Metabolic Mechanisms of Coloration and Decoloration in Juvenile Blood Parrotfish (Vieja melanurus ♀ × Amphilophus citrinellus ♂) Revealed by UHPLC-Q-TOF/MS

Metabolic Mechanisms of Coloration and Decoloration in Juvenile Blood Parrotfish (Vieja melanurus ♀ × Amphilophus citrinellus ♂) Revealed by UHPLC-Q-TOF/MS | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Metabolic Mechanisms of Coloration and Decoloration in Juvenile Blood Parrotfish (Vieja melanurus ♀ × Amphilophus citrinellus ♂) Revealed by UHPLC-Q-TOF/MS Adekunle David Micah, Bin Wen, Abdullateef Yusuf, Meriyamoh Mero Onimisi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7107321/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study explored the role of astaxanthin, a carotenoid supplement, in the metabolic mechanism underlying body color formation in juvenile blood parrotfish ( Vieja melanurus ♀ × Amphilophus citrinellus ♂ ) cultured in a recirculating aquaculture system. Fish were divided into three groups: a control group (C) fed a basal diet for 12 weeks, a coloration group (AX) fed an astaxanthin-enriched diet for 12 weeks, and a decoloration group (AXM) fed the enriched diet for 6 weeks followed by a basal diet for another 6 weeks. Using UHPL-Q-TOF/MS, key metabolic pathways and compounds associated with coloration and decoloration were characterized. Metabolic analysis identified 2007 differentially expressed metabolites (DEMs), with OPLS-DA clearly distinguishing skin metabolite profiles between the AX and AXM groups. Notably, compounds such as astaxanthin, all-trans-4-ketoretinoic acid, octadecanoic acid, myristic acid, 1-oleoyl-2-myristoyl-sn-glycero-3- phosphocholine, (+)-.alpha.-tocopherol, and linoleic acid were significantly elevated in the AX group while prostaglandin i2, pc 38:7, N-tetracose-noyl-4-shingenine, lauroyl-1-carnitine, and (z)-5,8,11-trihydroxyoctadec-9-enoic acid were reduced in AXM group. KEGG pathway analysis revealed enrichment of ABC transporters, biosynthesis of amino acids, protein digestion and absorption, aminoacyl-tRNA biosynthesis, glycine, serine, and threonine metabolism in the AX group. In contrast, galactose metabolism, D-arginine and D-ornithine metabolism, taurine and hypotaurine metabolism were significantly enriched in AXM group. These findings enhance our understanding of the metabolic basis of body coloration in blood parrotfish and offer insights for optimizing ornamental fish nutrition and feed strategies. Astaxanthin Blood parrotfish Metabolic mechanisms UHPLC-Q-TOF/MS Coloration/decoloration Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Skin pigmentation is a key phenotypic trait in fish, governed by various specialized pigment cells known as chromatophores. These cells are classified based on the pigments they contain into melanophores (black/brown), xanthophore (yellow), erythrophores (orange/red), iridophores (iridescent), leucophores (white), and cyanophores (blue) (Fujii, 2000 ; Burton, 2002 ). Pigment cells store pigments endogenously within the cell (Tripathy et al., 2019 ). Among these, carotenoids (lipophilic molecules) play a central role in coloration. Structurally, carotenoids are divided into carotenes (hydrocarbons without oxygen, e.g., α-carotene, β-carotene, γ-carotene) and xanthophylls (oxygenated derivatives, e.g., zeaxanthin, lutein, canthaxanthin, astaxanthin), with approximately 850 (800 xanthophylls and 50 carotenes) types identified in nature (Maoka, 2020 ). Xanthophylls are particularly important in producing red, orange, yellow, and pink hues in both aquaculture and ornamental fish species (Lim et al., 2018 ; Maoka, 2020 ; Jin et al., 2021 ). Carotenoids are obtained from natural sources such as marine crustaceans ( Pandalus borealis ), plants, fungi ( Phaffia rhodozyma ), and algae ( Haematoccocus pluvialis , Chlorella zofingiensis , C. sorokiniana , and Neochloris wimmeri ), or synthesized chemically (e.g. astaxanthin, canthaxanthin, capsanthin) (Jiao et al., 2015 ; Lim et al. 2018 ; Lu et al., 2021 ; Yadavalli et al., 2021 ). Numerous studies have explored the effects of astaxanthin supplementation on fish pigmentation, including clown anemonefish ( Amphiprion ocellaris ) (Clark, 2016 ), dwarf gourami ( Trichogaster lalius ) (Baron et al., 2008 ), red devil ( Cichlosoma citrinellum ) (Pan and Chien, 2009 ), and Hong Kong grouper ( Epinephelus akaara ) (Song et al., 2021 ). Notably, the absence of dietary carotenoids in captive or cultured fish can lead to significant loss of pigmentation (Ahi et al., 2020a ). Body coloration can be maintained through dietary supplementation with astaxanthin, as fish are unable to synthesize this carotenoid de novo . While metabolic studies on carotenoids remain limited, research at the genetic and transcriptomic levels has provided valuable insights into the molecular mechanisms underlying carotenoid-based coloration in aquatic species. For instance, Ahi et al. ( 2020b ) identified several genes such as dhrsx , nlrc3 , tcaf2 , urah , and ttc39b that are involved in the metabolic regulation of carotenoid-dependent pigmentation. Notably, ttc39b exhibited elevated expression in the red skin of cichlid genera Tropheus and Aulonocana . Additional genes implicated in carotenoid coloration across vertebrates include the ketolase enzyme cyp2j19 (Mundy et al., 2016 ), the lipoprotein receptor sr-b1 / scarb1 (Toomey et al., 2017 ), and the carotenoid cleaving enzyme bco2 (Gazda et al., 2020 ). Recent metabolomic analyses have shed light on the biochemical pathways involved in carotenoid deposition. Yang et al. ( 2021 ) identified several key metabolites including L-arginine (associated with ABC transporters), docosahexaenoic acid (DHA), arachidonic acid, linoleic acid, eicosapentaenoic acid (EPA), 1-stearoyl-2-oleoyl-sn-glycerol-3-phosphocholine, dodecanoic acid, and myristic acid as playing significant roles in lipid metabolism and carotenoid accumulation. Complementing these findings, Zhu et al. ( 2021 ) reported that increased dietary intake of arachidonic acid enhanced carotenoid uptake, transport, and accumulation in the red-colored leopard coral grouper. Additional metabolic studies exploring pigmentation and body color regulation have been documented by Cho et al. ( 2016 ), Wang et al. ( 2016 ), Wei et al. ( 2019 ), and Li et al. ( 2020 ). Despite these advances, research on the metabolic mechanisms underlying body color formation in relation to the presence or absence of dietary carotenoids in fish remains limited. The blood parrotfish ( Vieja melanurus ♀ × Amphilophus citrinellus ♂ ) is a hybrid species developed in Taiwan during the late 1980s. It has gained widespread popularity in countries suc as China and Japan due to its vibrant red coloration and distinctive plump body shape (Sui et al., 2016 ). The striking red hue is highly valued by ornamental fish enthusiasts and significantly influences market price within the aquarium trade. To enhance body coloration, various studies have investigated the effects of dietary astaxanthin supplementation in blood parrotfish. For instance, Li et al. ( 2016 ) reported that synthetic astaxanthin significantly improved skin pigmentation. Similarly, Song et al. ( 2016 ) and Li et al. ( 2018 ) demonstrated that a combination of alfalfa saponins and natural astaxanthin positively influenced body coloration. More recently, Micah et al. ( 2024 ) found that astaxanthin supplementation increased both skin redness and chromatophore cells density in juvenile blood parrotfish. Despite these findings, knowledge of the specific metabolites involved in carotenoid-based pigmentation remains limited. In the present study, we employed untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with time-of-flight mass spectrometry (UHPLC-Q-TOF MS) to investigate skin metabolite differences between pigmented and non-pigmented juvenile blood parrotfish. The primary objective was to identify and characterize key metabolic pathways and compounds metabolites associated with astaxanthin-induced coloration and its absence. Materials and Methods Animal maintenance and handling procedures This study was approved by the Institutional Animal Care and Committee (IACUS) of Shanghai Ocean University, Shanghai, China. All procedures involved in the handling and treatment were conducted following the guidelines of the IACUS on the care and use of animals for scientific purposes. Experimental diet formulation and proximate composition analysis Two experimental diets with identical basal composition (Table 1 ) were formulated for juvenile blood parrotfish. The treatment diet was supplemented with 0.45 g/kg of synthetic astaxanthin (Carophyll® pink 10% CWS, DSM Nutritional Products Ltd). All feed ingredients were finely ground, sieved, and thoroughly mixed to ensure homogeneity. Distilled water was added to the mixture to form a cohesive dough, which was then extruded into 1 mm diameter pellets. The pellets were air-dried, sieved, and sorted to ensure uniform size. To preserve astaxanthin stability, both diets were stored at -20°C. Table 1 Composition of dietary ingredients and proximate analysis of basal and treatment diets. Feed ingredients Basal diet (g/kg) Treatment diet (g/kg) a Fish meal (imported) 400 400 a Soybean meal 150 150 a Cotton seed meal 110 110 a Fish oil 25 25 a Soybean oil 20 20 a Wheat flour 160 160 a Wheat middling 100 100 b Mineral premix 15 15 c Vitamin premix 10 10 a Cellulose (binder) 10 9.55 d Astaxanthin 0 0.45 Total 1,000 1,000 Proximate analysis Moisture content (%) 7.69 7.65 Dry matter content (%) 92.31 92.35 Ash content (%) 2.08 2.34 Crude lipid (%) 12.06 12.04 Crude protein (%) 52.51 51.55 Astaxanthin (g/kg) 0.025 0.471 a Yuehai Feed Mill, Zhejiang, China. b Per kg mineral premix contains: 0.8 g Co; 0.02 g Se; 3 g Cu; 10 g Zn; 3.8 g Mn; 1 g Fe; 12g Mg; 90 g K; 10.5 g Ca. c Per kg vitamin premix contains: 8 million IU of Vitamin A; 5 g Thiamine-HCl; 15 g Riboflavin; 2 million IU of Cholecalciferol; 50 g DL-α-Tocopherol; 8 g Pyridoxine-HCl; 10 g Menadione; 0.02 g Cyanocobalamin; 40 g Nicotinamide; 25 g Ca-pantothenate; 2.5 g Folic acid; 0.08 g Biotin; 100 g Inositol. d Carophyll® pink 10% CWS, DSM Nutritional products Ltd. Proximate composition analysis of the basal and treatment diets was conducted following standard procedures outlined by the Association of Official Analytical Chemists (AOAC 1995 ). Moisture content was determined by oven-drying samples at 105°C until a constant weight was achieved, and dry matter was calculated by subtracting moisture content from 100%. Crude protein content (N x 6.25) was measured using the Kjeldahl method after acid digestion, with quantification performed using an Auto Kjeldahl System (2300-Autoanalyzer Foss Tecator, Sweden). Crude lipid was assessed via chloroform-methanol extraction, following the method described by Cejas et al. ( 2004 ). Additionally, astaxanthin concentrations in both diets were quantified using a fish astaxanthin ELISA kit (Shanghai Enzyme-linked Biotechnology Co., Ltd. (mlbio) Shanghai, China), according to the manufacturer’s instructions. Experimental fish and rearing conditions A total of 360 juvenile blood parrotfish, with an average initial weight of 10.16 ± 0.38 g, were obtained from a commercial fish farm in Hainan, China. Prior to the experiment, all fish underwent a two-week acclimation period under laboratory conditions, during which they were fed the control diet. After acclimation, the fish were randomly assigned to 18 glass aquaria (48 cm × 45 cm × 30 cm) with 20 fish per tank. The experimental design consisted of three dietary treatments, each with six replicates. The control group (C) received a basal diet without astaxanthin for the entire 12-week period. The coloration group (AX) was fed a diet supplemented with 0.45 g/kg of synthetic astaxanthin for 12 weeks. The decoloration group (AXM) was initially fed the AX diets for six weeks, followed by the control diet for the remaining six weeks. Water quality parameters were carefully monitored and maintained throughout both the