International Journal of Molecular Sciences Article Viral Infection Drives the Regulation of Feeding Behavior Related Genes in Salmo salar David Muñoz 1,† , Ricardo Fuentes 2,† , Beatriz Carnicero 1 , Andrea Aguilar 1 , Nataly Sanhueza 1 , Sergio San-Martin 3 , Cristian Agurto 3 , Andrea Donoso 3 , Leonardo E. Valdivia 4 , Jesús M. Miguez 5 , Lluis Tort 6 and Sebastián Boltana 1, * 1 Centro de Biotecnología, Departamento de Oceanografía, Universidad de Concepción, Concepción 4030000, Chile; bio.dnmunoz10@gmail.com (D.M.); b.carniceroarnanz@gmail.com (B.C.); aguilar.espinoza@gmail.com (A.A.); natalysanhueza@udec.cl (N.S.) 2 Departamento de Biología Celular, Facultad de Ciencias Biológicas, Universidad de Concepción, Concepción 4030000, Chile; ricfuentes@udec.cl 3 Grupo Interdisciplinario en Biotecnología Marina (GIBMAR), Centro de Biotecnología, Departamento de Ciencia y Tecnología de los Alimentos, Facultad de Farmacia, Universidad de Concepción, Concepción 4030000, Chile; sergio.sanmartin.p@gmail.com (S.S.-M.); cagurto@udec.cl (C.A.); andreadonoso@udec.cl (A.D.) 4 Center for Integrative Biology, Faculty of Sciences, Universidad Mayor, Santiago 7500000, Chile; LEONARDO.VALDIVIA@UMAYOR.CL 5 Centro de Investigación Marina, Laboratorio de Fisiología Animal, Departamento de Bioloxía Funcional e  Ciencias de la Salud, Facultad de Biología, Universidade de Vigo, 36310 Vigo, Spain; jmmiguez@uvigo.es  6 Department of Cell Biology, Physiology and Immunology, Universitat Autonoma de Barcelona, Citation: Muñoz, D.; Fuentes, R.; 08193 Barcelona, Spain; Lluis.Tort@uab.cat * Correspondence: sboltana@udec.cl; Tel.: +56-41-266-16-17 Carnicero, B.; Aguilar, A.; Sanhueza, † These authors contributed equally to this work. N.; San-Martin, S.; Agurto, C.; Donoso, A.; Valdivia, L.E.; Miguez, J.M.; et al. Viral Infection Drives the Abstract: The feeding behavior in fish is a complex activity that relies on the ability of the brain Regulation of Feeding Behavior to integrate multiple signals to produce appropriate responses in terms of food intake, energy ex- Related Genes in Salmo salar. Int. J. penditure, and metabolic activity. Upon stress cues including viral infection or mediators such as Mol. Sci. 2021, 22, 11391. the proinflammatory cytokines, prostaglandins, and cortisol, both Pomc and Npy/Agrp neurons https://doi.org/10.3390/ from the hypothalamus are stimulated, thus triggering a response that controls both energy storage ijms222111391 and expenditure. However, how appetite modulators or neuro-immune cues link pathogenesis and energy homeostasis in fish remains poorly understood. Here, we provide the first evidence of a Academic Editor: molecular linkage between inflammation and food intake in Salmon salar. We show that in vivo viral Alessandra Ferramosca challenge with infectious pancreatic necrosis virus (IPNV) impacts food consumption by activating anorexic genes such as mc4r, crf, and pomcb and 5-HT in the brain of S. salar. At the molecular level, Received: 20 July 2021 viral infection induces an overall reduction in lipid content in the liver, favoring the production of Accepted: 3 September 2021 Published: 21 October 2021 AA and EPA associated with the increment of elovl2 gene. In addition, infection upregulates leptin signaling and inhibits insulin signaling. These changes are accompanied by a robust inflammatory Publisher’s Note: MDPI stays neutral response represented by the increment of Il-1b, Il-6, Tnfa, and Pge2 as well as an increased cortisol with regard to jurisdictional claims in level in vivo. Thus, we propose a model in which hypothalamic neurons respond to inflamma- published maps and institutional affil- tory cytokines and stress-related molecules and interact with appetite induction/inhibition. These iations. findings provide evidence of crosstalk between pathogenesis-driven inflammation and hypothalamic– pituitary–adrenocortical axes in stress-induced food intake behavior in fish. Keywords: feeding behavior; lipid metabolism; inflammation; infection Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and 1. Introduction conditions of the Creative Commons Feeding behavior is a complex activity that is associated with food intake. Fish are Attribution (CC BY) license (https:// excellent experimental models for studying the regulation of feeding behavior