Protein-sparing effects of lipids in the diet of golden pompano (Trachinotus ovatus): evaluation of growth, feed utilization, and lipid metabolism

Protein-sparing effects of lipids in the diet of golden pompano (Trachinotus ovatus): evaluation of growth, feed utilization, and lipid metabolism | 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 Protein-sparing effects of lipids in the diet of golden pompano (Trachinotus ovatus): evaluation of growth, feed utilization, and lipid metabolism Xinyi Li, Liuling Gao, Fang Chen, Junfeng Guan, Shuqi Wang, Dizhi Xie, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4425646/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Aug, 2024 Read the published version in Fish Physiology and Biochemistry → Version 1 posted 14 You are reading this latest preprint version Abstract To investigate the influences of dietary protein and lipid levels on the growth, feed utilization, body composition, and lipid metabolism of golden pompano ( Trachinotus ovatus ), nine test diets containing three protein levels (35%, 40% and 45%) and three lipid levels (8%, 13% and 18%) were designed in the present study. Each diet (named D1-D9) was randomly assigned to feed triplicate groups of golden pompano juvenile (initial weight ~ 70 g) for 50 days. The results showed that the dietary lipid levels positively correlated with weight gain, specific growth rate, and protein efficiency ratio (PER), suggesting that the high lipid diets (18%) can be efficiently utilized in this fish species. The dietary protein levels have no significant influences on the growth and feed utilization except for the PER. Increasing dietary protein levels resulted in a decrease in HSI, VSI, and ISI, while the dietary lipid level did not have a significant impact on morphological indices except for ISI. The dietary protein and lipid levels had no significant influences on the contents of crude lipid, crude ash, and moisture of whole body, while the crude protein contents was significantly affected by the dietary protein levels. Serum biochemical indexes, including cholesterol (CHO), TG, HDL, and LDL, as well as HDL/CHO ratio were significantly affected by the dietary lipid levels, but not by the dietary protein levels. The expression levels of genes and their associated proteins involved in hepatic lipogenesis (Srebp-1c and Fas) as well as lipolysis (Pparα and Cpt-1) were up-regulated with increasing dietary lipid levels. With dietary protein levels increasing, the expression levels of genes and their associated proteins involved in hepatic lipolysis (Pparα and Cpt-1) and lipogenesis (Srebp-1c and Fas) were up-regulated and down-regulated. Considering the present results in terms of growth performance, feed utilization, morphometric parameters, and lipid metabolism, the recommended dietary protein and lipid levels for golden pompano are 40% and 18%, respectively. The findings suggested that this species exhibits a significant protein-sparing effect on lipid utilization. Trachinotus ovatus dietary protein and lipid levels growth feed utilization lipid metabolism Figures Figure 1 Introduction Protein, lipid and carbohydrate are three important essential nutrients for the growth, reproduction and maintenance of fish (Hardy et al. 2021). Dietary lipid and carbohydrate, especially for lipid, are major energy sources for fish, while dietary protein is necessary for all kinds of biological processes and tissue synthesis, and also be consumed as energy sources when the dietary non-protein energy is not enough (Hardy et al. 2021). Additionally, aquatic animals have particularly high requirements for deitary protein and amino acids (AA) compared with domestic animals, and aquafeeds are reliant of the high-priced and resource-limited fish meal resources, which contributes to the largest cost of the aquatic feed (Hua et al. 2019 ). Thus, it is important, from a nutritional and economical view, to enhance the protein utilization for biological processes and tissue synthesis rather than for energy consume in fish. Although lipid and carbohydrate are two important non-protein energy sources, lipid is more effective dietary energy supplementation than carbohydrate, because lipid provides 2.25 times as much energy per unit as carbohydrate, and the carbohydrate utilizing is inefficient for fish, especially for carnivorous fish (Hardy et al. 2021). Accordingly, in recent years, high-fat diets (HFD) have been extensively adopte in the intensification of fish farms to reduce the protein consumption by the protein-sparing (Naiel et al. 2023 , Suloma et al. 2023 ). On the other hand, HFD within a certain range of lipid levels and short-term HFD feeding are beneficial in the fish productivity, and nitrogen and phosphorus emission, however, HFD within excessive lipid levels and long-term HFD feeding caused a serial of adverse impacts on the metabolism, health and growth in farmed fish (Naiel et al. 2023 ). For example, studies have shown that HFD feeding is prone to metabolic disorders, and eventually result in lipid accumulation, inflammation, oxidative stress in different fish species, such as blunt snout bream ( Megalobrama amblycephala ), Nile tilapia ( Oreochromis niloticus ), European sea bass ( Dicentrarchus labrax )(Zhou et al. 2023 ). Therefore, from the perspective of achieving high growth, maintaining well health, and reducing feed costs, it is important to optimize the dietary protein and lipid ratio in cultured fishes. Golden pompano ( Trachinotus ovatus ), an increasingly popular marine fish species, is well suited to various farming mode, and its annual output is more than 240 thousand tons in recent two years in China (Yearbook 2023 ). T. ovatus , like other carnivorous marine species, is more inclined to dietary lipid as energy source rather than carbohydrate, and its suitable dietary lipid level has been indicated as about 11% (Song et al. 2023 ). Our previous studies showed that juvenile T. ovatus fed HFD with 45% protein level also exhibit high growth performance, while when this fish fed HFD with 38% protein level showed low growth and excessive hepatic lipid deposition (Shao et al. 2022 , Zhang et al. 2023 ).Therefore, to investigate the influences of dietary protein and lipid levels on the growth performance, lipid metabolism of T. ovatus , nine diets with three protein levels and three lipid levels were designed in the present study. The results contribute to the development of environmentally friendly and efficient diets for T. ovatus . Material and methods Experimental diets Nine diets containing three protein levels (35%, 40% and 45%) and three lipid levels (8%, 13% and 18%). In order to study the optimal dietary protein-to-energy ratio and its effects and mechanisms on growth performance and nutrient utilization of golden pompano ( Trachinotus ovatus ). Nine Iso-energetic diets with graded levels of P/E ratios (17.96, 17.4, 16.94, 20.17, 19.55, 18.99, 22.34, 21.75 and 20.99 mg·kJ − 1 ), then named D1, D2, D3, D4, D5, D6, D7, D8 and D9. All feed ingredients were crushed and sieved through 60 µm mesh accurately weighed according to the formula, mixed well, and then made into floating pellets through a twin-screwed extruder (EXT50A, Yang gong Machine, China) in which the processing parameters were: moisture 25%, and four-zone temperature were 100, 100, 100, 130°C. All diets were dried naturally, and stored at -20°C. The proximate compositions and energy content of diets are presented in Table 1 . Table 1 Formulation and proximate composition of the experimental diets (dry mass %) Ingredient Diet groups D1 D2 D3 D4 D5 D6 D7 D8 D9 Fish meal 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 Soybean meal 19.0 20.0 22.0 24.0 22.0 20.0 11.0 9.0 3.0 Cottonseed protein concentrate 0.0 0.0 0.0 0.0 3.0 5.0 18.0 20.0 25.0 Wheat gluten powder 0.0 0.0 0.0 5.0 5.0 5.0 5.0 5.0 5.0 Fish oil 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 Sunflower oil 0.3 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Perilla oil 0.9 1.0 1.0 0.9 1.0 1.1 1.1 1.2 1.4 Coconut oil 0.0 4.4 9.8 0.0 4.3 9.4 0.0 4.0 8.9 Wheat flour 40.33 34.92 27.64 30.87 25.33 20.00 25.06 20.83 16.44 Lysine (78%) 0.69 0.69 0.67 0.50 0.61 0.73 1.02 1.12 1.47 Methionine 0.38 0.39 0.39 0.33 0.35 0.38 0.43 0.45 0.51 Others 1 8.4 8.4 8.4 8.4 8.4 8.4 8.4 8.4 8.4 Analyzed nutrients proximate (%) Crude protein 36.1 36.2 35.9 41.1 40.7 41.4 45.8 45.8 45.9 Crude fat 7.9 12.7 17.8 7.6 12.3 17.8 8.0 13.0 18.1 Crude ash 7.0 6.98 6.78 7.05 7.19 7.17 7.40 7.66 7.5 Gross energy /kJ·g − 1 19.99 20.81 21.30 20.17 21.05 21.80 20.55 21.07 21.82 Protein energy ratio /mg·kJ − 1 17.96 17.40 16.94 20.17 19.55 18.99 22.34 21.76 20.99 1 Others contained soybean phospholipid (50%), 1.5; yeast polysaccharide, 0.1; yeast extract, 0.3; calcium phosphate, 1.5; Y 2 O 3 , 0.1; taurine, 0.5; choline chloride (50%), 0.4; A blend of vitamins and minerals premix, 3.0 (purchased from Guangzhou Ashare Aquatech Co., Ltd). Fish and feeding trial Trachinotus ovatus were carried from a commercial fish farm and fed in local marine net cages in Hainan Province. All fish were acclimated in the experimental net cages (1 m × 1 m × 1.2 m) for 14 days. During the acclimation, fish were fed the mixed test diets randomly. At the beginning of the experiment, fish with average initial body weight of 70 g were fasted for 48 h and 20 fishes were bulk-weighed and stocked into experimental cages. Each diet was assigned three cages randomly. During the feeding trial, the fish were fed by hand to an apparent satiation twice a day (8:00 and 17:30) for 50 days. Water temperature (28°C-32°C), dissolved oxygen (> 5 mg/L), pH value (8.0) and ammonia nitrogen content (< 0.1 mg/L) in the experimental pens were measured every other day. The number and weight of dead fish and feed consumption were recorded and weighed every day. Sampling and evaluation of growth performance, and morphological indices After the feeding experiment, all fish were subjected to a 24 h fasting period, euthanized using MS-222 (Sigma, USA), and subsequently weighed, and counted the total number for evaluating growth performance. Ten fish were collected randomly from each cage, and two of them were collected and kept at − 20 ℃ for the determination of the proximate components of the whole fish. Blood samples were obtained from four additional fish via the caudal vein using syringes, followed by centrifugation at 3000 g and 4°C for 15 min. Subsequently, serum was collected, flash frozen in liquid nitrogen, and stored at − 80°C for subsequent biochemical analysis. And then liver samples were also immediately frozen in liquid nitrogen and stored at − 80°C until analyzed. Other four fish were individually measured length and weighed and then dissected to obtain viscera, hepatopancreas, intestine, and abdominal lipid for calculating morphological indices. All calculations for growth performance, feed utilization indices and morphological characteristics, such as, weight gain rate (WGR), specific growth rate (SGR), protein efficiency ratio (PER), survival rate (SUR), feed conversion