Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-22T23:45:41.999Z Has data issue: false hasContentIssue false

Nutritional programming of large yellow croaker (Larimichthys crocea) larvae by dietary vegetable oil: effects on growth performance, lipid metabolism and antioxidant capacity

Published online by Cambridge University Press:  11 July 2022

Yongtao Liu
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China
Chuanwei Yao
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China
Kun Cui
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China
Tingting Hao
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China
Zhaoyang Yin
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China
Wenxuan Xu
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China
Wenxing Huang
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China
Kangsen Mai
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong, People’s Republic of China
Qinghui Ai*
Affiliation:
Key laboratory of Aquaculture Nutrition and Feed, Ministry of Agriculture and Rural Affairs, and the Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, Shandong 266003, People’s Republic of China Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong, People’s Republic of China
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

The nutritional status experienced in the early development of life plays a vital role in the long-term metabolic state of the individual, which is known as nutritional programming. The present study investigated the long-term effects of vegetable oil (VO) nutritional programming during the early life of large yellow croaker. First, larvae were fed either a fish oil (FO) diet or a VO diet for 30 d. Subsequently, under the same conditions, all fish were fed a commercial diet for 90 d and thereafter challenged with an FO or VO diet for 30 d. The results showed that growth performance was significantly lower in larvae fed the VO diet than in those in fed the FO diet in the stimulus phase. Notably, VO nutritional history fish showed lower levels of liver lipids liver total triglycerides and serum nonesterified free fatty acids than the FO nutritional history fish when juveniles were challenged with the VO diet, which was consistent with the expression of lipogenesis-related genes and proteins. Moreover, the VO nutritional history fish showed lower liver damage and higher antioxidant capacity than FO nutritional history fish when challenged with the VO diet. In summary, this study showed that a short VO stimulus during the early life stage of large yellow croaker, had a long-term effect on lipid metabolism and the antioxidant system. Specifically, VO nutritional programming had a positive effect on alleviating abnormal lipid deposition on the liver, liver damage, and the reduction of hepatic antioxidant capacity caused by a VO diet.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Nutrition Society

With the rapid development of world aquaculture and the decline in fish oil (FO) production, searching for suitable FO substitutes has become a research hotspot(1,2) . Due to the high availability, steady growth in production and stable prices, vegetable oil (VO) is often used as a substitute for FO. However, compared with FO, VO contains no long-chain PUFA, such as EPA and DHA, while the content of α-linolenic acid and linoleic acid (LA) are higher(Reference Shi, Zhao and Zhai3,Reference Torstensen, Espe and Sanden4) . Previous studies have established that excessive dietary FO replaced by VO often leads to abnormal lipid deposition, reduction of antioxidant capacity and nonspecific immunity in large yellow croaker (Larimichthys crocea)(Reference Li, Cui and Fang5,Reference Xu, Ding and Liu6) , black carp (Mylopharyngodon piceus)(Reference Sun, Ye and Chen7), Atlantic salmon (Salmo salar L.)(Reference Torstensen, Frøyland and Lie8) and blunt snout bream (Megalobrama amblycephala)(Reference Li, Liang and Zhang9). Consequently, it is imperative to find nutritional measures to alleviate the adverse effects of the substitution of VO for FO.

Nutritional programming proposed by Lucas(Reference Lucas10) means that an early stimulus or insult during a ‘critical window’ period may reset physiological pathways with long-term consequences(Reference Engrola, Aragão and Valente11). These ‘programming effects’ can be reflected in gene expression changes in key metabolic pathways and critical organ development later in life(Reference Zambonino-Infante, Panserat and Servili12Reference George, Zhang and Tuersunjiang14). In mammalian research, nutritional programming is usually associated with various metabolic diseases such as obesity, insulin resistance, glucose intolerance, hypertension and hypertriglyceridaemia(Reference Petry, Ozanne and Hales15,Reference Symonds, Sebert and Hyatt16) . In recent years, nutritional programming has also been studied in fish, which is a promising strategy to increase aquaculture production at a lower cost and with fewer environmental impacts(Reference Hou and Fuiman17). VO nutritional programming may be one of the ways through which the utilisation of VO in juvenile fish can be improved and reduce the adverse effects caused by FO substitution. Clarkson et al. (Reference Clarkson, Migaud and Metochis18) confirmed that short exposure to a vegetable-based diet during the first exogenous feeding of Atlantic salmon could promote the use of a similar diet when challenged in later life. Turkmen et al.(Reference Turkmen, Zamorano and Fernandez-Palacios19) reported that nutritional programming of gilthead sea bream (Sparus aurata) through broodstock feeding could improve utilisation of low-FM/FO diets and growth of juvenile fish. In general, nutritional programming studies carried out on fish include high carbohydrates(Reference Fang, Liang and Zhou20Reference Rocha, Dias and Engrola22), plant protein(Reference Kwasek, Wojno and Iannini23Reference Lazzarotto, Corraze and Larroquet25), methionine(Reference Craig and Moon26) and micronutrients(Reference Skjaerven, Jakt and Dahl27,Reference Skjaerven, Jakt and Fernandes28) or nonnutritional stimuli such as hypoxia(Reference Liu, Dias and Plagnes-Juan13,Reference Liu, Plagnes-Juan and Geurden29) . However, to our knowledge, few reports have focused on the alleviation of the negative effects of VO replacement through VO nutritional programming.

Large yellow croaker is a crucial marine fish in China with high yield (254 062 tons in 2020) and great popularity among consumers(Reference Luo, Li and Jin30,31) . Due to the enormous scale of farming, VO has been widely used in diets, which has caused growth retardation, abnormal lipid deposition on the liver and decreased antioxidant capacity(Reference Li, Cui and Fang5,Reference Wang, Li and Hou32,Reference Li, Ji and Cui33) . The purpose of the present study was to investigate the long-term effects of early VO nutritional programming on the growth performance, lipid metabolism and antioxidant capacity of large yellow croaker, particularly when juveniles were fed the VO diet.

Materials and methods

Ethics statement

The present study was conducted in strict accordance with the Management Rule of Laboratory Animals (Chinese Order No. 676 of the State Council, revised 1 March 2017) and approved by the Institutional Animal Care and Use Committee of Ocean University of China.

Experimental design

Larvae were obtained from Xiangshan Harbour Aquatic Seeds Company, Ningbo, China. The experimental design is shown in Fig. 1. The feeding experiment was conducted in the Marine and Fishery Science and Technology Innovation Base, Ningbo, China.

Fig. 1. Experimental design. FO or VO dietary stimulus was applied to large yellow croaker larvae for 30 d, and then juveniles were fed the commercial diet for 90 d. Subsequently, juveniles were fed to a 30 d challenge test with a FO or VO diet.

Stimulus phase

This phase was aimed at performing nutritional conditioning on larvae. Fish larvae were fed rotifers (Brachionus plicatilis) from 3 to 8 d after hatching (DAH), Artemia nauplii from 6 to 11 DAH and live copepods (Calanus sinicus) and the FO diet from 10 to 14 DAH. After 14 DAH, large yellow croaker larvae were fed either a 30-d FO diet (Table 1) or a VO diet (Table 1) (Fig. 1, Stimulus phase). The two treatment groups were named F and V, respectively. Each group was conducted in triplicate tanks. Larvae were distributed in six blue plastic tanks (water volume 700 l, 5000 larvae/tank). Throughout the experiment, the environmental conditions (water temperature: 24·6 ± 1·12°C; dissolved oxygen: 6·57 ± 0·39 mg/l; pH: 8·15 ± 0·18; salinity: 22·52 ± 1·47 %) were maintained within the specified range, and 150–200 % of the water was renewed daily. Larvae were fed seven times daily (06:30, 08:30, 10:30, 13:30, 15:30, 17:30 and 23:00) to apparent satiation.