because creativecommons.org/licenses/by/ they have versatile feeding habits and patterns. Many inputs regulate the feeding behavior 4.0/). Int. J. Mol. Sci. 2021, 22, 11391. https://doi.org/10.3390/ijms222111391 https://www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2021, 22, 11391 2 of 17 in the brain including homeostatic signals such as body fat stores, food intake, and circu- lating glucose and fatty acids, and also by non-homeostatic signals such as learning and experience, hedonics, stress, social situation, and opportunity [1]. As in mammals, the hy- pothalamus of fish receives and processes information from endocrine signals originating in peripheral tissues, precisely from the gastrointestinal tract, liver, adipose tissue, and brain through neuroendocrine actions [2,3]. In the brain, the feeding behavior control resides in the arcuate nucleus of the hy- pothalamus (ARH), where the pro-opiomelanocortin (Pomc) neurons (anorexigenic) and the neuropeptide Y (Npy)/agouti-related peptide (Agrp) neurons (orexigenic) suppress or increase the appetite, respectively [4]. The Pomc neurons can respond to serotonin (5-HT), dopamine (DA), leptin, and insulin signaling molecules by expressing receptors for each of them [5]. Remarkably, leptin is known to inhibit feeding behavior [6] and exerts control on hypothalamic neurons including Pomc and Agrp neurons [7]. The Pomc neurons initiate a cascade of signaling events under the action of leptin including activation of the signal transducer and activator of transcription 3 (Stat3). This activation drives the expression of the pomc gene, triggering the secretion of the anorexigenic Pomc-derived peptide α-melanocyte-stimulating hormone (α-Msh) [8]. Thus, Pomc neurons through α-Msh inhibit the release of orexigenic signals from Npy/Agrp neurons [9]. Alternatively, among the multiple external factors that stimulate orexigenic neu- rons, it has been described that only the peptide hormone ghrelin exerts an orexigenic effect [3,10,11]. Mechanistically, ghrelin binds to the growth hormone secretagogue receptor (Ghsr) expressed in the brain and Npy/Agrp neurons. This interaction triggers the release of orexigenic peptides such as Npy/Agrp and GABA, two inhibitory neurotransmitters that suppress the anorexigenic Pomc neurons [12,13]. Under stress conditions, Pomc and Agrp display changes in the feeding behavior, mainly because the nutrient-sensing mechanisms and the neural appetite signals do not operate normally [4]. This disturbance modifies the expression of appetite-related neu- ropeptides [14] to restore internal homeostasis after an external disturbance, mainly by mobilizing fuel stores to make energy available for increased metabolic demand [15]. Among stressors, pathogen infection represents a fundamental challenge for homeostasis maintenance since it involves activating the immune system, resolving the challenge, and protecting the host against potentially toxic inflammatory processes. Upon infection, the immune system triggers the release of immune mediators including pro-inflammatory cytokines such as tumor necrosis factor-alpha (Tnfa), interleukin-1 (Il-1), interleukin-6 (Il-6), and the type I interferons (Ifn-a/b) [16,17]. Pro-inflammatory cytokines activate the transcription factor Stat3, which triggers the production of cyclooxygenase 2 (Cox-2), the enzyme involved in the synthesis of prostaglandin E2 (Pge2) and D2 (Pgd2). Thus, the biogenesis of Pge2/Pgd2 regulates a mechanism that acts in synergy with the central nervous system (CNS) in response to infection, thus inducing the development of fever in mammals, and behavioral fever in fish [18,19]. The polyunsaturated fatty acids such as arachidonic acid (AA) and eicos- apentaenoic acid (EPA) are intimately involved in synthesizing proinflammatory and-anti- inflammatory mediators. Specifically, AA is a precursor of Pge2, and EPA can suppress the inflammatory response via Tnfa and Il-6 [20]. A proposed mechanism for this interaction assumes a competition between AA and EPA for cyclooxygenases (Cox), key enzymes involved in prostaglandin biosynthesis [21]. The released cytokines, contributing to the progression of the immune response to pathogen infection, can also activate the HPI axis and induce the secretion of adrenal glucocorticoids such as cortisol [22–24]. The release of cortisol triggers the mobilization of energy reserves through glycolysis and gluconeo- genesis [25,26]. This mechanism allows the organisms to meet the energetic requirements during stressful scenarios such as pathogenic challenge [27,28]. In this context, cortisol plays a crucial role in regulating the feeding behavior by stimulating the anorexigenic pathway [29]. Thus, the CNS senses signals of stress condition (i.e., cortisol) and triggers the release of corticotropin-releasing factor (Crf) from the hypothalamus [30,31]. This mech- Int. J. Mol. Sci. 2021, 22, 11391 3 of 17 anism promotes adrenocorticotropic hormone (Acth) synthesis, which spatially controls food intake in Pomc neurons [8,32,33]. Under stress conditions, the collective data show that in fish, feeding behavior and nutrient-sensing are inhibited [34–36]. However, how this system copes with pathogen infections are still poorly understood. Remarkably, to date, the complete understanding of the monoamine release and the neurotransmitters modulating this circuit remains elusive. In the present study, we identified new factors controlling food intake during pathogenesis. We took advantage of the salmon since it is an ectotherm, mobile organism susceptible to infectious pancreatic necrosis virus (IPNV). Previous studies have shown that fish challenged with IPNV induce an inflammatory response within 24 h post-viral challenge [19,37]. In the present study, we show that viral infection impact feeding behavior in fish. This virus-mediated feeding behavior acts in concert with inflammatory cytokine signaling to modulate the activity of orexigenic molecules such as AgRP and NPY. We also assessed the impact of a pathogenic challenge on food intake-related genes and the crucial modulation of the inflammatory response induced by changes in the fatty acid composition. We hypothesized that these changes disrupt the synthesis of lipid-derived inflammatory cues, affecting the immune response of the fish exposed to viral challenge. 2. Results 2.1. IPNv Viral Infection Increases the Levels of Cortisol To address whether food intake behavior is modified by a stress condition, we exposed salmon parr to an IPNV challenge. All fish were infected at 12 ◦ C for 96 h (enough time for the virus to initiate the infection and trigger an inflammatory response, see Boltana et al., 2018 [18,19,37]). We also evaluated IPNV load over time in infected individuals. Quantitative analysis of the VP2 segment mRNA as a readout of viral load (Figure S1) revealed that all fish significantly decreased systemic replication of the virus. Phenotypic analysis performed on each infected fish showed no physical abnormalities. To describe the components of the inflammatory response in salmon, we evaluated the expression levels of il-β, il-6, tnfa, and cox2 genes in the hind kidney by quantitative real-time PCR (Figure 1). The transcripts of proinflammatory cytokines (il-1β, il-6, tnfa) and cox2 were significantly (p < 0.05) upregulated at 24 h post-infection (hpi) in IPNv-infected fish (Figure 1A–D). These levels return to baseline at 72 hpi, remaining similar to the control (one-way ANOVA, p < 0.05). To gain insights into the relationship between the stress and inflammation induced by infection viral, we measured the plasma levels of Tnfa, Il-6, Pge2, and cortisol through the ELISA assay (Figure 2). We detected a significant increment in the proinflammatory cytokines Tnfa and Il-6 at 24, 48, and 72 hpi compared to control individuals (Figure 2A,B). Similarly, the plasma levels of Pge2 in the challenged specimens peaked at 24 hpi, reaching 0.1499 ng/mL, showing significant differences (p < 0.01) (Figure 2C). This content dropped over time, still being significantly higher than the control group levels. In the inflammation process, the plasma cortisol concentration also showed a significant increase (p < 0.001) after viral challenge when compared to the non-challenged group, peaking at 24 hpi with 13.05 ng/mL and returning to baseline levels by 48 hpi and 72 hpi, respectively (one-way ANOVA, p < 0.001, Figure 2D). Int. J. Mol. Sci. 2021, 22, 11391 4 of 17 Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 4 of 18 Figure 1. Expression profile of proinflammatory cytokines during infection. The tnfa (A), il1b (B), il6 (C), and