ratio efficiency (FCR), hepatosomatic index (HSI), viscerosomatic index (VSI), intestinalomatic index (ISI), abdominal fat index (AFI), and condition factor (CF), were based on the following expressions: WGR (%) = 100 × ( Wt - Wo ) / Wo ; SGR (%/day) = 100 × (ln Wt - ln Wo ) / t ; PER (%) = ( Wt - Wo ) / (feed weight × dietary crude protein content); SUR (%) = 100 × final fish number / initial fish number; HSI (%) = 100 × hepatopancreas weight (g) /body weight (g); VSI (%) = 100 × viscera weight (g) / body weight (g); ISI (%) = 100 × intestine weight (g) / body weight (g); AFI (%) = 100 × abdominal fat weight (g) / body weight (g); CF (%) = 100 × body weight (g) / body length (cm) 3 ; Where Wt was final body weight of each cage; Wo was initial body weight of each cage; t was days of feeding trial. Proximate analysis of whole fish Proximate compositions (moisture, crude protein, crude lipid and ash) of diets and whole fish were determined by the Association of Official Analytical Chemists. In brief, the Kjeldahl method was employed to determine crude protein levels, while the Soxhlet extractor method was used to assess crude lipid content. Ash content was determined through cauterization at 550°C and sample moisture was determined by drying the samples at 105°C until a constant weight was achieved. Analysis of biochemical indicators in serum and liver The serum biochemical indicators, including total cholesterol (CHO), triglycerides (TG), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), were measured by commercial assay kits (Nanjing Jiancheng Bioengineering Co. Ltd, Nanjing, China) and BS-800M automatic biochemical analyzer according to the manufacturer instructions. Based on the concentrations of CHO, HDL, and LDL, the ratio of HDL/LDL, HDL/CHO, and LDL/CHO were also measured. For determining the hepatic Fas and Cpt-I enzymatic activities, and Pparα and Srebp-1c concentrations, frozen liver tissue were taken out from − 80°C, thawed out at 4°C, rinsed in frozen physiological saline to remove blood, dried by the filter paper, weighed accurately, and then added 0.86% cold physiological saline (9 times volume by weight (g): volume (mL) = 1:9), homogenized 1 min/time for 3 to 5 times. All homogenized fluid were centrifuged at low-temperature low-speed (3000 r/min, 10 min), and sucked out the supernatant. Hepatopancreas supernate were quantitatively determined using fish ELISA kit (Shanghai Yiji industrial Co., Ltd.) according to the manufacturer's instructions. The optical density of each well was detected within 15 min, using a microplate reader (BioTEK) set to 450 nm. The concentration of each sample was calculated based on the established standard curve. Quantitative Real Time PCR Analysis For analyzing the change of lipogenesis and lipolysis in the liver among the different dietary groups, the expression levels of cpt-I , fas , pparα , and srebp-1c were measured. The liver samples (6 replicates per group) were subjected to total RNA extraction using the BioFlux total RNA extraction kit (BioFlux, Beijing, China). The samples were uniformly diluted to achieve consistent RNA concentrations. Reverse transcription of the RNA was performed using the PrimeScript TMRT reagent kit (Takara, Tokyo, Japan). The primer sequences utilized in this study are elaborated upon in Table S1. Quantitative real-time PCR (qRT-PCR) was performed using SYBR® Green Master Mix (Toyobo Co., Ltd., Osaka, Japan) in conjunction with a CFX Connect Real-Time System (Bio-Rad Laboratories, Inc., Hercules, CA, USA). The 2 −ΔΔCT method was employed for the analysis of gene expression. Statistical analysis Data statistics and analysis were performed using SPSS 20.0 (IBM SPSS Statistics), and the results data were presented as means ± SEM (standard error of the mean). The data were subjected to one-way analysis of variance (ANOVA) and Duncan's post hoc test for group comparisons. The levels of protein and lipid were analyzed using two-way ANOVA. The significant level and extremely significant level were set at P < 0.05 and P < 0.01, respectively. Results Growth performance and feed utilization The growth performance and feed utilization of golden pompano fed diets with different P/L ratio were presented in Table 2 . At the end of trial, the SR of fish was 96.67% − 100%, and showed no significant differences among the nine groups ( P > 0.05), while the FBW, WGR and SGR of the D6 group were significantly higher than those of the other groups ( P < 0.05), and low FC was observed in the D3, D6, D8 and D9 groups compared with that of D1 group ( P < 0.05). The PER of the D3 and D6 groups exhibited a significantly higher level compared to the other experimental groups, with the exception of the D2 group ( P < 0.05). When conducting a 2×3 factor two-way ANOVA to analyze the effects of protein and lipid levels, it was found that protein level had no statistically significant impact on FBW, WGR, SGR, FC, and SR ( P > 0.05), except for PER which showed a significant increase with higher protein levels ( P 0.05), but had a significant effect on FBW, WGR, SGR, FC and PER ( P < 0.05). Increasing lipid levels led to an upward trend in FBW, WGR, SGR and PER while causing a downward trend in FC. The interaction between protein and fat had a significant effect on FBW, WGR and SGR ( P 0.05). Table 2 Growth performance and feed coefficient of golden pompano fed with different diets Groups Items IBW /g FBW /g WGR /% SGR /%·d − 1 FC PER SR /% D1 69.92 ± 0.07 149.91 ± 3.69 c 114.40 ± 5.45 d 1.56 ± 0.05 d 1.59 ± 0.08 a 1.76 ± 0.10 c 100.00 ± 0.00 D2 69.91 ± 0.14 162.78 ± 3.86 bc 132.84 ± 5.53 cd 1.72 ± 0.05 cd 1.35 ± 0.09 ab 2.06 ± 0.15 ab 100.00 ± 0.00 D3 70.09 ± 0.04 176.81 ± 5.78 b 152.24 ± 8.40 b 1.89 ± 0.06 b 1.25 ± 0.05 b 2.22 ± 0.10 a 100.00 ± 0.00 D4 69.86 ± 0.12 164.13 ± 9.30 bc 126.19 ± 5.10 d 1.66 ± 0.05 d 1.34 ± 0.08 ab 1.75 ± 0.05 c 100.00 ± 0.00 D5 70.10 ± 0.04 160.82 ± 5.77 bc 121.27 ± 4.09 d 1.62 ± 0.04 d 1.38 ± 0.05 ab 1.72 ± 0.02 c 96.67 ± 3.33 D6 70.05 ± 0.07 199.26 ± 5.36 a 179.68 ± 7.16 a 2.10 ± 0.05 a 1.23 ± 0.05 b 2.05 ± 0.08 ab 98.33 ± 1.67 D7 69.91 ± 0.08 167.33 ± 10.53 bc 130.93 ± 11.29 cd 1.70 ± 0.10 cd 1.39 ± 0.12 ab 1.52 ± 0.10 c 96.67 ± 1.67 D8 70.04 ± 0.15 177.20 ± 4.04 b 148.81 ± 10.47 bc 1.86 ± 0.05 bc 1.20 ± 0.20 b 1.80 ± 0.13 bc 96.67 ± 1.67 D9 69.81 ± 0.01 174.39 ± 3.31 b 149.79 ± 4.75 bc 1.87 ± 0.04 bc 1.31 ± 0.02 b 1.66 ± 0.03 c 100.00 ± 0.00 Two-way ANOVA Protein 0.57 0.06 0.13 0.14 0.20 < 0.001 0.20 Lipid 0.30 < 0.001 < 0.001 < 0.001 0.02 0.002 0.39 Interaction 0.23 0.03 < 0.01 < 0.01 0.14 0.08 0.43 Values were represented as mean ± SEM (n = 3), and values in the same column with different superscript letters were significantly different (P < 0.05). Morphometric parameters The dietary P/L ratio exhibited a significant impact on morphological characteristics, as demonstrated in Table 3 . The HSI, VSI, and ISI of the D2 group exhibited significantly higher values compared to those of the D6, D7, D8, and D9 groups ( P < 0.05). The CF in the D5, D6, and D7 groups showed a significant increase when compared with that in the D1 group ( P 0.05). The AFI of the D9 group demonstrated a significantly higher value than that of both the D1 and D2 groups ( P 0.05). In the two-way analysis, protein levels significantly affected HSI, VSI, ISI, and CF ( P 0.05). Increasing protein levels led to a decrease in HSI, VSI, and ISI. The addition of 40% protein level resulted in significantly higher CF compared to the other two levels. Lipid level did not significantly affect HSI, VSI, CF, and AFI ( P > 0.05), but showed an upward trend with increasing fat level for ISI. The interaction between protein and lipid had a significant effect on HSI, VSI, ISI, and CF ( P < 0.05), while no significant effect was observed for AFI. Table 3 Morphological indices of golden pompano fed with different diets Groups Items HSI VSI ISI CF AFI D1 1.54 ± 0.08 abc 5.60 ± 0.38 bc 2.09 ± 0.11 b 3.88 ± 0.14 c 0.48 ± 0.12 abc D2 1.75 ± 0.11 a 6.80 ± 0.27 a 2.67 ± 0.18 a 4.03 ± 0.13 abc 0.60 ± 0.09 ab D3 1.60 ± 0.11 ab 6.22 ± 0.20 ab 2.61 ± 0.25 a 4.18 ± 0.08 abc 0.44 ± 0.05 bc D4 1.39 ± 0.06 bcd 5.94 ± 0.36 ab 1.97 ± 0.12 b 4.20 ± 0.08 abc 0.31 ± 0.08 c D5 1.32 ± 0.08 bcd 6.15 ± 0.29 ab 2.05 ± 0.12 b 4.25 ± 0.10 ab 0.37 ± 0.06 bc D6 1.41 ± 0.09 bcd 5.52 ± 0.29 bc 2.14 ± 0.09 b 4.37 ± 0.06 a 0.39 ± 0.06 bc D7 1.13 ± 0.11 d 4.79 ± 0.23 c 2.03 ± 0.10 b 4.28 ± 0.14 ab 0.34 ± 0.06 c D8 1.14 ± 0.11 d 4.92 ± 0.23 c 2.06 ± 0.11 b 3.95 ± 0.12 bc 0.41 ± 0.05 bc D9 1.29 ± 0.07 cd 4.75 ± 0.24 c 2.14 ± 0.13 b 3.97 ± 0.11 bc 0.67 ± 0.09 a Two-way ANOVA Protein < 0.001 < 0.001 < 0.01 0.01 0.06 Lipid 0.07 0.06 0.04 0.58 0.15 Interaction 0.39 0.23 0.26 0.06 0.03 Values were represented as mean ± SEM (n = 3), and values in the same column with different superscript letters were significantly different ( P < 0.05). Proximate composition of whole fish The results showed that the combination of dietary protein and lipid significantly affected the overall body composition in terms of protein, lipid, and ash contents, but had no obviously impact on moisture contents (Table 4 ). D4-D6 groups had significantly higher crude protein contents compared to other groups ( P < 0.05). The crude fat contents of D3 group had significantly higher than D4 and D5 groups ( P < 0.05), while D6 group exhibited significantly higher ash content than D2-D5 groups ( P 0.05). However, it significantly influenced the crude protein content of whole fish ( P < 0.05), with the highest crude protein contents observed at fish fed diets with a 40% protein level. The dietary lipid level did not significantly affect the proximate compositions of whole fish ( P < 0.05). The interaction between protein and lipid had a significant effect on the crude protein content of whole fish ( P < 0.05), while no significant effect was observed for other proximate composition. Table 4 Proximate composition of whole body in golden pompano fed with different diets Groups Items Crude protein Crude lipid Crude ash Moisture D1 16.08 ± 0.09 c 8.91 ± 0.16 ab 3.64 ± 0.21 ab 70.11 ± 0.69 D2 15.30 ± 0.09 c 8.75 ± 0.76 ab 3.44 ± 0.06 b 70.87 ± 2.00 D3 16.27 ± 0.06 c 10.29 ± 0.25 a 3.53 ± 0.12 b 68.16 ± 0.65 D4 18.16 ± 0.08 a 7.44 ± 0.92 b 3.60 ± 0.12 b 68.15 ± 1.12 D5 17.48 ± 0.34 bc 7.46 ± 0.36 b 3.47 ± 0.06 b 69.75 ± 2.39 D6 17.71 ± 0.36 ab 9.65 ± 1.49 ab 4.06 ± 0.10 a 66.25 ± 0.81 D7 16.37 ± 0.02 c 9.38 ± 0.38 ab 3.66 ± 0.16 ab 68.93 ± 1.75 D8 17.03 ± 0.15 c 8.88 ± 0.7 ab 3.86 ± 0.08 ab 67.84 ± 1.87 D9 16.49 ± 0.12 c 8.55 ± 0.12 ab 3.63 ± 0.22 ab 70.06 ± 1.00 Two-way ANOVA Protein < 0.001 0.16 0.23 0.41 Lipid 0.97 0.14 0.40 0.55 Interaction 0.02 0.27 0.06 0.39 Values were represented as mean ± SEM (n = 3), and values in the same column with different superscript letters were significantly different (P < 0.05). Serum biochemical parameters The effects of dietary lipid and protein levels on the serum biochemistry of fish were shown in Table 5 . The highest levels of serum CHO, TG, HDL, and LDL were observed at D9, while the lowest levels were observed at D1. Fish fed diets