acclimation and experimental periods. Dissolved oxygen levels averaged 7.2 ± 0.1 mg/L, temperature was maintained at 26 ± 1°C, pH at 7.1 ± 0.2, and ammonia levels at 0.02 ± 0.01 mg/L. Dissolved oxygen, temperature, and pH were measured using Hanna equipment (model H198194), while ammonia concentrations were determined using the HI-700 ammonia kit. The aquaria were part of a recirculating aquaculture system, with 30% of the water replaced daily from the bottom of each tank. Fish were hand-fed to apparent satiation twice daily at 10:00 am and 4:00 pm and maintained under a natural photoperiod. The experimental protocol is illustrated in Fig. S1 . Tissue collection for metabolomic analysis A total of 36 skin samples, including scales, were collected from juvenile blood parrotfish at weeks 0, 6, and 12 from the control (C), coloration (AX), and decoloration (AXM) groups. Immediately after excision, all samples were snap-frozen in liquid nitrogen to preserve metabolite integrity. Each sample was then section on dry ice (~ 80 mg) and transferred into a 2 mL Eppendorf tube. For homogenization, 200 µL of distilled water and five ceramic beads were added to each tube, and tissues were homogenized using a bead-based homogenizer. Subsequently, 800 µL methanol/acetonitrile (1:1, v/v) was added to the homogenate for metabolic extraction. The mixture was centrifuged at 14000 x g for 15 mins at 4°C, and the resulting supernatant was collected and dried using a vacuum centrifuge. Dried extracts were reconstituted in 100 µL of acetonitrile/water (1:1, v/v) for subsequent LC-MS analysis. LC-MS/MS analysis Metabolic profiling was conducted using an ultra-high performance liquid chromatography system (UHPLC 1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, AB Sciex) at Shanghai Applied Protein Technology Co., Ltd. For hydrophilic interaction liquid chromatography (HILIC) separation, samples were analyzed using a 2.1 mm x 100 mm ACQUIY UPLC BEH column (1.7 µm particle size; Waters, Ireland). The mobile phase consisted of solvent A (25 mM ammonium acetate and 25 mM ammonium hydroxide in water) and solvent B (acetonitrile). The gradient program began with 85% B for 1 min, linearly decreased to 65% over 11 min, then rapidly dropped to 40% in 0.1 min and held for 4 min. It then increased back to 85% in 0.1 min, followed by a 5 min re-equilibration period. For reverse-phase liquid chromatography (RPLC) separation, a 2.1 mm x 100 mm ACQUIY UPLC HSS T3 (1.8 µm particle size; Waters, Ireland) was used. In positive electrospray ionization (ESI) mode, the mobile phase consisted of solvent A (water with 0.1% formic acid) and solvent B (acetonitrile with 0.1% formic acid). In negative ESI negative mode, solvent A was 0.5 mM ammonium fluoride in water, and solvent B was acetonitrile. The gradient started at 1% B for 1.5 min, increased linearly to 99% over 11.5, held for 3.5 min, then returned to 1% in 0.1 min, followed by a 3.4 min re-equilibration. All separation were performed at a flow rate of 0.3 mL/min with the column temperature maintained at 25°C. A 2 µL aliquot of each sample was injected. The ESI source parameters were set as follows: Ion Source Gas1 and Gas 2 at 60 psi, curtain gas at 30 psi, source temperature at 600°C, and Ion Spray Voltage Floating (ISVF) at ± 5500 V. For MS-only acquisition, data were collected over an m/z range of 60–1000 Da with a TOF MS scan accumulation time of 0.20 s per spectrum. For auto MS/MS acquisition, the m/z range was 25 − 1000 Da with a product ion scan accumulation time of 0.05 s per spectrum. Product ion scans were acquired using information-dependent acquisition (IDA) in high-sensitivity mode. Collision energy (CE) was set at 35 V with a spread of ± 15 eV, and declustering potential (DP) was set at + 60 V and − 60 V for positive and negative modes, respectively. Isotopes within 4 Da were excluded, and up to 10 candidate ions were monitored per cycle. Data processing Raw mass spectrometry data files (wiff.scan format) were first converted to the mzXML format using ProteoWizard MSConvert to enable compatibility with downstream analysis tools. Peak detection, alignment, and quantification were performed using the open-source XCMS software. For peak picking, the centWave algorithm was applied with the following parameters: mass accuracy (m/z) = 10 ppm, peak width = c(10, 60), and prefilter = c(10, 100). Peak grouping was conducted using bandwidth (bw) = 5, m/z width (mzwid) = 0.025, and minimum fraction (minfrac) = 0.5. To annotate isotopes and adducts, the CAMERA (Collection of Algorithms for Metabolite pRofile Annotation) package was employed. From the extracted ion features, only variables with non-zero measurements in more than 50% of samples within at least one experimental group were retained for further analysis to ensure data robustness. Metabolite identification was performed by matching accurate mass values (within 10 ppm) and MS/MS fragmentation spectra against an in-house spectral database developed using authentic standards (Luo et al., 2017 ; Zhaobing et al., 2018 ). This approach enabled high-confidence annotation of metabolites relevant to carotenoid metabolism and pigmentation. Data analysis Following sum normalization, the processed metabolomic data were analyzed using the ropls package in R. Multivariate statistical analyses were performed, including Pareto-scaled principal component analysis (PCA) to explore overall sample distribution, and orthogonal partial least squares discriminant analysis (OPLS-DA) to identify group-specific metabolic differences. Model robustness was assessed using 7-fold cross-validation and response permutation testing. Variable importance in projection (VIP) scores was calculated from the OPLS-DA model to evaluate each metabolite’s contribution to group separation. Metabolites with VIP scores greater than 1 and p-values less than 0.05 (determined by Student’s T-test) were considered significantly altered. Pearson’s correlation analysis was conducted to assess relationships between selected metabolite pairs. Pathway enrichment analysis of differentially expressed metabolites (DEMs) was performed using the Phyper function in R, based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Significantly enriched pathways were identified using a modified Fisher’s exact test, with a threshold of p < 0.05. Results Quality control The response intensity and retention times of peaks in the quality control (QC) samples showed high overlap, indicating minimal variation due to instrumental error (Fig. 1 A and B). Principal component analysis (PCA) revealed that QC samples clustered tightly, demonstrating strong experimental repeatability (Fig. 1 C and D). Additionally, Hotelling’s T² analysis confirmed that all samples fell within the 99% confidence interval, suggesting the absence of outliers (Fig. 1 E and F). These results collectively indicate that the observed metabolic differences are likely attributable to biological variation among the experimental groups rather than technical artifacts. Identification and quantification of metabolites In total, 1,044 metabolites were identified in positive ion mode and 963 in negative ion mode across all samples. Figure 2 illustrates the distribution of identified metabolites by chemical classification among the control, coloration, and decoloration groups of blood parrotfish. The most abundant classes included lipids and lipid-like molecules (30.64%), organic acids and derivatives (19.03%), organoheterocyclic compounds (9.97%), organic oxygen compounds (7.92%), benzenoids (7.52%), phenylpropanoids and polyketides (4.34%), and organic nitrogen compounds (2.44%). Metabolites that could not be assigned to a specific chemical class were categorized as 'undefined'. PCA and OPLS-DA analysis Principal component analysis (PCA) was performed on all skin samples and revealed clear separations between multiple comparison groups, including Wk6C vs Wk0C, Wk12C vs Wk6C, Wk6AX vs Wk0C, Wk6AX vs Wk6C, Wk12AX vs Wk12C, Wk12AX vs Wk6AX, Wk12AXM vs Wk12C, and Wk12AXM vs Wk12AX, in both negative (Fig. 3 A) and positive ion modes (Fig. 3 B). These results confirm the validity and reliability of the metabolomic data. Further differentiation among sample groups was achieved using orthogonal partial least squares discriminant analysis (OPLS-DA). The OPLS-DA models demonstrated distinct separations across the same comparison groups in both ionization modes (Fig. 4 A and B). Model performance was evaluated using R²Y and Q² values, both exceeding 0.5 in positive and negative modes (Fig. S2A and B), indicating strong model validity and predictive capability. These findings support the presence of biologically meaningful metabolic differences among the experimental groups. Differential metabolites Based on volcano plot analyses across eight pairwise comparisons, a total of 97 differentially expressed metabolites (DEMs) were identified in the Wk6C vs Wk0C group, including 60 upregulated and 37 downregulated metabolites. In the Wk12C vs Wk6C group, 39 DEMs were detected (29 upregulated, 10 downregulated). The Wk6AX vs Wk0C comparison revealed 162 DEMs (101 upregulated, 61 downregulated), while Wk6AX vs Wk6C showed 47 DEMs (18 upregulated, 29 downregulated). For Wk12AX vs Wk12C, 99 DEMs were identified (35 upregulated, 64 downregulated), and Wk12AX vs Wk6AX yielded 54 DEMs (18 upregulated, 36 downregulated). In the Wk12AXM vs Wk12C group, 9 DEMs were found (3 upregulated, 6 downregulated), and 28 DEMs (18 upregulated, 10 downregulated) were identified in Wk12AXM vs Wk12AX. These results were consistent across both negative (Fig. 5 A–H) and positive ion modes (Fig. 6 A–H), highlighting significant metabolic alterations in the skin of juvenile blood parrotfish across control (C), coloration (AX), and decoloration (AXM) treatments. To visualize differences in skin metabolite expression across groups, hierarchical clustering analysis was performed and presented as heatmaps. In the negative ion mode (Fig. 7 A–H), the Wk6C vs Wk0C comparison revealed 22 upregulated and 48 downregulated metabolites. In Wk12C vs Wk6C, 8 metabolites were upregulated and 14 downregulated. The Wk6AX vs Wk0C group showed 21 upregulated and 41 downregulated metabolites, while Wk6AX vs Wk6C had 14 upregulated and 17 downregulated. For Wk12AX vs Wk12C, 29 metabolites were upregulated and 19 downregulated; Wk12AX vs Wk6AX showed 17 upregulated and 7 downregulated; Wk12AXM vs Wk12C had 1 upregulated and 4 downregulated; and Wk12AXM vs Wk12AX revealed 4 upregulated and 9 downregulated metabolites. Similarly, in the positive ion mode (Fig. 8 A–G), Wk6C vs Wk0C showed 9 upregulated and 18 downregulated metabolites. Wk12C vs Wk6C had 5 upregulated and 15 downregulated; Wk6AX vs Wk0C revealed 28 upregulated and 55 downregulated; Wk6AX vs Wk6C had 2 upregulated and 11 downregulated; Wk12AX vs Wk12C showed 26 upregulated and 20 downregulated; Wk12AX vs Wk6AX had 17 upregulated and 11 downregulated; and Wk12AXM vs Wk12AX showed 3 upregulated and 10 downregulated metabolites. However, no distinct clustering was observed in the Wk12AXM vs Wk12C comparison under positive ion mode, likely due to the absence of significant differences in metabolite expression between these groups. Metabolic pathway analysis Metabolic pathway enrichment analysis revealed distinct biological processes associated with each comparison group. In the Wk6C vs Wk0C group, the most significantly enriched pathways were galactose metabolism and ABC transporters (Fig. 9 A). For Wk12C vs Wk6C, enriched pathways included sphingolipid signaling, sphingolipid metabolism, and ferroptosis (Fig. 9 B). In the Wk6AX vs Wk0C group, key enriched pathways were protein digestion and absorption, aminoacyl-tRNA biosynthesis, ABC transporters, and amino acid biosynthesis (Fig. 9 C). Similarly, ABC transporters were the dominant pathway in the Wk6AX vs Wk6C comparison (Fig. 9 D). In the Wk12AX vs Wk12C group, enriched pathways included protein digestion and absorption, aminoacyl-tRNA biosynthesis, ABC