA following by one-way ANOVA when the interaction is significant, Tukey's post-hoc test when appropriate; different letters indicate a significant difference (P < 0.05) between diet and time (n = 8).</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Fig. 6.** Relative expression of mRNA encoding calcium-signaling pathways of genes after meal in tongue and olfactory tissue. Relative gene expression measured by RT-PCR of selected calcium signaling-pathways (plcb3, plcb4, orai1a, stim1a) genes in tongue (left panel) and olfactory rosette (right panel) tissue of trout fed the C or V diet 20 min, 2, 6, 10 or 24 h after meal. Datas are expressed as group mean ± SEM; fold change $2^{-\Delta\Delta Ct}$ vs before meal (T0) for all genes. Two-way ANOVA following by one-way ANOVA when the interaction is significant, Tukey's post-hoc test when appropriate; different letters indicate a significant difference ($P < 0.05$) between diet and time ($n = 8$).</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Fig. 7.** Influence of C and V diets after meal on serotonin and dopamine turnover in tongue tissue. Tongue concentration of indolamines (left panel: 5-HT, 5-HIAA and turnover ratio 5-HT/5-HIAA) and catecholamine (right panel: L-DOPA, HVA and turnover ratio HVA/L-DOPA of trout fed the C or V diet 20 min, 2, 6, 10 or 24 h after meal. Datas are shown as means ± SEM; fold change vs. before meal (TO). Two-way ANOVA following by one-way ANOVA when the interaction is significant, Tukey's post-hoc test when appropriate; different letters indicate a significant difference (P < 0.05) between diet and time (n = 10).</figcaption></figure>

affinity observed in mammals. Finally, it would be interesting to explore the selective endogenous ligands of these fatty acid receptors in fish, as they could play a crucial role in regulating feed intake through both gustatory and olfactory systems, potentially affecting growth performance. The difference in fatty acid receptor sensitivity based on their location (nose or tongue) could suggest that fatty acid detection varies depending on whether they are in food or dispersed in water, despite fatty acids being insoluble.

Unlike fatty acids, amino acids are water-soluble and can thus be present in the surrounding water. However, our data suggest that amino acid receptors in the tongue of alevins were highly responsive not only to meals but also to the C diet, showing increased sensitivity in fish fed this regimen. In contrast, the olfactory rosettes could be less sensitive to amino acids, though they exhibit a slight sensitivity for the V diet. When examining the amino acid composition of the diets, the major differences between the C and V diets are found in a few specific amino acids. For instance, glycine levels are 34% higher in the C diet compared to the V diet. Previous research on fish indicates that while adding 0.5%

glycine had no effect on feed intake or growth in grass carp (*Ctenopharyngodon idella*) (Xie et al., 2017) or Nile tilapia (*Oreochromis niloticus*), higher doses (1–2%) promoted growth in hybrid striped bass (*Morone saxatilis* ♀ × *Morone chrysops* ♂) and tended to increase feed consumption (He et al., 2024). In contrast to glycine, the V diet in this study contained higher levels of proline and leucine, with increases of 17% and 16%, respectively. In rainbow trout, a study (Comesaña et al., 2018a) found that central administration of leucine reduced feed intake, while proline is highly palatable to carnivorous fish species (Morais, 2017), including rainbow trout, and has been shown to elicit strong gustatory responses (Jones, 1989). However, intraperitoneal administration of proline did not affect feed intake in rainbow trout (Comesaña et al., 2018b). More recent findings suggest that oral administration of proline significantly decreased voluntary food intake in juvenile rainbow trout 2–3 h after administration (Comesaña et al., 2020). Interestingly, during the early stages of feeding, amino acid stimuli triggered reflexive biting/snapping behavior in rainbow trout and brook trout (*Salvelinus fontinalis*) alevins (Valentinčić et al., 1999). In both
<figure><img src="image_10.png" /><figcaption>**Fig. 8.** Relative expression of mRNA encoding food intake markers of genes after meal in brain tissue. Relative gene expression measured by RT-PCR of *npya*, *npyb*, *agpr1*, *agpr2*, *pomca*, *pomcb*, *cartpt*, *mc4ra*, *mc4rb* in brain tissue of trout fed the C or V diet 20 min, 2, 6, 10 or 24 h after meal. Data are shown as means ± SEM; fold change 2⁻⁰·⁰⁵⁻⁰·⁰⁵ vs. before meal (T0). Two-way ANOVA following by one-way ANOVA when the interaction is significant, Tukey's post-hoc test when appropriate; different letters indicate a significant difference (P < 0·05) between diet and time (n = 8).</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>**Fig. 9.** Relative expression of mRNA encoding intestinal hormone markers of genes after meal in gut tissue. Relative gene expression measured by RT-PCR of selected intestinal hormone marker (cck, pyy, lepa1, ghrl) genes in gut tissue of trout fed the C or V diet 20 min, 2, 6, 10 or 24 h after meal. Data are shown as means ± SEM; fold change 2⁻⁰·ΔΔCT vs. before meal (T0). Two-way ANOVA following by one-way ANOVA when the interaction is significant, Tukey's post-hoc test when appropriate; different letters indicate a significant difference (P < 0·05) between diet and time (n = 8).</figcaption></figure>