with high lipid content exhibited relatively elevated levels of serum CHO, TG, HDL, and LDL. High serum TG levels were also found in the fish fed diets with low protein levels, while relatively high CHO, HDL, and LDL were found in the fish fed diets with high protein levels. In addition, the fish fed with diets D6 exhibited high serum HDL/LDL and HDL/CHO ratios, suggesting that a diet containing 40% protein and 18% lipid could also be beneficial for maintaining fish health. The interaction between protein and lipid had no significant effect was observed for the serum biochemical parameters. Table 5 Serum biochemical indexes of golden pompano fed with different diets Groups Items TG /mmol·L − 1 CHO /mmol·L − 1 HDL /mmol·L − 1 LDL /mmol·L − 1 HDL/LDL HDL/CHO LDL/CHO D1 1.76 ± 0.24 cd 4.84 ± 0.02 c 2.59 ± 0.26 d 1.22 ± 0.03 c 2.12 ± 0.12b 0.54 ± 0.03b 0.25 ± 0.03 D2 2.03 ± 0.21 ab 5.05 ± 0.14 bc 3.03 ± 0.26 cd 1.30 ± 0.03 b 2.33 ± 0.14a 0.60 ± 0.02a 0.26 ± 0.01 D3 2.33 ± 0.27 a 5.99 ± 0.15 ab 3.68 ± 0.14 ab 1.57 ± 0.05 ab 2.34 ± 0.06a 0.61 ± 0.03a 0.26 ± 0.02 D4 1.49 ± 0.14 d 5.29 ± 0.07 bc 2.91 ± 0.20 cd 1.36 ± 0.03 b 2.14 ± 0.17b 0.55 ± 0.05b 0.26 ± 0.02 D5 1.96 ± 0.16 bc 5.38 ± 0.15 bc 3.21 ± 0.16 bcd 1.47 ± 0.07 b 2.18 ± 0.15b 0.60 ± 0.04a 0.27 ± 0.04 D6 2.19 ± 0.40 ab 6.02 ± 0.26 ab 3.77 ± 0.14 ab 1.54 ± 0.08 ab 2.45 ± 0.06 a 0.63 ± 0.04a 0.26 ± 0.01 D7 1.46 ± 0.24 d 5.05 ± 0.36 bc 2.84 ± 0.09 cd 1.30 ± 0.09 b 2.18 ± 0.06b 0.56 ± 0.03b 0.26 ± 0.02 D8 1.92 ± 0.14 bc 5.57 ± 0.36 bc 3.36 ± 0.12 abc 1.47 ± 0.14 b 2.29 ± 0.14ab 0.60 ± 0.05a 0.26 ± 0.01 D9 2.15 ± 0.34 ab 6.87 ± 0.81 a 3.95 ± 0.31 a 1.89 ± 0.29 a 2.09 ± 0.15b 0.57 ± 0.02ab 0.28 ± 0.03 Two-way ANOVA Protein 0.36 0.19 0.56 0.12 0.62 0.47 0.43 Lipid < 0.001 < 0.001 < 0.001 < 0.01 < 0.01 0.16 0.57 Interaction 0.93 0.49 0.91 0.29 0.46 0.37 0.41 Values were represented as mean ± SEM (n = 3), and values in the same column with different superscript letters were significantly different (P < 0.05). Enzyme activities related to hepatic lipid metabolism As shown in the Fig. 1 A and 1 B, the peroxisome proliferator-activated receptor α (Pparα) contents and carnitine palmitoyltransferase-1 (Cpt-1) activities were high in the liver of fish fed with high lipid diets compared with the fish fed with low lipid diets ( P < 0.05), while relatively low sterol regulatory element-binding protein-1c (Srebp-1c) contents and fatty acid syntheses (Fas) activities were detected in high dietary lipid groups. The two-factor analysis showed that the protein level had no significant impact on the liver Pparα and Srebp-1c contents, as well as the Cpt-1 and Fas activities ( P > 0.05). The interaction between protein and lipid had a significant effect on the Pparα contents ( P < 0.05), while no significant effect was observed for Srebp-1c contents, as well as the Cpt-1 and Fas activities. mRNA relative expression genes related to lipid metabolism The relative mRNA expression levels of hepatic lipid metabolism-related genes are presented in Fig. 1 C and 1 D. In regard to expression level of gene related to lipolysis, the mRNA levels of hepatic cpt-I and its transcription factor ( pparα ) was increased with the increasing dietary lipid levels ( P < 0.05). Regarding the expression level of genes related to lipogenesis, the fas mRNA levels in fish fed with high lipid diets were lower than those of fish fed with low lipid diets. The srebp-1c mRNA levels of groups D4 and D7-D9 were relatively higher than those of other groups. The two-factor analysis showed that the protein level had significant impact on the gene expression involving in lipogenesis and lipolysis ( P < 0.05), with the high mRNA expression level of cpt-I , pparα , srebp-1c , and fas were observed in the liver of fish fed diets with a 45% protein level. The interaction between protein and lipid had a extremely significant effect on the lipogenesis and lipolysis ( P < 0.01). Discussion Dietary protein are the first feed cost source in the aquatic feed of fish, especially for carnivorous fish species, thus, high non-protein energy diets (elevating the dietary lipid or carbohydrate levels) have been extensively applied to reduce the protein consumption by the protein-sparing (Teles et al. 2020 ). In the study of Asian red-tailed catfish ( Hemibagrus wyckioides ) demonstrated that high lipid diets (12.0% lipid diets containing 39% protein) resulted in high growth performance and protein sparing effect (Hung et al. 2017 ). Consistently, decreasing dietary P/L ratio (with relatively low dietary protein and high dietary lipid) supported the sufficient growth and feed utilization were also reported in rockfish ( Sebastes schlegeli ), European grayling ( Thymallus thymallus ), and loach ( Paramisgurnus dabryanus )(Li et al. 2023 , Rahimnejad et al. 2021 , Wang et al. 2023 ). However, demonstrated that high lipid diets (12.5% lipid content) do not exhibit protein-sparing effects in golden pompano, requiring dietary protein supplementation of 45.0%-49.0%. Such a no protein-sparing effect of dietary lipid was also reported in crucian carp ( Carassius auratus ) (Ding et al. 2022 ). Interestingly, in this study, high dietary lipid levels resulted in modifications in WGR, SGR, PER, and FC with regards to growth and feed utilization. The results were consistent with previous findings, indicating that golden pompano can effectively utilize high lipid diets (13%-19%) (Li et al. 2021 , Song et al. 2023 , Zhang et al. 2023 ). Therefore, the optimal dietary protein and lipid levels for golden pompano were determined to be 40% and 18%, respectively, in order to achieve maximum growth and protein-sparing effects. Although dietary non-protein energy is beneficial for protein utilization and feed cost, an imbalance or excessive amount of non-protein energy may lead to increased lipid deposition in fish body and tissue (Hardy et al. 2021). Compared to low lipid diets (containing 9% lipid), high lipid diets (containing 12% lipid) significantly increased the HIS and VSI of rockfish, while these indices were unaffected by dietary protein levels (Li et al. 2023 ). Such a detriment with high dietary lipid levels has also been found in northern whiting ( Sillago sihama ) and redspotted grouper ( Epinephelus akaara ) (Liu et al. 2021 , Wang et al. 2017 ). Surprisingly, in this study, the HSI and VSI were negatively correlated with dietary protein levels but showed no significant correlation with dietary lipid levels. The studies of meagre (A rgyrosomus regius ), Asian red-tailed catfish, and crucian carp also showed that increasing dietary lipid levels did not contributed to liver and abdominal lipid contents (Ding et al. 2022 , Fountoulaki et al. 2017 , Hung et al. 2017 ). The contrasting effects of dietary lipid levels on abdominal lipid depositions mentioned above may be attributed to variations in tissue-specific lipid accumulation among different fish species, and the lipid distribution of golden pompano have a preference for muscle and liver (Wu et al. 2015 ). As expected, the whole body lipid contents did not show significant changes with varying levels of dietary lipids and proteins, which is similar with the observation in golden pompano, European grayling ( Thymallus thymallus ), and rockfish(Li et al. 2023 , Rahimnejad et al. 2021 , Wang et al. 2013 ). Serum physiological and biochemical indexes often serves as important means for evaluating the health and metabolism status in an organism (Hossain et al. 2016 ). For example, the contents of TG, CHO, and lipoproteins (HDL and LDL) are used as useful indicators to evaluate the profiles of endogenous lipid metabolism (Hossain et al. 2016 ). As reported, high levels of TG, CHO, and LDL were found to be associated with impaired lipid transport and poorer health conditions (Hossain et al. 2016 , Rahimnejad et al. 2021 ). As dietary lipid levels increased, increment of serum TG, CHO, and LDL concentrations were confirmed in rockfish (Li et al. 2023 ), European grayling (Rahimnejad et al. 2021 ), and crucian carp (Ding et al. 2022 ). In our case, the relatively high levels of CHO, HDL and LDL were presented in the fish fed diets with high lipid levels, while high TG levels were also found in the fish fed diets with low protein levels. Such an increase of serum TG and CHO concentrations with lower dietary protein levels is consistent with observations in hybrid grouper ( Epinephelus lanceolatus × E. fuscoguttatus ), grass carp ( Ctenopharyngodon idella ), black sea bream ( Acanthopagrus schlegelii ), and European grayling (Jiang et al. 2015 , Jin et al. 2015 , Rahimnejad et al. 2021 , Wang et al. 2019 ), which suggests the proper dietary P/L ratio may have a beneficial effect on the fish plasma lipid metabolism. In addition, the fish fed with diets D6 exhibited high serum HDL/LDL and HDL/CHO ratios, suggesting that a diet containing 40% protein and 18% lipid could also be beneficial for maintaining fish health. This may provide one explanation for the high growth observed in the D6 group. The liver is a vital organ for nutrition and energy metabolism, serving as a metabolic hub that connects various tissues, including the intestine, muscle, and adipose tissue (Han et al. 2021 ), which plays an irreplaceable role in maintaining the metabolic homeostasis (Zhou et al. 2023 ). The metabolic functions of the liver are also influenced by the availability of nutritional substrates, and dietary nutrition can regulate hepatic metabolism by modulating the expression of enzymes and transcription factors involved in metabolic processes(Han et al. 2021 ). Accumulating studies have demonstrated that high-lipid diets are prone to inducing hepatic lipid metabolic disorders and fat accumulation, which can seriously impact the health and growth of fish (Naiel et al. 2023 , Zhou et al. 2023 ). The previous studies have indicated that Srebp-1 and Pparα play pivotal roles as transcriptional regulators in the expression regulation of enzymatic genes associated with lipogenic and lipidolytic metabolism, respectively (Song et al. 2023 , Zhou et al. 2023 ). Consistently, the enzymatic activities and mRNA levels of Cpt-I / cpt-I , a rate-limiting enzyme in lipidolytic metabolism, were significantly improved in the liver of fish fed with diets D3 and D6 (containing 18% lipid, 36%~40% protein), meanwhile the contents and expression of Pparα / pparα exhibited similar alterations among these groups. The expression levels of lipogenic genes ( fas and srebp-1c ) and their corresponding protein contents exhibited a down-regulated trend as the dietary lipid levels increased. The transcriptome analysis of golden pompano detected the activation of lipogenesis and suppression of lipolysis with increasing dietary lipid levels (Song et al. 2023 ), Such a changing trend of hepatic lipogenesis and lipolysis with the varying dietary lipid levels were also found in large yellow croaker black sea bream ( Acanthopagrus schlegelii ), large yellow croaker ( Larimichthys croce a), and largemouth bass ( Micropterus salmoides )(Ding et al. 2022 , Wang et al. 2021 , Yin et al. 2021 ). The findings of these studies demonstrate that fish exhibits a distinct capacity for coordinating lipogenesis and lipolysis in response to high lipid diets. Notably, in this study, the hepatic lipogenesis and lipolysis metabolism were also activated by high protein diets (45% dietary protein), which is consistent with the effects of dietary protein on morphometric parameters and plasma lipid metabolism. Similarly, the grass carp exhibited a consistent decline in both tissue and plasma lipid contents, as well as hepatic lipogenesis, in response to increasing dietary protein levels(Jin et al. 2015 ). The relative expression of hepatic fas and lpl was up-regulated in the small yellow croaker ( Larimichthys polyactis ) fed with increasing dietary protein levels(Ma et al., 2020 ). Mammal studies showed that high protein diets could up-regulate the expression of genes involved in lipogenesis and lipolysis to maintain the balance of lipid metabolism in liver (Liu et al., 2015 , Liu et al., 2021 ). The data showed that the expression of genes related to lipid anabolism ( fas and srebp-1c ) is consistent with that of lipid catabolism ( cpt-I and pparα ), which may be the strategy for reducing lipid decomposition in golden pompano, thereby achieving lipid metabolism balance with the increased dietary protein energy levels. Conclusion In conclusion, based on the analysis of growth performance, feed utilization, morphometric parameters, and lipid metabolism, the recommended dietary protein and lipid levels for golden pompano are 40% and 18%, respectively. Additionally, this species exhibits a significant protein-sparing effect on lipid utilization. Furthermore, in order to maintain health and prevent excessive lipid accumulation in the liver, this particular fish species demonstrates a distinct ability to coordinate lipogenesis and lipolysis in response to high lipid or protein diets. Declarations Author contribution Xinyi Li contributed to Conceptualization, Writing – Original Draft Preparation; Liuling Gao and Fang Chen contributed to Investigation, Data curation; Junfeng Guan contributed to Formal analysis, Writing – Review & Editing; Qing Pan and Dizhi Xie contributed to Supervision, Project administration, Funding acquisition. All authors read and approved the final manuscript. Funding This research was supported by Department of Ocean and Fishery of Guangdong Province (A201701C03) and Guangdong Provincial Key Laboratory of Marine Biotechnology (GPKLMB202202). Data availability Data generated or analyzed during this study are available from the corresponding author upon reasonable request. Declarations Ethical approval All the animal experiments were approved by the College of Marine Sciences at South China Agricultural University. Competing interests The authors declare no competing interests. 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Rahimnejad, S., Dabrowski, K., Izquierdo, M., Malinovskyi, O., Kolarova, J., and Policar, T. 2021. Effects of Dietary Protein and Lipid Levels on Growth, Body Composition, Blood Biochemistry, Antioxidant Capacity and Ammonia Excretion of European Grayling (Thymallus thymallus). Front Mar Sci 8. Shao, Y., Xie, Z., Liang, S., Chen, C., Tocher, D.R., Lin, L., Huang, Y., Li, Y., Xie, D., Hong, Y., Wang, S., and You, C. 2022. Dietary calcium pyruvate could improve growth performance and reduce excessive lipid deposition in juvenile golden pompano (Trachinotus ovatus) fed a high fat diet. Fish Physiol BiochemI 48(3): 555–570. Song, F., Qin, Y., Geng, H., He, C., Yang, P., Wang, W., and Chen, Y. 2023. Transcriptome analysis reveals the effects of dietary lipid level on growth performance and immune response in golden pompano (Trachinotus ovatus). Aquaculture 563. Suloma, A., Mabroke, R.S., Khattab, M.S., Salaah, S., El-Husseiny, O.M., and Eid, A. 2023. 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Dietary berberine regulates lipid metabolism in muscle and liver of black sea bream (Acanthopagrus schlegelii) fed normal or high-lipid diets. Brit J Nutr 125(5): 481–493. Wang, L., Zhang, W., Gladstone, S., Ng, W., Zhang, J., and Shao, Q. 2019. Effects of isoenergetic diets with varying protein and lipid levels on the growth, feed utilization, metabolic enzymes activities, antioxidative status and serum biochemical parameters of black sea bream (Acanthopagrus schlegelii). Aquaculture 513. Wang, Z., Li, S., Zhou, Q., Zhang, J., Li, Y., Li, Y., Yuan, Z., and Huang, G. 2023. Effects of different protein and lipid levels on the growth performance and intestinal microflora of loach (Paramisgurnus dabryanus). Animal Nutrition 13: 229–239. Wu, J., Zhang, J., Du, X., Shen, Y., Lao, X., Zhang, M., Chen, L., and Du, Z. 2015. Evaluation of the distribution of adipose tissues in fish using magnetic resonance imaging (MRI). Aquaculture 448: 112–122. Yearbook, C.F.S. 2023. 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Additional Declarations No competing interests reported. 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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-4425646","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":309482366,"identity":"0eb97ad1-f5ed-42b6-9264-8828f73efe2f","order_by":0,"name":"Xinyi Li","email":"","orcid":"","institution":"South China Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xinyi","middleName":"","lastName":"Li","suffix":""},{"id":309482367,"identity":"ed606ede-1a65-4aa0-ac5d-03788f0e2aae","order_by":1,"name":"Liuling Gao","email":"","orcid":"","institution":"South China Agricultural 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University","correspondingAuthor":true,"prefix":"","firstName":"Qing","middleName":"","lastName":"Pan","suffix":""}],"badges":[],"createdAt":"2024-05-15 13:58:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4425646/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4425646/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10695-024-01392-9","type":"published","date":"2024-08-01T15:57:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57850870,"identity":"f9bd6321-a7b4-492b-b9da-ac2858d03abe","added_by":"auto","created_at":"2024-06-06 11:51:00","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":367889,"visible":true,"origin":"","legend":"\u003cp\u003eExpression levels of protein (A and B) and genes (C and D) related to the lipid metabolism of golden pompano fed with different diets\u003c/p\u003e","description":"","filename":"file.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4425646/v1/1523bd77ec473009ba1ad140.jpg"},{"id":61793538,"identity":"d50dfe78-35cb-40f8-8e1b-6a0ffec7e6b0","added_by":"auto","created_at":"2024-08-05 16:13:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1203977,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4425646/v1/613efdc8-9e33-47fc-8df7-3b4969789fa9.pdf"},{"id":57850869,"identity":"dd24756a-5ae2-49a1-862a-1398061dc202","added_by":"auto","created_at":"2024-06-06 11:51:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14669,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1Theprimersdesignedinthisexperiment.docx","url":"https://assets-eu.researchsquare.com/files/rs-4425646/v1/0dc85251085686bd78f2968a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Protein-sparing effects of lipids in the diet of golden pompano (Trachinotus ovatus): evaluation of growth, feed utilization, and lipid metabolism","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProtein, lipid and carbohydrate are three important essential nutrients for the growth, reproduction and maintenance of fish (Hardy et al. 2021). Dietary lipid and carbohydrate, especially for lipid, are major energy sources for fish, while dietary protein is necessary for all kinds of biological processes and tissue synthesis, and also be consumed as energy sources when the dietary non-protein energy is not enough (Hardy et al. 2021). Additionally, aquatic animals have particularly high requirements for deitary protein and amino acids (AA) compared with domestic animals, and aquafeeds are reliant of the high-priced and resource-limited fish meal resources, which contributes to the largest cost of the aquatic feed (Hua et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Thus, it is important, from a nutritional and economical view, to enhance the protein utilization for biological processes and tissue synthesis rather than for energy consume in fish. Although lipid and carbohydrate are two important non-protein energy sources, lipid is more effective dietary energy supplementation than carbohydrate, because lipid provides 2.25 times as much energy per unit as carbohydrate, and the carbohydrate utilizing is inefficient for fish, especially for carnivorous fish (Hardy et al. 2021). Accordingly, in recent years, high-fat diets (HFD) have been extensively adopte in the intensification of fish farms to reduce the protein consumption by the protein-sparing (Naiel et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Suloma et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn the other hand, HFD within a certain range of lipid levels and short-term HFD feeding are beneficial in the fish productivity, and nitrogen and phosphorus emission, however, HFD within excessive lipid levels and long-term HFD feeding caused a serial of adverse impacts on the metabolism, health and growth in farmed fish (Naiel et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For example, studies have shown that HFD feeding is prone to metabolic disorders, and eventually result in lipid accumulation, inflammation, oxidative stress in different fish species, such as blunt snout bream (\u003cem\u003eMegalobrama amblycephala\u003c/em\u003e), Nile tilapia (\u003cem\u003eOreochromis niloticus\u003c/em\u003e), European sea bass (\u003cem\u003eDicentrarchus labrax\u003c/em\u003e)(Zhou et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, from the perspective of achieving high growth, maintaining well health, and reducing feed costs, it is important to optimize the dietary protein and lipid ratio in cultured fishes.\u003c/p\u003e \u003cp\u003eGolden pompano (\u003cem\u003eTrachinotus ovatus\u003c/em\u003e), an increasingly popular marine fish species, is well suited to various farming mode, and its annual output is more than 240 thousand tons in recent two years in China (Yearbook \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003eT. ovatus\u003c/em\u003e, like other carnivorous marine species, is more inclined to dietary lipid as energy source rather than carbohydrate, and its suitable dietary lipid level has been indicated as about 11% (Song et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Our previous studies showed that juvenile \u003cem\u003eT. ovatus\u003c/em\u003e fed HFD with 45% protein level also exhibit high growth performance, while when this fish fed HFD with 38% protein level showed low growth and excessive hepatic lipid deposition (Shao et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Zhang et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).Therefore, to investigate the influences of dietary protein and lipid levels on the growth performance, lipid metabolism of \u003cem\u003eT. ovatus\u003c/em\u003e, nine diets with three protein levels and three lipid levels were designed in the present study. The results contribute to the development of environmentally friendly and efficient diets for \u003cem\u003eT. ovatus\u003c/em\u003e.