Dietary carbohydrate levels and lipid sources modulate the growth performance, fatty acid profiles and intermediary metabolism of blunt snout bream Megalobrama amblycephala in an interactive pattern

Aquaculture 481 (2017) 140–153

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Dietary carbohydrate levels and lipid sources modulate the growth performance, fatty acid profiles and intermediary metabolism of blunt snout bream Megalobrama amblycephala in an interactive pattern

MARK

Bing-Ke Wang, Wen-Bin Liu, Chao Xu, Xiu-Fei Cao, Xiao-Qun Zhong, Hua-Juan Shi, Xiang-Fei Li⁎ Key Laboratory of Aquatic Nutrition and Feed Science of Jiangsu Province, College of Animal Science and Technology, Nanjing Agricultural University, No.1 Weigang Road, Nanjing 210095, People's Republic of China.

A R T I C L E I N F O

A B S T R A C T

Keywords: Blunt snout bream Carbohydrate level Lipid source Growth performance Metabolism

This study aimed to investigate the interactive effects of dietary carbohydrate levels and lipid sources on growth performance, tissue fatty acid (FA) profiles and intermediary metabolism of Megalobrama amblycephala. Fish (average weight: 37.98 ± 0.07 g) were randomly fed one of eight diets containing two carbohydrate levels (30% and 43%) and four lipid sources (fish oil, FO; soybean oil, SO; palm oil, PaO; and mixed oil (FO: SO: PaO = 1:1:1), MO) for 11 weeks. Little difference (P > 0.05) was observed in growth performance and wholebody composition (except for lipid). However, energy retention, body lipid content, tissue lipid and glycogen contents and plasma metabolites concentrations all increased significantly (P < 0.05) with increasing carbohydrate levels. Additionally, nitrogen retention (NRE), body and tissue (liver and muscle) lipid content, liver and intraperitoneal fat glycogen contents and plasma metabolites concentrations were all significantly affected (P < 0.05) by lipid sources. Hepatic and muscle monounsaturated fatty acids (MUFA) contents increased significantly (P < 0.05) with increasing carbohydrate levels, whereas the opposite was true for eicosapentaenoic acid, docosahexaenoic acid, polyunsaturated fatty acids (PUFA) and n −3 long-chain PUFA (n −3 LC-PUFA) contents (P < 0.05). In terms of lipid sources, fish fed FO presented a high proportion of n− 3 LC-PUFA, EPA and DHA (P < 0.05); while fish received SO and PaO obtained a high proportion of n−6 LC-PUFA and MUFA, respectively (P < 0.05). Liver glucokinase, glycogen synthase, fatty acid synthetase (FAS), acetyl-CoA carboxylase α, delta-6 fatty acyl desaturase and peroxisome proliferator-activated receptor γ (PPARγ) as well as muscle pyruvate kinase (PK) expressions all increased significantly (P < 0.05) with increasing carbohydrate levels, whereas the opposite was true for the transcriptions of enzymes involved in β-oxidation and gluconeogenesis. Hepatic FAS and muscle phosphoenolpyruvate carboxykinase (PEPCK) transcriptions were significantly affected (P < 0.05) by lipid sources. Furthermore, an interaction between dietary carbohydrate levels and lipid sources was also observed in feed intake, NRE, body/tissue lipid and glycogen contents, plasma lipids, tissue MUFA, PUFA, n− 3 LC-PUFA and n −6 LC-PUFA contents as well as the transcriptions of enzymes involved in glucose and lipid metabolism (P < 0.05). Overall, these findings suggested that blunt snout bream can efficiently utilize various lipid sources at different carbohydrate levels. Dietary carbohydrate levels and lipid sources as well as their interaction significantly affected nutrient retention, tissue lipid and glycogen contents, plasma metabolites, tissue FA profiles and the intermediary metabolism, but not growth and feed efficiency.

1. Introduction

mammals, fish generally have a poor ability to use glucose for energy purposes (Polakof et al., 2012). Generally, the nutritional values of carbohydrates vary greatly among different fish species with omnivorous and herbivorous fish being capable to utilize much higher levels of carbohydrates than carnivorous ones (Wilson, 1994). In fact, a more efficient regulation of plasma glucose is observed in omnivorous and herbivorous fish, when compared with carnivorous ones, after glucose administration or high-carbohydrate intake (Hemre et al., 2002). To

Carbohydrates are usually regarded as the cheapest energy source for fish due to their rich availability and low cost (Wilson, 1994). The incorporation of this nutrient could improve the pelleting quality of feed. Of greater quantitative importance is its capability to spare protein and lipids in feed as well as to reduce the nitrogenous losses of fish into environment (Hemre and Deng, 2015). However, compared with

⁎

Corresponding author. E-mail address: xfl[email protected] (X.-F. Li).

http://dx.doi.org/10.1016/j.aquaculture.2017.08.034 Received 14 June 2017; Received in revised form 26 July 2017; Accepted 25 August 2017 Available online 04 September 2017 0044-8486/ © 2017 Elsevier B.V. All rights reserved.

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date, the mechanisms underlying these metabolic differences are still poorly understood. Furthermore, the carbohydrate utilization of fish have been reported to be affected by a large number of factors besides feeding habits, such as species, genotypes, digestive system functions, growth and/or developmental stages, dietary compositions, feed manufacturing, feeding regimes, water temperature and so on. (Morata et al., 1982; Hung and Storebakken, 1994; Enes et al., 2009; Polakof et al., 2012; Zhou et al., 2013c; Jin et al., 2014). This indicated that the carbohydrate utilization and metabolism of fish is quite complicated, as warrants extensive studies. Carbohydrates and lipids are two important non-protein energy sources for fish (Erfanullah and Jafri, 1998), and usually have a close relationship with each other in glycolipid metabolism (Zhou et al., 2016). In fact, glucose and fatty acids generally has a strong interaction in fish, which can remarkably affect glucose utilization (C. Castro et al., 2016a). This suggested that the carbohydrate utilization and metabolism of fish might be largely affected by dietary lipids. Indeed, both the growth performance and glucose metabolism of fish has been reported to be remarkably affected by dietary carbohydrate to lipid ratios (Johnston et al., 2003; Li et al., 2013; Wang et al., 2014). In addition, an interaction between dietary carbohydrate levels and lipid contents was also observed in some fish species, like blunt snout bream (Megalobrama amblycephala) (Li et al., 2014), red drum (Sciaenops ocellatus) (Ellis and Reigh, 1991) and rainbow trout (Oncorhynchus mykiss) (Gümüş and İKİZ, 2009). Furthermore, the carbohydrate utilization and intermediary glucose metabolism of certain fish have recently been reported to be affected by dietary lipid sources. For example, recently lipid sources have been reported to remarkably affect the growth performance, feed utilization, tissue fatty acids composition and plasma metabolites of both European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata) fed different dietary carbohydrate levels, although very few interactions were observed (Castro et al., 2015; C. Castro et al., 2016a). In addition, a combination of dietary vegetable oils and starch may negatively affect the intermediary metabolism (especially the cholesterol absorption and transport) of both species (Castro et al., 2015; L.F. Castro et al., 2016). These studies all suggested that the growth performance and intermediary metabolism of fish might be significantly affected by the interactive effects between dietary carbohydrates and lipids, which are still poorly understood, thus deserving our special attention. Blunt snout bream is an economically important herbivorous freshwater fish in China (which is also distributed worldwide) with high potential for intensive aquaculture (Li et al., 2010). In commercial production, diets formulated for this species usually contain large proportions of non-protein energy in order to reduce the feed cost. However, inappropriate use of carbohydrates and lipids might cause metabolic burden of this species, as consequently results in growth retardation and impaired health status (Li et al., 2012; Zhou et al., 2013a). Therefore, it is quite urgent to investigate the non-protein energy utilization of this species, and find an effective approach to promote it. Considering the close relationship between dietary carbohydrates and lipids, the carbohydrate utilization of this fish might be affected by different lipid sources. To test this hypothesis, the present study was conducted to investigate the effects of dietary carbohydrate levels and lipid sources as well as their interaction on the growth performance, body composition and liver and muscle fatty acid profiles of blunt snout bream. The results obtained here might provide us some new insights into the non-protein energy utilization by fish, as might facilitate the development of low-protein and high-energy feed for aquatic animals.

Table 1 Fatty acid composition (% of total fatty acids) of the lipid sources. FA

FO

SO

PaO

MO

C14:0 C16:0 C18:0 C20:0 ΣSFA C16:1n− 9 C18:1n− 9 C20:1n− 9 ΣMUFA C18:2n− 6 C18:3n− 3 C20:5n− 3EPA C22:5n− 3 C22:6n− 3DHA ΣPUFA Σn −3 Σn −6

5.379 18.163 3.833 0.572 27.947 5.701 19.348 3.112 28.161 13.633 2.436 9.196 1.008 10.769 37.042 23.409 13.633

0.061 10.529 3.821 0.338 14.749 0.091 25.823 0.25 26.164 52.669 5.954 – – – 58.623 5.954 52.669

0.851 26.527 2.951 0.283 30.612 0.239 50.075 0.243 50.557 17.753 0.753 – – – 18.506 0.753 17.753

1.886 18.642 3.528 0.366 24.422 1.805 32.388 1.008 35.201 28.204 3.013 2.863 0.320 3.655 38.055 9.851 28.204

FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). ΣSFA, saturated fatty acids; ΣMUFA, monounsaturated fatty acids; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; ΣPUFA, polyunsaturated fatty acids; Σn − 3, n − 3 long-chain PUFA; Σn − 6, n − 6 long-chain PUFA.