cox2 (D) gene Figure 1. Expression profile of proinflammatory cytokines during infection. The tnfa (A), il1b (B), il6 (C), and cox2 (D) gene expression after IPNv infection in the hind kidney of salmon. Control sample corresponds to unchallenged fish. Data expression after IPNvtheinfection represent mean ± SEM.in the hindANOVA; One-way kidney pof< 0.05 salmon. Controlstatistically was considered sample corresponds to unchallenged significant. Different letters denote fish. Data representInt.the significant mean differences. ± SEM. One-way ANOVA; p < 0.05 was considered statistically significant. Different letters J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 5 of 18denote significant differences. To gain insights into the relationship between the stress and inflammation induced by infection viral, we measured the plasma levels of Tnfa, Il-6, Pge2, and cortisol through the ELISA assay (Figure 2). We detected a significant increment in the proinflammatory cytokines Tnfa and Il-6 at 24, 48, and 72 hpi compared to control individuals (Figure 2A,B). Similarly, the plasma levels of Pge2 in the challenged specimens peaked at 24 hpi, reaching 0.1499 ng/mL, showing significant differences (p < 0.01) (Figure 2C). This content dropped over time, still being significantly higher than the control group levels. In the inflammation process, the plasma cortisol concentration also showed a significant increase (p < 0.001) after viral challenge when compared to the non-challenged group, peaking at 24 hpi with 13.05 ng/mL and returning to baseline levels by 48 hpi and 72 hpi, respectively (one-way ANOVA, p < 0.001, Figure 2D). Figure 2. Expression profile of inflammatory mediators during infection. Plasmatic concentration of Tnfa (A), Il6 (B), Pge2 Figure 2. Expression profile(D) (C) and cortisol ofininflammatory salmon after IPNvmediators infection.during infection. Data represent Plasmatic the mean ± SEM.concentration of Tnfa One-way ANOVA. (A), p < 0.05 Il6 (B), Pge2 was (C) and cortisol (D) instatistically considered salmon after IPNv significant. infection. Different lettersData denoterepresent the mean ± SEM. One-way ANOVA. p < 0.05 was significant differences. considered statistically significant. Different letters denote significant differences. 2.2. Upregulation of elovl2 in the Liver of Juvenile Salmon Is Linked with the Increases of AA and EPA during Infection with IPNv Arachidonic acid (AA) and eicosapentaenoic acid (EPA) are two long-chain polyunsaturated fatty acids synthesizing pro and anti-inflammatory cytokines, respectively. We tested how the lipid metabolism in the liver may promote Pge2-mediated inflammatory activity in our infection model by gas chromatography analysis (Figure 3). Int. J. Mol. Sci. 2021, 22, 11391 5 of 17 2.2. Upregulation of elovl2 in the Liver of Juvenile Salmon Is Linked with the Increases of AA and EPA during Infection with IPNv Arachidonic acid (AA) and eicosapentaenoic acid (EPA) are two long-chain polyun- saturated fatty acids synthesizing pro and anti-inflammatory cytokines, respectively. We tested how the lipid metabolism in the liver may promote Pge2-mediated inflammatory activity in our infection model by gas chromatography analysis (Figure 3). We found that AA (C20:4) was upregulated at 24 hpi (9.5%), 48 hpi (8.81%), and 72 hpi (7.98%) of infected specimens (Figure 3), which is consistent with increased Pge2 levels at similar time points post-viral challenge (see Figure 2A). Although in the control group EPA (C20:5) was not detected, a 4.78% increase at 24 hpi, 6.7 % increase at 48 hpi, and 4.5% decrease at 72 hpi Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW (Figure 3; p < 0.05) was noted. Values for the contents of various lipids present 6inofthe18 control and experimental livers are shown in Table 1. Figure Figure 3.3. Lipid Lipid content content profile in the profile in the liver livertissue tissueofofsalmon salmonduring duringinfection. infection.Composition Compositionofof lipids lipids in in the liver of salmon infected at 24 to 72 hpi. Control sample corresponds to unchallenged the liver of salmon infected at 24 to 72 hpi. Control sample corresponds to unchallenged fish. Data fish. Data represent the mean ± SEM. Two-way ANOVA; p < 0.05 was considered statistically significant. represent the mean ± SEM. Two-way