Table 1. Formulation and proximate composition of the experimental diets

* Commercially available from Great Seven Biotechnology Co., Ltd in Shandong, China; elementary composition (dry matter): White fish meal, crude protein, 71.73 %, crude lipid, 4.76 %; Krill meal, crude protein, 64.86 %, crude lipid, 8.0 %.

Commercially available from market squid, then drying and crushing; elementary composition (dry matter): Squid meal, crude protein, 81.81 %, crude lipid, 5.16 %.

Commercially available from Zhejiang Dongcheng Biotechnology Co., Ltd.

§ Composition of vitamin premix (mg or gkg–1): vitamin A palmitate, 3 000 000 mg; vitamin D3 1 200 000 mg; DL-α-vitamin E 40.0 g/kg; menadione, 8.0 g/kg; thiamine-HCl, 5.0 g/kg; riboflavin, 5.0 g/kg; D-calcium pantothenate, 16.0 mg/kg; pyridoxine-HCl, 4.0 mg/kg; inositol, 200.0 mg/kg; biotin, 8.0 mg/kg; folic acid, 1.5 mg/kg; 4-aminobenzoic acid, 5.0 mg/kg; niacin, 20.0 mg/kg; vitamin B12, 0.01 mg/kg; L-ascorgyl-2-monophosphate-Na (35 %) 2000.0 mg/kg.

Composition of mineral premix (g kg–1 premix): Ca(H2PO4)·H2O, 675.0; COSO4·H2O, 0.15; CuSO4·H2O, 5.0; FeSO4·7H2O, 50.0; KCl, 0.1; MgSO4·2H2O, 101.7; MnSO4·2H2O, 18.0; NaCl, 80.0; NaSeO3·H2O, 0.05; ZnSO4·7H2O, 20.0.

Growth phase

All fish were fed a commercial diet (New Love Larva Yu Bao, Hayashikane Sangyo Co., Ltd.) for 90 d (Fig. 1, Growth phase). According to the difference in nutritional history, the two treatment groups were named FC and VC. Each group was conducted in triplicate tanks. Fish were distributed in six blue plastic tanks (water volume 700 l, 100 fish/tank). Throughout the experiment, the environmental conditions (water temperature: 27·19 ± 0·72°C; dissolved oxygen: 6·57 ± 0·39 mg/l; pH: 8·15 ± 0·18; salinity: 22·52 ± 1·47 %) were maintained within the specified range, and 150–200 % of the water was renewed daily. Fish were fed two times daily (06:30 and 17:30) to apparent satiation.

Challenge phase

At the end of the growth trial, juvenile fish were subjected to a 30-d challenge test with an FO or VO diet (Fig. 1, Challenge phase). According to the differences in nutritional history and challenge diets, the three treatment groups were named FCF, FCV and VCV. Each group was conducted in triplicate tanks. Fish were distributed in nine blue plastic tanks (water volume 700 l, 30 fish/tank). Throughout the experiment, the environmental conditions (water temperature: 28·4 ± 0·97°C; dissolved oxygen: 6·57 ± 0·39 mg/l; pH: 8·15 ± 0·18; salinity: 22·52 ± 1·47 %) were maintained within the specified range, and 150–200 % of the water was renewed daily. Fish were fed two times daily (06:30 and 17:30) to apparent satiation.

Sampling and growth monitoring

At the termination of each phase, larvae or juvenile fish were fasted for 24 h before sampling and then anaesthetised (eugenol, 1:10 000).

Stimulus phase

The visceral mass was collected from forty larvae of each tank, which was immediately frozen in liquid nitrogen and stored at −80°C for gene expression analysis. Eighty other whole larvae were sampled from each tank, immediately frozen in liquid nitrogen and stored at −80°C for fatty acid analysis. The total number was determined by counting the individuals remaining in each tank. Except for the larvae used in the next phase of the experiment, three hundred fish were collected to measure proximate composition. Fifty larvae from each tank were collected randomly to monitor the final body weight and the final body length.

Growth phase and challenge phase

For gene expression analysis, the liver of fish was collected and stored at –80°C. For biochemical analysis, whole fish, liver and muscle tissue were collected and stored at −20°C. Fish blood was collected from the caudal vein, placed at 4°C for coagulation and stratification and then centrifuged (2300 g , 10 min) to obtain the serum. The serum was stored at –80°C for further analysis. Faeces were collected by siphoning after 5 h of feeding and frozen at –20°C. In the growth phase, the total fish in each tank were collected to monitor the final body weight; thirty fish were collected to measure the final body length. In the challenge phase, the total fish in each tank were collected to monitor the final body weight and body length.

Biochemical analysis

Proximate composition and fatty acid profile analysis

The diet, whole fish, liver and muscle proximate composition (crude protein, crude lipid and moisture) were measured according to the instructions of the Association of Official Analytical Chemists(34). The moisture content of the samples was determined by drying to a constant weight at 105°C. Crude protein was determined by measuring the n content (n × 6·25) through the Kjeldahl method. Crude lipids were quantified with ether extraction by the Soxhlet method. The fish tissue (liver and muscle) was freeze-dried in a lyophilised chamber (α 1–4 LDplus; Christ), which was used for fatty acid profile analysis.

The fatty acid profile was determined according to the protocol of Li et al. (Reference Li, Cui and Fang5). Fatty acids were esterified into fatty acid methyl esters by KOH–ethanol and methanolic hydrogen chloride. Fatty acid methyl ester was separated and measured by an HP6890 GC (Agilent Technologies Inc.). The results were expressed as the percentage of each fatty acid in the total fatty acid content.

Plasma biochemical indices

The contents of total cholesterol, TAG, total protein, HDL-cholesterol, LDL-cholesterol, aspartate aminotransferase and alanine transaminase were measured by an automatic biochemical analyser (Cobas c311, Roche). The NEFA and alkaline phosphatase level was measured by commercial assay kits (Nanjing Jiancheng Bioengineering Institute), following the manufacturer’s instructions.

Activities of antioxidant enzymes and malondialdehyde content assay

Total antioxidant capacity, reduced GSH content, superoxide dismutase (SOD) activity and malondialdehyde (MDA) content in the liver was determined by commercial assay kits (Nanjing Jiancheng Bioengineering Institute), following the manufacturer’s instructions.

cDNA synthesis and RT–qPCR

Total RNA was extracted from the visceral mass or liver using RNAiso Plus (Takara). RNA was reverse-transcribed to cDNA with a Prime Script-RT reagent Kit (Takara). The mRNA level was measured by RT–qPCR using ChamQ Universal SYBR qPCR Master Mix (Vazyme, China) using the supplied primers (online Supplementary Table 2). According to Zuo et al. (Reference Zuo, Ai and Mai35), the fluorescence data obtained were normalised to β-actin by the 2−ΔΔCT method.

Western blot analysis

Liver protein was extracted by RIPA (Solarbio) with protease and phosphatase inhibitor cocktails (Roche). Protein was separated on a 10 % SDS–PAGE gel for 1 h at 150 V and then transferred to PVDF membranes (Millipore) for 1 h at 100 V. Then, the PVDF membranes were blocked for 1 h at room temperature and incubated with a primary antibody in Tris-buffered saline with Tween overnight in the 4°C freezers. After washing with Tris-buffered saline with Tween, the membranes were incubated with the secondary antibody in Tris-buffered saline with Tween for 1 h at room temperature. Next, the signal was measured by using ELC reagents (Beyotime Institute of Biotechnology). The intensity of the protein bands was quantified by using ImageJ 1·44p software (U.S. National Institutes of Health).