species, proline and alanine induced swimming, turning, and snapping behaviors, suggesting an active food-seeking behavior. In contrast, proline triggered vigorous swimming but not snapping behavior in european huchen (*Hucho hucho*) alevins, another salmonid species, indicating a reduced olfactory sensitivity to this amino acid in the latter species (Valentinčić et al., 1999). Compared to fatty acids, fish may be significantly more sensitive to amino acids, and this sensitivity could develop much earlier, even before their first meal, through both the olfactory and gustatory systems. A study involving the incorporation of amino acids into agar granules revealed that proline acted as an attractive taste substance for carp (*Cyprinus carpio*), while lysine was perceived as repulsive (Kasumyan et al., 2009). Conversely, asparagine in cod (*Gadus morhua*) appeared to be neutral, indicating that this amino acid relates to substances with indifferent taste properties for intraoral taste reception. Notably, this study found that olfactory stimulation prior to feeding significantly increased the average number of graspings per granule with either indifferent or repulsive taste properties. This intriguing study suggests a subtle interplay between the two systems in nutrient detection, which may influence food intake.

Regarding flavor taste receptors, our data after 30 days of feeding show increased sensitivity across the studied receptors, with a noticeable effect of the meal on both sensory organs. However, the gustatory system appears more sensitive in alevins fed a C diet. It is well-known that fish can perceive the five primary tastes: amino acids (umami), sugars (sweet), bitter substances, salts (salty), and acids (sour) (Kasumyan and Døving, 2003). Fish exhibit both positive and negative taste responses, with certain compounds being preferred, while others trigger aversive reactions. An interesting example is sucrose, which is often viewed as neutral or even repellent by species like channel catfish (*Ictalurus punctatus*) (Kanwal and Caprio, 1983) and kutum (*Rutilus frisii*

kutum) (Goli et al., 2015), likely due to its low prevalence in aquatic environments and limited nutritional importance for fish, especially carnivores (Wilson, 1994; Callet et al., 2020). In grass carp, a behavioral olfactory experiment using a custom Y-maze tank demonstrated a preference for fructose over glucose (Yuan et al., 2020). These findings could offer new insights into the adaptive evolution of sweet taste receptors and their role in shaping feeding behaviors in fish. For trout, Jones et al. have demonstrated that sugars elicited a positive behavioural response (cotton pellets flavoured or not; swallowed v. rejected) and to certain amides (acetamide, valeramide and caproic amide), alcohols (hexanol and octanol) suggested that trout are sensitive to a wide range of compounds (Jones, 1989), which may be important to study in the context of alternative plants products. Moreover, bitterness has recently been identified as a potential nutritional strategy for Nile tilapia by incorporating orange peel powder into their diet (Gressler et al., 2024). Additionally, the use of sweet flavor, through the addition of sweet orange peel, has been tested as a feed additive for Nile tilapia alevins, resulting in improved growth rates (Salem and Abdel-Ghany, 2018). Despite previous studies, few researches has focused on the impact of flavors on food detection systems, and even less on their influence on feed intake. Flavors are often derived from amino acids present in the diet. In this context, a study examining 32 fish species analyzed the relationship between the taste attractiveness of free amino acids and their biological properties (Kasumyan, 2016). For most fish species, this relationship between taste attractiveness and the physical, chemical, and biological properties of amino acids appears weak or absent, indicating an indirect nature and the difficulty in uncovering these connections. Given the results of this study and previous research, it would be highly beneficial to conduct olfactory behavior tests alongside gustatory preference tests, exploring the effects of various
fatty acids based on their chain length and amino acids according to their flavor properties. This approach could offer valuable insights into how these sensory systems contribute to nutrient detection and food preferences in fish.

To conclude on receptor results, our data reveal that a large number of nutrient receptors (ffar1, ffar2a2, ffar2b1.1, ffar2b2a, gpr119, lpar5, tlr1-1, tlr3, tasr2r4, otop1) particularly in gustatory tissue, exhibited sustained postprandial expression in fish fed the C diet, especially at 6 and 10 h after feeding. Gene expression levels ranged from 2- to 5-fold, which are generally considered biologically meaningful in the context of nutrient sensing, as previously reported in other species. For example, Ozdener et al. demonstrated that incubation of mouse taste cells with omega-6 fatty acids led to strong upregulation of *cd36* gene expression, supporting the idea that such nutrients can act as functional modulators of sensory receptors (Ozdener et al., 2014). Consistent with this, subjects (human) with attenuated expression of *cd36*, as a result of genetic variants, exhibit decreased sensitivity for oro-gustatory perception of dietary lipids (Pepino et al., 2012). In our study, the observed gene regulation could likely reflects physiologically relevant adjustments to dietary cues, rather than incidental transcriptional variation.