transporters, and amino acid biosynthesis (Fig. 9 E). The Wk12AX vs Wk6AX group showed enrichment in protein digestion and absorption, thiamine metabolism, glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis, amino acid biosynthesis, methane metabolism, and ABC transporters (Fig. 9 F). For Wk12AXM vs Wk12C, the most enriched pathways were D-arginine and D-ornithine metabolism, taurine and hypotaurine metabolism, and ABC transporters (Fig. 9 G). Lastly, in the Wk12AXM vs Wk12AX group, galactose metabolism and ABC transporters were the most significantly enriched pathways (Fig. 9 H). Discussion Metabolites represent the end products of gene expression and reflect the physiological state of an organism (Jordan et al., 2009 ). In this study, we identified a diverse array of metabolites with varying abundances and chemical classifications, revealing metabolic pathways associated with body coloration in juvenile blood parrotfish under conditions of carotenoid presence or absence. In the Wk6C vs Wk0C and Wk12C vs Wk6C comparisons, several metabolites were significantly downregulated, including all-trans-4-ketoretinoid acid, 1-stearoyl-2-myristoyl-sn-glycero-3-phosphocholine, DL-arginine, 2-arachidonoyl-1-palmitoyl-sn-glycero-3-phosphoethanamine, sn-glycerol-3-phosphoethanolamine, N-(1-3-dihydroxyoctadeca-4,14-dien-2-yl) docosanimidic acid, N-tetracosenoyl-4-sphingenine, and harpagoside. Most of these metabolites belong to the lipid and lipid-like molecules category, except DL-arginine, which is classified under organic acids and derivatives. The downregulation of DL-arginine is particularly noteworthy, as previous research has shown that L-arginine, associated with ABC transporters, plays a critical role in carotenoid deposition (Yang et al., 2021 ). Its reduced expression in this study may contribute to impaired carotenoid transport and accumulation, leading to decoloration. Furthermore, since carotenoids are lipid-soluble molecules, their absorption, metabolism, and transport are influenced by dietary fat content (Desmarchelier & Borel, 2017 ; Ribaya-Mercado, 2002 ). These findings suggest that both lipid metabolism and amino acid-related pathways are integral to the regulation of carotenoid-based pigmentation in blood parrotfish. In the comparisons between Wk12AXM vs Wk12C and Wk12AXM vs Wk12AX groups, several metabolites were significantly downregulated, including PC 38:7, N-tetracosenoyl-4-sphingenine, lauroyl-1-carnitine, geranic acid, corticosterone, (Z)-5,8,11-trihydroxyoctadec-9-enoic acid, 21-hydroxypregnenolone, and prostaglandin I2. This reduction in metabolite levels is associated with diminished carotenoid-based body coloration in juvenile blood parrotfish. Most of these metabolites belong to the lipid and lipid-like molecule category, which plays a critical role in carotenoid absorption, transport, and deposition in vertebrate tissues. As previously discussed, carotenoids are lipophilic compounds, and their bioavailability is closely linked to lipid metabolism. Therefore, the observed decrease in these lipid-related metabolites likely contributes to reduced carotenoid accumulation and subsequent loss of pigmentation in the decoloration group. Astaxanthin (3,3′-dihydroxy-4,4′-diketo-β,β-carotene), a ketocarotenoid pigment, is a key metabolite known for its pigmentation properties in ornamental fish (Casella et al., 2020). In this study, astaxanthin levels were significantly elevated in the Wk6AX vs Wk0C, Wk6AX vs Wk6C, Wk12AX vs Wk12C, and Wk12AX vs Wk6AX comparisons, indicating its direct role in enhancing body coloration in juvenile blood parrotfish. Similar pigmentation effects of astaxanthin have been reported in various ornamental and aquaculture species, including discus fish ( Symphysodon spp.), clown anemonefish ( Amphiprion ocellaris ), blood parrotfish ( Cichlasoma citrinellum × Cichlasoma synspilum ), red porgy ( Pagrus pagrus ), and Oscar fish ( Astronotus ocellatus ) (Song et al., 2017 ; Ho et al., 2013 ; Li et al., 2018 ; Nogueira et al., 2021 ; Alishahi et al., 2015 ). Additionally, (+)-α-tocopherol, a fat-soluble vitamin E metabolite, was significantly upregulated in the Wk6AX vs Wk0C group. This compound may enhance carotenoid coloration by facilitating carotenoid transport via the scavenger receptor class B type 1 (SR-B1), which mediates uptake in the small intestine before distribution to target tissues. Previous studies have shown that increased dietary levels of vitamin E can improve pigment deposition in fish (Bjerkeng et al., 1999 ), further supporting its potential synergistic role in carotenoid-based pigmentation. Similarly, all-trans-4-ketoretinoic acid, which is a metabolite of all-trans-retinoic acid, a form of retinoid (vitamin A/retinol) was highly expressed in blood parrotfish in both Wk6AXvsWk6C and Wk12AXvsWk12C comparisons. This suggests a potential increase in skin astaxanthin levels. Carotenoids, once absorbed in the gut, are metabolized into vitamin A (Reboul, 2013 ), a process influenced by the enzyme BCO1 (Hessel et al., 2007 ). Therefore, elevated retinol levels may contribute to enhanced astaxanthin accumulation in the skin (Gamer et al., 2010 ). In this study, several metabolites associated with lipid metabolism including glycerophosphocholine, 1-stearoyl-2-oleoyl-sn-glycero-3-phosphocholine (SOPC), 1-stearoyl-2-hydroxy-sn-glycero-3-phosphocholine, alpha-linolenic acid, 1,2-ditetradecanoyl-sn-glycero-3-phosphocholine, 1-palmitoyl-2-myristoyl-sn-glycero-3-phosphocholine, 1-oleoyl-2-myristoyl-sn-glycero-3-phosphocholine, 1,2-dipentadecanoyl-sn-glycero-3-phosphocholine, prostaglandin E1, thymol-β-D-glucoside, myristic acid, octadecanoic acid, PG 36:5, (Z)-5,8,11-trihydroxyoctadec-9-enoic acid, (10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid, 9-(2,3-dihydroxypropoxy)-9-oxononanoic acid, and 21-hydroxypregnenolone—were significantly elevated in Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, and Wk12AXvsWk6AX groups. These increases suggest enhanced carotenoid transport and deposition in the skin of blood parrotfish. This is consistent with findings by Yang et al. ( 2021 ), who reported that lipid metabolism-related compounds such as docosahexaenoic acid, arachidonic acid, linoleic acid, eicosapentaenoic acid, SOPC, dodecanoic acid, and myristic acid play key roles in carotenoid deposition in yellow discus fish. Lipids are essential macromolecules for carotenoid transport due to the lipophilic nature of carotenoids (Das & Biswas, 2016 ; Vo et al., 2021 ). In animals, carotenoids are primarily absorbed in the small intestine after incorporation into mixed micelles formed by bile salts, phospholipids, dietary lipids, and their hydrolysates (Yang et al., 2021 ). Following absorption, carotenoids accumulate mainly in the liver and are transported via lipoproteins through the bloodstream to target tissues such as muscle, skin, gonads, and intestines (Bjerkeng, 2008 ; Parker, 1996 ). Supporting this, Ahi et al. ( 2020a ) reported high expression of the plin6 gene linked to lipid metabolism in the yellow skin regions of Tropheus duboisi . Similarly, apod , a gene associated with lipid transport, has been implicated in carotenoid-based coloration in the golden pheasant and other bird species (Gao et al., 2016 ; Walsh et al., 2012 ). Vo et al. ( 2021 ) also demonstrated that body coloration in Atlantic salmon is closely tied to lipid digestion, with lipoproteins, serum albumin, and fatty acid-binding proteins playing critical roles in carotenoid absorption, transport, and deposition. The ABC transporters pathway was significantly enriched in Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, and Wk12AXvsWk6AX blood parrotfish, indicating active carotenoid deposition linked to skin pigmentation. SR-B1, a member of the ABC transporter family, is well-documented for its role in carotenoid transport and absorption in mammals (Kotake-Nara & Nagao, 2011 ; Reboul & Borel, 2011 ), suggesting that similar mechanisms may operate in fish. These findings support the hypothesis that ABC transporters are key mediators of carotenoid uptake and binding in blood parrotfish tissues (Rajasingh et al., 2006 ; Wade et al., 2009 ), contributing to the development of vibrant coloration. Interestingly, enrichment of the ABC transporter pathway was also observed in Wk6CvsWk0C, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX blood parrotfish. This may be attributed to the presence of carotenoids in the control diet, although further investigation is needed to validate this hypothesis. These findings highlight the potential involvement of ABC transporters even under baseline dietary conditions, suggesting a broader role in carotenoid handling beyond supplementation. Future research should focus on identifying the specific transporter proteins responsible for intracellular carotenoid trafficking in fish, which would deepen our understanding of their contribution to pigmentation and nutrient metabolism. Comparison of the enriched glycine, serine, and threonine metabolism pathway in Wk12AXvsWk6AX blood parrotfish with findings from Rodríguez et al. (2020) revealed that the phgdh and shmt2 genes were highly expressed in red frogs, facilitating the biosynthesis of serine and glycine. This observation aligns with our findings of enriched aminoacyl-tRNA biosynthesis and amino acid biosynthesis pathways in Wk6AXvsWk0C, Wk12AXvsWk12C, and Wk12AXvsWk6AX groups. These results suggest a conserved role for these metabolic pathways in pigment-related physiological processes. However, targeted metabolomics studies are needed to confirm the presence and functional significance of these specific amino acids in blood parrotfish. Additionally, the protein digestion and absorption pathway were significantly enriched across the same comparisons, suggesting that carotenoid fragments may interact with proteins during metabolic processing (Reboul, 2019 ). This observation is consistent with findings in humans, where carotenoids are incorporated into mixed micelles and are potentially transported via carrier proteins such as SR-B1, CD36, and NPC1L1 (Reboul, 2019 ). Despite these parallels, the specific proteins responsible for intracellular carotenoid transport in fish have yet to be identified, highlighting an important area for future research. Moreover, studies by McClements and Li ( 2010 ) and Soukoulis and Bohn (2015) have demonstrated that proteins contribute to the emulsification of polar dietary compounds during digestion. This further supports the potential interaction between carotenoids and proteins, reinforcing their role in facilitating nutrient absorption and metabolic integration. Conversely, taurine which is a water-soluble bioactive compound (Spitze et al., 2003 ) was linked to the enrichment of the taurine and hypotaurine metabolism pathway in Wk12AXMvsWk12C blood parrotfish. This pathway may negatively affect carotenoid absorption, transport, and deposition in tissues, potentially leading to reduced skin pigmentation. Despite this, taurine plays a crucial role in maintaining metabolic homeostasis. Its involvement in galactose metabolism, as observed in Wk12AXMvsWk12AX and Wk6CvsWk0C groups, supports glycolytic activity and contributes to the overall physiological function of the fish. Additionally, the enrichment of the D-arginine and D-ornithine metabolism pathway in Wk12AXMvsWk12C blood parrotfish suggests increased protein synthesis and enhanced detoxification capacity. While carotenoids are widely recognized for their antioxidant and immune-boosting properties in animals (Maoka, 2020 ), their role in immune modulation may paradoxically suppress visible coloration. For example, in nestling great tits ( Parus major ), elevated immune activity stimulated by carotenoids was associated with reduced plumage coloration (Fitze et al., 2007 ). This highlights a potential trade-off between immune function and pigmentation, which may also be relevant in fish. Conclusion In this study, UHPLC-Q-TOF/MS was utilized to profile key metabolites and pathways