diets were formulated to contain two dietary carbohydrate (namely nitrogen-free extract) levels (30% and 43%) and four lipid sources (fish oil, FO; soybean oil, SO; palm oil, PaO; and mixed oil (FO: SO: PaO = 1:1:1), MO), respectively. The MO contained 1/3 of FO, 1/3 of SO and 1/3 of PaO. According to our previous studies, the optimal dietary carbohydrate level for juvenile blunt snout bream is 29–32% (Li et al., 2013, 2014; Jiang et al., 2016). Therefore, a diet containing 30% carbohydrate was adopted as the control, while that of 43% was designated as the high-carbohydrate diet. In addition, FO, SO and PaO were selected here based on a previous study investigating the utilization of dietary lipid sources by blunt snout bream (Li et al., 2015a). Fatty acids (FA) composition of different lipid sources was presented in Table 1. Formulation, proximate composition and FA composition of the experimental diets were presented in Tables 2 and 3, respectively. Fish meal, soybean meal, rapeseed meal and cottonseed meal served as protein sources. Corn starch was used as the main carbohydrate source. Microcrystalline cellulose was used to compensate for the carbohydrate levels required. All diets were prepared in our laboratory. Dry ingredients were grounded, weighed, then mixed with oils. An appropriate amount of water was added to produce dough. The dough was later pelleted using a laboratory pellet machine (MUZL 180, Jiangsu Muyang Group Co., Ltd., Yangzhou, China) and dried in a ventilated oven at 30 °C. After drying, the diets were broken up and sieved into proper pellet size. All diets were stored at −20 °C in plastic-lined bags until use. 2.2. Fish and the feeding trial Blunt snout bream were obtained from the Fish Hatchery of Yangzhou (Jiangsu, China). Prior to the feeding trial, fish were acclimated to the experimental conditions in several cages (1 × 1 × 1.5 m, L:W:H) by feeding a commercial diet (feed No. 191, Tongwei feed group Co., Ltd., Wuxi, China) containing 32% protein and 5% lipid for 2 weeks. After the acclimation, fish of similar sizes (average weight: 37.98 ± 0.07 g) were randomly distributed into 24 cages (1 × 1 × 1.5 m, L:W:H) at a rate of 15 fish per cage. Fish in each cage were randomly fed one of eight experimental diets. Each diet was tested in triplicate. Fish were hand-fed to apparent satiation three times daily (07:30, 11:30 and 16:30) for 11 weeks. During the feeding trial, fish were reared under the following conditions: water temperature ranged from 26 to 29 °C; dissolved oxygen was maintained at 5.0–6.0 mg/L; pH fluctuated between 7.1 and 7.3; and total ammonia nitrogen was

2. Materials and methods 2.1. Experimental diets A 2 × 4 factorial design was used in this study. Eight experimental 141

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Table 2 Formulation and proximate composition of the experimental diets.

Table 3 Fatty acid composition (% of total fatty acids) of the experimental diets.

Diets CL

30%

LS

FO

Ingredients (% dry weight) Fish meal 5.00 Soybean meal 30.00 Rapeseed meal 18.40 Cottonseed meal 15.00 Fish oil 3.60 Soybean oil 0 Palm oil 0 Corn starch 12.00 Microcrystalline 13.00 cellulose Calcium 1.80 biphosphate Premixa 1.20 Proximate analyses Dry matter Crude protein Crude lipid Ash Crude fiber Nitrogen-free extractb Gross energy (MJ/kg)

FA 43% SO

PaO

MO

FO

SO

PaO

MO

5.00 30.00 18.40 15.00 0 3.60 0 12.00 13.00

5.00 30.00 18.40 15.00 0 0 3.60 12.00 13.00

5.00 30.00 18.40 15.00 1.20 1.20 1.20 12.00 13.00

5.00 30.00 18.40 15.00 3.60 0 0 25.00 0

5.00 30.00 18.40 15.00 0 3.60 0 25.00 0

5.00 30.00 18.40 15.00 0 0 3.60 25.00 0

5.00 30.00 18.40 15.00 1.20 1.20 1.20 25.00 0

1.80

1.80

1.80

1.80

1.80

1.80

1.80

1.20

1.20

1.20

1.20

1.20

1.20

1.20

89.69 30.63 5.30 6.84 16.61 30.31

90.31 30.59 6.23 6.90 16.69 29.90

88.67 30.45 5.95 6.82 3.24 42.21

88.43 29.91 5.90 6.73 3.6 42.29

89.81 30.74 6.74 6.91 3.35 42.07

89.45 30.64 5.81 6.90 3.82 42.28

19.04

19.15

18.24

19.16

18.34

19.48

C14:0 C16:0 C18:0 C20:0 ΣSFA C16:1n− 9 C18:1n− 9 C20:1n− 9

(% air-dry basis) 89.64 89.63 30.94 29.91 5.30 6.10 6.85 6.88 15.76 16.88 30.79 29.86 18.36

CL

19.12

ΣMUFA C18:2n− 6 C18:3n− 3 C20:5n− 3EPA C22:5n− 3 C22:6n− 3DHA

CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). a Premix supplied the following minerals (g/kg of diet) and vitamins (IU or mg/kg of diet): CuSO4·5H2O, 2.0 g; FeSO4·7H2O, 25 g; ZnSO4·7H2O, 22 g; MnSO4·4H2O, 7 g; Na2SeO3, 0.04 g; KI, 0.026 g; CoCl2·6H2O, 0.1 g; Vitamin A, 900,000 IU; vitamin D, 200,000 IU; vitamin E, 4500 mg; vitamin K3, 220 mg; vitamin B1, 320 mg; vitamin B2, 1090 mg; vitamin B5, 2000 mg; vitamin B6, 500 mg; vitamin B12, 1.6 mg; vitamin C, 5000 mg; pantothenate, 1000 mg; folic acid, 165 mg; choline, 60,000 mg. b Calculated by difference (dry matter − crude protein − crude lipid − ash − crude fiber).

ΣPUFA Σn −3 Σn −6

30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43%

LS FO

SO

PaO

MO

1.891 3.172 18.868 17.503 4.532 3.660 0.277 0.372 25.568 24.707 2.404 3.639 24.217 22.923 0.993 1.638 27.614 28.200 29.625 24.607 3.315 3.214 3.613 5.958 0.474 0.645 7.013 8.808 44.040 43.232 14.415 18.625 29.625 24.607

0.696 0.558 13.297 12.725 3.778 3.717 0.303 0.329 18.074 17.329 0.939 0.762 26.827 26.742 0.385 0.438 28.151 27.942 44.961 46.325 5.159 5.333 0.920 0.843 0.136 0.116 1.536 1.259 52.712 53.876 7.751 7.551 44.961 46.325

1.059 0.893 22.755 22.494 3.030 3.159 0.277 0.248 27.121 26.794 0.859 0.768 41.787 38.699 0.295 0.371 42.941 39.838 24.942 27.088 2.105 2.337 0.794 0.902 0.106 0.140 1.263 1.961 29.210 32.428 4.268 5.340 24.942 27.088

1.128 1.584 18.995 18.387 4.167 3.595 0.253 0.279 24.543 23.845 1.396 1.721 28.190 30.414 0.643 0.590 30.229 32.725 33.025 31.306 3.494 3.435 1.983 2.576 0.280 0.294 4.720 3.962 43.502 41.573 10.477 10.267 33.025 31.306

CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). ΣSFA, saturated fatty acids; ΣMUFA, monounsaturated fatty acids; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; ΣPUFA, polyunsaturated fatty acids; Σn − 3, n − 3 long-chain PUFA; Σn − 6, n − 6 long-chain PUFA.

kept < 0.04 mg/L.

Höganäs, Sweden). Ash was analyzed by combustion at 550 °C for 4 h. Gross energy was determined using a Bomb Calorimeter (PARR 1281, Parr Instrument Company, Moline, IL, USA). Crude fiber was analyzed by fritted glass crucible method using an automatic analyzer (ANKOM A2000i, Macedon, New York, NY, USA). The lipid contents of liver, muscle and intraperitoneal fat were extracted following the procedures described by Folch et al. (1957). Tissue glycogen contents were measured according to the method described by Keppler et al. (1974).

2.3. Sample collection Before the feeding trial, 6 fish were randomly collected for the analysis of initial body composition. At the end of the feeding trial, fish were starved for 24 h to evacuate the alimentary tract contents prior to sampling. All fish in each cage were counted and weighed. Then, 4 fish were randomly collected from each cage (with a total of 12 fish from each treatment), and were anesthetized in diluted MS-222 (tricaine methanesulfonate, Sigma, USA) at the concentration of 100 mg/L. Thereafter, blood sample was obtained from caudal vein using heparinized syringes and centrifuged at 3000g at 4 °C for 10 min. The supernatant was then stored at − 80 °C for subsequent analysis. Then, these fish were sampled for liver, muscle, viscera and intraperitoneal fat. These samples were stored in liquid nitrogen for further analysis. In addition, 2 fish were randomly collected from each cage and were stored at −20 °C for the determination of body composition.

2.4.2. FA composition analysis FA methyl esters (FAME) were determined by acid transmethylation of total lipids using boron trifluoride (BF3) in methanol (14%) as described by Shantha and Ackman (1990). The FA composition of lipid sources, diets, liver and muscle were determined using the gas chromatography (Agilents Technologies Inc., Santa Clara, CA, USA) according to the method detailed by Z.X. Gao et al. (2012). 2.4.3. Analysis of plasma metabolites Plasma glucose (GLU) was measured by the glucose oxidase method as described by Asadi et al. (2009). Plasma triglycerides (TG), total cholesterol (T-CHO) and non-esterified fatty acid (NEFA) were quantified by the protocols detailed previously (McNamara and Schaefer, 1987).