The antibody used were sterol-regulatory element binding protein 1 c (SREBP1c) (WL02093, Wanleibio), diacylglycerol acyltransferase 1 (DGAT1) (Gensript), acetyl-CoA carboxylase (3662, CST), acyl-CoA oxidase (ab184032, Abcam, UK), PPARα (117 362, Absin), carnitine palmitoyl transferase 1 α (15184-1-AP, Proteintech) and glyceraldehyde-3-phosphate dehydrogenase (R001, Goodhere).

Calculations and statistical analysis

$${\rm{Survival}}{\mkern 1mu} \,{\rm{rate}}\;\left( \% \right) = {{\rm{N}}_{\rm{t}}} \times 100{\rm{/}}{{\rm{N}}_{\rm{i}}}$$
$${\rm{Specific}}\,{\mkern 1mu} {\rm{growth}}\,{\mkern 1mu} {\rm{rate}}\;\left( {\% {{\rm{d}}^{ - 1}}} \right) = \left( {{\rm{Ln}}{{\rm{W}}_{\rm{t}}} - {\rm{Ln}}{{\rm{W}}_{\rm{i}}}} \right) \times 100{\rm{/d}}$$
$${\rm{Feed}}{\mkern 1mu} \,{\rm{intake}}\;\left( \% \right) = {{\rm{W}}_{\rm{f}}}_{\rm{/}}\left( {\left( {{{\rm{W}}_i} + {{\rm{W}}_{\rm{t}}}} \right)/2} \right){\rm{/d}} \times 100$$
$${\rm{Feed}}{\mkern 1mu} \,{\rm{efficiency}}\,{\mkern 1mu} {\rm{ratio}}\;\left( \% \right) = \left( {{{\rm{W}}_t} - {{\rm{W}}_{\rm{i}}}} \right){\rm{/}}{{\rm{W}}_{\rm{f}}}$$
\begin{align}&{\rm{Apparent}}\,{\mkern 1mu} {\rm{digestibility}}\,{\mkern 1mu} {\rm{coefficients}}{\mkern 1mu} \,{\rm{of}}\,{\mkern 1mu} {\rm{dry}}\,{\mkern 1mu} {\rm{matter}}\;\left( \% \right)\\ &\quad \quad = \left( {{\rm{1 - }}{{\rm{Y}}_{\rm{2}}}{{\rm{O}}_{\rm{3}}}\;{\rm{in}}\,{\mkern 1mu} {\rm{the}}\,{\mkern 1mu} {\rm{diet/}}{{\rm{Y}}_{\rm{2}}}{{\rm{O}}_{\rm{3}}}{\rm{in}}\,{\mkern 1mu} {\rm{faeces}}} \right) \times {\rm{100}}\end{align}
\begin{align}& {\rm{Apparent}}{\mkern 1mu} {\mkern 1mu} {\rm{digestibility}}{\mkern 1mu} {\mkern 1mu} {\rm{coefficients}}{\mkern 1mu} {\mkern 1mu} {\rm{of}}{\mkern 1mu} {\mkern 1mu} {\rm{lipid}}\;\left( \% \right){\rm{ }} =\\ &\qquad \qquad \qquad {\rm{ }}\left( {\rm{1}} - {{\rm{Y}}_{\rm{2}}}{{\rm{O}}_{\rm{3}}}{\mkern 1mu} {\rm{in}}{\mkern 1mu} {\mkern 1mu} {\rm{the}}{\mkern 1mu} {\mkern 1mu} {\rm{diet}} \times {\rm{lipid}}{\mkern 1mu} {\mkern 1mu} {\rm{in}}{\mkern 1mu} {\mkern 1mu} {\rm{feces/}}\right.\\ &\qquad \qquad\qquad \,\, \left.{{\rm{Y}}_{\rm{2}}}{{\rm{O}}_{\rm{3}}}{\rm{in}}{\mkern 1mu} {\rm{faeces}} \times {\rm{lipid}}{\mkern 1mu} \,{\rm{in}}\,{\mkern 1mu} {\rm{diet}} \right) \times 100\end{align}
$${\rm{Hepatosomatic}}\,{\mkern 1mu} {\rm{index}}\;\left( {{\rm{HSI}},{\mkern 1mu} \% } \right) = {\rm{liver}}\,{\mkern 1mu} {\rm{weight/fish}}\,{\mkern 1mu} {\rm{weight}} \times 100$$
$${\rm{Visceral}}{\mkern 1mu} \,{\rm{somatic}}\,{\mkern 1mu} {\rm{index}}\;\left( \% \right) = {\rm{viscera}}{\mkern 1mu} {\rm{weight/fish}}{\mkern 1mu} {\rm{weight}} \times 100$$

where Nt and Ni represent the final and initial numbers of larvae or juvenile fish in each tank, respectively; Wt is the final body weight and Wi is the initial body weight; Wf is the weight of feed; and d is the experimental duration in days.

Statistical analysis was performed in SPSS 23.0 (SPSS Inc.), and the results are presented as the mean ± SE of the mean (sem) (n 3). Data from each treatment were subjected to ANOVA followed by Tukey’s test or independent-samples t-test. For statistically significant differences, P < 0·05 was needed.

Results

Survival and growth performance

The survival rate was slightly lower in larvae fed the VO diet than in those fed the FO diet in the stimulus phases (P > 0·05) (Table 2). During the growth phase and challenge phase, there were no effects of nutritional history on the survival rate of juveniles. Final length, final weight and specific growth rate were significantly lower in larvae fed the VO diet than in those fed the FO diet in the stimulus phase (P < 0·05) (Table 2). However, fish with a VO nutritional history showed higher specific growth rate than fish with a FO nutritional history in the growth phase (P < 0·05) (Table 2). Like the survival rate, although the nutritional history of juvenile fish was different, there was no significant difference in the growth performance among treatments during the challenge phase.

Table 2. Survival and growth rate of fish during each of the three nutritional phases

(Mean values with their standard errors of the mean, n 3)

* P < 0.05, significant differences between groups.

In this phase, data in the same row sharing the same superscript letter are not significantly different, determined by Tukey’s test (P > 0.05).

Feed utilisation

No significant difference in feed intake, feed efficiency ratio or apparent digestibility coefficients of dry matter was observed in juvenile fish in the challenge phase. Juveniles fed the FO diet showed significantly higher apparent digestibility coefficients of lipid than other groups in the challenge phase (P < 0·05) (Fig. 2).

Fig. 2. Feed utilisation of juvenile large yellow croaker in the challenge phase. FI, feed intake; FER, feed efficiency ratio; ADCD, apparent digestibility coefficients of dry matter; ADCL, apparent digestibility coefficients of lipid. Values are means (n 3), with their standard errors represented by vertical bars. Bars bearing the same letters were not significantly different (P > 0·05, Tukey’s test).

Body composition, tissue lipids and TAG content

No significant difference in crude protein and crude lipid was observed in whole larvae or fish among groups during the three phases. FCV-fish showed significantly higher liver lipid and TAG content than FCF-fish in the challenge phase (P < 0·05) (Table 3). Although no significant difference between FCV-fish and VCV-fish in liver lipid and TAG content was observed, there was a trend that VO nutritional history reduced the liver lipid content of fish when juveniles were challenged with the VO diet.