associated with differential skin coloration in juvenile blood parrotfish. A total of 2,007 metabolites were identified: 1,044 in positive ion mode and 963 in negative ion mode. OPLS-DA analysis revealed clear distinctions in skin metabolite profiles between the coloration and decoloration groups. Metabolites such as astaxanthin, all-trans-4-ketoretinoic acid, octadecanoic acid, myristic acid, (+)-α-tocopherol, and various phosphocholines were significantly elevated in the coloration group, while compounds like prostaglandin I2 and lauroyl-1-carnitine were reduced in the decoloration group. KEGG pathway enrichment analysis further highlighted the involvement of ABC transporters, amino acid biosynthesis, protein digestion and absorption, aminoacyl-tRNA biosynthesis, and glycine, serine, and threonine metabolism in the coloration group. In contrast, galactose metabolism, D-arginine and D-ornithine metabolism, and taurine and hypotaurine metabolism were predominantly enriched in the decoloration group. Collectively, these findings provide novel insights into the metabolomic mechanisms underlying carotenoid-driven pigmentation in juvenile blood parrotfish, emphasizing the influence of dietary carotenoids on skin coloration and metabolic regulation. Abbreviations AX, Coloration diet (0.45 g/kg astaxanthin); AXM, Decoloration diet (0.45 g/kg + 0 g/kg); C, Control; CE, Collision energy; CUR, Curtain gas; Da, Dalton; DEMs, Differentially expressed metabolites; DP, Declustering potential; ESI, Electro spray ionization; HP-LC, High performance-liquid chromatography; IDA, Information-dependent acquisition; ISVF, Ion spray voltage floating; KEGG, Kyoto encyclopedia of genes and genomes; LC-MS, Liquid chromatography-mass spectrometry; g, Gravity; SD, Standard deviation; SPSS, Statistical package for the social sciences; UHPLC-Q-TOF/MS, Ultrahigh-pressure liquid chromatography quadrupole time-of-flight mass spectrometry; OPLS-DA, Orthogonal partial least-squares discriminant analysis; PCA, Principal component analysis; QC, Quality control; VIP, Variable importance in the projection. Declarations Conflicts of interest The authors declare that they have no conflicts of interest. Author Contribution Z-Z. C, B. W., J-Z. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7107321","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":506553955,"identity":"f32fb58f-7445-48cf-b886-93a3b6199250","order_by":0,"name":"Adekunle David Micah","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYDACZiiSYGBgPMBQwcBgAJORIEILwwGGM8RoYUDWwthGhBbdduaHnwtqrOUkZ+QeOPBx3mF5c/bmAww/KhgSZzZg12J2mM1YesaxdGNpibyEgzO3HTbc2XMsgbHnDEPibBy2mB3mYZDmYTucOE8ix+Aw77bDjBtu5BgwA12YOA+3FubfPP8O14O1/J1z2J4YLWzSvG2HE6RBWhgbDifCteB2GJuZNW9fuuHMnjcGB3uOpSdvOHMs4WDPGQljnN4/f/jxbZ5v1vISx3MMH/yosbbdcLz54IMfFTayMw7gsAYNNIPJA/gjEhXUEa1yFIyCUTAKRg4AAJJjXkCfd/EMAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai Ocean University","correspondingAuthor":true,"prefix":"","firstName":"Adekunle","middleName":"David","lastName":"Micah","suffix":""},{"id":506553956,"identity":"93fae3bc-839f-4726-9a59-c34e96f5a9fc","order_by":1,"name":"Bin Wen","email":"","orcid":"","institution":"Shanghai Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Wen","suffix":""},{"id":506553957,"identity":"9af9da9c-7219-46e8-ab75-5adf10c76d6e","order_by":2,"name":"Abdullateef Yusuf","email":"","orcid":"","institution":"Shanghai Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Abdullateef","middleName":"","lastName":"Yusuf","suffix":""},{"id":506553958,"identity":"f23a7fe6-c352-4fe3-99cd-de63f97661b1","order_by":3,"name":"Meriyamoh Mero Onimisi","email":"","orcid":"","institution":"Kogi State University","correspondingAuthor":false,"prefix":"","firstName":"Meriyamoh","middleName":"Mero","lastName":"Onimisi","suffix":""},{"id":506553959,"identity":"b706b7bf-5fa4-4e67-9730-ff113c72e489","order_by":4,"name":"Samuel Olusegun Adeyemi","email":"","orcid":"","institution":"Kogi State University","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"Olusegun","lastName":"Adeyemi","suffix":""},{"id":506553960,"identity":"3b06337a-e7f9-4e2b-89f4-720b6c926f8d","order_by":5,"name":"Jian-Zhong Gao","email":"","orcid":"","institution":"Shanghai Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Jian-Zhong","middleName":"","lastName":"Gao","suffix":""},{"id":506553961,"identity":"fb473918-3313-46bf-853d-d7112f952ab7","order_by":6,"name":"Zai-Zhong Chen","email":"","orcid":"","institution":"Shanghai Ocean University","correspondingAuthor":false,"prefix":"","firstName":"Zai-Zhong","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-07-12 09:53:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7107321/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7107321/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90159869,"identity":"b0449683-bc1d-4f5e-a3eb-8751509c83c1","added_by":"auto","created_at":"2025-08-29 08:55:25","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":304924,"visible":true,"origin":"","legend":"\u003cp\u003eQuality control of metabolomic data from blood parrotfish skin samples. Total ion chromatograms are shown for (A) negative ion mode and (B) positive ion mode. Principal component analysis (PCA) plots illustrate sample clustering in (C) negative ion mode and (D) positive ion mode. Hotelling’s T2 plots for outlier detection are presented in (E) negative ion mode and (F) positive ion mode. Samples include control, coloration, and decoloration groups.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/f11ee87a6eff19d3e2786edf.jpeg"},{"id":90159870,"identity":"2a088616-bd53-4d2c-aaf3-de1297e6bb17","added_by":"auto","created_at":"2025-08-29 08:55:25","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":295383,"visible":true,"origin":"","legend":"\u003cp\u003eChemical classification of identified metabolites across control, coloration, and decoloration groups in juvenile blood parrotfish.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/ee002abba75633cc9f06624f.jpeg"},{"id":90159871,"identity":"3a3ca895-547d-4cf6-a31b-b1ad37e78d5c","added_by":"auto","created_at":"2025-08-29 08:55:25","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":478654,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Component Analysis (PCA) of skin metabolite profiles in juvenile blood parrotfish under negative ion mode (A) and positive ion mode (B). Comparisons include Wk6CvsWk0C, Wk12CvsWk6C, Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, Wk12AXvsWk6AX, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX. Group labels: C = control, AX = coloration, AXM = decoloration.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/88746767a17ab47f9a40719d.jpeg"},{"id":90160253,"identity":"59479cd0-6624-41c3-b165-8fcb4c83a52c","added_by":"auto","created_at":"2025-08-29 09:03:25","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":510867,"visible":true,"origin":"","legend":"\u003cp\u003eOPLS-DA score plots illustrating metabolic differentiation among blood parrotfish groups under negative ion mode (A) and positive ion mode (B). Comparisons include Wk6CvsWk0C, Wk12CvsWk6C, Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, Wk12AXvsWk6AX, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX. Group labels: C = control, AX = coloration, AXM = decoloration.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/f2cd4f6e1c8426f5f1580982.jpeg"},{"id":90160254,"identity":"f9cedc45-78f5-45f9-9536-18db3ccf8828","added_by":"auto","created_at":"2025-08-29 09:03:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":191399,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano plots illustrating differential metabolite expression across eight comparison groups in juvenile blood parrotfish under negative ion mode (A–H): Wk6CvsWk0C, Wk12CvsWk6C, Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, Wk12AXvsWk6AX, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX. Group labels: C = control, AX = coloration, AXM = decoloration. Black dots represent non-significant metabolites, red dots indicate upregulated metabolites, and blue dots indicate downregulated metabolites.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/7be16183a4013b09269abff8.png"},{"id":90159873,"identity":"d0ac7604-fce6-47c8-a8ab-45f178ab87aa","added_by":"auto","created_at":"2025-08-29 08:55:25","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":295858,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano plots showing differential metabolite expression across eight comparison groups in juvenile blood parrotfish under positive ion mode (A-H): Wk6CvsWk0C, Wk12CvsWk6C, Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, Wk12AXvsWk6AX, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX. Group labels: C = control, AX = coloration, AXM = decoloration. Black dots represent non-significant metabolites, red dots indicate upregulated metabolites, and blue dots indicate downregulated metabolites.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/0b1256d85abd17d4d237c0bd.jpeg"},{"id":90161190,"identity":"4f8c39d1-9144-4dd5-a98e-31bcbebc4b3b","added_by":"auto","created_at":"2025-08-29 09:11:25","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1163753,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmaps of differential metabolite expression in blood parrotfish skin across eight comparison groups under negative ion mode (A-H): Wk6CvsWk0C, Wk12CvsWk6C, Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, Wk12AXvsWk6AX, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX. Group labels: C = control, AX = coloration, AXM = decoloration.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/7fa5da8f7c0fbe4fa8310a3a.jpeg"},{"id":90159888,"identity":"693a3f14-dda7-41b2-a1e4-0084a1e21d4f","added_by":"auto","created_at":"2025-08-29 08:55:25","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1116899,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmaps of differential metabolite expression in blood parrotfish skin across eight comparison groups under positive ion mode (A–H): Wk6CvsWk0C, Wk12CvsWk6C, Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, Wk12AXvsWk6AX, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX. Group labels: C = control, AX = coloration, AXM = decoloration.\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/9a4331e1b13f655bf813749b.jpeg"},{"id":90159875,"identity":"fc19cfbb-97a0-4515-8451-f748695651c5","added_by":"auto","created_at":"2025-08-29 08:55:25","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":392719,"visible":true,"origin":"","legend":"\u003cp\u003ePathway mapping based on differential metabolites identified in blood parrotfish skin across eight comparison groups (A–H): Wk6CvsWk0C, Wk12CvsWk6C, Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, Wk12AXvsWk6AX, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX. Group labels: C = control, AX = coloration, AXM = decoloration. Bubble size represents the impact of each pathway, while bubble color indicates statistical significance, ranging from highest (red) to lowest (green).\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/310dd07c2d76a3d5504638ec.jpeg"},{"id":98624013,"identity":"2a93d6b3-4d48-49be-af6d-f507fbc8c4f0","added_by":"auto","created_at":"2025-12-19 17:07:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5553980,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/b32f5c01-6763-4cbf-8531-135c0201c237.pdf"},{"id":90161448,"identity":"4c8e021c-0630-4e9d-87f7-32d4f682d80c","added_by":"auto","created_at":"2025-08-29 09:19:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":290263,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigurefile.docx","url":"https://assets-eu.researchsquare.com/files/rs-7107321/v1/563e5df54058c9ce00cdca15.