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003eExperimental diets\u003c/p\u003e\n\u003cp\u003eNine diets containing three protein levels (35%, 40% and 45%) and three lipid levels (8%, 13% and 18%). In order to study the optimal dietary protein-to-energy ratio and its effects and mechanisms on growth performance and nutrient utilization of golden pompano (\u003cem\u003eTrachinotus ovatus\u003c/em\u003e). Nine Iso-energetic diets with graded levels of P/E ratios (17.96, 17.4, 16.94, 20.17, 19.55, 18.99, 22.34, 21.75 and 20.99 mg\u0026middot;kJ\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), then named D1, D2, D3, D4, D5, D6, D7, D8 and D9.\u003c/p\u003e\n\u003cp\u003eAll feed ingredients were crushed and sieved through 60 \u0026micro;m mesh accurately weighed according to the formula, mixed well, and then made into floating pellets through a twin-screwed extruder (EXT50A, Yang gong Machine, China) in which the processing parameters were: moisture 25%, and four-zone temperature were 100, 100, 100, 130\u0026deg;C. All diets were dried naturally, and stored at -20\u0026deg;C. The proximate compositions and energy content of diets are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eFormulation and proximate composition of the experimental diets (dry mass %)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eIngredient\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"9\" align=\"left\"\u003e\n\u003cp\u003eDiet groups\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD3\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD4\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD5\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD6\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD7\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD8\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD9\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFish meal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSoybean meal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCottonseed protein concentrate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWheat gluten powder\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFish oil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSunflower oil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePerilla oil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCoconut oil\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWheat flour\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.44\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLysine (78%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.67\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.47\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMethionine\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.51\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"10\" align=\"left\"\u003e\n\u003cp\u003eAnalyzed nutrients proximate (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCrude protein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCrude fat\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCrude ash\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGross energy /kJ\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.80\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.82\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProtein energy ratio /mg\u0026middot;kJ\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.99\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Others contained soybean phospholipid (50%), 1.5; yeast polysaccharide, 0.1; yeast extract, 0.3; calcium phosphate, 1.5; Y\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e, 0.1; taurine, 0.5; choline chloride (50%), 0.4; A blend of vitamins and minerals premix, 3.0 (purchased from Guangzhou Ashare Aquatech Co., Ltd).\u003c/p\u003e\n\u003cp\u003eFish and feeding trial\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTrachinotus ovatus\u003c/em\u003e were carried from a commercial fish farm and fed in local marine net cages in Hainan Province. All fish were acclimated in the experimental net cages (1 m \u0026times; 1 m \u0026times; 1.2 m) for 14 days. During the acclimation, fish were fed the mixed test diets randomly. At the beginning of the experiment, fish with average initial body weight of 70 g were fasted for 48 h and 20 fishes were bulk-weighed and stocked into experimental cages. Each diet was assigned three cages randomly. During the feeding trial, the fish were fed by hand to an apparent satiation twice a day (8:00 and 17:30) for 50 days. Water temperature (28\u0026deg;C-32\u0026deg;C), dissolved oxygen (\u0026gt;\u0026thinsp;5 mg/L), pH value (8.0) and ammonia nitrogen content (\u0026lt;\u0026thinsp;0.1 mg/L) in the experimental pens were measured every other day. The number and weight of dead fish and feed consumption were recorded and weighed every day.\u003c/p\u003e\n\u003cp\u003eSampling and evaluation of growth performance, and morphological indices\u003c/p\u003e\n\u003cp\u003eAfter the feeding experiment, all fish were subjected to a 24 h fasting period, euthanized using MS-222 (Sigma, USA), and subsequently weighed, and counted the total number for evaluating growth performance. Ten fish were collected randomly from each cage, and two of them were collected and kept at \u0026minus;\u0026thinsp;20 ℃ for the determination of the proximate components of the whole fish. Blood samples were obtained from four additional fish via the caudal vein using syringes, followed by centrifugation at 3000 g and 4\u0026deg;C for 15 min. Subsequently, serum was collected, flash frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent biochemical analysis. And then liver samples were also immediately frozen in liquid nitrogen and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until analyzed.\u003c/p\u003e\n\u003cp\u003eOther four fish were individually measured length and weighed and then dissected to obtain viscera, hepatopancreas, intestine, and abdominal lipid for calculating morphological indices. All calculations for growth performance, feed utilization indices and morphological characteristics, such as, weight gain rate (WGR), specific growth rate (SGR), protein efficiency ratio (PER), survival rate (SUR), feed conversion ratio efficiency (FCR), hepatosomatic index (HSI), viscerosomatic index (VSI), intestinalomatic index (ISI), abdominal fat index (AFI), and condition factor (CF), were based on the following expressions:\u003c/p\u003e\n\u003cp\u003eWGR (%)\u0026thinsp;=\u0026thinsp;100 \u0026times; (\u003cem\u003eWt\u003c/em\u003e - \u003cem\u003eWo\u003c/em\u003e) / \u003cem\u003eWo\u003c/em\u003e;\u003c/p\u003e\n\u003cp\u003eSGR (%/day)\u0026thinsp;=\u0026thinsp;100 \u0026times; (ln\u003cem\u003eWt\u003c/em\u003e - ln\u003cem\u003eWo\u003c/em\u003e) / \u003cem\u003et\u003c/em\u003e;\u003c/p\u003e\n\u003cp\u003ePER (%) = (\u003cem\u003eWt\u003c/em\u003e - \u003cem\u003eWo\u003c/em\u003e) / (feed weight \u0026times; dietary crude protein content);\u003c/p\u003e\n\u003cp\u003eSUR (%)\u0026thinsp;=\u0026thinsp;100 \u0026times; final fish number / initial fish number;\u003c/p\u003e\n\u003cp\u003eHSI (%)\u0026thinsp;=\u0026thinsp;100 \u0026times; hepatopancreas weight (g) /body weight (g);\u003c/p\u003e\n\u003cp\u003eVSI (%)\u0026thinsp;=\u0026thinsp;100 \u0026times; viscera weight (g) / body weight (g);\u003c/p\u003e\n\u003cp\u003eISI (%)\u0026thinsp;=\u0026thinsp;100 \u0026times; intestine weight (g) / body weight (g);\u003c/p\u003e\n\u003cp\u003eAFI (%)\u0026thinsp;=\u0026thinsp;100 \u0026times; abdominal fat weight (g) / body weight (g);\u003c/p\u003e\n\u003cp\u003eCF (%)\u0026thinsp;=\u0026thinsp;100 \u0026times; body weight (g) / body length (cm)\u003csup\u003e3\u003c/sup\u003e;\u003c/p\u003e\n\u003cp\u003eWhere \u003cem\u003eWt\u003c/em\u003e was final body weight of each cage; \u003cem\u003eWo\u003c/em\u003e was initial body weight of each cage; \u003cem\u003et\u003c/em\u003e was days of feeding trial.\u003c/p\u003e\n\u003cp\u003eProximate analysis of whole fish\u003c/p\u003e\n\u003cp\u003eProximate compositions (moisture, crude protein, crude lipid and ash) of diets and whole fish were determined by the Association of Official Analytical Chemists. In brief, the Kjeldahl method was employed to determine crude protein levels, while the Soxhlet extractor method was used to assess crude lipid content. Ash content was determined through cauterization at 550\u0026deg;C and sample moisture was determined by drying the samples at 105\u0026deg;C until a constant weight was achieved.\u003c/p\u003e\n\u003cp\u003eAnalysis of biochemical indicators in serum and liver\u003c/p\u003e\n\u003cp\u003eThe serum biochemical indicators, including total cholesterol (CHO), triglycerides (TG), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), were measured by commercial assay kits (Nanjing Jiancheng Bioengineering Co. Ltd, Nanjing, China) and BS-800M automatic biochemical analyzer according to the manufacturer instructions. Based on the concentrations of CHO, HDL, and LDL, the ratio of HDL/LDL, HDL/CHO, and LDL/CHO were also measured.\u003c/p\u003e\n\u003cp\u003eFor determining the hepatic Fas and Cpt-I enzymatic activities, and Ppar\u0026alpha; and Srebp-1c concentrations, frozen liver tissue were taken out from \u0026minus;\u0026thinsp;80\u0026deg;C, thawed out at 4\u0026deg;C, rinsed in frozen physiological saline to remove blood, dried by the filter paper, weighed accurately, and then added 0.86% cold physiological saline (9 times volume by weight (g): volume (mL)\u0026thinsp;=\u0026thinsp;1:9), homogenized 1 min/time for 3 to 5 times. All homogenized fluid were centrifuged at low-temperature low-speed (3000 r/min, 10 min), and sucked out the supernatant. Hepatopancreas supernate were quantitatively determined using fish ELISA kit (Shanghai Yiji industrial Co., Ltd.) according to the manufacturer's instructions. The optical density of each well was detected within 15 min, using a microplate reader (BioTEK) set to 450 nm. The concentration of each sample was calculated based on the established standard curve.\u003c/p\u003e\n\u003cp\u003eQuantitative Real Time PCR Analysis\u003c/p\u003e\n\u003cp\u003eFor analyzing the change of lipogenesis and lipolysis in the liver among the different dietary groups, the expression levels of \u003cem\u003ecpt-I\u003c/em\u003e, \u003cem\u003efas\u003c/em\u003e, \u003cem\u003eppar\u0026alpha;\u003c/em\u003e, and \u003cem\u003esrebp-1c\u003c/em\u003e were measured. The liver samples (6 replicates per group) were subjected to total RNA extraction using the BioFlux total RNA extraction kit (BioFlux, Beijing, China). The samples were uniformly diluted to achieve consistent RNA concentrations. Reverse transcription of the RNA was performed using the PrimeScript TMRT reagent kit (Takara, Tokyo, Japan). The primer sequences utilized in this study are elaborated upon in Table S1. Quantitative real-time PCR (qRT-PCR) was performed using SYBR\u0026reg; Green Master Mix (Toyobo Co., Ltd., Osaka, Japan) in conjunction with a CFX Connect Real-Time System (Bio-Rad Laboratories, Inc., Hercules, CA, USA). The 2\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;CT\u003c/sup\u003e method was employed for the analysis of gene expression.