2.4. Analytic procedures 2.4.1. Proximate composition analysis Proximate compositions of diets and fish were both analyzed by the standard methods of AOAC (1995). Moisture was measured by oven drying at 105 °C until constant weight. Crude protein (nitrogen × 6.25) was determined by the micro-Kjeldahl method using an Auto Kjeldahl System (FOSS KT260, Switzerland). Crude lipid was measured by solvent extraction using a Soxtec System (Soxtec System HT6, Tecator,

2.4.4. Quantitative RT-PCR Total RNA was extracted from liver and muscle using Trizol 142

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Table 4 Nucleotide sequences of primers used to quantify gene expressions by real-time PCR. Target gene

Forward (5′–3′)

Reverse (5′–3′)

Accession number

GK PK PEPCK GS FAS CPT-1 △6 FAD Elovl5 PPARα PPARβ PPARγ ACCα EF1α

AAAATGCTGCCCACTTAT GCCGAGAAAGTCTTCATCGCACAG TGGCCCGTGTGGAGAGTAAAA CCTCCAGTAACAACTCACAACA AGCGAGTACGGTGATGGT TACTTCCAAAGCGGTGAG TCAATGCGTTTGTAGTGGGAA ATGTCAGTGTATCAGGGCGGA ACCGAAACAAGTGCCAATA CATCCTCACGGGCAAGAC AGCTTCAAGCGAATGGTTCTG GAAGGTCAACGGTGCGG CTTCTCAGGCTGACTGTGC

AATGCCCTTATCCAAATC CGTCCAGAACCGCATTAGCCAC ATGTGTTCTGCCAGCCAG CAGATAGATTGGTGGTTACGC GGATGATGCCTGAGATGG AGAGGTATTGTCCGAGCC TTGTGCTGATGGTTGTAAGGC ATGTTGAGCATGGTGGCGTG TCAGTCACCGTCTCAACC CACTGGCAGCGGTAGAAG AGGCCTCGGGCTTCCA CGGTGAAGTGGGATGCC CCGCTAGCATTACCCTCC

KJ141202.1 J. Gao et al. (2012b) J. Gao et al. (2012b) J. Gao et al. (2012b) KF918747.1 Lu et al. (2014) Li et al. (2016) Li et al. (2016) Li et al. (2016) Li et al. (2016) Li et al. (2016) Lu et al. (2014) X77689.1

GK, glucokinase; PK, pyruvate kinase; PEPCK, phosphoenolpyruvate carboxykinase; GS, glycogen synthase; FAS, fatty acid synthetase; CPT I, carnitine palmitoyl transferase I; Δ6 FAD, delta-6 fatty acyl desaturase; elovl5, elongase of very long chain fatty acids; PPAR, peroxisome proliferator-activated receptor; ACCα, acetyl-CoA carboxylase α; EF1α, elongation factor 1 alpha.

Viscera index (VSI) = Viscera weight × 100 / fish weight. Intraperitoneal fat (IPF) ratio (%) = Intraperitoneal fat weight × 100 / body weight. Protein efficiency ratio = Wet weight gain / total protein fed. Nitrogen and energy retention (NRE and ERE) (%) = [(Wt × Ct) − (W0 × C0)] × 100 / (Cdiet × feed intake), where W0 and Wt are the initial and final body weights, C0 and Ct are the initial and final contents in body respectively, and Cdiet is the content in the diets.

(Invitrogen, CA, USA) following the protocols, and treated by RQ1 RNase-free DNase (Takara Co. Ltd., Japan) to eliminate genomic DNA contamination. The quantity and purity of the RNA was determined by absorbance measures at 260 and 280 nm. The ratio of absorbance at 260 and 280 nm is used to assess the purity of RNA. And, a ratio near 2.0 is generally accepted as “pure” for RNA. Its integrity was further measured by electrophoresis in 1.0% formaldehyde denaturing agarose gels. cDNA was generated from 500 ng DNase-treated RNA by a RT-PCR kit (Takara Co. Ltd., Japan) following the manufacturer's instructions. The reaction mixture volume was 10 μL, containing 2 μL buffer (5 ×), 0.5 μL dNTP mixture (10 mM each), 0.25 μL RNase inhibitor (40 U μL− 1), 0.5 μL dT-AP primer (50 mM), 0.25 μL ExScript™ RTase (200 U μL− 1) and 6.5 μL DEPC water. Cycling conditions were 42 °C for 40 min, 90 °C for 2 min, and 4 °C thereafter. After reverse transcription, real-time PCR was employed to determine mRNA levels using a SYBR Green II Fluorescence Kit (Takara Bio. Inc., Japan). Gene primers were designed using the Primer 5 software according to available sequences (Table 4). Real-time PCR assays were carried out on a Mini Option real-time detector (BIO-RAD, USA). The assays were performed with a reaction mix of 20 μL per sample, each of which contained 2 μL template (equivalent to 100 ng cDNA), 10 μL SYBR® premix Ex Taq™ (TaKaRa), 0.4 μL ROX Reference DyeII (TaKaRa), 0.4 μL of each primer (10 μmol L− 1) and 6.8 μL dH2O. The protocol was set as follows: initial denaturation at 95 °C for 5 s followed by 40 cycles, annealing at 60 °C for 34 s and a final extension at 95 °C for 5 s, followed by a melt curve analysis of 15 s from 95 to 60 °C, 1 m for 60 °C and then up to 95 °C for 15 s. To analyze the relative transcriptional levels, the transcriptions of target genes were normalized by a reference gene elongation factor 1 alpha (EF1α) (Zhang et al., 2013) using the 2− ΔΔCT method (Livak and Schmittgen, 2001).

The data were analyzed by two-way ANOVA test using the SPSS program version 19.0 (SPSS Inc., Michigan Avenue, Chicago, IL, USA) for significant differences among treatment means based on carbohydrate level, lipid source and their interaction. If significant (P < 0.05) differences were found in the interaction, each factor was further analyzed separately by one-way ANOVA, taking into account the normality of the data distribution and the homogeneity of variances. In addition, data between the two carbohydrate levels at each lipid source was also analyzed by one-way ANOVA. If significant (P < 0.05) differences were found, Tukey's HSD multiple range test was conducted to rank the means. All data were presented as means ± S.E.M. (standard error of the mean).

3. Results 3.1. Growth performance and feed utilization Growth performance and feed utilization of blunt snout bream were shown in Table 5 and Fig. 1. No mortality was observed during the 11week feeding trial. No difference (P > 0.05) was observed in final weight, WG, SGR, FCR, FER and VSI among all the treatments. ERE, HSI and the IPF ratio all increased significantly (P < 0.05) with increasing dietary carbohydrate levels in terms of dietary carbohydrate levels, whereas no statistical difference (P > 0.05) was observed in these parameters in terms of lipid sources. Unlikely, NRE was significantly (P < 0.05) affected by dietary lipid sources with the highest value observed in fish fed SO, but showed little difference (P > 0.05) in terms of dietary carbohydrate levels. In addition, feed intake, nitrogen and energy intake, NRE, HSI and the IPF ratio were all significantly (P < 0.05) affected by the interaction between dietary carbohydrate levels and lipid sources. Fish fed 30% carbohydrate and SO obtained the highest NRE, but the lowest feed intake, nitrogen and energy intake and HSI. Furthermore, the lowest IPF ratio was observed in fish fed 30% carbohydrate and PaO.

2.5. Calculations and statistical analysis The growth parameters adopted in this study were calculated as follows: Weight gain rate (WGR) = (Final body weight − initial body weight) × 100 / initial body weight. Specific growth rate (SGR) = (LnWt − LnW0) × 100 / T, where W0 and Wt are the initial and final body weights, and T is the culture period in days. Feed conversion ratio (FCR) = Feed intake / total wet weight gain rate. Hepatosomatic index (HSI) = Liver weight × 100 / body weight. 143

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Table 5 Growth performance of blunt snout bream fed diets differing in carbohydrate levels and lipid sources. CL

Initial weight (g)

30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43%

Final weight (g) SGR (% day

−1

LS

)

FCR PER Nitrogen intake (g per fish) Energy intake (MJ per fish) VSI (%) HSI (%) IPF (%)

Two-way ANOVA

FO

SO

PaO

MO

38.18 ± 0.05 37.87 ± 0.21 150.97 ± 2.78 160.92 ± 4.94 1.78 ± 0.02 1.88 ± 0.03 1.93 ± 0.03 1.75 ± 0.03 1.75 ± 0.05 1.92 ± 0.06 10.78 ± 0.12a 10.77 ± 0.74 4.00 ± 0.04a 4.03 ± 0.28 9.99 ± 0.48 10.54 ± 0.29 1.16 ± 0.04 1.23 ± 0.04 2.14 ± 0.19ab 2.78 ± 0.23A⁎

37.96 ± 0.19 38.09 ± 0.19 169.76 ± 0.53 159.51 ± 6.48 1.95 ± 0.01 1.86 ± 0.06 1.45 ± 0.03 1.71 ± 0.13 2.32 ± 0.05 2.03 ± 0.11 9.12 ± 0.15b 10.31 ± 0.77 3.64 ± 0.06b 4.13 ± 0.31 9.39 ± 0.34 9.62 ± 0.23 1.08 ± 0.03 1.38 ± 0.05⁎⁎⁎ 2.21 ± 0.22ab 2.80 ± 0.15A⁎

38.31 ± 0.19 37.74 ± 0.18 156.69 ± 11.24 163.02 ± 10.06 1.92 ± 0.09 1.89 ± 0.08 1.86 ± 0.19 1.62 ± 0.14 1.78 ± 0.17 2.04 ± 0.16 10.62 ± 0.18a 9.87 ± 0.42 4.13 ± 0.07a 3.68 ± 0.16 9.35 ± 0.66 10.04 ± 0.47 1.11 ± 0.05 1.31 ± 0.06⁎ 1.85 ± 0.18b 2.38 ± 0.13AB⁎

37.89 ± 0.39 37.80 ± 0.14 156.53 ± 10.49 158.91 ± 10.23 1.84 ± 0.10 1.86 ± 0.08 1.95 ± 0.16 1.54 ± 0.15 1.73 ± 0.15 2.26 ± 0.21 11.21 ± 0.34a 9.04 ± 0.22⁎ 4.39 ± 0.13a 3.59 ± 0.09⁎ 10.01 ± 0.23 10.77 ± 0.66 1.23 ± 0.05 1.26 ± 0.06 2.73 ± 0.30a 2.26 ± 0.12B