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Metabolic Mechanisms of Coloration and Decoloration in Juvenile Blood Parrotfish (Vieja melanurus ♀ × Amphilophus citrinellus ♂) Revealed by UHPLC-Q-TOF/MS","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSkin pigmentation is a key phenotypic trait in fish, governed by various specialized pigment cells known as chromatophores. These cells are classified based on the pigments they contain into melanophores (black/brown), xanthophore (yellow), erythrophores (orange/red), iridophores (iridescent), leucophores (white), and cyanophores (blue) (Fujii, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Burton, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Pigment cells store pigments endogenously within the cell (Tripathy et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Among these, carotenoids (lipophilic molecules) play a central role in coloration. Structurally, carotenoids are divided into carotenes (hydrocarbons without oxygen, e.g., α-carotene, β-carotene, γ-carotene) and xanthophylls (oxygenated derivatives, e.g., zeaxanthin, lutein, canthaxanthin, astaxanthin), with approximately 850 (800 xanthophylls and 50 carotenes) types identified in nature (Maoka, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Xanthophylls are particularly important in producing red, orange, yellow, and pink hues in both aquaculture and ornamental fish species (Lim et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Maoka, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Jin et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Carotenoids are obtained from natural sources such as marine crustaceans (\u003cem\u003ePandalus borealis\u003c/em\u003e), plants, fungi (\u003cem\u003ePhaffia rhodozyma\u003c/em\u003e), and algae (\u003cem\u003eHaematoccocus pluvialis\u003c/em\u003e, \u003cem\u003eChlorella zofingiensis\u003c/em\u003e, \u003cem\u003eC. sorokiniana\u003c/em\u003e, and \u003cem\u003eNeochloris wimmeri\u003c/em\u003e), or synthesized chemically (e.g. astaxanthin, canthaxanthin, capsanthin) (Jiao et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lim et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yadavalli et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Numerous studies have explored the effects of astaxanthin supplementation on fish pigmentation, including clown anemonefish (\u003cem\u003eAmphiprion ocellaris\u003c/em\u003e) (Clark, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), dwarf gourami (\u003cem\u003eTrichogaster lalius\u003c/em\u003e) (Baron et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), red devil (\u003cem\u003eCichlosoma citrinellum\u003c/em\u003e) (Pan and Chien, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), and Hong Kong grouper (\u003cem\u003eEpinephelus akaara\u003c/em\u003e) (Song et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Notably, the absence of dietary carotenoids in captive or cultured fish can lead to significant loss of pigmentation (Ahi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBody coloration can be maintained through dietary supplementation with astaxanthin, as fish are unable to synthesize this carotenoid \u003cem\u003ede novo\u003c/em\u003e. While metabolic studies on carotenoids remain limited, research at the genetic and transcriptomic levels has provided valuable insights into the molecular mechanisms underlying carotenoid-based coloration in aquatic species. For instance, Ahi et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e) identified several genes such as \u003cem\u003edhrsx\u003c/em\u003e, \u003cem\u003enlrc3\u003c/em\u003e, \u003cem\u003etcaf2\u003c/em\u003e, \u003cem\u003eurah\u003c/em\u003e, and \u003cem\u003ettc39b\u003c/em\u003e that are involved in the metabolic regulation of carotenoid-dependent pigmentation. Notably, \u003cem\u003ettc39b\u003c/em\u003e exhibited elevated expression in the red skin of cichlid genera \u003cem\u003eTropheus\u003c/em\u003e and \u003cem\u003eAulonocana\u003c/em\u003e. Additional genes implicated in carotenoid coloration across vertebrates include the ketolase enzyme \u003cem\u003ecyp2j19\u003c/em\u003e (Mundy et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), the lipoprotein receptor \u003cem\u003esr-b1\u003c/em\u003e/\u003cem\u003escarb1\u003c/em\u003e (Toomey et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and the carotenoid cleaving enzyme \u003cem\u003ebco2\u003c/em\u003e (Gazda et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRecent metabolomic analyses have shed light on the biochemical pathways involved in carotenoid deposition. Yang et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) identified several key metabolites including L-arginine (associated with ABC transporters), docosahexaenoic acid (DHA), arachidonic acid, linoleic acid, eicosapentaenoic acid (EPA), 1-stearoyl-2-oleoyl-sn-glycerol-3-phosphocholine, dodecanoic acid, and myristic acid as playing significant roles in lipid metabolism and carotenoid accumulation. Complementing these findings, Zhu et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported that increased dietary intake of arachidonic acid enhanced carotenoid uptake, transport, and accumulation in the red-colored leopard coral grouper. Additional metabolic studies exploring pigmentation and body color regulation have been documented by Cho et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), Wang et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), Wei et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and Li et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Despite these advances, research on the metabolic mechanisms underlying body color formation in relation to the presence or absence of dietary carotenoids in fish remains limited.\u003c/p\u003e\u003cp\u003eThe blood parrotfish (\u003cem\u003eVieja melanurus\u003c/em\u003e \u003cb\u003e♀\u003c/b\u003e \u003cem\u003e\u0026times; Amphilophus citrinellus ♂\u003c/em\u003e) is a hybrid species developed in Taiwan during the late 1980s. It has gained widespread popularity in countries suc as China and Japan due to its vibrant red coloration and distinctive plump body shape (Sui et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The striking red hue is highly valued by ornamental fish enthusiasts and significantly influences market price within the aquarium trade. To enhance body coloration, various studies have investigated the effects of dietary astaxanthin supplementation in blood parrotfish. For instance, Li et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) reported that synthetic astaxanthin significantly improved skin pigmentation. Similarly, Song et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Li et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) demonstrated that a combination of alfalfa saponins and natural astaxanthin positively influenced body coloration. More recently, Micah et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that astaxanthin supplementation increased both skin redness and chromatophore cells density in juvenile blood parrotfish. Despite these findings, knowledge of the specific metabolites involved in carotenoid-based pigmentation remains limited. In the present study, we employed untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with time-of-flight mass spectrometry (UHPLC-Q-TOF MS) to investigate skin metabolite differences between pigmented and non-pigmented juvenile blood parrotfish. The primary objective was to identify and characterize key metabolic pathways and compounds metabolites associated with astaxanthin-induced coloration and its absence.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cb\u003eAnimal maintenance and handling procedures\u003c/b\u003e\u003c/p\u003e\u003cp\u003e This study was approved by the Institutional Animal Care and Committee (IACUS) of Shanghai Ocean University, Shanghai, China. All procedures involved in the handling and treatment were conducted following the guidelines of the IACUS on the care and use of animals for scientific purposes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExperimental diet formulation and proximate composition analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwo experimental diets with identical basal composition (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were formulated for juvenile blood parrotfish. The treatment diet was supplemented with 0.45 g/kg of synthetic astaxanthin (Carophyll\u0026reg; pink 10% CWS, DSM Nutritional Products Ltd). All feed ingredients were finely ground, sieved, and thoroughly mixed to ensure homogeneity. Distilled water was added to the mixture to form a cohesive dough, which was then extruded into 1 mm diameter pellets. The pellets were air-dried, sieved, and sorted to ensure uniform size. To preserve astaxanthin stability, both diets were stored at -20\u0026deg;C.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComposition of dietary ingredients and proximate analysis of basal and treatment diets.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeed ingredients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBasal diet (g/kg)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTreatment diet (g/kg)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eFish meal (imported)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e400\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eSoybean meal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eCotton seed meal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eFish oil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eSoybean oil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eWheat flour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eWheat\u0026nbsp;middling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eMineral premix\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ec\u003c/sup\u003eVitamin premix\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eCellulose (binder)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003csup\u003ed\u003c/sup\u003eAstaxanthin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProximate analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMoisture content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDry matter content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsh content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrude lipid (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrude protein (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAstaxanthin (g/kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.471\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003ea\u003c/sup\u003eYuehai Feed Mill, Zhejiang, China. \u003csup\u003eb\u003c/sup\u003ePer kg mineral premix contains: 0.8 g Co; 0.02 g Se; 3 g Cu; 10 g Zn; 3.8 g Mn; 1 g Fe; 12g Mg; 90 g K; 10.5 g Ca. \u003csup\u003ec\u003c/sup\u003ePer kg vitamin premix contains: 8\u0026nbsp;million IU of Vitamin A; 5 g Thiamine-HCl; 15 g Riboflavin; 2\u0026nbsp;million IU of Cholecalciferol; 50 g DL-α-Tocopherol; 8 g Pyridoxine-HCl; 10 g Menadione; 0.02 g Cyanocobalamin; 40 g Nicotinamide; 25 g Ca-pantothenate; 2.5 g Folic acid; 0.08 g Biotin; 100 g Inositol. \u003csup\u003ed\u003c/sup\u003eCarophyll\u0026reg; pink 10% CWS, DSM Nutritional products Ltd.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eProximate composition analysis of the basal and treatment diets was conducted following standard procedures outlined by the Association of Official Analytical Chemists (AOAC \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Moisture content was determined by oven-drying samples at 105\u0026deg;C until a constant weight was achieved, and dry matter was calculated by subtracting moisture content from 100%. Crude protein content (N x 6.25) was measured using the Kjeldahl method after acid digestion, with quantification performed using an Auto Kjeldahl System (2300-Autoanalyzer Foss Tecator, Sweden). Crude lipid was assessed via chloroform-methanol extraction, following the method described by Cejas et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Additionally, astaxanthin concentrations in both diets were quantified using a fish astaxanthin ELISA kit (Shanghai Enzyme-linked Biotechnology Co., Ltd. (mlbio) Shanghai, China), according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExperimental fish and rearing conditions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 360 juvenile blood parrotfish, with an average initial weight of 10.