Table 3. Body composition, liver and muscle lipid content in fish during each of the three nutritional phases

(Mean values with their standard errors of the mean, n 3)

d.w.: dry weight.

In this phase, *P < 0.05, significant differences between groups.

In this phase, data in the same row sharing the same superscript letter are not significantly different, determined by Tukey’s test (P > 0.05).

Fatty acid composition

In the stimulus phase, the whole larvae SFA (14:0 and 16:0) and 16:1n-7 were significantly lower in larvae fed the VO diet than in larvae fed the FO diet (P < 0·05) (Table 4). However, the contents of 18:1n-9, 18:2n-6, 18:3n-3, ∑MUFA, ∑n-6 PUFA and ∑n-3 PUFA was significantly higher in larvae fed the VO diet than in larvae fed the FO diet (P < 0·05) (Table 4).

Table 4. Fatty acid composition of whole larvae in the stimulus phase

(Mean values with their standard errors of the mean, n 3)

* P < 0.05, significant differences between groups.

Some fatty acids, of which the contents are minor, trace amount or not detected, such as 4:0, 6:0, 8:0, 10:0, 11:0, 12:0, 13:0, 24:0, 14:1, 20:1n-9, 22:1n-11, 20:2n-6, 23:0, 20:3n-6, are not listed in the table.

During the challenge stage, the liver fatty acid content (14:0, 16:0, 16:1n-7, 20:4n-6, 20:5n-3, 22:6n-3 and ∑n-3 PUFA) was significantly higher in FCF-fish, while 18:2n-6, 18:3n-3 and ∑n-6 PUFA content was significantly lower than in other groups (P < 0·05) (Table 5).

Table 5. Fatty acid composition in the liver of juvenile large yellow croaker in the challenge phase*

(Mean values with their standard errors of the mean, n 3)

* Some fatty acids, of which the contents are minor, trace amount or not detected, such as 4:0, 6:0, 8:0, 10:0, 11:0, 12:0, 13:0, 24:0, 14:1, 20:1n-9, 22:1n-11, 20:2n-6, 23:0, 20:3n-6, are not listed in the table.

Data in the same row sharing the same superscript letter are not significantly different, determined by Tukey’s test (P > 0.05).

Like the liver, the muscle fatty acid content (14:0, 16:0, 16:1n-7, 20:4n-6, 20:5n-3, 22:6n-3 and ∑n-3 PUFA) was significantly higher in the FCF-fish than in the other groups (P < 0·05) (Table 6). In addition, lower content of 18:1n-9, 18:2n-6, 18:3n-3, ∑n-6 PUFA and ∑n-3 PUFA was observed in FCF-fish than in other groups (P < 0·05) (Table 6).

Table 6. Fatty acid composition in the muscle of juvenile large yellow croaker in the challenge phase*

(Mean values with their standard errors of the mean, n 3)

* Some fatty acids, of which the contents are minor, trace amount or not detected, such as 4:0, 6:0, 8:0, 10:0, 11:0, 12:0, 13:0, 24:0, 14:1, 20:1n-9, 22:1n-11, 20:2n-6, 23:0, 20:3n-6, are not listed in the table.

Data in the same row sharing the same superscript letter are not significantly different, determined by Tukey’s test (P > 0.05).

Serum biochemical indices

During the challenge stage, FCV-fish had significantly higher serum nonesterified free fatty acid than other groups (P < 0·05) (Table 7). However, neither nutritional history nor different oil source stimulation had significant effects on serum TAG, total cholesterol, LDL-cholesterol, HDL-cholesterol and total protein.

Table 7. Serum metabolite profiles of fish in the challenge phase

(Mean values with their standard errors of the mean, n 3)

TC, total cholesterol; TP, total protein; NEFA, nonesterified free fatty acids.

Data in the same row sharing the same superscript letter are not significantly different, determined by Tukey’s test (P > 0.05).

Expression of liver lipid metabolism-related genes and proteins

During the stimulus phase, the expression of a lipogenesis-related gene (acc1) was significantly higher in larvae fed the VO diet than in larvae fed the FO diet (P < 0·05) (Fig. 3(a)). However, no significant difference was observed in other lipogenesis or lipolysis-related genes (P > 0·05) (Fig. 3(a)). Meanwhile, higher expression of long chain-PUFA (LC-PUFA) synthesis genes (△6fad and elovl4) was observed in larvae fed the VO diet than in larvae fed the FO diet (P < 0·05) (Fig. 3(b)). For lipid transport-related genes, compared to larvae fed the FO diet, dietary VO downregulated the expression of apob100 and apobAI (P < 0·05) (Fig. 3(c)).

Fig. 3. Expression of lipid metabolism-related genes in the visceral mass of large yellow croaker larvae during the stimulus phase. (a) Lipid lipogenesis and lipolysis; (b) LC-FUFA synthesis and (c) lipid transport. Values are means (n 3), with their standard errors represented by vertical bars. *P < 0·05, significant differences between groups.

During the growth phase, no significant difference was observed in lipogenesis or lipolysis-related genes (P > 0·05) (Fig. 4(a)). Effects of VO nutritional history on the expression of LC-PUFA synthesis and lipid transport genes still existed after the 90-d growth trial. Higher expression of △6fad and elovl5 was observed in VC fish than in FC fish (P < 0·05) (Fig. 4(b)). Meanwhile, lower expression of mtp was also observed in VC fish than FC fish (P < 0·05) (Fig. 4(c)).

Fig. 4. Expression of lipid metabolism-related genes in the liver of large yellow croaker during the growth phase. (a) Lipid lipogenesis and lipolysis; (b) LC-FUFA synthesis and (c) lipid transport. Values are means (n 3), with their standard errors represented by vertical bars. *P < 0·05, significant differences between groups.

During the challenge phase, the expression of lipogenesis-related genes (srebp1c, dgat1, acc1, and fas) and proteins (SREBP1c, DGAT1 and acetyl-CoA carboxylase) in FCV-fish was higher than that in FCF- or VCV-fish (Fig. 5(a) and Fig. 6). Neither nutritional history nor VO stimulation had a significant effect on the genes involved in lipolysis among treatments (Fig. 5(a)). Higher expression of the LC-PUFA synthesis gene (△6fad) was observed in VCV-fish than FCF-fish (Fig. 5(b)). Furthermore, the lipid transport-related gene expression (apob100 and mtp) of FCF-fish was significantly higher than that of the other groups (P < 0·05) (Fig. 5(c)).

Fig. 5. Expression of lipid metabolism-related genes in the liver of large yellow croaker during the challenge phase. (a) Lipid lipogenesis and lipolysis; (b) LC-FUFA synthesis and (c) lipid transport. Values are means (n 3), with their standard errors represented by vertical bars. Bars bearing the same letters were not significantly different (P > 0·05, Tukey’s test).

Fig. 6. Expression of lipid lipogenesis and lipolysis-related proteins in the liver of large yellow croaker during the challenge phase. p-SREBP1c, precursor SREBP1c; m-SREBP1c, mature SREBP1c. Values are means (n 3), with their SE represented by vertical bars. Bars bearing the same letters were not significantly different (P > 0·05, Tukey’s test).