CL

LS

CL × LS

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

⁎⁎⁎

⁎

ns ns

ns ⁎

⁎

ns ⁎

⁎

CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). Significant differences (P < 0.05) among different lipid sources within each carbohydrate level are indicated by different letters (lower case for 30% carbohydrate level, upper case for 43% carbohydrate level). *Indicates a significant difference (P < 0.05) between the carbohydrate levels at each lipid source, ns: not significant. ⁎ P < 0.05. ⁎⁎⁎ P < 0.001.

intraperitoneal fat) lipid and glycogen contents all increased significantly (P < 0.05) with increasing dietary carbohydrate levels in terms of dietary carbohydrate levels. In addition, while-body and liver lipid contents of fish fed MO were significantly (P < 0.05) higher than that of the other groups in terms of lipid sources. Liver and

3.2. Whole-body composition and tissue lipid and glycogen contents As can be seen from Table 6, whole-body moisture, protein, ash and energy contents all showed no statistical difference (P > 0.05) among all the treatments. Whole-body lipid and tissue (liver, muscle and

B

A a

a

a

b

200

*

150 100

Two-way ANOVA CL: ns LS: ns CL×LS: ns 30%CL 43%CL

400

Two-way ANOVA CL: ns LS: ns CL×LS: ** 30%CL

300 WGR(%)

43%CL

200 100

50

Pa O

FO

M O

SO

FO

Pa O

LS

LS

D

C

ab

Two-way ANOVA

40

20

NRE(%)

CL: * LS: ns CL×LS: ns

30

30%CL 43%CL

10

Two-way ANOVA CL: ns

a

50

40

b b

30 20

LS: * CL×LS: * 30%CL 43%CL

10

O M

Pa

FO

M O

Pa O

SO

FO

O

0

0

SO

ERE(%)

M O

0

0

SO

Feed intake (g per fish)

250

LS

LS

Fig. 1. Feed intake (A), weight gain rate (WGR, B), energy retention efficiency (ERE, C) and nitrogen retention efficiency (NRE, D) of blunt snout bream fed diets differing in carbohydrate levels and lipid sources. CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). Each data represents the mean of three replicates. Significant differences (P < 0.05) among different lipid sources within each carbohydrate level are indicated by different letters (lower case for 30% carbohydrate level, upper case for 43% carbohydrate level). *Indicates a significant difference between the carbohydrate levels at each lipid source. *P < 0.05, **P < 0.01, ns: not significant.

144

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Table 6 Whole-body composition and tissue glycogen and lipid contents of blunt snout bream fed experimental diets differing in carbohydrate levels and lipid sources. Initial

Whole-body Moisture (%)

78.00

Crude protein (%)

15.17

Crude lipid (%)

3.30

Ash (%)

3.53

Energy (MJ/kg)

4.56

Liver Lipid (%) Glycogen (mg/g) Muscle Lipid (%) Glycogen (μg/g) Intraperitoneal fat Lipid (%) Glycogen (μg/g)

CL

LS

Two-way ANOVA

FO

SO

PaO

MO

CL

LS

CL × LS

30% 43% 30% 43% 30% 43% 30% 43% 30% 43%

71.81 ± 0.13 69.69 ± 0.62 17.10 ± 0.43 16.37 ± 0.63 6.82 ± 0.21b 8.04 ± 0.26⁎ 3.44 ± 0.11 3.19 ± 0.16 6.96 ± 0.15 7.38 ± 0.20

71.74 ± 0.57 70.77 ± 0.55 18.08 ± 0.56 17.18 ± 0.37 6.84 ± 0.28b 7.94 ± 0.48 3.59 ± 0.13 3.84 ± 0.57 7.21 ± 0.19 7.45 ± 0.16

71.49 ± 1.23 70.35 ± 0.37 18.41 ± 1.36 17.64 ± 0.26 6.90 ± 0.47b 8.56 ± 0.53 4.03 ± 0.40 3.61 ± 0.09 7.32 ± 0.35 7.94 ± 0.20

68.92 ± 1.39 69.99 ± 0.37 15.83 ± 1.07 16.23 ± 0.41 8.92 ± 0.56a 8.18 ± 0.07 3.23 ± 0.04 3.49 ± 0.19 7.64 ± 0.11 7.41 ± 0.14

ns

ns

ns

ns

ns

ns

⁎

⁎

⁎

ns

ns

ns

ns

ns

ns

30% 43% 30% 43%

6.79 ± 0.20bc 16.34 ± 0.63A⁎⁎⁎ 17.99 ± 2.73 21.99 ± 2.01B

5.48 ± 0.76c 12.31 ± 0.27B⁎⁎ 16.34 ± 1.78 42.17 ± 1.38A⁎⁎⁎

7.09 ± 0.15b 10.82 ± 0.18C⁎⁎⁎ 14.24 ± 1.38 31.00 ± 5.05B⁎

14.69 15.03 14.82 24.24

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎

⁎⁎

30% 43% 30% 43%

5.23 7.06 2.13 2.70

6.47 5.32 2.62 2.77

4.10 3.87 2.54 3.08

2.98 6.11 2.03 2.93

⁎⁎

⁎⁎⁎

⁎⁎⁎

ns

ns

30% 43% 30% 43%

48.33 ± 3.57 68.26 ± 5.91 6.42 ± 0.19bc 7.03 ± 0.46C

± ± ± ±

0.28b 0.27A⁎ 0.14 0.07

± ± ± ±

55.02 64.27 10.22 10.55

0.25a 0.45B 0.13 0.04

± ± ± ±

4.89 2.32 0.58a 0.32A

± ± ± ±

0.09c 0.24C 0.19 0.27

54.98 ± 2.03 68.53 ± 2.04 6.82 ± 0.67b 7.49 ± 0.33BC

± ± ± ±

± ± ± ±

0.36a 0.50A 2.86 0.38B⁎

0.16d 0.50AB⁎⁎ 0.09 0.09

60.57 ± 4.80 63.57 ± 4.04 5.13 ± 0.31c 8.62 ± 0.39B⁎⁎

⁎⁎⁎

⁎⁎

⁎⁎

ns

ns

⁎⁎⁎

⁎⁎

CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). Significant differences (P < 0.05) among different lipid sources within each carbohydrate level are indicated by different letters (lower case for 30% carbohydrate level, upper case for 43% carbohydrate level). *Indicates a significant difference (P < 0.05) between the carbohydrate levels at each lipid source, ns: not significant. ⁎ P < 0.05. ⁎⁎ P < 0.01. ⁎⁎⁎ P < 0.001.

intraperitoneal fat glycogen contents of fish fed SO were both significantly higher than those of the other groups (P < 0.05). Furthermore, whole-body lipid content, liver lipid and glycogen contents, muscle lipid and intraperitoneal fat glycogen contents were all significantly (P < 0.05) affected by the interaction between dietary carbohydrate levels and lipid sources. The highest whole-body lipid was observed in fish fed 30% carbohydrate and MO, while this held true for liver and muscle lipid contents in fish fed 43% carbohydrate and FO. Additionally, the highest liver and intraperitoneal fat glycogen contents were both observed in fish fed 43% carbohydrate and SO.

the FA composition of diets, as was shown in Tables 8 and 9. In liver, no statistical difference (P > 0.05) was observed in C14:0 and C20:0 contents among all the treatments. C18:1n −9 and MUFA both increased significantly (P < 0.05) with increasing dietary carbohydrate levels in terms of dietary carbohydrate levels, whereas the opposite was true for PUFA, n− 3 LC-PUFA, n −6 LC-PUFA, DHA and EPA contents (P < 0.05). In addition, MUFA, PUFA, n − 3 LC-PUFA, n − 6 LC-PUFA, DHA and EPA contents were significantly (P < 0.05) affected by dietary lipid sources. Fish fed FO presented a higher proportion of n −3 LC-PUFA, EPA and DHA (P < 0.05) than those of the other treatments. However, fish offered SO and PaO obtained significantly high levels of PUFA (also n− 6 LC-PUFA) and MUFA, respectively (P < 0.05). Furthermore, SFA, MUFA, EPA, DHA, PUFA, n− 3 LC-PUFA and n −6 LCPUFA contents were all significantly (P < 0.05) affected by the interaction between dietary carbohydrate levels and lipid sources. Fish fed 30% carbohydrate and 1) FO obtained the highest levels of n −3 LC-PUFA, EPA and DHA; 2) PaO presented the most abundant SFA; and 3) SO obtained the richest PUFA and n − 6 LC-PUFA contents. However, the highest MUFA level was observed in fish fed 43% carbohydrate and MO (Table 8). As can been seen from Table 9, little difference (P > 0.05) was observed in muscle C16:0, C20:0 and SFA contents among all the treatments. MUFA levels increased significantly (P < 0.05) with increasing dietary carbohydrate levels in terms of dietary carbohydrate levels, while the opposite was true for PUFA, n − 3 LC-PUFA, DHA and EPA contents (P < 0.05). EPA, DHA, PUFA and n −3 LC-PUFA contents of fish fed FO was all significantly higher than those of the other groups in terms of lipid sources (P < 0.05). Fish fed SO and PaO presented a higher proportion of n − 6 LC-PUFA and MUFA

3.3. Plasma metabolites Plasma metabolites of blunt snout bream were shown in Table 7. No difference (P > 0.05) was observed in NEFA among all the treatments. Plasma GLU, TG and T-CHO concentrations increased significantly (P < 0.05) with increasing dietary carbohydrate levels in terms of dietary carbohydrate levels. In addition, GLU, TG and T-CHO were significantly (P < 0.05) affected by dietary lipid sources. Fish fed FO presented a lower proportion (P < 0.05) of both GLU and TG than those of the other treatments, while the opposite was true for T-CHO. Furthermore, TG and T-CHO were significantly (P < 0.05) affected by the interaction between dietary carbohydrate levels and lipid sources with the highest values both observed in fish fed 43% carbohydrate and FO. 3.4. Liver and muscle FA profiles The FA composition of liver and muscle of fish generally reflected 145