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38 g, were obtained from a commercial fish farm in Hainan, China. Prior to the experiment, all fish underwent a two-week acclimation period under laboratory conditions, during which they were fed the control diet. After acclimation, the fish were randomly assigned to 18 glass aquaria (48 cm \u0026times; 45 cm \u0026times; 30 cm) with 20 fish per tank. The experimental design consisted of three dietary treatments, each with six replicates. The control group (C) received a basal diet without astaxanthin for the entire 12-week period. The coloration group (AX) was fed a diet supplemented with 0.45 g/kg of synthetic astaxanthin for 12 weeks. The decoloration group (AXM) was initially fed the AX diets for six weeks, followed by the control diet for the remaining six weeks. Water quality parameters were carefully monitored and maintained throughout both the acclimation and experimental periods. Dissolved oxygen levels averaged 7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 mg/L, temperature was maintained at 26\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C, pH at 7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2, and ammonia levels at 0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 mg/L. Dissolved oxygen, temperature, and pH were measured using Hanna equipment (model H198194), while ammonia concentrations were determined using the HI-700 ammonia kit. The aquaria were part of a recirculating aquaculture system, with 30% of the water replaced daily from the bottom of each tank. Fish were hand-fed to apparent satiation twice daily at 10:00 am and 4:00 pm and maintained under a natural photoperiod. The experimental protocol is illustrated in Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTissue collection for metabolomic analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 36 skin samples, including scales, were collected from juvenile blood parrotfish at weeks 0, 6, and 12 from the control (C), coloration (AX), and decoloration (AXM) groups. Immediately after excision, all samples were snap-frozen in liquid nitrogen to preserve metabolite integrity. Each sample was then section on dry ice (~\u0026thinsp;80 mg) and transferred into a 2 mL Eppendorf tube. For homogenization, 200 \u0026micro;L of distilled water and five ceramic beads were added to each tube, and tissues were homogenized using a bead-based homogenizer. Subsequently, 800 \u0026micro;L methanol/acetonitrile (1:1, v/v) was added to the homogenate for metabolic extraction. The mixture was centrifuged at 14000 x g for 15 mins at 4\u0026deg;C, and the resulting supernatant was collected and dried using a vacuum centrifuge. Dried extracts were reconstituted in 100 \u0026micro;L of acetonitrile/water (1:1, v/v) for subsequent LC-MS analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLC-MS/MS analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMetabolic profiling was conducted using an ultra-high performance liquid chromatography system (UHPLC 1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, AB Sciex) at Shanghai Applied Protein Technology Co., Ltd. For hydrophilic interaction liquid chromatography (HILIC) separation, samples were analyzed using a 2.1 mm x 100 mm ACQUIY UPLC BEH column (1.7 \u0026micro;m particle size; Waters, Ireland). The mobile phase consisted of solvent A (25 mM ammonium acetate and 25 mM ammonium hydroxide in water) and solvent B (acetonitrile). The gradient program began with 85% B for 1 min, linearly decreased to 65% over 11 min, then rapidly dropped to 40% in 0.1 min and held for 4 min. It then increased back to 85% in 0.1 min, followed by a 5 min re-equilibration period.\u003c/p\u003e\u003cp\u003eFor reverse-phase liquid chromatography (RPLC) separation, a 2.1 mm x 100 mm ACQUIY UPLC HSS T3 (1.8 \u0026micro;m particle size; Waters, Ireland) was used. In positive electrospray ionization (ESI) mode, the mobile phase consisted of solvent A (water with 0.1% formic acid) and solvent B (acetonitrile with 0.1% formic acid). In negative ESI negative mode, solvent A was 0.5 mM ammonium fluoride in water, and solvent B was acetonitrile. The gradient started at 1% B for 1.5 min, increased linearly to 99% over 11.5, held for 3.5 min, then returned to 1% in 0.1 min, followed by a 3.4 min re-equilibration. All separation were performed at a flow rate of 0.3 mL/min with the column temperature maintained at 25\u0026deg;C. A 2 \u0026micro;L aliquot of each sample was injected.\u003c/p\u003e\u003cp\u003eThe ESI source parameters were set as follows: Ion Source Gas1 and Gas 2 at 60 psi, curtain gas at 30 psi, source temperature at 600\u0026deg;C, and Ion Spray Voltage Floating (ISVF) at \u0026plusmn;\u0026thinsp;5500 V. For MS-only acquisition, data were collected over an m/z range of 60\u0026ndash;1000 Da with a TOF MS scan accumulation time of 0.20 s per spectrum. For auto MS/MS acquisition, the m/z range was 25 \u0026minus;\u0026thinsp;1000 Da with a product ion scan accumulation time of 0.05 s per spectrum. Product ion scans were acquired using information-dependent acquisition (IDA) in high-sensitivity mode. Collision energy (CE) was set at 35 V with a spread of \u0026plusmn;\u0026thinsp;15 eV, and declustering potential (DP) was set at +\u0026thinsp;60 V and \u0026minus;\u0026thinsp;60 V for positive and negative modes, respectively. Isotopes within 4 Da were excluded, and up to 10 candidate ions were monitored per cycle.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData processing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRaw mass spectrometry data files (wiff.scan format) were first converted to the mzXML format using ProteoWizard MSConvert to enable compatibility with downstream analysis tools. Peak detection, alignment, and quantification were performed using the open-source XCMS software. For peak picking, the \u003cem\u003ecentWave\u003c/em\u003e algorithm was applied with the following parameters: mass accuracy (m/z)\u0026thinsp;=\u0026thinsp;10 ppm, peak width\u0026thinsp;=\u0026thinsp;c(10, 60), and prefilter\u0026thinsp;=\u0026thinsp;c(10, 100). Peak grouping was conducted using bandwidth (bw)\u0026thinsp;=\u0026thinsp;5, m/z width (mzwid)\u0026thinsp;=\u0026thinsp;0.025, and minimum fraction (minfrac)\u0026thinsp;=\u0026thinsp;0.5.\u003c/p\u003e\u003cp\u003eTo annotate isotopes and adducts, the CAMERA (Collection of Algorithms for Metabolite pRofile Annotation) package was employed. From the extracted ion features, only variables with non-zero measurements in more than 50% of samples within at least one experimental group were retained for further analysis to ensure data robustness.\u003c/p\u003e\u003cp\u003eMetabolite identification was performed by matching accurate mass values (within 10 ppm) and MS/MS fragmentation spectra against an in-house spectral database developed using authentic standards (Luo et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhaobing et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This approach enabled high-confidence annotation of metabolites relevant to carotenoid metabolism and pigmentation.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eFollowing sum normalization, the processed metabolomic data were analyzed using the ropls package in R. Multivariate statistical analyses were performed, including Pareto-scaled principal component analysis (PCA) to explore overall sample distribution, and orthogonal partial least squares discriminant analysis (OPLS-DA) to identify group-specific metabolic differences. Model robustness was assessed using 7-fold cross-validation and response permutation testing.\u003c/p\u003e\u003cp\u003eVariable importance in projection (VIP) scores was calculated from the OPLS-DA model to evaluate each metabolite\u0026rsquo;s contribution to group separation. Metabolites with VIP scores greater than 1 and p-values less than 0.05 (determined by Student\u0026rsquo;s T-test) were considered significantly altered. Pearson\u0026rsquo;s correlation analysis was conducted to assess relationships between selected metabolite pairs.\u003c/p\u003e\u003cp\u003ePathway enrichment analysis of differentially expressed metabolites (DEMs) was performed using the Phyper function in R, based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Significantly enriched pathways were identified using a modified Fisher\u0026rsquo;s exact test, with a threshold of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eQuality control\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe response intensity and retention times of peaks in the quality control (QC) samples showed high overlap, indicating minimal variation due to instrumental error (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and B). Principal component analysis (PCA) revealed that QC samples clustered tightly, demonstrating strong experimental repeatability (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and D). Additionally, Hotelling\u0026rsquo;s T\u0026sup2; analysis confirmed that all samples fell within the 99% confidence interval, suggesting the absence of outliers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003eE and F). These results collectively indicate that the observed metabolic differences are likely attributable to biological variation among the experimental groups rather than technical artifacts.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIdentification and quantification of metabolites\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn total, 1,044 metabolites were identified in positive ion mode and 963 in negative ion mode across all samples. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the distribution of identified metabolites by chemical classification among the control, coloration, and decoloration groups of blood parrotfish. The most abundant classes included lipids and lipid-like molecules (30.64%), organic acids and derivatives (19.03%), organoheterocyclic compounds (9.97%), organic oxygen compounds (7.92%), benzenoids (7.52%), phenylpropanoids and polyketides (4.34%), and organic nitrogen compounds (2.44%). Metabolites that could not be assigned to a specific chemical class were categorized as 'undefined'.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePCA and OPLS-DA analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePrincipal component analysis (PCA) was performed on all skin samples and revealed clear separations between multiple comparison groups, including Wk6C vs Wk0C, Wk12C vs Wk6C, Wk6AX vs Wk0C, Wk6AX vs Wk6C, Wk12AX vs Wk12C, Wk12AX vs Wk6AX, Wk12AXM vs Wk12C, and Wk12AXM vs Wk12AX, in both negative (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) and positive ion modes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). These results confirm the validity and reliability of the metabolomic data.\u003c/p\u003e\u003cp\u003eFurther differentiation among sample groups was achieved using orthogonal partial least squares discriminant analysis (OPLS-DA). The OPLS-DA models demonstrated distinct separations across the same comparison groups in both ionization modes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and B). Model performance was evaluated using R\u0026sup2;Y and Q\u0026sup2; values, both exceeding 0.5 in positive and negative modes (Fig. S2A and B), indicating strong model validity and predictive capability. These findings support the presence of biologically meaningful metabolic differences among the experimental groups.