ANOVA; p < 0.05 was considered statistically significant. Long-chain Long-chainfatty fattyacidacidbiosynthesis depends biosynthesis depends on on thethecomplementary complementary rolesroles of fatty acyl of fatty elongases (Elovls) and desaturases (fads). To investigate whether the acyl elongases (Elovls) and desaturases (fads). To investigate whether the accumulation accumulation of AA and EPA in the liver was accompanied by changes in both of AA and EPA in the liver was accompanied by changes in both lipid elongation and lipid elongation and desaturation desaturationcycles, cycles,we wemeasured measuredmRNA mRNAlevels levelsofofelovl5 elovl5andand elovl2 elovl2 and and d5fad d5fad and and d6fad, d6fad, and and two two recognized elongases and recognized elongases anddesaturases desaturasescodifying codifyinggenes, genes,respectively. respectively.AsAs shown shown in in Figure Figure 4A, 4A, elovl5liver elovl5 liverlevels levelsdecreased decreasedsignificantly significantlyfromfrom57 57to to three three copy copy numbers numbers after after IPNV IPNV infection infection compared compared to to non-infected non-infected fish fish (Figure (Figure 4A; 4A; pp << 0.01). 0.01). Similarly, Similarly, d5fad d5fad and and d6fad transcripts significantly decreased at all post-infection stages (Figure d6fad transcripts significantly decreased at all post-infection stages (Figure 4C,D; p < 0.001). 4C,D; p < 0.001). In contrast, elovl2 was upregulated in infected fish livers at 24 In contrast, elovl2 was upregulated in infected fish livers at 24 and 48 hpi (Figure 4B; and 48 hpi (Figure 4B; p < p0.05). < 0.05). Int. J. Mol. Sci. 2021, 22, 11391 6 of 17 Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 7 of 18 Figure4.4.Elongases Figure Elongasesand anddesaturases desaturasesexpression expressionprofiles profilesininthe theliver liverofofsalmon salmonduring duringinfection. infection.The Theelovl5 elovl5(A), (A),elovl2 elovl2(B), (B), d5fad (C), and d6fad (D) gene expression profiles after IPNv infection on salmon liver tissue. Control sample corresponds d5fad (C), and d6fad (D) gene expression profiles after IPNv infection on salmon liver tissue. Control sample corresponds to to unchallenged fish. Data represent the mean ± SEM. One-way ANOVA; p < 0.05 was considered statistically significant. unchallenged fish. Data represent the mean ± SEM. One-way ANOVA; p < 0.05 was considered statistically significant. Different letters denote significant differences. Different letters denote significant differences. 2.3.Anorexigenic 2.3. AnorexigenicGenes GenesAreAreUpregulated Upregulatedduring duringInfection InfectionininJuvenile JuvenileSalmon Salmon Weassessed We assessedthe theexpression expressionlevels levelsof of several several genes genes related related to feeding to feeding behavior behavior in- including expression levels of leptin and leptin receptor (lepr). We cluding expression levels of leptin and leptin receptor (lepr). We observed that leptin observed that leptin expressionsignificantly expression significantly increased increased (p(p << 0.01) 0.01) in inlivers liversofofIPNv IPNvchallenged challengedfish fishatat2424and and48 hpi when compared to non-infected individuals, peaking at 48 hpi 48 hpi when compared to non-infected individuals, peaking at 48 hpi with 384 transcripts with 384 transcripts andreturning and returningtotobase baselevels levelsatat72 72hpi hpi(Figure (Figure5A).5A).Leptin Leptinreceptor receptor(lepr) (lepr)expression expressionalso also showed a significant increase compared to non-challenged fish (Figure showed a significant increase compared to non-challenged fish (Figure 5B), registering the5B), registering the highest expression levels at 24 hpi with 29 transcripts (p < 0.01). To further highest expression levels at 24 hpi with 29 transcripts (p < 0.01). To further link metabolic link metabolic responsesand responses andinflammation, inflammation,we weassessed assessedinsulin insulinsignaling signalingrelated relatedgenes, genes,observing observingthat that viralinfection viral infectionsignificantly significantlydecreased decreasedtranscriptional transcriptionallevels levelsofofigf1 igf1and anditsitsreceptor receptorigf1r igf1rinin theliver the liverof ofIPNv IPNvchallenged challengedfish fish(Figure (Figure5C,D). 