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Table 7 Plasma metabolites (mmol L− 1) of blunt snout bream fed experimental diets differing in carbohydrate levels and lipid sources. CL

LS

Two-way ANOVA

FO GLU TG T-CHO NEFA

30% 43% 30% 43% 30% 43% 30% 43%

7.93 9.51 1.18 1.86 9.39 9.69 0.39 0.47

± ± ± ± ± ± ± ±

0.65 0.26 0.01c 0.01A⁎⁎⁎ 0.19a 0.15A 0.09 0.02

SO

PaO

MO

10.26 ± 0.63 12.4 ± 0.10 1.66 ± 0.05b 1.72 ± 0.06B 8.12 ± 0.18b 8.65 ± 0.27AB 0.39 ± 0.01 0.41 ± 0.03

10.44 ± 0.27 10.26 ± 0.55 1.57 ± 0.09b 1.81 ± 0.01AB 8.41 ± 0.20b 8.09 ± 0.45B 0.54 ± 0.01 0.49 ± 0.06

10.23 ± 0.38 10.66 ± 0.55 1.85 ± 0.06a 1.53 ± 0.03C⁎⁎ 7.25 ± 0.40c 9.26 ± 0.39A⁎ 0.51 ± 0.02 0.39 ± 0.08

CL

LS

CL × LS

⁎⁎⁎

⁎⁎

⁎⁎⁎

⁎

⁎⁎⁎

⁎⁎⁎

⁎

⁎⁎

ns

ns

ns

ns

CL, carbohydrate level; LS, lipid source. GLU, glucose; TG, triglycerides; T-CHO, total cholesterol; NEFA, non-esterified fatty acid. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). Significant differences (P < 0.05) among different lipid sources within each carbohydrate level are indicated by different letters (lower case for 30% carbohydrate level, upper case for 43% carbohydrate level). *Indicates a significant difference (P < 0.05) between the carbohydrate levels at each lipid source, ns: not significant. ⁎ P < 0.05. ⁎⁎ P < 0.01. ⁎⁎⁎ P < 0.001. Table 8 Liver fatty acid profile (% of total fatty acids) of blunt snout bream fed diets differing in carbohydrate levels and lipid sources. CL

C14:0 C16:0 C18:0 C20:0 SFA C16:1n −9 C18:1n −9 C20:1n −9 MUFA C18:2n −6 C18:3n −3 C20:5n −3EPA C22:5n −3 C22:6n −3DHA PUFA Σn − 3 Σn − 6

30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43%

LS

Two-way ANOVA

FO

SO

PaO

MO

CL

1.77 ± 0.06 1.67 ± 0.20 21.18 ± 0.45b 20.3 ± 1.29 13.59 ± 1.08 16.04 ± 0.22A 0.16 ± 0.02 0.14 ± 0.03 36.70 ± 1.42a 38.16 ± 1.62 2.93 ± 0.05 3.00 ± 0.38 28.70 ± 0.92c 42.82 ± 0.96A⁎⁎⁎ 1.57 ± 0.17 1.38 ± 0.03 33.20 ± 0.94bc 47.20 ± 1.32A⁎⁎ 8.50 ± 0.51c 4.40 ± 0.19C⁎⁎ 0.94 ± 0.15b 0.43 ± 0.02B⁎ 1.83 ± 0.07a 0.73 ± 0.03A⁎⁎⁎ 0.51 ± 0.03a 0.33 ± 0.04A⁎ 11.53 ± 0.82a 5.14 ± 0.50A⁎⁎ 23.31 ± 1.08b 11.02 ± 0.66B⁎⁎ 14.81 ± 0.79a 6.63 ± 0.53A⁎⁎ 8.50 ± 0.51c 4.40 ± 0.19C⁎⁎

0.92 ± 0.10 1.52 ± 0.23 17.7 ± 0.15c 21.27 ± 1.06⁎ 12.38 ± 1.43 15.99 ± 1.02A 0.14 ± 0.01 0.11 ± 0.01 31.15 ± 1.56b 38.88 ± 1.11⁎ 1.60 ± 0.14 2.53 ± 0.26 27.09 ± 1.54c 38.66 ± 0.70B⁎⁎ 0.68 ± 0.09 0.97 ± 0.06 29.38 ± 1.75c 42.16 ± 0.81B⁎⁎ 18.08 ± 0.38a 10.69 ± 0.18A⁎⁎⁎ 2.20 ± 0.27a 0.98 ± 0.01A⁎ 0.48 ± 0.01c 0.24 ± 0.03BC⁎⁎ 0.26 ± 0.02b 0.13 ± 0.01B⁎⁎ 6.34 ± 0.57b 2.79 ± 0.02B⁎⁎ 27.36 ± 0.98a 14.83 ± 0.16A⁎⁎⁎ 9.28 ± 0.82b 4.14 ± 0.06B⁎⁎ 18.08 ± 0.38a 10.69 ± 0.18A⁎⁎⁎

1.35 ± 0.19 1.22 ± 0.08 24.17 ± 0.89a 22.64 ± 0.79 13.68 ± 0.70 11.34 ± 0.55B 0.1 ± 0.01 0.13 ± 0.01 39.29 ± 1.57a 35.32 ± 0.24 2.77 ± 0.02 2.79 ± 0.26 39.09 ± 2.54a 42.48 ± 0.71A 1.04 ± 0.09 1.29 ± 0.08 42.89 ± 2.50a 46.56 ± 0.89A 5.27 ± 0.16d 8.58 ± 0.58B⁎⁎ 0.55 ± 0.11b 0.78 ± 0.14A 0.24 ± 0.03d 0.22 ± 0.02C 0.13 ± 0.01c 0.15 ± 0.01B 3.75 ± 0.20c 2.89 ± 0.36B 9.95 ± 0.18d 12.62 ± 0.86B⁎ 4.68 ± 0.33c 4.03 ± 0.42B 5.27 ± 0.16d 8.58 ± 0.58B⁎⁎

1.48 ± 0.20 1.45 ± 0.34 21.29 ± 0.28b 21.55 ± 1.04 15.29 ± 1.09 15.86 ± 0.04A 0.12 ± 0.01 0.11 ± 0.02 38.19 ± 1.27a 38.97 ± 0.75 2.72 ± 0.20 2.88 ± 0.12 33.91 ± 0.28b 43.26 ± 0.31A⁎⁎⁎ 1.03 ± 0.06 1.20 ± 0.16 37.66 ± 0.46ab 47.34 ± 0.42A⁎⁎⁎ 11.61 ± 0.27b 5.56 ± 0.61C⁎⁎ 1.10 ± 0.07b 0.47 ± 0.01B⁎⁎ 0.82 ± 0.04b 0.33 ± 0.04B⁎⁎ 0.30 ± 0.03b 0.19 ± 0.01B⁎ 6.76 ± 0.16b 4.69 ± 0.15A⁎⁎ 20.58 ± 0.51c 11.24 ± 0.47B⁎⁎⁎ 8.97 ± 0.25b 5.68 ± 0.19A⁎⁎⁎ 11.61 ± 0.27b 5.56 ± 0.61C⁎⁎

ns

LS

CL × LS

ns

ns

⁎⁎

⁎

⁎

⁎

ns

ns

ns

ns

ns

ns ns

ns ⁎⁎⁎

ns

⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎

ns ⁎⁎

ns

⁎⁎⁎

⁎⁎⁎

⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). ΣSFA, saturated fatty acids; ΣMUFA, monounsaturated fatty acids; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; ΣPUFA, polyunsaturated fatty acids; Σn −3, n −3 long-chain PUFA; Σn − 6, n6 long-chain PUFA. Significant differences (P < 0.05) among different lipid sources within each carbohydrate level are indicated by different letters (lower case for 30% carbohydrate level, upper case for 43% carbohydrate level). *Indicates a significant difference (P < 0.05) between the carbohydrate levels at each lipid source, ns: not significant. ⁎ P < 0.05. ⁎⁎ P < 0.01. ⁎⁎⁎ P < 0.001.

146

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Table 9 Muscle fatty acid profile (% of total fatty acids) of blunt snout bream fed diets differing in carbohydrate levels and lipid sources. CL

C14:0 C16:0 C18:0 C20:0 SFA C16:1n −9 C18:1n −9 C20:1n −9 MUFA C18:2n −6 C18:3n −3 C20:5n −3EPA C22:5n −3 C22:6n −3DHA PUFA Σn − 3 Σn − 6

30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43% 30% 43%

LS

Two-way ANOVA

FO

SO

PaO

MO

CL

1.89 ± 0.14a 1.32 ± 0.08⁎ 20.42 ± 0.78 20.77 ± 0.24 10.09 ± 0.76 9.76 ± 0.92 0.21 ± 0.03 0.18 ± 0.01 32.60 ± 1.11 32.02 ± 1.22 2.89 ± 0.19a 2.15 ± 0.06⁎ 26.72 ± 0.69b 27.96 ± 0.67B 1.33 ± 0.12a 0.88 ± 0.04A⁎ 30.94 ± 0.94b 30.99 ± 0.70C 13.48 ± 1.20b 15.76 ± 1.08A 1.45 ± 0.14b 1.46 ± 0.08B 2.82 ± 0.04a 1.90 ± 0.04A⁎⁎⁎ 0.88 ± 0.06a 0.63 ± 0.06A⁎ 12.31 ± 0.83a 10.58 ± 0.21A 30.94 ± 0.58a 30.33 ± 1.10A 17.46 ± 0.62a 14.57 ± 0.15A⁎ 13.48 ± 1.20b 15.76 ± 1.08A