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDifferential metabolites\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBased on volcano plot analyses across eight pairwise comparisons, a total of 97 differentially expressed metabolites (DEMs) were identified in the Wk6C vs Wk0C group, including 60 upregulated and 37 downregulated metabolites. In the Wk12C vs Wk6C group, 39 DEMs were detected (29 upregulated, 10 downregulated). The Wk6AX vs Wk0C comparison revealed 162 DEMs (101 upregulated, 61 downregulated), while Wk6AX vs Wk6C showed 47 DEMs (18 upregulated, 29 downregulated). For Wk12AX vs Wk12C, 99 DEMs were identified (35 upregulated, 64 downregulated), and Wk12AX vs Wk6AX yielded 54 DEMs (18 upregulated, 36 downregulated). In the Wk12AXM vs Wk12C group, 9 DEMs were found (3 upregulated, 6 downregulated), and 28 DEMs (18 upregulated, 10 downregulated) were identified in Wk12AXM vs Wk12AX. These results were consistent across both negative (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;H) and positive ion modes (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003eA\u0026ndash;H), highlighting significant metabolic alterations in the skin of juvenile blood parrotfish across control (C), coloration (AX), and decoloration (AXM) treatments.\u003c/p\u003e\u003cp\u003eTo visualize differences in skin metabolite expression across groups, hierarchical clustering analysis was performed and presented as heatmaps. In the negative ion mode (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e7\u003c/span\u003eA\u0026ndash;H), the Wk6C vs Wk0C comparison revealed 22 upregulated and 48 downregulated metabolites. In Wk12C vs Wk6C, 8 metabolites were upregulated and 14 downregulated. The Wk6AX vs Wk0C group showed 21 upregulated and 41 downregulated metabolites, while Wk6AX vs Wk6C had 14 upregulated and 17 downregulated. For Wk12AX vs Wk12C, 29 metabolites were upregulated and 19 downregulated; Wk12AX vs Wk6AX showed 17 upregulated and 7 downregulated; Wk12AXM vs Wk12C had 1 upregulated and 4 downregulated; and Wk12AXM vs Wk12AX revealed 4 upregulated and 9 downregulated metabolites.\u003c/p\u003e\u003cp\u003eSimilarly, in the positive ion mode (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e8\u003c/span\u003eA\u0026ndash;G), Wk6C vs Wk0C showed 9 upregulated and 18 downregulated metabolites. Wk12C vs Wk6C had 5 upregulated and 15 downregulated; Wk6AX vs Wk0C revealed 28 upregulated and 55 downregulated; Wk6AX vs Wk6C had 2 upregulated and 11 downregulated; Wk12AX vs Wk12C showed 26 upregulated and 20 downregulated; Wk12AX vs Wk6AX had 17 upregulated and 11 downregulated; and Wk12AXM vs Wk12AX showed 3 upregulated and 10 downregulated metabolites. However, no distinct clustering was observed in the Wk12AXM vs Wk12C comparison under positive ion mode, likely due to the absence of significant differences in metabolite expression between these groups.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMetabolic pathway analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMetabolic pathway enrichment analysis revealed distinct biological processes associated with each comparison group. In the Wk6C vs Wk0C group, the most significantly enriched pathways were galactose metabolism and ABC transporters (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eA). For Wk12C vs Wk6C, enriched pathways included sphingolipid signaling, sphingolipid metabolism, and ferroptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eB). In the Wk6AX vs Wk0C group, key enriched pathways were protein digestion and absorption, aminoacyl-tRNA biosynthesis, ABC transporters, and amino acid biosynthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). Similarly, ABC transporters were the dominant pathway in the Wk6AX vs Wk6C comparison (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eIn the Wk12AX vs Wk12C group, enriched pathways included protein digestion and absorption, aminoacyl-tRNA biosynthesis, ABC transporters, and amino acid biosynthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eE). The Wk12AX vs Wk6AX group showed enrichment in protein digestion and absorption, thiamine metabolism, glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis, amino acid biosynthesis, methane metabolism, and ABC transporters (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eF). For Wk12AXM vs Wk12C, the most enriched pathways were D-arginine and D-ornithine metabolism, taurine and hypotaurine metabolism, and ABC transporters (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eG). Lastly, in the Wk12AXM vs Wk12AX group, galactose metabolism and ABC transporters were the most significantly enriched pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e9\u003c/span\u003eH).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMetabolites represent the end products of gene expression and reflect the physiological state of an organism (Jordan et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In this study, we identified a diverse array of metabolites with varying abundances and chemical classifications, revealing metabolic pathways associated with body coloration in juvenile blood parrotfish under conditions of carotenoid presence or absence. In the Wk6C vs Wk0C and Wk12C vs Wk6C comparisons, several metabolites were significantly downregulated, including all-trans-4-ketoretinoid acid, 1-stearoyl-2-myristoyl-sn-glycero-3-phosphocholine, DL-arginine, 2-arachidonoyl-1-palmitoyl-sn-glycero-3-phosphoethanamine, sn-glycerol-3-phosphoethanolamine, N-(1-3-dihydroxyoctadeca-4,14-dien-2-yl) docosanimidic acid, N-tetracosenoyl-4-sphingenine, and harpagoside. Most of these metabolites belong to the lipid and lipid-like molecules category, except DL-arginine, which is classified under organic acids and derivatives.\u003c/p\u003e\u003cp\u003eThe downregulation of DL-arginine is particularly noteworthy, as previous research has shown that L-arginine, associated with ABC transporters, plays a critical role in carotenoid deposition (Yang et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Its reduced expression in this study may contribute to impaired carotenoid transport and accumulation, leading to decoloration. Furthermore, since carotenoids are lipid-soluble molecules, their absorption, metabolism, and transport are influenced by dietary fat content (Desmarchelier \u0026amp; Borel, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ribaya-Mercado, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). These findings suggest that both lipid metabolism and amino acid-related pathways are integral to the regulation of carotenoid-based pigmentation in blood parrotfish.\u003c/p\u003e\u003cp\u003eIn the comparisons between Wk12AXM vs Wk12C and Wk12AXM vs Wk12AX groups, several metabolites were significantly downregulated, including PC 38:7, N-tetracosenoyl-4-sphingenine, lauroyl-1-carnitine, geranic acid, corticosterone, (Z)-5,8,11-trihydroxyoctadec-9-enoic acid, 21-hydroxypregnenolone, and prostaglandin I2. This reduction in metabolite levels is associated with diminished carotenoid-based body coloration in juvenile blood parrotfish. Most of these metabolites belong to the lipid and lipid-like molecule category, which plays a critical role in carotenoid absorption, transport, and deposition in vertebrate tissues. As previously discussed, carotenoids are lipophilic compounds, and their bioavailability is closely linked to lipid metabolism. Therefore, the observed decrease in these lipid-related metabolites likely contributes to reduced carotenoid accumulation and subsequent loss of pigmentation in the decoloration group.\u003c/p\u003e\u003cp\u003eAstaxanthin (3,3\u0026prime;-dihydroxy-4,4\u0026prime;-diketo-β,β-carotene), a ketocarotenoid pigment, is a key metabolite known for its pigmentation properties in ornamental fish (Casella et al., 2020). In this study, astaxanthin levels were significantly elevated in the Wk6AX vs Wk0C, Wk6AX vs Wk6C, Wk12AX vs Wk12C, and Wk12AX vs Wk6AX comparisons, indicating its direct role in enhancing body coloration in juvenile blood parrotfish. Similar pigmentation effects of astaxanthin have been reported in various ornamental and aquaculture species, including discus fish (\u003cem\u003eSymphysodon\u003c/em\u003e spp.), clown anemonefish (\u003cem\u003eAmphiprion ocellaris\u003c/em\u003e), blood parrotfish (\u003cem\u003eCichlasoma citrinellum \u0026times; Cichlasoma synspilum\u003c/em\u003e), red porgy (\u003cem\u003ePagrus pagrus\u003c/em\u003e), and Oscar fish (\u003cem\u003eAstronotus ocellatus\u003c/em\u003e) (Song et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ho et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Nogueira et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Alishahi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAdditionally, (+)-α-tocopherol, a fat-soluble vitamin E metabolite, was significantly upregulated in the Wk6AX vs Wk0C group. This compound may enhance carotenoid coloration by facilitating carotenoid transport via the scavenger receptor class B type 1 (SR-B1), which mediates uptake in the small intestine before distribution to target tissues. Previous studies have shown that increased dietary levels of vitamin E can improve pigment deposition in fish (Bjerkeng et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), further supporting its potential synergistic role in carotenoid-based pigmentation.\u003c/p\u003e\u003cp\u003eSimilarly, all-trans-4-ketoretinoic acid, which is a metabolite of all-trans-retinoic acid, a form of retinoid (vitamin A/retinol) was highly expressed in blood parrotfish in both Wk6AXvsWk6C and Wk12AXvsWk12C comparisons. This suggests a potential increase in skin astaxanthin levels. Carotenoids, once absorbed in the gut, are metabolized into vitamin A (Reboul, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), a process influenced by the enzyme BCO1 (Hessel et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Therefore, elevated retinol levels may contribute to enhanced astaxanthin accumulation in the skin (Gamer et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study, several metabolites associated with lipid metabolism including glycerophosphocholine, 1-stearoyl-2-oleoyl-sn-glycero-3-phosphocholine (SOPC), 1-stearoyl-2-hydroxy-sn-glycero-3-phosphocholine, alpha-linolenic acid, 1,2-ditetradecanoyl-sn-glycero-3-phosphocholine, 1-palmitoyl-2-myristoyl-sn-glycero-3-phosphocholine, 1-oleoyl-2-myristoyl-sn-glycero-3-phosphocholine, 1,2-dipentadecanoyl-sn-glycero-3-phosphocholine, prostaglandin E1, thymol-β-D-glucoside, myristic acid, octadecanoic acid, PG 36:5, (Z)-5,8,11-trihydroxyoctadec-9-enoic acid, (10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid, 9-(2,3-dihydroxypropoxy)-9-oxononanoic acid, and 21-hydroxypregnenolone\u0026mdash;were significantly elevated in Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, and Wk12AXvsWk6AX groups. These increases suggest enhanced carotenoid transport and deposition in the skin of blood parrotfish.\u003c/p\u003e\u003cp\u003eThis is consistent with findings by Yang et al. (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who reported that lipid metabolism-related compounds such as docosahexaenoic acid, arachidonic acid, linoleic acid, eicosapentaenoic acid, SOPC, dodecanoic acid, and myristic acid play key roles in carotenoid deposition in yellow discus fish. Lipids are essential macromolecules for carotenoid transport due to the lipophilic nature of carotenoids (Das \u0026amp; Biswas, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Vo et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In animals, carotenoids are primarily absorbed in the small intestine after incorporation into mixed micelles formed by bile salts, phospholipids, dietary lipids, and their hydrolysates (Yang et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Following absorption, carotenoids accumulate mainly in the liver and are transported via lipoproteins through the bloodstream to target tissues such as muscle, skin, gonads, and intestines (Bjerkeng, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Parker, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1996\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSupporting this, Ahi et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e) reported high expression of the \u003cem\u003eplin6\u003c/em\u003e gene linked to lipid metabolism in the yellow skin regions of \u003cem\u003eTropheus duboisi\u003c/em\u003e. Similarly, \u003cem\u003eapod\u003c/em\u003e, a gene associated with lipid transport, has been implicated in carotenoid-based coloration in the golden pheasant and other bird species (Gao et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Walsh et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Vo et al. (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) also demonstrated that body coloration in Atlantic salmon is closely tied to lipid digestion, with lipoproteins, serum albumin, and fatty acid-binding proteins playing critical roles in carotenoid absorption, transport, and deposition.