Live damage and antioxidant capacity

During the challenge stage, the activities of alanine transaminase and aspartate aminotransferase were significantly higher in FCV-fish than in other groups (P < 0·05) (Fig. 7(a)). Similarly, FCV-fish showed significantly higher alkaline phosphatase activity than FCF-fish (P < 0·05) (Fig. 7(a)). The lowest activities of SOD, total antioxidant capacity and GSH were observed in FCV-fish (Fig. 7(b)). Meanwhile, FCV-fish had significantly higher MDA content than the other groups (P < 0·05) (Fig. 7(b)). Furthermore, the lowest antioxidant-related gene (sod2 and nrf2) expression was observed in FCV-fish (Fig. 7(c)).

Fig. 7. Liver damage and antioxidant capacity-related parameters of large yellow croaker during the challenge phase. (a) Liver damage: serum ALT, AST and AKP; (b) antioxidant parameters: liver SOD, T-AOC, GSH and MDA and (c) antioxidant genes. Values are means (n 3), with their standard errors represented by vertical bars. Bars bearing the same letters were not significantly different (P > 0·05, Tukey’s test).

Discussion

Previous studies have extensively demonstrated that early life history may profoundly affect metabolic adaptability and disease risk in adult mammals, so nutritional programming (metabolic programming) has become a hot research area(Reference Liu, Dias and Plagnes-Juan13). In recent years, nutritional programming has also been gradually applied to aquatic animals, which has been considered a promising strategy to enhance VO or vegetable protein utilisation in aquafeed(Reference Clarkson, Migaud and Metochis18,Reference Geurden, Borchert and Balasubramanian36) . The ‘critical window’ is an extremely crucial aspect of nutritional programming. For mammals, it is mostly during gestation or lactation, while for fish, it is usually during the egg or larval stage, or during the spawning season (broodstock)(Reference Engrola, Aragão and Valente11). For fish, the embryonic and larval stages are characterised by organogenesis, establishment of metabolic pathways and strong metabolic plasticity(Reference Hou and Fuiman17). Therefore, most studies have chosen to conduct nutritional/non-nutritive stimulation at the first feeding or embryonic stage. In the present study, we started the VO stimulus at 15 dph (completely exogenous feeding starts at 7 dph). The start of this stimulation was slightly later than the embryonic stage or first feeding. There are many reasons for the choice of this stimulation time point: (1) large yellow croaker larvae are still in the process of organ formation and rapid development during 15–45 dph(Reference Mai, Yu and Ma37); (2) large yellow croaker larvae are not like rainbow trout(Reference Liu, Dias and Plagnes-Juan13), Atlantic salmon(Reference Clarkson, Migaud and Metochis18) and other fish in consuming formulated microdiets during first feeding and (3) there are also studies that chose to stimulate at a later time(Reference Geurden, Borchert and Balasubramanian36,Reference Vagner, Zambonino Infante and Robin38) or at multiple stages(Reference Rocha, Dias and Geurden39). The results of this study also partially prove that slightly later stimulation in the larval phase was effective in inducing significant physiological and metabolic changes. This provides the possibility to conduct nutritional programming studies for fish species with extremely high mortality in the early stage, that is, to conduct nutritional stimulation later. For the current study, the aim was to investigate the potential long-term metabolic effects of early short-term nutritional programming of large yellow croaker.

In this study, early short VO intervention significantly reduced the growth performance of larvae. Similarly, Turkmen et al.(Reference Turkmen, Castro and Caballero40) found that feeding the low n-3 LC-PUFA (main lipid source: linseed oil and soybean lecithin) diet led to a lower larval weight, total length and survival rate of gilthead seabream larvae. This may be due to the low content of ARA, EPA or DHA in the VO diet, which cannot satisfy the nutritional requirements of large yellow croaker larvae. Another reason might be the low acceptance of VO diets by large yellow croaker larvae causing a decrease in the feeding rate and, ultimately, growth retardation, although this could not be accurately measured in the stimulus phase of the present study. Similarly, studies have demonstrated that Atlantic salmon(Reference Clarkson, Migaud and Metochis18) and turbot(Reference Fournier, Huelvan and Desbruyeres41) are reluctant to eat a vegetable-based diet, especially when it is first introduced. After the 90-d growth phase, regardless of the nutritional history, no significant difference in final body weight was observed among the groups. Since the VC groups had smaller initial weights (93·72 ± 3·00 mg) in the growth phase than the FC group (114·31 ± 5·25 g), the final body weight was similar between the two groups (FC:11·83 ± 0·29; VC: 11·05 ± 0·02), and VO history fish showed higher specific growth rate than FO history fish in the growth phase. The compensatory growth of fish during the growth phase may be one of the reasons for this phenomenon(Reference Ali, Nicieza and Wootton42). Comparable results were also found in yellow perch (Perca flavescens)(Reference Kemski, Wick and Dabrowski43) and European sea bass(Reference Zambonino-Infante, Panserat and Servili12). Indeed, this may be limited by fish species, stimulation type and stimulation duration, and the clarification of which will require additional studies. The analysis of growth-related gene changes through nutrigenomics, and microarray technology can provide a more accurate explanation. During the challenge phase, VO nutritional history did not affect the utilisation of the VO diet (Feed intake, feed efficiency ratio, apparent digestibility coefficients of lipid and apparent digestibility coefficients of dry matter) or the growth performance of juvenile large yellow croaker. This indicated that the early VO stimuli did not cause long-term effects on the overall growth performance at the late juvenile stage, even when faced with a VO challenge. Similarly, the growth of European sea bass juveniles was not affected by larval nutritional conditioning (low/high LC-PUFA) when fed an LC-PUFA-deprived experimental diet(Reference Vagner, Zambonino Infante and Robin38). However, those results differed from studies in Atlantic salmon(Reference Clarkson, Migaud and Metochis18) and rainbow trout (Oncorhynchus mykiss)(Reference Geurden, Borchert and Balasubramanian36), in which early nutritional exposure through a vegetable or plant-based diet improved the utilisation of a vegetable or plant-based diet when challenged later in life. Balasubramanian et al.(Reference Balasubramanian, Panserat and Dupont-Nivet44) found that early feeding exposure to a plant-based diet could alter the expression of genes related to visual transduction processes, olfactomedin, a member of the taste receptor family (Tas1r2) and appetite regulating factors in rainbow trout juveniles, thereby increasing their utilisation and acceptance of plant-based diet to achieve growth-promoting effects. How nutritional programming affects the expression of the above genes may be related to epigenetic modifications represented by DNA methylation(Reference Candler, Kühnen and Prentice45). In addition, nutritional programming can also affect growth by directly affecting the expression of protein synthesis genes. Zhu et al.(Reference Zhu, Wang and He46) demonstrated that early leucine programming could affect the methylation and expression of genes involved in protein synthesis in zebrafish. Whether early nutritional programming has long-term effects on the growth performance of different fish remains uncertain, and experimental results may be influenced by a variety of factors, such as fish species, causes, critical window and duration (persistence).