0.89 ± 0.06b 1.29 ± 0.25 18.73 ± 0.68 20.58 ± 0.67 10.53 ± 0.19 10.24 ± 0.48 0.15 ± 0.01 0.18 ± 0.01 30.30 ± 0.86 32.28 ± 1.14 1.50 ± 0.04c 2.36 ± 0.18⁎ 26.76 ± 0.71b 31.50 ± 0.72B⁎⁎ 0.56 ± 0.07c 0.94 ± 0.07A⁎ 28.83 ± 0.81b 34.80 ± 0.53B⁎⁎ 21.83 ± 0.82a 17.38 ± 0.48A⁎ 1.95 ± 0.09a 1.67 ± 0.02A⁎ 0.65 ± 0.02c 1.11 ± 0.03B⁎⁎⁎ 0.37 ± 0.03c 0.46 ± 0.02B 6.14 ± 0.29c 6.07 ± 0.43C 30.93 ± 0.91a 26.69 ± 0.65B⁎ 9.10 ± 0.26c 9.31 ± 0.42C 21.83 ± 0.82a 17.38 ± 0.48A⁎

0.98 ± 0.05b 1.01 ± 0.07 22.56 ± 0.26 23.22 ± 0.58 9.61 ± 0.39 8.05 ± 0.27 0.15 ± 0.01 0.17 ± 0.01 33.30 ± 0.20 32.45 ± 0.88 1.78 ± 0.04c 2.03 ± 0.18 34.91 ± 0.40a 37.19 ± 1.72A 0.69 ± 0.04bc 0.60 ± 0.05B 37.37 ± 0.44a 39.82 ± 1.68A 13.40 ± 0.27b 16.12 ± 0.24A⁎ 0.92 ± 0.03c 1.28 ± 0.04C⁎⁎ 0.54 ± 0.05c 0.50 ± 0.02C 0.33 ± 0.02c 0.23 ± 0.04C 5.33 ± 0.11c 3.62 ± 0.13D⁎⁎ 20.50 ± 0.23c 21.75 ± 0.34C 7.11 ± 0.04d 5.63 ± 0.10D⁎⁎⁎ 13.40 ± 0.27b 16.12 ± 0.24A⁎

1.37 ± 0.24ab 1.02 ± 0.08 21.41 ± 0.73 22.12 ± 0.42 8.75 ± 0.32 9.97 ± 0.29 0.18 ± 0.02 0.13 ± 0.01 31.71 ± 1.24 33.24 ± 0.48 2.25 ± 0.03b 2.06 ± 0.07 31.90 ± 0.98a 30.55 ± 0.74B 0.95 ± 0.03b 0.74 ± 0.02AB⁎⁎ 35.10 ± 1.01a 33.35 ± 0.66BC 15.23 ± 0.11b 13.08 ± 0.72B 1.24 ± 0.12bc 1.03 ± 0.02D 1.37 ± 0.08b 1.06 ± 0.10B 0.58 ± 0.02b 0.49 ± 0.04B 7.98 ± 0.43b 8.62 ± 0.28B 26.40 ± 0.51b 24.29 ± 1.09BC 11.17 ± 0.54b 11.21 ± 0.41B 15.23 ± 0.11b 13.08 ± 0.72B

ns ns ns ns ns

LS

CL × LS

⁎⁎

⁎

ns

ns

⁎

ns

ns ns

ns

ns

⁎⁎⁎

⁎⁎⁎

⁎

⁎⁎⁎

⁎

⁎

⁎⁎⁎

⁎⁎⁎

⁎

⁎⁎⁎

⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎⁎

⁎⁎

⁎⁎⁎

⁎⁎

⁎

⁎⁎⁎

⁎

⁎

⁎⁎⁎

⁎

⁎⁎

⁎⁎⁎

⁎⁎

⁎⁎⁎

⁎⁎⁎

ns

ns ns

ns

CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). ΣSFA, saturated fatty acids; ΣMUFA, monounsaturated fatty acids; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; ΣPUFA, polyunsaturated fatty acids; Σn −3, n −3 long-chain PUFA; Σn − 6, n − 6 long-chain PUFA. Significant differences (P < 0.05) among different lipid sources within each carbohydrate level are indicated by different letters (lower case for 30% carbohydrate level, upper case for 43% carbohydrate level). *Indicates a significant difference (P < 0.05) between the carbohydrate levels at each lipid source, ns: not significant. ⁎ P < 0.05. ⁎⁎ P < 0.01. ⁎⁎⁎ P < 0.001.

(P < 0.05), respectively. Furthermore, MUFA, EPA, DHA, PUFA, n − 3 LC-PUFA and n − 6 LC-PUFA contents were all significantly (P < 0.05) affected by the interaction between dietary carbohydrate levels and lipid sources. Fish fed 30% carbohydrate and FO obtained the highest contents of PUFA, n −3 LC-PUFA, EPA and DHA, whereas the richest n − 6 LC-PUFA was observed in fish offered 30% carbohydrate and SO. In addition, fish received 43% carbohydrate and PaO presented the most abundant MUFA (Table 9).

significantly (P < 0.05) affected by the interaction between dietary carbohydrate levels and lipid sources with the highest values observed in fish fed 43% carbohydrate/PaO and 30% carbohydrate/SO, respectively. As was shown in Fig. 3, the expressions of liver fatty acid synthetase (FAS), acetyl-CoA carboxylase α (ACCα), delta-6 fatty acyl desaturase (Δ6 FAD) and peroxisome proliferator-activated receptor γ (PPARγ) as well as muscle Δ6 FAD and ACCα all increased significantly (P < 0.05) with increasing dietary carbohydrate levels (P < 0.05), whereas the opposite was true for liver carnitine palmitoyl transferase I (CPT I) and PPARα transcriptions. In addition, hepatic FAS expression of fish fed MO was significantly (P < 0.05) higher than that of the other groups in terms of lipid sources. Furthermore, liver FAS expression was significantly (P < 0.05) affected by the interaction between dietary carbohydrate levels and lipid sources with the highest value observed in fish fed 43% carbohydrate and FO.

3.5. The mRNA expressions of enzymes involved in glucose and lipid metabolism As can been seen from Fig. 2, hepatic pyruvate kinase (PK) and phosphoenolpyruvate carboxykinase (PEPCK) and muscle glycogen synthase (GS) expressions all showed no significant difference (P > 0.05) among all the treatments. However, liver glucokinase (GK) and GS as well as muscle PK transcriptions all increased significantly (P < 0.05) with increasing dietary carbohydrate levels, whereas the opposite was true for muscle PEPCK. In addition, the transcriptional levels of PEPCK in the muscle of fish fed SO was significantly (P < 0.05) higher than those of the other groups in terms of lipid sources. Furthermore, muscle PK and PEPCK expressions were both

4. Discussion 4.1. Growth performance In the present study, either dietary carbohydrate levels or lipid 147

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B

2.0

Two-way ANOVA LS: ns CL: * CL×LS: ns 30%CL

1.5 1.0

43%CL

0.5

2.0

Two-way ANOVA LS: ns CL: ns CL×LS: ns 30%CL

1.5 L-PK/EF1α

1.0

43%CL

0.5

LS

D

2.0

Two-way ANOVA LS: ns CL: ns CL×LS: ns 30%CL

1.5 1.0

43%CL

0.5

3.0

Two-way ANOVA LS: ns CL: * CL×LS: ns 30%CL

2.5 L-GS/EF1α

L-PEPCK/EF1α

M O

FO

M O

Pa O

SO

FO

LS

C

Pa O

0.0

0.0

SO

L-GK/EF1α

A

2.0 1.5 1.0

43%CL

0.5

0.0

F

A*

2.5

Two-way ANOVA LS: ns CL: * CL×LS: ** 30%CL

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LS Fig. 2. The transcriptional levels of genes involved in glucose metabolism (glucokinase (GK), pyruvate kinase (PK), phosphoenolpyruvate carboxykinase (PEPCK) and glycogen synthase (GS)) in the liver (L) and muscle (M) of blunt snout bream fed diets differing in carbohydrate levels and lipid sources. CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). Expression values are normalized with the transcription of EF1α. Each data represents the mean of four replicates. Significant differences (P < 0.05) among different lipid sources within each carbohydrate level are indicated by different letters (lower case for 30% carbohydrate level, upper case for 43% carbohydrate level). *Indicates a significant difference (P < 0.05) between the carbohydrate levels at each lipid source. *P < 0.05, **P < 0.01, ***P < 0.001, ns: not significant.

fish could convert linoleic acid (18:2n − 6, LA) and linolenic acid (18:3n − 3, LNA) to n− 6 and n −3 long-chain polyunsaturated fatty acids (LC-PUFA), respectively (Sargent et al., 1999). Therefore, vegetable oils did not negatively affect the growth of this fish. This also suggested that SO, PaO and MO could all be considered as potential oils to replace FO in the diet of this fish. In addition, high-carbohydrate feeding led to a remarkable increase of ERE. According to previous studies, high-carbohydrate intake usually promotes lipid and glycogen deposition in fish (Moreira et al., 2008; C. Castro et al., 2016a). This might inevitably result in the increased body energy content, as might

sources exerted little difference on final body weight, WG, SGR, feed intake, FCR and PER of fish. According to previous studies, as an herbivorous fish, blunt snout bream has a high carbohydrate tolerance compare with most carnivorous and omnivorous species (Zhou et al., 2013b; Li et al., 2014). Therefore, high dietary carbohydrate did not lead to a severe growth retardation of this species. As for lipid sources, the present results were in accordance with that of a previous study, which reported that FO, SO, PaO, canola oil and peanut oil had no significant influence on the growth performance of the same species (Li et al., 2015a). This could be ascribed to the fact that most freshwater 148