\u003c/p\u003e\u003cp\u003eThe ABC transporters pathway was significantly enriched in Wk6AXvsWk0C, Wk6AXvsWk6C, Wk12AXvsWk12C, and Wk12AXvsWk6AX blood parrotfish, indicating active carotenoid deposition linked to skin pigmentation. SR-B1, a member of the ABC transporter family, is well-documented for its role in carotenoid transport and absorption in mammals (Kotake-Nara \u0026amp; Nagao, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Reboul \u0026amp; Borel, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), suggesting that similar mechanisms may operate in fish. These findings support the hypothesis that ABC transporters are key mediators of carotenoid uptake and binding in blood parrotfish tissues (Rajasingh et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Wade et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), contributing to the development of vibrant coloration.\u003c/p\u003e\u003cp\u003eInterestingly, enrichment of the ABC transporter pathway was also observed in Wk6CvsWk0C, Wk12AXMvsWk12C, and Wk12AXMvsWk12AX blood parrotfish. This may be attributed to the presence of carotenoids in the control diet, although further investigation is needed to validate this hypothesis. These findings highlight the potential involvement of ABC transporters even under baseline dietary conditions, suggesting a broader role in carotenoid handling beyond supplementation. Future research should focus on identifying the specific transporter proteins responsible for intracellular carotenoid trafficking in fish, which would deepen our understanding of their contribution to pigmentation and nutrient metabolism.\u003c/p\u003e\u003cp\u003eComparison of the enriched glycine, serine, and threonine metabolism pathway in Wk12AXvsWk6AX blood parrotfish with findings from Rodr\u0026iacute;guez et al. (2020) revealed that the \u003cem\u003ephgdh\u003c/em\u003e and \u003cem\u003eshmt2\u003c/em\u003e genes were highly expressed in red frogs, facilitating the biosynthesis of serine and glycine. This observation aligns with our findings of enriched aminoacyl-tRNA biosynthesis and amino acid biosynthesis pathways in Wk6AXvsWk0C, Wk12AXvsWk12C, and Wk12AXvsWk6AX groups. These results suggest a conserved role for these metabolic pathways in pigment-related physiological processes. However, targeted metabolomics studies are needed to confirm the presence and functional significance of these specific amino acids in blood parrotfish.\u003c/p\u003e\u003cp\u003eAdditionally, the protein digestion and absorption pathway were significantly enriched across the same comparisons, suggesting that carotenoid fragments may interact with proteins during metabolic processing (Reboul, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This observation is consistent with findings in humans, where carotenoids are incorporated into mixed micelles and are potentially transported via carrier proteins such as SR-B1, CD36, and NPC1L1 (Reboul, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Despite these parallels, the specific proteins responsible for intracellular carotenoid transport in fish have yet to be identified, highlighting an important area for future research.\u003c/p\u003e\u003cp\u003eMoreover, studies by McClements and Li (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and Soukoulis and Bohn (2015) have demonstrated that proteins contribute to the emulsification of polar dietary compounds during digestion. This further supports the potential interaction between carotenoids and proteins, reinforcing their role in facilitating nutrient absorption and metabolic integration.\u003c/p\u003e\u003cp\u003eConversely, taurine which is a water-soluble bioactive compound (Spitze et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) was linked to the enrichment of the taurine and hypotaurine metabolism pathway in Wk12AXMvsWk12C blood parrotfish. This pathway may negatively affect carotenoid absorption, transport, and deposition in tissues, potentially leading to reduced skin pigmentation. Despite this, taurine plays a crucial role in maintaining metabolic homeostasis. Its involvement in galactose metabolism, as observed in Wk12AXMvsWk12AX and Wk6CvsWk0C groups, supports glycolytic activity and contributes to the overall physiological function of the fish.\u003c/p\u003e\u003cp\u003eAdditionally, the enrichment of the D-arginine and D-ornithine metabolism pathway in Wk12AXMvsWk12C blood parrotfish suggests increased protein synthesis and enhanced detoxification capacity. While carotenoids are widely recognized for their antioxidant and immune-boosting properties in animals (Maoka, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), their role in immune modulation may paradoxically suppress visible coloration. For example, in nestling great tits (\u003cem\u003eParus major\u003c/em\u003e), elevated immune activity stimulated by carotenoids was associated with reduced plumage coloration (Fitze et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This highlights a potential trade-off between immune function and pigmentation, which may also be relevant in fish.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, UHPLC-Q-TOF/MS was utilized to profile key metabolites and pathways associated with differential skin coloration in juvenile blood parrotfish. A total of 2,007 metabolites were identified: 1,044 in positive ion mode and 963 in negative ion mode. OPLS-DA analysis revealed clear distinctions in skin metabolite profiles between the coloration and decoloration groups. Metabolites such as astaxanthin, all-trans-4-ketoretinoic acid, octadecanoic acid, myristic acid, (+)-α-tocopherol, and various phosphocholines were significantly elevated in the coloration group, while compounds like prostaglandin I2 and lauroyl-1-carnitine were reduced in the decoloration group.\u003c/p\u003e\u003cp\u003eKEGG pathway enrichment analysis further highlighted the involvement of ABC transporters, amino acid biosynthesis, protein digestion and absorption, aminoacyl-tRNA biosynthesis, and glycine, serine, and threonine metabolism in the coloration group. In contrast, galactose metabolism, D-arginine and D-ornithine metabolism, and taurine and hypotaurine metabolism were predominantly enriched in the decoloration group.\u003c/p\u003e\u003cp\u003eCollectively, these findings provide novel insights into the metabolomic mechanisms underlying carotenoid-driven pigmentation in juvenile blood parrotfish, emphasizing the influence of dietary carotenoids on skin coloration and metabolic regulation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAX, Coloration diet (0.45 g/kg astaxanthin); AXM, Decoloration diet (0.45 g/kg + 0 g/kg); C, Control; CE, Collision energy; CUR, Curtain gas; Da, Dalton; DEMs, Differentially expressed metabolites; DP, Declustering potential; ESI, Electro spray ionization; HP-LC, High performance-liquid chromatography; IDA, Information-dependent acquisition; ISVF, Ion spray voltage floating; KEGG, Kyoto encyclopedia of genes and genomes; LC-MS, Liquid chromatography-mass spectrometry; g, Gravity; SD, Standard deviation; SPSS, Statistical package for the social sciences; UHPLC-Q-TOF/MS, Ultrahigh-pressure liquid chromatography quadrupole time-of-flight mass spectrometry; OPLS-DA, Orthogonal partial least-squares discriminant analysis; PCA, Principal component analysis; QC, Quality control; VIP, Variable importance in the projection.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZ-Z. C, B. W., J-Z. G.: Funding acquisition, Conceptualization, Project administration, Review and editing, and Supervision; A. D. M.: Investigation, Data curation, Formal analysis, Methodology, Software and original draft; A. Y.: Methodology, Analysis and Validation; M. M. O., S. O. A.: Review and editing.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors appreciate the support provided by Hao-Ren Zhang, Xiang-Nan Feng, and Yan-Shang Zhang for feed formulation and sample collection. This work was funded by the Shanghai Sailing Program, China (19YF1419400) and the Natural Science Foundation of Shanghai (20ZR1423600).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhi EP, Lecaudey LA, Ziegelbecker A, Steiner O, Glabonjat R, Goessler W, Hois V, Wagner C, Lass A, Sefc KM (2020a) Comparative transcriptomics reveals candidate carotenoid color genes in an East African cichlid fish. 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Frontiers in marine science 8:1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":true,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Astaxanthin, Blood parrotfish, Metabolic mechanisms, UHPLC-Q-TOF/MS, Coloration/decoloration","lastPublishedDoi":"10.21203/rs.3.rs-7107321/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7107321/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study explored the role of astaxanthin, a carotenoid supplement, in the metabolic mechanism underlying body color formation in juvenile blood parrotfish (\u003cem\u003eVieja melanurus ♀ \u0026times; Amphilophus citrinellus\u003c/em\u003e \u003cb\u003e♂\u003c/b\u003e\u003cb\u003e)\u003c/b\u003e cultured in a recirculating aquaculture system. Fish were divided into three groups: a control group (C) fed a basal diet for 12 weeks, a coloration group (AX) fed an astaxanthin-enriched diet for 12 weeks, and a decoloration group (AXM) fed the enriched diet for 6 weeks followed by a basal diet for another 6 weeks. Using UHPL-Q-TOF/MS, key metabolic pathways and compounds associated with coloration and decoloration were characterized. Metabolic analysis identified 2007 differentially expressed metabolites (DEMs), with OPLS-DA clearly distinguishing skin metabolite profiles between the AX and AXM groups. Notably, compounds such as astaxanthin, all-trans-4-ketoretinoic acid, octadecanoic acid, myristic acid, 1-oleoyl-2-myristoyl-sn-glycero-3- phosphocholine, (+)-.alpha.-tocopherol, and linoleic acid were significantly elevated in the AX group while prostaglandin i2, pc 38:7, N-tetracose-noyl-4-shingenine, lauroyl-1-carnitine, and (z)-5,8,11-trihydroxyoctadec-9-enoic acid were reduced in AXM group. KEGG pathway analysis revealed enrichment of ABC transporters, biosynthesis of amino acids, protein digestion and absorption, aminoacyl-tRNA biosynthesis, glycine, serine, and threonine metabolism in the AX group. In contrast, galactose metabolism, D-arginine and D-ornithine metabolism, taurine and hypotaurine metabolism were significantly enriched in AXM group. These findings enhance our understanding of the metabolic basis of body coloration in blood parrotfish and offer insights for optimizing ornamental fish nutrition and feed strategies.\u003c/p\u003e","manuscriptTitle":"Metabolic Mechanisms of Coloration and Decoloration in Juvenile Blood Parrotfish (Vieja melanurus ♀ × Amphilophus citrinellus ♂) Revealed by UHPLC-Q-TOF/MS","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-29 08:55:20","doi":"10.21203/rs.3.rs-7107321/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3b994b7b-a512-4fdf-b6f3-51b58ea534cd","owner":[],"postedDate":"August 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-17T21:38:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-29 08:55:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7107321","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7107321","identity":"rs-7107321","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}