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eData statistics and analysis were performed using SPSS 20.0 (IBM SPSS Statistics), and the results data were presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (standard error of the mean). The data were subjected to one-way analysis of variance (ANOVA) and Duncan's post hoc test for group comparisons. The levels of protein and lipid were analyzed using two-way ANOVA. The significant level and extremely significant level were set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, respectively.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eGrowth performance and feed utilization\u003c/p\u003e \u003cp\u003eThe growth performance and feed utilization of golden pompano fed diets with different P/L ratio were presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. At the end of trial, the SR of fish was 96.67% \u0026minus;\u0026thinsp;100%, and showed no significant differences among the nine groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), while the FBW, WGR and SGR of the D6 group were significantly higher than those of the other groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and low FC was observed in the D3, D6, D8 and D9 groups compared with that of D1 group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The PER of the D3 and D6 groups exhibited a significantly higher level compared to the other experimental groups, with the exception of the D2 group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). When conducting a 2\u0026times;3 factor two-way ANOVA to analyze the effects of protein and lipid levels, it was found that protein level had no statistically significant impact on FBW, WGR, SGR, FC, and SR (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05), except for PER which showed a significant increase with higher protein levels (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). Dietary lipid levels did not significantly affect SR (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05), but had a significant effect on FBW, WGR, SGR, FC and PER (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). Increasing lipid levels led to an upward trend in FBW, WGR, SGR and PER while causing a downward trend in FC. The interaction between protein and fat had a significant effect on FBW, WGR and SGR (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), but no significant effect on PER, FC, or SR (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGrowth performance and feed coefficient of golden pompano fed with different diets\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIBW /g\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFBW /g\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWGR /%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSGR /%\u0026middot;d\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePER\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSR /%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e149.91\u0026thinsp;\u0026plusmn;\u0026thinsp;3.69\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114.40\u0026thinsp;\u0026plusmn;\u0026thinsp;5.45\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.86\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132.84\u0026thinsp;\u0026plusmn;\u0026thinsp;5.53\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176.81\u0026thinsp;\u0026plusmn;\u0026thinsp;5.78\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e152.24\u0026thinsp;\u0026plusmn;\u0026thinsp;8.40\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164.13\u0026thinsp;\u0026plusmn;\u0026thinsp;9.30\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e126.19\u0026thinsp;\u0026plusmn;\u0026thinsp;5.10\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160.82\u0026thinsp;\u0026plusmn;\u0026thinsp;5.77\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121.27\u0026thinsp;\u0026plusmn;\u0026thinsp;4.09\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96.67\u0026thinsp;\u0026plusmn;\u0026thinsp;3.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199.26\u0026thinsp;\u0026plusmn;\u0026thinsp;5.36\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e179.68\u0026thinsp;\u0026plusmn;\u0026thinsp;7.16\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e98.33\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167.33\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130.93\u0026thinsp;\u0026plusmn;\u0026thinsp;11.29\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e177.20\u0026thinsp;\u0026plusmn;\u0026thinsp;4.04\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e148.81\u0026thinsp;\u0026plusmn;\u0026thinsp;10.47\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174.39\u0026thinsp;\u0026plusmn;\u0026thinsp;3.31\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149.79\u0026thinsp;\u0026plusmn;\u0026thinsp;4.75\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eTwo-way ANOVA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues were represented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;3), and values in the same column with different superscript letters were significantly different (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eMorphometric parameters\u003c/p\u003e \u003cp\u003eThe dietary P/L ratio exhibited a significant impact on morphological characteristics, as demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The HSI, VSI, and ISI of the D2 group exhibited significantly higher values compared to those of the D6, D7, D8, and D9 groups (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). The CF in the D5, D6, and D7 groups showed a significant increase when compared with that in the D1 group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while no significant differences were observed among the other experimental groups (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05). The AFI of the D9 group demonstrated a significantly higher value than that of both the D1 and D2 groups (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), with no significant differences found among the remaining experimental groups (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05). In the two-way analysis, protein levels significantly affected HSI, VSI, ISI, and CF (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), but had no significant effect on AFI (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05). Increasing protein levels led to a decrease in HSI, VSI, and ISI. The addition of 40% protein level resulted in significantly higher CF compared to the other two levels. Lipid level did not significantly affect HSI, VSI, CF, and AFI (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05), but showed an upward trend with increasing fat level for ISI. The interaction between protein and lipid had a significant effect on HSI, VSI, ISI, and CF (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), while no significant effect was observed for AFI.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMorphological indices of golden pompano fed with different diets\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHSI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVSI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eISI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAFI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eTwo-way ANOVA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues were represented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;3), and values in the same column with different superscript letters were significantly different (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eProximate composition of whole fish\u003c/p\u003e \u003cp\u003eThe results showed that the combination of dietary protein and lipid significantly affected the overall body composition in terms of protein, lipid, and ash contents, but had no obviously impact on moisture contents (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e). D4-D6 groups had significantly higher crude protein contents compared to other groups (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). The crude fat contents of D3 group had significantly higher than D4 and D5 groups (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), while D6 group exhibited significantly higher ash content than D2-D5 groups (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). The two-factor analysis showed that the protein level had no significant impact on the crude lipid, crude ash, and moisture contents of whole fish (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05). However, it significantly influenced the crude protein content of whole fish (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), with the highest crude protein contents observed at fish fed diets with a 40% protein level. The dietary lipid level did not significantly affect the proximate compositions of whole fish (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). The interaction between protein and lipid had a significant effect on the crude protein content of whole fish (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), while no significant effect was observed for other proximate composition.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProximate composition of whole body in golden pompano fed with different diets\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude protein\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCrude lipid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCrude ash\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMoisture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.49\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eTwo-way ANOVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues were represented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;3), and values in the same column with different superscript letters were significantly different (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eSerum biochemical parameters\u003c/p\u003e \u003cp\u003eThe effects of dietary lipid and protein levels on the serum biochemistry of fish were shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The highest levels of serum CHO, TG, HDL, and LDL were observed at D9, while the lowest levels were observed at D1. Fish fed diets with high lipid content exhibited relatively elevated levels of serum CHO, TG, HDL, and LDL. High serum TG levels were also found in the fish fed diets with low protein levels, while relatively high CHO, HDL, and LDL were found in the fish fed diets with high protein levels. In addition, the fish fed with diets D6 exhibited high serum HDL/LDL and HDL/CHO ratios, suggesting that a diet containing 40% protein and 18% lipid could also be beneficial for maintaining fish health. The interaction between protein and lipid had no significant effect was observed for the serum biochemical parameters.