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Fig. 3. The transcriptional levels of genes involved in lipid metabolism (fatty acid synthetase (FAS), acetyl-CoA carboxylase α (ACCα), carnitine palmitoyl transferase I (CPT I), peroxisome proliferator-activated receptor (PPAR) and delta-6 fatty acyl desaturase (Δ6 FAD) and elongase of very long chain fatty acids (Elovl5)) in the liver (L) and muscle (M) of blunt snout bream fed diets differing in carbohydrate levels and lipid sources. CL, carbohydrate level; LS, lipid source. FO, fish oil; SO, soybean oil; PaO, palm oil; MO, mixed oil (FO:SO:PaO = 1:1:1). Expression values are normalized with the transcription of EF1α. Each data represents the mean of four replicates. Significant differences (P < 0.05) among different lipid sources within each carbohydrate level are indicated by different letters (lower case for 30% carbohydrate level, upper case for 43% carbohydrate level). *Indicates a significant difference (P < 0.05) between the carbohydrate levels at each lipid source. *P < 0.05, **P < 0.01, ***P < 0.001, ns: not significant.

important role in protein synthesis (Suryapratama and Suhartati, 2012). This might facilitate feed utilization and body protein deposition, as might consequently benefit NRE (González-Félix et al., 2016). Furthermore, an interaction between dietary carbohydrate levels and lipid sources was also observed in feed intake, nitrogen and energy intake and NRE. Fish fed SO obtained the lowest feed intake, nitrogen and energy intake and the highest NRE when dietary carbohydrate level was

consequently lead to an improved ERE. This was further supported by the results of whole-body energy content in this study, which generally increased with increasing dietary carbohydrate levels although no significant difference was observed. Unlikely, NRE was significantly affected only by dietary lipid sources with the best observed in fish fed SO. According to previous studies, SO is rich in PUFAs, especially LA, which is EFAs for freshwater fish (Li et al., 2016), and also plays an 149

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J

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dietary carbohydrate levels could increase the hepatic activities of FAS, glucose-6-phosphate dehydrogenase and malic enzyme in fish, thereby promoting glycogenesis and lipogenesis (Moreira et al., 2008; C. Castro et al., 2016a). This might inevitably result in glycogen and lipid deposition in tissues, as consequently increase the HSI and IPF ratio. This result was in accordance with previous studies on this species (Zhou et al., 2013b) and other fish (Coutinho et al., 2012; Kamalam et al., 2012).

30%, whereas little difference was detected when offered high-carbohydrate diets. Due to the fact that relevant literature is quite limited, it is difficult to justify this interaction. However, the best results obtained in fish received 30% carbohydrate and SO is not surprising, since this diet has the optimum carbohydrate level and lipid source for blunt snout bream (Zhou et al., 2013b; Li et al., 2016). Nevertheless, although no significance was observed, the best growth was found in fish fed SO when dietary carbohydrate level was 30%, whereas this was true for fish fed PaO when offered high-carbohydrate diets. The underlying mechanisms are still unclear. Further in-depth studies are warranted to elucidate this. In this study, high-carbohydrate intake resulted in a remarkable increase of HSI and the IPF ratio. This was not surprising since high

4.2. Whole-body composition and tissue lipid and glycogen deposition A positive correlation between whole-body lipid content and dietary carbohydrate levels was observed in the present study, as also held true 150

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be explained by the fact that SO is rich in LA and LNA, both of which could be converted to n − 6 and n −3 LC-PUFA respectively by most freshwater fish including blunt snout bream (Li et al., 2015b). In this study, the percentages of LA, LNA and PUFA in liver and muscle were all lower than those in diets, whereas the opposite was true for MUFA and SFA. This result was justifiable since both LA and LNA are dietary essential FAs for most freshwater fish, and are specifically designed to meet the energy requirements of fish (Dosanjh et al., 1998; Luo et al., 2008). This inevitably led to an enhanced oxidation of both FAs, thus lowering their (also the PUFA) levels in tissues (Bell et al., 2001; Francis et al., 2006). The consumption of PUFA (particularly in the form of LA and LNA) by fish generally generates MUFA and SFA in the meantime, as might consequently lead to the accumulation of these FAs in piscine tissues (Turchini et al., 2006; Blanchard et al., 2008; Li et al., 2015b). Furthermore, fish fed FO had higher contents of n − 3 LC-PUFA, EPA and DHA in liver and muscle. This result was in expectation since FO is quite rich in EPA and DHA, both of which could be preferentially retained by fish (Bell et al., 2002; Torstensen et al., 2004). What is more, it was noteworthy that an interaction between dietary lipid sources and carbohydrate levels was also observed in MUFA, PUFA, n −3 LC-PUFA, n −6 LC-PUFA, DHA and EPA contents in both liver and muscle in this study. This was quite different from the results in European sea bass and gilthead sea bream, both of which showed very few interactions (between starch levels and lipid sources) in tissue FA composition and the transcriptional levels of proteins involved in cholesterol and LC-PUFA biosynthesis (Castro et al., 2015; C. Castro et al., 2016a). This suggested that the interactive effects of dietary carbohydrate levels and lipid sources might affect the tissue FA composition and FA biosynthesis of fish differently according to species, feeding habits, dietary carbohydrate levels, lipid sources and so on (Castro et al., 2015; C. Castro et al., 2016a; L.F. Castro et al., 2016), as warrants further studies. Nevertheless, a future investigation concerning this interactive effect on the FA biosynthesis of blunt snout bream is needed to elucidate this.

for tissue lipid and glycogen contents. This further supported the fact that high dietary carbohydrate enhanced lipogenesis and glycogenesis of blunt snout bream (Zhou et al., 2013b; C. Castro et al., 2016a). In addition, MO resulted in a remarkable increase of whole-body and liver lipid content in terms of lipid sources. This indicated that compared with other single lipid sources, blended oils might more easily promote lipid deposition in this fish. According to previous studies, MO could up-regulate the activities of ACC and lipoprotein lipase (LPL) in fish, as might consequently boost lipid accumulation (Liang et al., 2002). This was supported by the fact that ACC is closely involved in FA biosynthesis (C. Castro et al., 2016b), while LPL is a rate-limiting enzyme in the provision of tissue FA determining how lipids are partitioned towards storage or utilization (Yin and Tsutsumi, 2003). In addition, an interaction between dietary carbohydrate levels and lipid sources was also observed in body, liver and muscle lipid contents as well as liver and intraperitoneal fat glycogen contents. Fish fed MO obtained the highest lipid content when dietary carbohydrate level was 30%, whereas little difference was observed when fish were offered highcarbohydrate diets. Lipid sources also regulated tissue glycogen deposition differently at different carbohydrate levels. This indicated that high dietary carbohydrates might attenuate the influence of lipids source on the body lipid and glycogen deposition of fish, probably due to the interaction between FAs and glucose (C. Castro et al., 2016a). However, further in-depth studies are needed to elucidate this. 4.3. Plasma metabolites In the present study, high-carbohydrate intake resulted in a remarkable increase of plasma GLU, TG and T-CHO. According to previous studies, high dietary carbohydrate intake usually leads to elevated plasma glucose (Ge et al., 2007; Xu et al., 2017). The high glycemia might in turn stimulate insulin synthesis and release, as might consequently lead to an enhanced lipogenesis (Xu et al., 2017). In terms of lipid sources, fish offered FO obtained relatively low levels of GLU and TG, but high T-CHO values. Previous studies have shown that replacing FO with VO usually reduced cholesterol content (Morais et al., 2011; C. Castro et al., 2016a) in fish, but there was no evidence that GLU and TG could be affected by dietary lipid sources. Therefore, further studies are warranted to elucidate this. Furthermore, an interaction between dietary carbohydrate levels and lipid sources was observed in TG concentrations. Fish fed FO obtained the lowest TG when offered 30% carbohydrate, whereas the opposite was true when dietary carbohydrate levels reached 43%. This indicated that high dietary carbohydrate might attenuate the beneficial effects of FO on the lipid metabolism of this species (Zderic et al., 2004; Zhou et al., 2013b), as still needs further investigations.

4.5. Transcriptions of enzymes involved in glucose and lipid metabolism In this study, liver GK, GS and muscle PK expressions all increased significantly with increasing dietary carbohydrate levels. Similar results were also observed in liver PK and muscle GS transcriptions although no statistical difference was found. This result indicated that high carbohydrate intake could promote the glycolysis and glycogenesis of blunt snout bream (Robison et al., 2008; Enes et al., 2009; C. Castro et al., 2016a). This was supported by the facts that 1) being the first glycolytic enzyme, GK played an important role in blood glucose homoeostasis by catalysing the phosphorylation of glucose and providing the first substrate for glycolysis, glycogenesis and the pentose phosphate pathway in liver (C. Castro et al., 2016a); 2) PK is one of the rate-limiting enzymes in glycolysis (Panserat et al., 2001); and 3) GS was closely involved in glycogen synthesis (Xu et al., 2017). This was in line with the HSI, IPF ration and tissue lipid and glycogen contents obtained in this study, further suggesting that the liver glucose pool was directed towards glycogen and/or FA synthesis (C. Castro et al., 2016a). In addition, high dietary carbohydrate levels led to a remarkable decrease of liver and muscle PEPCK expressions, suggesting that long-term consumption of high-carbohydrate diets suppressed the gluconeogenesis of this fish. This might be ascribed to the fact that high carbohydrate intake could reduce the ability of fish to convert oxaloacetate and glucose-6-phosphate into phosphoenolpyruvate (the first step of gluconeogenesis) and glucose (the last step of gluconeogenesis and glycogenolysis), respectively (Enes et al., 2009). In terms of lipid sources, fish fed SO presented a remarkably high transcription of PEPCK in muscle, suggesting that SO might facilitate the gluconeogenesis of this species. In addition, an interaction between dietary carbohydrate levels and lipid sources was also observed in muscle PK and PEPCK expressions. The highest PK expression was observed in fish fed 43% carbohydrate and PaO, as was in line with the results in muscle glycogen,