5C,D). Int. J. Mol. Sci. 2021, 22, 11391 7 of 17 Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 8 of 18 Figure 5. Figure 5. Leptin Leptin and andinsulin insulinexpression expressionprofiles profilesinin the the liver liver of of salmon salmon during during infection. infection. TheThe leptin leptin (A),(A), lepr lepr (B), (B), igf-1igf-1 (C), (C), and and igf-1r igf-1r (D) gene (D) gene expression expression afterafter IPNvIPNv infection infection on salmon on salmon liver liver tissue. tissue. Control Control sample sample corresponds corresponds to unchallenged to unchallenged fish. fish. Data Data represent represent the mean the mean ± SEM.± SEM. One-way One-way ANOVA; ANOVA; p < 0.05p 9 samples per treatment and time met the suggested quality standards). cDNA was synthesized from 50 µL of total RNA (200 ng/µL) using the RevertAid H Minus First Strand cDNA Synthesis Kit (Fermentas, Waltham, MA, USA), according to the manufacturer’s indications. RT-qPCR was performed using the StepOnePlus™ Real-Time PCR System (Applied Biosystems, Life Technologies, Waltham, MA, USA), and each assay was run in triplicate using the Maxima SYBR Green qPCR Master Mix-2X (Bio-Rad, Hercules, CA, USA). For qPCR assays, 5 µL of synthesized cDNA were diluted with 15 µL of nuclease-free water (Qiagen, Hilden, Germany). Each qPCR mixture contained the SYBR Green Master Mix, 2 µL of diluted cDNA, 500 nmol/L each primer, and RNase-free water to a final volume of 10 µL. The primers used are indicated in Supplementary Table S2 Amplification was performed using the Bio-rad CFX 96 Real Time System on 96-well plates with the following thermal cycling conditions: initial activation for 10 min at 95 ◦ C, followed by 40 cycles of 15 s (s) at 95 ◦ C, 30 s at 60 ◦ C, and 30 s at 72 ◦ C. A dilution series made from known concentrations of plasmids containing the PCR inserts were used to calculate absolute copy numbers for each examined gene in Table S1. Int. J. Mol. Sci. 2021, 22, 11391 13 of 17 4.4. Monoamine Analysis For the monoamine analysis, brains and whole bodies were snap-frozen in liquid nitrogen and stored at −80 ◦ C. The brain and body content of dopamine (DA) and 5- HT were determined by high performance liquid chromatography with electrochemical detection [72]. The procedure was described previously [73]. 4.5. Cortisol and Prostaglandin E2 ELISA Assays Blood plasma was obtained from ten previously sampled fish (see details in Section 4.2) and stored at −80 ◦ C until use. Measurement of plasma cortisol and prostaglandin E2 (Pge2) levels was carried out using a commercial monoclonal enzyme immunoassay (EIA), according to the manufacturer’s instructions (Cayman, MI, USA). This assay has a range from 8.6 to 2000 pg/mL and sensitivity (80% B/B0) of approximately 30 pg/mL. Prior to the determination of Pge2 levels, plasma samples were diluted five times in EIA assay buffer. Results were obtained after absorbance reading at 412 nm. Samples were stored at −80 ◦ C until being used. 4.6. Lipid Content Lipids were extracted from liver (three fish per time and treatment; n = 18 total) as described by Bligh and Dyer [74]. Subsequently, transesterification was conducted by adding 2 mL of borontrifluoride (BF3)/methanol (12%) and then incubating at 100 ◦ C for 30 min. After cooling the samples, 1 mL of isooctane was added, followed by stirring. To separate the phases, 2 mL of saturated NaCl was added. The upper phase was transferred into 2 mL amber vials and dried under a stream of nitrogen. Then, it was resuspended in 100 µL of hexane and analyzed on a gas chromatograph, where a mixture of 36 fatty acid methyl esters (FAME) (Restek, Food Industry FAME MIX) was used as the standard. The temperature range to allow chromatography was 100 ◦ C to 240 ◦ C, maintaining the final temperature for 20 min. The injection volume was 2 µL per sample and the carrier gas was nitrogen at 100 kPa. The injector temperature was 225 ◦ C and the FID detector temperature was adjusted up to 250 ◦ C. The data were obtained using the Autochro Data Module interface and Autochro 3000 software (Young Lin Instrument). The FAME profiles of the samples were identified by comparing the retention times and the area of the FAME peaks (mV) with the standard. 