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSerum biochemical indexes of golden pompano fed with different diets\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTG /mmol\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCHO /mmol\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHDL /mmol\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLDL /mmol\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHDL/LDL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHDL/CHO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLDL/CHO\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003ebcd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTwo-way\u003c/em\u003e ANOVA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues were represented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (n\u0026thinsp;=\u0026thinsp;3), and values in the same column with different superscript letters were significantly different (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eEnzyme activities related to hepatic lipid metabolism\u003c/p\u003e \u003cp\u003eAs shown in the Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, the peroxisome proliferator-activated receptor α (Pparα) contents and carnitine palmitoyltransferase-1 (Cpt-1) activities were high in the liver of fish fed with high lipid diets compared with the fish fed with low lipid diets (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), while relatively low sterol regulatory element-binding protein-1c (Srebp-1c) contents and fatty acid syntheses (Fas) activities were detected in high dietary lipid groups. The two-factor analysis showed that the protein level had no significant impact on the liver Pparα and Srebp-1c contents, as well as the Cpt-1 and Fas activities (\u003cem\u003eP\u0026thinsp;\u0026gt;\u003c/em\u003e\u0026thinsp;0.05). The interaction between protein and lipid had a significant effect on the Pparα contents (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), while no significant effect was observed for Srebp-1c contents, as well as the Cpt-1 and Fas activities.\u003c/p\u003e \u003cp\u003emRNA relative expression genes related to lipid metabolism\u003c/p\u003e \u003cp\u003eThe relative mRNA expression levels of hepatic lipid metabolism-related genes are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD. In regard to expression level of gene related to lipolysis, the mRNA levels of hepatic \u003cem\u003ecpt-I\u003c/em\u003e and its transcription factor (\u003cem\u003epparα\u003c/em\u003e) was increased with the increasing dietary lipid levels (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05). Regarding the expression level of genes related to lipogenesis, the \u003cem\u003efas\u003c/em\u003e mRNA levels in fish fed with high lipid diets were lower than those of fish fed with low lipid diets. The \u003cem\u003esrebp-1c\u003c/em\u003e mRNA levels of groups D4 and D7-D9 were relatively higher than those of other groups. The two-factor analysis showed that the protein level had significant impact on the gene expression involving in lipogenesis and lipolysis (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05), with the high mRNA expression level of \u003cem\u003ecpt-I\u003c/em\u003e, \u003cem\u003epparα\u003c/em\u003e, \u003cem\u003esrebp-1c\u003c/em\u003e, and \u003cem\u003efas\u003c/em\u003e were observed in the liver of fish fed diets with a 45% protein level. The interaction between protein and lipid had a extremely significant effect on the lipogenesis and lipolysis (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDietary protein are the first feed cost source in the aquatic feed of fish, especially for carnivorous fish species, thus, high non-protein energy diets (elevating the dietary lipid or carbohydrate levels) have been extensively applied to reduce the protein consumption by the protein-sparing (Teles et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In the study of Asian red-tailed catfish (\u003cem\u003eHemibagrus wyckioides\u003c/em\u003e) demonstrated that high lipid diets (12.0% lipid diets containing 39% protein) resulted in high growth performance and protein sparing effect (Hung et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Consistently, decreasing dietary P/L ratio (with relatively low dietary protein and high dietary lipid) supported the sufficient growth and feed utilization were also reported in rockfish (\u003cem\u003eSebastes schlegeli\u003c/em\u003e), European grayling (\u003cem\u003eThymallus thymallus\u003c/em\u003e), and loach (\u003cem\u003eParamisgurnus dabryanus\u003c/em\u003e)(Li et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Rahimnejad et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, demonstrated that high lipid diets (12.5% lipid content) do not exhibit protein-sparing effects in golden pompano, requiring dietary protein supplementation of 45.0%-49.0%. Such a no protein-sparing effect of dietary lipid was also reported in crucian carp (\u003cem\u003eCarassius auratus\u003c/em\u003e) (Ding et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Interestingly, in this study, high dietary lipid levels resulted in modifications in WGR, SGR, PER, and FC with regards to growth and feed utilization. The results were consistent with previous findings, indicating that golden pompano can effectively utilize high lipid diets (13%-19%) (Li et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Song et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Zhang et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, the optimal dietary protein and lipid levels for golden pompano were determined to be 40% and 18%, respectively, in order to achieve maximum growth and protein-sparing effects.\u003c/p\u003e \u003cp\u003eAlthough dietary non-protein energy is beneficial for protein utilization and feed cost, an imbalance or excessive amount of non-protein energy may lead to increased lipid deposition in fish body and tissue (Hardy et al. 2021). Compared to low lipid diets (containing 9% lipid), high lipid diets (containing 12% lipid) significantly increased the HIS and VSI of rockfish, while these indices were unaffected by dietary protein levels (Li et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Such a detriment with high dietary lipid levels has also been found in northern whiting (\u003cem\u003eSillago sihama\u003c/em\u003e) and redspotted grouper (\u003cem\u003eEpinephelus akaara\u003c/em\u003e) (Liu et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Surprisingly, in this study, the HSI and VSI were negatively correlated with dietary protein levels but showed no significant correlation with dietary lipid levels. The studies of meagre (A\u003cem\u003ergyrosomus regius\u003c/em\u003e), Asian red-tailed catfish, and crucian carp also showed that increasing dietary lipid levels did not contributed to liver and abdominal lipid contents (Ding et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Fountoulaki et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Hung et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The contrasting effects of dietary lipid levels on abdominal lipid depositions mentioned above may be attributed to variations in tissue-specific lipid accumulation among different fish species, and the lipid distribution of golden pompano have a preference for muscle and liver (Wu et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). As expected, the whole body lipid contents did not show significant changes with varying levels of dietary lipids and proteins, which is similar with the observation in golden pompano, European grayling (\u003cem\u003eThymallus thymallus\u003c/em\u003e), and rockfish(Li et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Rahimnejad et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSerum physiological and biochemical indexes often serves as important means for evaluating the health and metabolism status in an organism (Hossain et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For example, the contents of TG, CHO, and lipoproteins (HDL and LDL) are used as useful indicators to evaluate the profiles of endogenous lipid metabolism (Hossain et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). As reported, high levels of TG, CHO, and LDL were found to be associated with impaired lipid transport and poorer health conditions (Hossain et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Rahimnejad et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As dietary lipid levels increased, increment of serum TG, CHO, and LDL concentrations were confirmed in rockfish (Li et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), European grayling (Rahimnejad et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and crucian carp (Ding et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In our case, the relatively high levels of CHO, HDL and LDL were presented in the fish fed diets with high lipid levels, while high TG levels were also found in the fish fed diets with low protein levels. Such an increase of serum TG and CHO concentrations with lower dietary protein levels is consistent with observations in hybrid grouper (\u003cem\u003eEpinephelus lanceolatus\u003c/em\u003e \u0026times; \u003cem\u003eE. fuscoguttatus\u003c/em\u003e), grass carp (\u003cem\u003eCtenopharyngodon idella\u003c/em\u003e), black sea bream (\u003cem\u003eAcanthopagrus schlegelii\u003c/em\u003e), and European grayling (Jiang et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Jin et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Rahimnejad et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which suggests the proper dietary P/L ratio may have a beneficial effect on the fish plasma lipid metabolism. In addition, the fish fed with diets D6 exhibited high serum HDL/LDL and HDL/CHO ratios, suggesting that a diet containing 40% protein and 18% lipid could also be beneficial for maintaining fish health. This may provide one explanation for the high growth observed in the D6 group.