4.4. Liver and muscle FA profiles In this study, high-carbohydrate intake resulted in a remarkable increase of MUFA but a decrease of PUFA (especially n − 3 LC-PUFA like EPA and DHA) in both liver and muscle. This result was justifiable since high dietary carbohydrate levels usually promoted lipogenesis of fish, which generally derived from the biosynthesis of MUFA rather than PUFA (C. Castro et al., 2016a). In addition, it might also suggest an increased catabolism of PUFA in fish fed high-carbohydrate diets. This was supported by the fact that long-term intake of high-carbohydrate diets could enhance the β-oxidation of PUFA in fish (C. Castro et al., 2016a), thus lowering their levels in tissues. In terms of lipid sources, the MUFA content in the liver and muscle of blunt snout bream fed PaO was significantly higher than that of the other groups. This may be attributed to the fact that PaO is quite rich in MUFA, as might lead to a preferential deposition and retention of MUFA in fish tissues (J. Gao et al., 2012a). In addition, fish fed SO presented remarkably high levels of LA, LNA and PUFA in liver, as was in agreement with a previous study using this species as the target animal (Li et al., 2016). This might 151

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Castro, C., Corraze, G., Pérez-Jiménez, A., Larroquet, L., Cluzeaud, M., Panserat, S., 2015. Dietary carbohydrate and lipid source affect cholesterol metabolism of European sea bass (Dicentrarchus labrax) juveniles. Brit. J. Nutr. 114, 1584–1593. Castro, C., Corraze, G., Basto, A., Larroquet, L., Panserat, S., Oliva-Teles, A., 2016a. Dietary lipid and carbohydrate interactions: implications on lipid and glucose absorption, transport in gilthead sea bream (Sparus aurata) juveniles. Lipids 51, 1–13. Castro, C., Corraze, G., Firmino-Diógenes, A., Larroquet, L., Panserat, S., Oliva-Teles, A., 2016b. Regulation of glucose and lipid metabolism by dietary carbohydrate levels and lipid sources in gilthead sea bream juveniles. Brit. J. Nutr. 116, 19–34. Castro, L.F., Tocher, D.R., Monroig, O., 2016. Long-chain polyunsaturated fatty acid biosynthesis in chordates: insights into the evolution of fads and elovl gene repertoire. Prog. Lipid Res. 62, 25–40. Coutinho, F., Peres, H., Guerreiro, I., 2012. Dietary protein requirement of sharpsnout sea bream (Diplodus puntazzo, Cetti 1777) juveniles. Aquaculture 356-357, 391–397. Dosanjh, B.S., Higgs, D.A., McKenzie, D.J., Randall, D.J., Eales, J.G., Rowshandeli, N., Rowshandeli, M., Deacon, G., 1998. Influence of dietary blends of menhaden oil and canola oil on growth, muscle lipid composition, and thyroidal status of Atlantic salmon (Salmo salar) in sea water. Fish Physiol. Biochem. 19, 123–134. Ellis, S.C., Reigh, R.C., 1991. Effects of dietary lipid and carbohydrate levels on growth and body composition of juvenile red drum, Sciaenops ocellatus. Aquaculture 97, 383–394. Enes, P., Panserat, S., Kaushik, S., Oliva-Teles, A., 2009. Nutritional regulation of hepatic glucose metabolism in fish. Fish Physiol. Biochem. 35, 519–539. Erfanullah, Jafri, A.K., 1998. Effect of dietary carbohydrate-to-lipid ratio on growth and body composition of walking catfish (Clarias batrachus). Aquaculture 161, 159–168. Folch, J., Lees, M., Sloane-Stanley, G.H., 1957. A simple method for the isolation and purification of the total lipid from animal tissue. J. Biol. Chem. 226, 497–509. Francis, D.S., Turchini, G.M., Jones, P.L., Silva, S.D., 2006. Effects of dietary oil source on growth and fillet fatty acid composition of Murray cod, Maccullochella peelii. Aquaculture 253, 547–556. Gao, Z.X., Luo, W., Liu, H., Zeng, C., Liu, X.L., Yi, S.K., Wang, W.M., 2012. Transcriptome analysis and SSR/SNP markers information of the blunt snout bream (Megalobrama amblycephala). PLoS One 7, e42637. Gao, J., Koshio, S., Ishikawa, M., Yokoyama, S., Mamauag, R.E.P., Han, Y., 2012a. Effects of dietary oxidized fish oil with vitamin E supplementation on growth performance and reduction of lipid peroxidation in tissues and blood of Red sea bream Pagrosomus major. Aquaculture 356-357, 73–79. Gao, J., Koshio, S., Ishikawa, M., Yokoyama, S., Ren, T., Komilus, C.F., 2012b. Effects of dietary palm oil supplements with oxidized and non-oxidized fish oil on growth performances and fatty acid compositions of juvenile Japanese sea bass, Lateolabrax japonicas. Aquaculture 324-325, 97–103. Ge, X.P., Liu, B., Xie, J., Yu, J.H., Tang, Y.K., Wu, T.T., 2007. Effect of different carbohydrate levels of dietary on growth, plasma biochemical indices and hepatic pancreas carbohydrate metabolic enzymes in top mouth culter (Erythroculter ilishaeformis Bleeker). J. Nanjing Agric. Univ. 30, 88–93. Ginanni, N., Zhan, Y., Tota, M., Wu, M., Roth, J., Ridenour, D., 2007. Kinetic analysis of the fatty acid synthesis pathway in hct-116 colon cancer cells: role of FAS and ACC1 in maintaining tumor cell viability and proliferation. Cancer Res. 67, 4473. González-Félix, M.L., Maldonado-Othón, C.A., Perez-Velazquez, M., 2016. Effect of dietary lipid level and replacement of fish oil by soybean oil in compound feeds for the shortfin corvina (Cynoscion parvipinnis). 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indicating that the combination of PaO and high carbohydrate could severely induce the glycolysis of blunt snout bream (Xu et al., 2017). Unlikely, the highest PEPCK expression was observed in fish fed 30% carbohydrate and SO, suggesting that SO might easily promote the gluconeogenesis of this species when offered the optimum carbohydrate level. In this study, liver FAS, ACCα, Δ6 FAD, PPARγ as well as muscle Δ6 FAD and ACCα expressions all increased with increasing dietary carbohydrate levels, whereas the opposite was true for hepatic CPT I and PPARα expressions. This suggested that high-carbohydrate intake could promote the lipogenesis of blunt snout bream coupled with an depression of FA β-oxidation. This was supported by the following facts that 1) both ACCα and FAS played an important role in body fatty acid biosynthesis (Ginanni et al., 2007); 2) Δ6FAD is a key desaturase involved in LC-PUFA synthesis of fish (C. Castro et al., 2016a); 3) PPARγ played an important role in tissue lipogenesis and lipid deposition (C. Castro et al., 2016a), while PPARα could facilitate the catabolism of fatty acids by regulating the key enzymes involved in fatty acid oxidation (Zheng et al., 2014; Li et al., 2015a); and 4) CPTI is a reliable marker of mitochondrial FA β-oxidation (Zheng et al., 2014; Bonacic et al., 2016). This was in line with the results observed in tissue lipid contents and FA profiles in this study. In terms of lipid sources, fish fed MO presented a remarkably high transcription of FAS in liver, suggesting that MO could facilitate the lipogenesis of blunt snout bream (Liang et al., 2002). This was further supported by the results of wholebody and liver lipid contents in this study. Furthermore, it was noteworthy that an interaction between dietary lipid sources and carbohydrate levels was also observed in liver FAS expression with the lowest value observed in fish fed 30% carbohydrate level and SO. This suggested that SO might not promote the lipogenesis of blunt snout bream when offered the optimum carbohydrate levels (Zhou et al., 2013b; Li et al., 2016). In conclusion, the results obtained in this study suggested that blunt snout bream could efficiently utilize various lipid sources at different carbohydrate levels. Dietary carbohydrate levels and lipid sources remarkably affected nutrient retention, tissue lipid and glycogen contents, plasma metabolites, tissue MUFA, EPA, DHA, PUFA as well as n − 3 and n − 6 LC-PUFA contents glycolysis, gluconeogenesis and lipogenesis, but not growth and feed efficiency. Their interaction mainly induced modifications in feed intake, tissue lipid and glycogen deposition, plasma metabolites, tissue FA profiles, glycolysis and gluconeogenesis. Acknowledgements This research was funded by the National Technology System of Conventional Freshwater Fish Industries of China (CARS-45-14) and the Fundamental Research Funds for the Central Universities in China (KYZ201645). References AOAC, 1995. Agricultural chemicals; contaminants, drugs. In: Official Methods of Analysis of AOAC International. AOAC International, Arlington, pp. 1298. Asadi, F., Asadian, A.H., Shahriari, A., Pourkabir, M., 2009. Serum lipid, free fatty acid, and proteins in juvenile sturgeons: Acipenser persicus and Acipenser stellatus. Comp. Clin. Pathol. 18, 287–289. Bell, J.G., Dick, J.R., Porter, A.E.A., 2001. Biosynthesis and tissue deposition of docosahexaenoic acid (22:6n − 3) in rainbow trout (Oncorhynchus mykiss). Lipids 36, 1153–1159. Bell, J.G., Henderson, R.J., Tocher, D.R., McGhee, F., Dick, J.R., Porter, A., Smullen, R.P., Sargent, J.R., 2002. Substituting fish oil with crude palm oil in the diet of Atlantic salmon (Salmo salar L.) affects muscle fatty acid composition and hepatic fatty acid metabolism. J. Nutr. 132, 222–230. Blanchard, G., Makombu, J.G., Kesternont, P., 2008. Influence of different dietary 18:3n −3/18:2n − 6 ratio on growth performance, fatty acid composition and hepatic ultrastructure in Eurasian perch, Perca fluviatilis. Aquaculture 284, 144–150. Bonacic, K., Estévez, A., Bellot, O., Conde-Sieira, M., Gisbert, E., Morais, S., 2016. Dietary fatty acid metabolism is affected more by lipid level than source in senegalese sole juveniles: interactions for optimal dietary formulation. Lipids 51, 105–122.

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