Taste receptors, which interact directly with tastants, are the initial step in taste perception. Upon activation, these receptors trigger multiple downstream signaling cascades that transduce the taste signal. Calcium signaling is the primary pathway following this receptor activation. The increase in intracellular calcium facilitates signal transmission within the sensory systems (Hichami et al., 2022). This process has also been well characterized in fish (Oike et al., 2007; Yasuoka et al., 2004), indicating a similar mechanism across species. The results of our study on calcium signaling showed that the selected components of this pathway were all responsive to feeding. Sensitivity was particularly heightened in the gustatory system for animals fed the C diet, while a stronger sensitivity was observed in the olfactory system for alevins fed the V diet. These findings aligned with receptor data, indicating greater sensitivity in the gustatory system for the C diet and heightened olfactory sensitivity for the V diet. Given that a vast majority of receptors are coupled to calcium signaling (Ahmad and Dalziel, 2020), it was logical to observe an increase in calcium pathway activity associated with potential receptor activation. However, it would have been useful to conduct cell culture experiments on isolated olfactory or gustatory cells, as has been done in mammals (Abdou-Azize et al., 2014, 2013), to further elucidate the taste receptor signaling pathways in fish. Moreover, the upregulation of *plcb3* and *plcb4* in tongue for fish fed C diet, key enzymes in calcium signaling, may enhance intracellular Ca²⁺ release and contribute to the activation of serotonin and dopamine release in sensory cells. This mechanism could provides a plausible link between diet-induced receptor stimulation and downstream neuromodulation of feeding behavior. Indeed, following the elevation of intracellular calcium in taste bud cells within the sensing system, numerous neurotransmitters, such as serotonin and dopamine, are released via afferent gustatory nerves (Roper and Chaudhari, 2017). The release of these neurotransmitters activates neurons located at the base of taste cells, allowing the transmission of taste information through several neural relays, ultimately reaching the brain. In our study, for the first time, we revealed that the serotonin pathway is active in trout alevins as early as their first month of feeding and highly responsive to diet. This key neurotransmitter, well-known in mammalian taste buds (Chaudhari and Roper, 2010), increases within minutes following a meal. While this effect was observed in the tongues of alevins fed a C diet, it was absent in those fed a V diet. More broadly, serotonin activity, reflected by the 5-HIAA/5-HT ratio, was much lower in alevins fed the V diet. Interestingly, the opposite trend was seen with another neurotransmitter, dopamine, which increased after meals in the tongues of alevins fed a V diet but decreased in those on the C diet. These findings are significant and demonstrate that diet strongly influences the regulation of neurotransmitters in the trout's tongue at an early stage of development. These neurotransmitters appear to be excellent markers

for nutrient detection at the gustatory level following a meal, depending on the type of food or nutrients consumed. While serotonin activity in the tongue is already known to be an essential in nutrition detection in mammals (Roper, 2006), as well as a molecule associated with hedonic sensation in fish (Baranek et al., 2024; Ruibal et al., 2002) dopamine has not yet been demonstrated as a similar marker in these species. However, it is well-known in mammals that neuropeptides regulating energy balance through the hypothalamus also modulate the activity of dopaminergic cells and their projections to regions involved in reward processes, which underlie food intake and sensory systems (Volkow et al., 2010). It is even hypothesized that this could be a mechanism by which diet and the resulting resistance to homeostatic signals alter the function of circuits involved in reward sensitivity. Thus, although more studies are needed, dopamine could play a crucial role in fish as a modulator of feeding behavior, particularly within sensory systems like the tongue, influencing nutrient detection signals that regulate food intake. Furthermore, the membrane depolarization that triggers the electrical signal from calcium signaling and neurotransmitter release is transmitted to various brain regions via different nerves, notably to the hypothalamus, the center responsible for regulating food intake, which is well-characterized in fish (Rønnestad et al., 2017; Volkoff, 2016). In this way, the post-meal differences in serotonin and dopamine levels across different diets could explain the observed effects on food intake regulation. Our data reveal that both anorexigenic and orexigenic markers was upregulated after a meal when a V diet is provided. Anorexigenic marker (*pomca*) was significantly upregulated long term after the meal, along with elevated *mc4r* gene expression, amplifying the anorexigenic effects (Schjolden et al., 2009), suggesting a diminished appetite in fish fed the V diet. However, brain orexigenic markers (*npya* and *npyb*) remain up-regulated throughout the postprandial period in fish fed the V diet, including ghrelin (*ghrl* gene), an orexigenic hormone in the gut of these alevins. This data does not align with the observed lower feed intake in fish on the V diet, suggesting a potential disconnect between circuitry of feeding behavior and actual feeding behavior.