It is widely known that the fatty acid profile of farmed fish can reflect the fatty acid composition of the diet(Reference Xu, Turchini and Francis47). In the present study, the effect of the current diet on fish body fatty acid composition was significantly stronger than that of nutritional history. Furthermore, the early VO nutritional stimulus had no major effect on the final fatty acid compositions of either whole body or tissues. Previous studies have shown that nutritional programming could also improve the LC-PUFA synthesis ability of fish. European seabass larvae were given either a high (2·2 %) or a low (0·8 %) LC-PUFA diet from the first feeding, followed by a commercial diet for 3 months. When juveniles were challenged with an LC-PUFA depleted diet (0·5 %) for 2 months, low LC-PUFA diet nutritional history fish had higher DHA content in polar lipids(Reference Vagner, Zambonino Infante and Robin38,Reference Vagner, Robin and Infante48) . In the present study, nutritional history did not significantly affect the LC-PUFA content of muscle or liver when the juveniles were challenged with the VO diet. VO nutritional history had a long-term effect only on the expression of the critical gene (△6fad) in the synthesis of LC-PUFA. Although early VO stimulation could continuously upregulate the gene expression of fatty acid desaturase, it was not enough to completely compensate for the lack of EPA and DHA in the VO diet during the challenge phase. Comparable results have been reported in Atlantic salmon(Reference Clarkson, Migaud and Metochis18). The mechanism of nutritional programming regulating the fatty acid synthesis pathways and key molecular marker gene expression (such as △6fad) may be related to the methylation level of the promoter region of △6fad. Xu et al.(Reference Xu, Dong and Ai49) indicated that the △6fad gene expression regulated by dietary fatty acids was significantly negatively correlated with the methylation rate of the △6fad gene promoter.

High-level VO in diets often leads to abnormal lipid deposition on the liver and damages the health of the fish, such as sharpsnout seabream (Diplodus puntazzo)(Reference Piedecausa, Mazon and Garcia50), gilthead sea bream (Sparus aurata L.)(Reference Fountoulaki, Vasilaki and Hurtado51) and large yellow croaker(Reference Xu, Ding and Liu6). To further investigate the effects of nutritional programming on lipid metabolism in large yellow croaker, we studied the body composition, serum biochemical indices, lipid metabolism-related genes and proteins of fish. In the present study, fish with a VO nutritional history showed lower liver lipid content, liver TAG, and serum NEFA than fish with an FO history when challenged with the VO diet. The expression of lipogenesis-related genes (srebp1c, acc1, dgat1 and fas) and proteins (SREBP1c, acetyl-CoA carboxylase and DGAT1) further confirmed this result, although nutritional history did not significantly affect the expression of lipolysis-related genes. For the lipid transport genes, regardless of the nutritional history in the larval stage, the VO diet significantly reduced the expression of mtp and apob100 in the challenge stage. The above results indicate that VO nutritional programming in the larval stage may alleviate the abnormal lipid deposition in the liver of juvenile fish caused by the VO diet to a certain extent by reducing lipogenesis. Less research has focused on the effect of VO nutritional programming on abnormal liver lipid deposition, while most studies have focused on the utilisation of VO and vegetable protein(Reference Clarkson, Migaud and Metochis18,Reference Geurden, Borchert and Balasubramanian36,Reference Vagner, Zambonino Infante and Robin38) , although studies on regulating liver lipid deposition through nutritional programming in mammals have been conducted. Cai et al.(Reference Cai, Wang and Jia52) reported that dietary betaine supplementation of the maternal pig during gestation attenuated hepatic lipogenesis in neonatal piglets via epigenetic (DNA methylation and histone methylation) and glucocorticoid receptor-mediated mechanisms. Heng et al.(Reference Heng, Tian and Zhang53) found that heat stress of the maternal pig regulated early fat deposition partly through modification of m6A RNA methylation in neonatal piglets. The mechanism of regulating fish liver lipid metabolism through VO nutritional programming may also be related to epigenetic modification (DNA methylation, histone methylation and RNA methylation, etc.), which needs more research to be confirmed.

Replacement of FO by VO will cause lipid accumulation in the liver and further leads to liver damage and decreased antioxidant capacity. Tan et al. (Reference Tan, Dong and Xu54) found that dietary VO could reduce the liver antioxidant capacity of Japanese sea bass (Lateolabrax japonicus). Thus, the present study further investigated the effect of VO nutritional programming on relieving liver damage and reducing hepatic antioxidant capacity. Aspartate aminotransferase, alanine transaminase and alkaline phosphatase are biomarkers of liver damage that are released from hepatocytes into the blood during liver injury(Reference Ji, Xiang and Li55,Reference Hyder, Hasan and Mohieldein56) . During the challenge stage, the activities of alanine transaminase, aspartate aminotransferase and alkaline phosphatase were lower in the VO nutritional history fish than in the FO nutritional history fish when juveniles were challenged with the VO diet, indicating that early VO nutritional programming may relieve liver damage caused by the VO diet in later life. Similarly, studies of nutritional programming affecting liver function have also been reported in mammals, where protein restriction during pregnancy and lactation or maternal high fat intake can cause liver damage in offspring(Reference Podaza, Echarte and Chisari57,Reference Bruce, Cagampang and Argenton58) . Oxidative stress causes overproduction of reactive oxygen species, leading to lipid peroxidation and DNA damage(Reference Lesser59). As one of the metabolites derived from lipid peroxidation, MDA is a widely known biomarker of oxidative stress damage(Reference Del Rio, Stewart and Pellegrini60). In this study, fish with a VO nutritional history showed significantly lower MDA content in the liver than fish with a FO nutritional history when challenged with the VO diet. Furthermore, antioxidant enzymes and substances (SOD, total antioxidant capacity and GSH) were higher in fish with a VO nutritional history than fish with a FO nutritional history when challenged with the VO diet, despite statistically significant differences only occurring in GSH. In addition, antioxidant genes (sod2 and nrf2) showed similar trends. Related results have been confirmed in mammals. Specifically, when maternal mice were fed a high-fat diet, adult offspring developed hypertension combined with increased MDA and decreased activity of SOD, CAT and GPx(Reference Resende, Emiliano and Cordeiro61). Nutritional programming can also be used to alleviate oxidative stress. Prenatal exposure to quercetin resulted in upregulation of Nrf2 and Sod2 in the liver of foetus at Day 14·5 of gestation and in both the liver and lung tissue of adult mice(Reference Vanhees, van Schooten and van Doorn-Khosrovani62). Barden et al.(Reference Barden, Mori and Dunstan63) demonstrated that high-dose n-3 PUFA supplementation in pregnancy can regulate foetal oxidative stress. There are few related studies in fish. Parental Se supplementation of rainbow trout has long-lasting effects on antioxidant metabolism even if it reduce the hypoxic stress resistance of the progeny(Reference Wischhusen, Larroquet and Durand64). However, early LC n-3 PUFA programming has no remarkable difference in the antioxidant activities of SOD, total antioxidant capacity, CAT and MDA of Siberian sturgeon at all three stages (early programming period, intermediate period and adaptability period)(Reference Luo, Wei and Ai65). In general, it could be speculated that early VO nutritional programming of large yellow croaker larvae may relieve liver damage and reduce hepatic antioxidant capacity caused by the VO diet in later life. However, the mechanism by which VO nutritional programming regulates hepatic antioxidant capacity and liver damage is still unclear. Although the stimulating factors are different, studies on mammals have shown that metabolic diseases such as oxidative stress and liver damage are mostly related to epigenetic modifications such as DNA methylation(Reference Vanhees, Vonhogen and van Schooten66Reference Milagro, Mansego and De Miguel68). Compared with mammals, there are fewer studies on nutritional programming in fish, and the underlying mechanism needs further study.

Conclusion

While no significant effects of nutritional programming on juvenile growth and survival were observed in this study, a short VO stimulus during the early life of large yellow croaker had a long-term effect on lipid metabolism and the antioxidant system. Specifically, VO nutritional programming had a positive effect on alleviating abnormal lipid deposition on the liver, liver damage and the reduction of hepatic antioxidant capacity caused by a VO diet. Further research is needed to better understand the potential epigenetic, metabolic and molecular mechanisms involved in the nutritional programming of large yellow croaker.