\u003c/p\u003e \u003cp\u003eThe liver is a vital organ for nutrition and energy metabolism, serving as a metabolic hub that connects various tissues, including the intestine, muscle, and adipose tissue (Han et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which plays an irreplaceable role in maintaining the metabolic homeostasis (Zhou et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The metabolic functions of the liver are also influenced by the availability of nutritional substrates, and dietary nutrition can regulate hepatic metabolism by modulating the expression of enzymes and transcription factors involved in metabolic processes(Han et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Accumulating studies have demonstrated that high-lipid diets are prone to inducing hepatic lipid metabolic disorders and fat accumulation, which can seriously impact the health and growth of fish (Naiel et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Zhou et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The previous studies have indicated that Srebp-1 and Pparα play pivotal roles as transcriptional regulators in the expression regulation of enzymatic genes associated with lipogenic and lipidolytic metabolism, respectively (Song et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Zhou et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Consistently, the enzymatic activities and mRNA levels of Cpt-I / \u003cem\u003ecpt-I\u003c/em\u003e, a rate-limiting enzyme in lipidolytic metabolism, were significantly improved in the liver of fish fed with diets D3 and D6 (containing 18% lipid, 36%~40% protein), meanwhile the contents and expression of Pparα / \u003cem\u003epparα\u003c/em\u003e exhibited similar alterations among these groups. The expression levels of lipogenic genes (\u003cem\u003efas\u003c/em\u003e and \u003cem\u003esrebp-1c\u003c/em\u003e) and their corresponding protein contents exhibited a down-regulated trend as the dietary lipid levels increased. The transcriptome analysis of golden pompano detected the activation of lipogenesis and suppression of lipolysis with increasing dietary lipid levels (Song et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Such a changing trend of hepatic lipogenesis and lipolysis with the varying dietary lipid levels were also found in large yellow croaker black sea bream (\u003cem\u003eAcanthopagrus schlegelii\u003c/em\u003e), large yellow croaker (\u003cem\u003eLarimichthys croce\u003c/em\u003ea), and largemouth bass (\u003cem\u003eMicropterus salmoides\u003c/em\u003e)(Ding et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Wang et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Yin et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The findings of these studies demonstrate that fish exhibits a distinct capacity for coordinating lipogenesis and lipolysis in response to high lipid diets.\u003c/p\u003e \u003cp\u003eNotably, in this study, the hepatic lipogenesis and lipolysis metabolism were also activated by high protein diets (45% dietary protein), which is consistent with the effects of dietary protein on morphometric parameters and plasma lipid metabolism. Similarly, the grass carp exhibited a consistent decline in both tissue and plasma lipid contents, as well as hepatic lipogenesis, in response to increasing dietary protein levels(Jin et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The relative expression of hepatic \u003cem\u003efas\u003c/em\u003e and \u003cem\u003elpl\u003c/em\u003e was up-regulated in the small yellow croaker (\u003cem\u003eLarimichthys polyactis\u003c/em\u003e) fed with increasing dietary protein levels(Ma et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Mammal studies showed that high protein diets could up-regulate the expression of genes involved in lipogenesis and lipolysis to maintain the balance of lipid metabolism in liver (Liu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Liu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The data showed that the expression of genes related to lipid anabolism (\u003cem\u003efas\u003c/em\u003e and \u003cem\u003esrebp-1c\u003c/em\u003e) is consistent with that of lipid catabolism (\u003cem\u003ecpt-I\u003c/em\u003e and \u003cem\u003epparα\u003c/em\u003e), which may be the strategy for reducing lipid decomposition in golden pompano, thereby achieving lipid metabolism balance with the increased dietary protein energy levels.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, based on the analysis of growth performance, feed utilization, morphometric parameters, and lipid metabolism, the recommended dietary protein and lipid levels for golden pompano are 40% and 18%, respectively. Additionally, this species exhibits a significant protein-sparing effect on lipid utilization. Furthermore, in order to maintain health and prevent excessive lipid accumulation in the liver, this particular fish species demonstrates a distinct ability to coordinate lipogenesis and lipolysis in response to high lipid or protein diets.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e Xinyi Li contributed to Conceptualization, Writing \u0026ndash; Original Draft Preparation; Liuling Gao and Fang Chen contributed to Investigation, Data curation; Junfeng Guan contributed to Formal analysis, Writing \u0026ndash; Review \u0026amp; Editing; Qing Pan and Dizhi Xie contributed to Supervision, Project administration, Funding acquisition. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis research was supported by Department of Ocean and Fishery of Guangdong Province (A201701C03) and Guangdong Provincial Key Laboratory of Marine Biotechnology (GPKLMB202202).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e Data generated or analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003eAll the animal experiments were approved by the College of Marine Sciences at South China Agricultural University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDing, L., Chen, W., Fu, H., Xiao, J., Fu, Y., and Ma, J. 2022. 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Aquaculture 565.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"fish-physiology-and-biochemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fish","sideBox":"Learn more about [Fish Physiology and Biochemistry](https://www.springer.com/journal/10695)","snPcode":"10695","submissionUrl":"https://submission.nature.com/new-submission/10695/3","title":"Fish Physiology and Biochemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Trachinotus ovatus, dietary protein and lipid levels, growth, feed utilization, lipid metabolism","lastPublishedDoi":"10.21203/rs.3.rs-4425646/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4425646/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo investigate the influences of dietary protein and lipid levels on the growth, feed utilization, body composition, and lipid metabolism of golden pompano (\u003cem\u003eTrachinotus ovatus\u003c/em\u003e), nine test diets containing three protein levels (35%, 40% and 45%) and three lipid levels (8%, 13% and 18%) were designed in the present study. Each diet (named D1-D9) was randomly assigned to feed triplicate groups of golden pompano juvenile (initial weight\u0026thinsp;~\u0026thinsp;70 g) for 50 days. The results showed that the dietary lipid levels positively correlated with weight gain, specific growth rate, and protein efficiency ratio (PER), suggesting that the high lipid diets (18%) can be efficiently utilized in this fish species. The dietary protein levels have no significant influences on the growth and feed utilization except for the PER. Increasing dietary protein levels resulted in a decrease in HSI, VSI, and ISI, while the dietary lipid level did not have a significant impact on morphological indices except for ISI. The dietary protein and lipid levels had no significant influences on the contents of crude lipid, crude ash, and moisture of whole body, while the crude protein contents was significantly affected by the dietary protein levels. Serum biochemical indexes, including cholesterol (CHO), TG, HDL, and LDL, as well as HDL/CHO ratio were significantly affected by the dietary lipid levels, but not by the dietary protein levels. The expression levels of genes and their associated proteins involved in hepatic lipogenesis (Srebp-1c and Fas) as well as lipolysis (Pparα and Cpt-1) were up-regulated with increasing dietary lipid levels. With dietary protein levels increasing, the expression levels of genes and their associated proteins involved in hepatic lipolysis (Pparα and Cpt-1) and lipogenesis (Srebp-1c and Fas) were up-regulated and down-regulated. Considering the present results in terms of growth performance, feed utilization, morphometric parameters, and lipid metabolism, the recommended dietary protein and lipid levels for golden pompano are 40% and 18%, respectively. The findings suggested that this species exhibits a significant protein-sparing effect on lipid utilization.\u003c/p\u003e","manuscriptTitle":"Protein-sparing effects of lipids in the diet of golden pompano (Trachinotus ovatus): evaluation of growth, feed utilization, and lipid metabolism","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-06 11:50:55","doi":"10.21203/rs.3.rs-4425646/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-04T07:36:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-28T08:34:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199570672532399082297982204472307289607","date":"2024-06-27T13:45:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210126010719410993543081705316017530831","date":"2024-06-25T08:03:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105368487330382737600913429625998364744","date":"2024-06-24T12:58:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"287075272900081390313380979916494209536","date":"2024-06-24T02:37:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-23T12:35:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"101379098178055237862424462008014745962","date":"2024-06-23T10:42:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"21255037560917138267959503685108763626","date":"2024-06-22T14:43:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11823860514447922093890960999769200716","date":"2024-06-22T13:34:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-22T12:42:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-24T21:14:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-17T06:39:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Fish Physiology and Biochemistry","date":"2024-05-15T13:56:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"fish-physiology-and-biochemistry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fish","sideBox":"Learn more about [Fish Physiology and Biochemistry](https://www.springer.com/journal/10695)","snPcode":"10695","submissionUrl":"https://submission.nature.com/new-submission/10695/3","title":"Fish Physiology and Biochemistry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1db8c492-a6c4-45db-b376-3ccaa052d8a8","owner":[],"postedDate":"June 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T16:04:30+00:00","versionOfRecord":{"articleIdentity":"rs-4425646","link":"https://doi.org/10.1007/s10695-024-01392-9","journal":{"identity":"fish-physiology-and-biochemistry","isVorOnly":false,"title":"Fish Physiology and Biochemistry"},"publishedOn":"2024-08-01 15:57:52","publishedOnDateReadable":"August 1st, 2024"},"versionCreatedAt":"2024-06-06 11:50:55","video":"","vorDoi":"10.1007/s10695-024-01392-9","vorDoiUrl":"https://doi.org/10.1007/s10695-024-01392-9","workflowStages":[]},"version":"v1","identity":"rs-4425646","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4425646","identity":"rs-4425646","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}