This uncoupling may reflect a failure in downstream signaling or a sensory mismatch between nutrient detection and hypothalamic integration of appetite signals, as previously reported (Baranek et al., 2023, 2024). In particular, although the neuropeptidergic circuitry involved in appetite regulation does not appear to be altered by a plant-based diet in juvenile trout, the hedonic perception, as indicated by neurotransmitter profiles, seems to be affected (Heraud et al., 2022). This may explain the observed alterations in feeding behavior towards diets devoid of fish meal and fish oil. A reduced desire to eat an unpalatable diet could, in turn, trigger a compensatory increase in hunger signals, as evidenced here by the upregulation of orexigenic neuropeptides and ghrelin.

Comparative studies in other teleost species suggest that the nutrient-sensing pathways identified here may be conserved across fish taxa (Kasumyan, 2019; Yue et al., 2025). However, species-specific sensitivities, particularly during early developmental stages, underscore the importance of conducting targeted research in the species under study. In this context, a deeper exploration of the tongue-brain axis, in conjunction with the olfactory system, during early ontogeny but also at long term, and a more comprehensive characterization of the neurotransmitter networks involved in appetite regulation, could clarify whether certain nutrients or flavor cues interfere with nutrient sensing pathways and, ultimately, modulate food intake in trout.

## 5. Conclusion

Our study highlights the early and heightened sensitivity of the nutrient sensing system in rainbow trout alevins, particularly during critical developmental stages, in response to alternative diets devoid of FM and FO. This sensitivity reflects the ability of alevins to detect changes in diet composition, suggesting that even at early life stages, their sensory systems, including olfactory and gustatory pathways, play a crucial role in nutrient detection and feed intake regulation. Moreover,
the study emphasizes the involvement of neurotransmitters such as serotonin and dopamine in modulating feeding behavior, revealing diet-induced alterations in their activity within the tongue. These findings underscore the complex interplay between nutrient sensing, sensory systems, and appetite regulation. Importantly, this work opens new perspectives for improving feed formulation by specifically targeting sensory receptors involved in feed detection and acceptance. In practical implication, the inclusion of palatability enhancers or the rebalancing of fatty acid profiles could help mitigate the limitations associated with fully plant-based diets during early trout development. Ultimately, such strategies may contribute to optimizing alternative diets to better support early growth, health, and sustainability in aquaculture practices.

## Ethics approval and consent to participate

Experiments were conducted at the INRAE facilities of Donzacq, France (authorisation number A40-228.1, Landes). All fish were reared and handled in strict accordance with the French (Decree No 2013-118, 1 February 2013) and European (i.e. Directive 2010/63/EU) animal welfare policies, followed ARRIVE guidelines.

## Funding

This research was funded by the French National Research Agency (grant no. ANR-21-CE20-0009-01 "FEEDOMEGA").

## CRediT authorship contribution statement

**Maud Martinat:** Writing – original draft, Software, Methodology, Formal analysis, Data curation. **Marie Lasserre:** Software, Data curation. **Anne Surget:** Formal analysis, Data curation. **Anthony Lanuque:** Methodology, Data curation. **Elodie Baranek:** Software, Data curation. **Cécile Heraud:** Software, Formal analysis, Data curation. **Frédéric Terrier:** Methodology, Data curation. **Jérôme Roy:** Writing – review & editing, Writing – original draft, Validation, Supervision, Investigation, Funding acquisition, Data curation, Conceptualization.

## Author Agreement Statement

We the undersigned declare that this manuscript is original, has not been published before and is not currently being considered for publication elsewhere.

We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.

We understand that the Corresponding Author is the sole contact for the Editorial process.

He/she is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs. For the purpose of Open Access, a CC-BY public copyright licence has been applied by the authors to the present document and will be applied to all subsequent versions up to the Author Accepted Manuscript arising from this submission.

## Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.aqrep.2025.102943.

## Data availability

All data supporting the findings in this study are available within the article. Raw phenotypic datasets are available from the Recherche Data Gouv public repository entitle "Effects of plant-based diet in first month of feeding of alevin rainbow trout (Oncorhynchus mykiss) on gustatory nutrient sensing systems developpement", https://doi.org/10.57745/789EYO. Correspondence and material requests should be addressed to Jérôme Roy (jerome.roy@inrae.fr).

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