Acknowledgements

We thank Xiaojun Xiang, Dan Xu, Shengnan Gao, Qiuchi Chen, Wei Fang, Weijia Li and Chukwuma Kennethchibuikem for their help during the experiment.

This research was financially supported by the earmarked fund for CARS-47 and the Key Program of National Natural Science Foundation of China (31830103).

Conceptualisation, Y. L.; Funding acquisition, K. M. and Q. A.; Investigation, Y. L. and C. Y.; Methodology and review, K. C., T. H., Z. Y., W. X. and W. H.; Supervision, Q. A.; Writing – original draft, Y. L.; Writing – review & editing, Y. L. and Q. A.

The authors declare that they have no conflict of interest.

Supplementary material

For supplementary material/s referred to in this article, please visit https://doi.org/10.1017/S0007114522001726

Footnotes

The online version of this article has been updated since original publication. A notice detailing the change has been published at https://doi.org/10.1017/S0007114524000692.

References

FAO (2020) The State of World Fisheries and Aquaculture 2020. Sustainability in Action. Rome: FAO.Google Scholar
EUMOFA (2021) Fishmeal and Fish Oil: Production and Trade Flows in the EU. https://aquahoy.com/fishmeal-fish-oil-production-trade-flows-eu/(accessed March 2022).Google Scholar
Shi, C, Zhao, H, Zhai, X, et al. (2019) Linseed oil can decrease liver fat deposition and improve antioxidant ability of juvenile largemouth bass, Micropterus salmoides . Fish Physiol Biochem 45, 15131521.CrossRefGoogle ScholarPubMed
Torstensen, BE, Espe, M, Sanden, M, et al. (2008) Novel production of Atlantic salmon (Salmo salar) protein based on combined replacement of fish meal and fish oil with plant meal and vegetable oil blends. Aquaculture 285, 193200.CrossRefGoogle Scholar
Li, X, Cui, K, Fang, W, et al. (2019) High level of dietary olive oil decreased growth, increased liver lipid deposition and induced inflammation by activating the p38 MAPK and JNK pathways in large yellow croaker (Larimichthys crocea). Fish Shellfish Immunol 94, 157165.CrossRefGoogle ScholarPubMed
Xu, N, Ding, T, Liu, Y, et al. (2021) Effects of dietary tributyrin on growth performance, body composition, serum biochemical indexes and lipid metabolism-related genes expression of juvenile large yellow croaker (Larimichthys crocea) fed with high level soybean oil diets. Aquacult Nutr 27, 395406.CrossRefGoogle Scholar
Sun, S, Ye, J, Chen, J, et al. (2011) Effect of dietary fish oil replacement by rapeseed oil on the growth, fatty acid composition and serum non-specific immunity response of fingerling black carp, Mylopharyngodon piceus . Aquacult Nutr 17, 441450.CrossRefGoogle Scholar
Torstensen, B, Frøyland, L & Lie, Ø (2004) Replacing dietary fish oil with increasing levels of rapeseed oil and olive oil–effects on Atlantic salmon (Salmo salar L.) tissue and lipoprotein lipid composition and lipogenic enzyme activities. Aquacult Nutr 10, 175192.CrossRefGoogle Scholar
Li, Y, Liang, X, Zhang, Y, et al. (2016) Effects of different dietary soybean oil levels on growth, lipid deposition, tissues fatty acid composition and hepatic lipid metabolism related gene expressions in blunt snout bream (Megalobrama amblycephala) juvenile. Aquaculture 451, 1623.CrossRefGoogle Scholar
Lucas, A (1998) Programming by early nutrition: an experimental approach. J Nutr 128, 401406.CrossRefGoogle ScholarPubMed
Engrola, S, Aragão, C, Valente, LM, et al. (2018) Nutritional modulation of marine fish larvae performance. In Emerging Issues in Fish Larvae Research, pp. 209228 [Manuel Yúfera, editor]. Switzerland: Springer.CrossRefGoogle Scholar
Zambonino-Infante, JL, Panserat, S, Servili, A, et al. (2019) Nutritional programming by dietary carbohydrates in European sea bass larvae: not always what expected at juvenile stage. Aquaculture 501, 441447.CrossRefGoogle Scholar
Liu, J, Dias, K, Plagnes-Juan, E, et al. (2017) Long-term programming effect of embryonic hypoxia exposure and high-carbohydrate diet at first feeding on glucose metabolism in juvenile rainbow trout. J Exp Biol 220, 36863694.Google ScholarPubMed
George, LA, Zhang, L, Tuersunjiang, N, et al. (2012) Early maternal undernutrition programs increased feed intake, altered glucose metabolism and insulin secretion, and liver function in aged female offspring. Am J Physiol Regul Integr Comp Physiol 302, 795804.CrossRefGoogle ScholarPubMed
Petry, CJ, Ozanne, SE & Hales, CN (2001) Programming of intermediary metabolism. Mol Cell Endocrinol 185, 8191.CrossRefGoogle ScholarPubMed
Symonds, ME, Sebert, SP, Hyatt, MA, et al. (2009) Nutritional programming of the metabolic syndrome. Nat Rev Endocrinol 5, 604610.CrossRefGoogle ScholarPubMed
Hou, Z & Fuiman, LA (2019) Nutritional programming in fishes: insights from mammalian studies. Rev Fish Biol Fish 30, 6792.CrossRefGoogle Scholar
Clarkson, M, Migaud, H, Metochis, C, et al. (2017) Early nutritional intervention can improve utilisation of vegetable-based diets in diploid and triploid Atlantic salmon (Salmo salar L.). Br J Nutr 118, 1729.CrossRefGoogle ScholarPubMed
Turkmen, S, Zamorano, MJ, Fernandez-Palacios, H, et al. (2017) Parental nutritional programming and a reminder during juvenile stage affect growth, lipid metabolism and utilisation in later developmental stages of a marine teleost, the gilthead sea bream (Sparus aurata). Br J Nutr 118, 500512.CrossRefGoogle Scholar
Fang, L, Liang, X, Zhou, Y, et al. (2014) Programming effects of high-carbohydrate feeding of larvae on adult glucose metabolism in zebrafish, Danio rerio . Br J Nutr 111, 808818.CrossRefGoogle ScholarPubMed
Geurden, I, Mennigen, J, Plagnes-Juan, E, et al. (2014) High or low dietary carbohydrate:protein ratios during first-feeding affect glucose metabolism and intestinal microbiota in juvenile rainbow trout. J Exp Biol 217, 33963406.CrossRefGoogle ScholarPubMed
Rocha, F, Dias, J, Engrola, S, et al. (2015) Glucose metabolism and gene expression in juvenile zebrafish (Danio rerio) challenged with a high carbohydrate diet: effects of an acute glucose stimulus during late embryonic life. Br J Nutr 113, 403413.CrossRefGoogle ScholarPubMed
Kwasek, K, Wojno, M, Iannini, F, et al. (2020) Nutritional programming improves dietary plant protein utilization in zebrafish Danio rerio . PLOS ONE 15, e0225917.CrossRefGoogle ScholarPubMed
Perera, E & Yufera, M (2017) Effects of soybean meal on digestive enzymes activity, expression of inflammation-related genes, and chromatin modifications in marine fish (Sparus aurata L.) larvae. Fish Physiol Biochem 43, 563578.CrossRefGoogle ScholarPubMed