4.7. Statistical Analysis The presented data are expressed as mean ± standard deviation (SD). Sigma Plot (ver- sion14.0) and GraphPad Prism 7 software were used for statistical analysis and graphing, respectively. The data obtained from gene expression after the absolute quantification of mRNA by real-time polymerase chain reaction (qPCR) were analyzed to determine the normality and homogeneity of the variations using Shapiro–Wilk. When necessary, the data were transformed into log10 to achieve homogeneity and homogenized variances. Data obtained for cortisol and prostaglandin E2 were analyzed by one-way ANOVA, while fatty acids by two-way ANOVA, followed by a post-hoc Tukey HSD test for multiple comparisons. These last tests were also used for monoamine content analysis. All statisti- cal analyses were performed using the SigmaPlot version 14 (SigmaPlot, Stata Statistical Software). Non-parametric statistics were also used when normality tests failed. Means and significance of test groups were compared to the controls. The significance indicator, or letter, above each graph represents a significant difference relative to control. A p < 0.05 was considered statistically significant. 5. Conclusions To our knowledge, these novel results identify an unprecedented link between inflam- mation and regulation of the appetite in fish. These results also correlate with differentially expressed neuropeptides and receptor complexes. We sought to solve a paradigm involving the relation between stress response and appetite-regulating genes in fish subjected to an Int. J. Mol. Sci. 2021, 22, 11391 14 of 17 immune challenge. Such a paradigm consists of the onset of a hypothalamic cue that leads to the execution of an endocrinological response. However, further functional assays are required to fully demonstrate this hypothesis. This effort may include loss-of-function stud- ies of the Pomc or leptin using genome editing technologies in a fish model (SB and DM, unpublished data). For the first time, our findings show that fish leads to a neuro–immune interaction, which might modulate the systemic inflammatory response and the regulation of the appetite under pathogen infection. Our work points to a conserved neural–immune link contributing to a better understanding of the pathogen-mediated inflammatory disease and immune disorder responses during metazoan evolution. In conclusion, this study generates a more complete molecular map of the neuroimmune regulation of the appetite in fish. Our molecular characterization opens the door for further discovery of related gene functions in a complex genetic model. Supplementary Materials: The following are available online at https://www.mdpi.com/article/ 10.3390/ijms222111391/s1. Author Contributions: The study was conceived by S.B. and L.T. Behavioral experiments were performed by N.S., A.A., D.M. and J.M.M. analyzed the hormone data. S.S.-M., A.D., L.T. and C.A. analyzed the lipid synthesis data. D.M., R.F., B.C., A.A., L.E.V. and A.D. performed the gene expression analysis and provided extensive additional input. S.B. obtained the funding acquisition. All authors have read and agreed to the published version of the manuscript. Funding: The results reported in this paper were financially supported by ANID (Chile) funds (FONDECYT 1190627); CONICYT-PCHA/National PhD 2018 grant (21181886) from Nataly Sanhueza; CONICYT-PCHA/National PhD grant from Beatriz Carnicero (21181886); and FONDEQUIP Chile funds (EQM180201). Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board Chilean National Commission for Scientific and Technological Research (CONICYT), authorized by the Universidad de Concepcion Institutional Animal Care and Use Committee. Acknowledgments: We thank the PhD Doctorate program “Ciencias con mención en Manejo de Recursos Acuáticos Renovables (MaReA)” at the Universidad de Concepción, Chile. Conflicts of Interest: The authors declare no conflict of interest. References 1. Woods, S.C.; Begg, D.P. Regulation of the motivation to eat. Behav. Neurosci. Motiv. 2015, 27, 15–34. 2. Rønnestad, I.; Gomes, A.S.; Murashita, K.; Angotzi, R.; Jönsson, E.; Volkoff, H. Appetite-controlling endocrine systems in teleosts. Front. Endocrinol. 2017, 8, 73. [CrossRef] [PubMed] 3. Volkoff, H. The neuroendocrine regulation of food intake in fish: A review of current knowledge. Front. 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