Lazzarotto, V, Corraze, G, Larroquet, L, et al. (2016) Does broodstock nutritional history affect the response of progeny to different first-feeding diets? A whole-body transcriptomic study of rainbow trout alevins. Br J Nutr 115, 20792092.CrossRefGoogle Scholar
Craig, PM & Moon, TW (2013) Methionine restriction affects the phenotypic and transcriptional response of rainbow trout (Oncorhynchus mykiss) to carbohydrate-enriched diets. Br J Nutr 109, 402412.CrossRefGoogle ScholarPubMed
Skjaerven, KH, Jakt, LM, Dahl, JA, et al. (2016) Parental vitamin deficiency affects the embryonic gene expression of immune, lipid transport and apolipoprotein genes. Sci Rep 6, 34535.CrossRefGoogle ScholarPubMed
Skjaerven, KH, Jakt, LM, Fernandes, JMO, et al. (2018) Parental micronutrient deficiency distorts liver DNA methylation and expression of lipid genes associated with a fatty-liver-like phenotype in offspring. Sci Rep 8, 3055.CrossRefGoogle ScholarPubMed
Liu, J, Plagnes-Juan, E, Geurden, I, et al. (2017) Exposure to an acute hypoxic stimulus during early life affects the expression of glucose metabolism-related genes at first-feeding in trout. Sci Rep 7, 363.CrossRefGoogle Scholar
Luo, J, Li, Y, Jin, M, et al. (2020) Effects of dietary exogenous xylanase supplementation on growth performance, intestinal health, and carbohydrate metabolism of juvenile large yellow croaker, Larimichthys crocea . Fish Physiol Biochem 46, 10931110.CrossRefGoogle ScholarPubMed
CFSY (2021) China Fishery Statistical Yearbook. Beijing: China Agriculture Press.Google Scholar
Wang, X, Li, Y, Hou, C, et al. (2012) Influence of different dietary lipid sources on the growth, tissue fatty acid composition, histological changes and peroxisome proliferator-activated receptor γ gene expression in large yellow croaker (Pseudosciaena crocea R.). Aquacult Res 43, 281291.CrossRefGoogle Scholar
Li, X, Ji, R, Cui, K, et al. (2019) High percentage of dietary palm oil suppressed growth and antioxidant capacity and induced the inflammation by activation of TLR-NF-κB signaling pathway in large yellow croaker (Larimichthys crocea). Fish Shellfish Immunol 87, 600608.CrossRefGoogle ScholarPubMed
AOAC (1995) Official Methods of Analysis, 16th ed. Arlington, VA: Association of Official Analytical Chemists.Google Scholar
Zuo, R, Ai, Q, Mai, K, et al. (2013) Effects of conjugated linoleic acid on growth, non-specific immunity, antioxidant capacity, lipid deposition and related gene expression in juvenile large yellow croaker (Larmichthys crocea) fed soyabean oil-based diets. Br J Nutr 110, 12201232.CrossRefGoogle ScholarPubMed
Geurden, I, Borchert, P, Balasubramanian, MN, et al. (2013) The positive impact of the early-feeding of a plant-based diet on its future acceptance and utilisation in rainbow trout. PLoS ONE 8, E83162.CrossRefGoogle ScholarPubMed
Mai, K, Yu, H, Ma, H, et al. (2005) A histological study on the development of the digestive system of Pseudosciaena crocea larvae and juveniles. J Fish Biol 67, 10941106.CrossRefGoogle Scholar
Vagner, M, Zambonino Infante, JL, Robin, JH, et al. (2007) Is it possible to influence European sea bass (Dicentrarchus labrax) juvenile metabolism by a nutritional conditioning during larval stage? Aquaculture 267, 165174.CrossRefGoogle Scholar
Rocha, F, Dias, J, Geurden, I, et al. (2016) Dietary glucose stimulus at larval stage modifies the carbohydrate metabolic pathway in gilthead seabream (Sparus aurata) juveniles: an in vivo approach using (14)C-starch. Comp Biochem Physiol A Mol Integr Physiol 201, 189199.CrossRefGoogle Scholar
Turkmen, S, Castro, PL, Caballero, MJ, et al. (2017) Nutritional stimuli of gilthead seabream (Sparus aurata) larvae by dietary fatty acids: effects on larval performance, gene expression and neurogenesis. Aquacult Res 48, 202213.CrossRefGoogle Scholar
Fournier, V, Huelvan, C & Desbruyeres, E (2004) Incorporation of a mixture of plant feedstuffs as substitute for fish meal in diets of juvenile turbot (Psetta maxima). Aquaculture 236, 451465.CrossRefGoogle Scholar
Ali, M, Nicieza, A & Wootton, RJ (2003) Compensatory growth in fishes: a response to growth depression. Fish Fisheries 4, 147190.CrossRefGoogle Scholar
Kemski, M, Wick, M & Dabrowski, K (2018) Nutritional programming effects on growth and reproduction of broodstock and embryonic development of progeny in yellow perch (Perca flavescens) fed soybean meal-based diets. Aquaculture 497, 452461.CrossRefGoogle Scholar
Balasubramanian, MN, Panserat, S, Dupont-Nivet, M, et al. (2016) Molecular pathways associated with the nutritional programming of plant-based diet acceptance in rainbow trout following an early feeding exposure. BMC Genomics 17, 449.CrossRefGoogle ScholarPubMed
Candler, T, Kühnen, P, Prentice, AM, et al. (2019) Epigenetic regulation of POMC; implications for nutritional programming, obesity and metabolic disease. Front Neuroendocrinol 54, 100773.CrossRefGoogle ScholarPubMed
Zhu, Q, Wang, J, He, S, et al. (2020) Early leucine programming on protein utilization and mTOR signaling by DNA methylation in zebrafish (Danio rerio). Nutr Metab 17, 67.CrossRefGoogle ScholarPubMed
Xu, H, Turchini, GM, Francis, DS, et al. (2020) Are fish what they eat? A fatty acid’s perspective. Prog Lipid Res 80, 101064.CrossRefGoogle ScholarPubMed
Vagner, M, Robin, JH, Infante, JLZ, et al. (2007) Combined effects of dietary HUFA level and temperature on sea bass (Dicentrarchus labrax) larvae development. Aquaculture 266, 179190.CrossRefGoogle Scholar
Xu, H, Dong, X, Ai, Q, et al. (2014) Regulation of tissue LC-PUFA contents, Δ6 fatty acyl desaturase (FADS2) gene expression and the methylation of the putative FADS2 gene promoter by different dietary fatty acid profiles in Japanese seabass (Lateolabrax japonicus). PLoS ONE 9, E87726.CrossRefGoogle ScholarPubMed
Piedecausa, MA, Mazon, MJ, Garcia, BG, et al. (2007) Effects of total replacement of fish oil by vegetable oils in the diets of sharpsnout seabream (Diplodus puntazzo). Aquaculture 263, 211219.CrossRefGoogle Scholar
Fountoulaki, E, Vasilaki, A, Hurtado, R, et al. (2009) Fish oil substitution by vegetable oils in commercial diets for gilthead sea bream (Sparus aurata L.); effects on growth performance, flesh quality and fillet fatty acid profile recovery of fatty acid profiles by a fish oil finishing diet under fluctuating water temperatures. Aquaculture 289, 317326.CrossRefGoogle Scholar
Cai, DM, Wang, JJ, Jia, YM, et al. (2016) Gestational dietary betaine supplementation suppresses hepatic expression of lipogenic genes in neonatal piglets through epigenetic and glucocorticoid receptor-dependent mechanisms. Biochim Biophys Acta 1861, 4150.CrossRefGoogle ScholarPubMed
Heng, J, Tian, M, Zhang, W, et al. (2019) Maternal heat stress regulates the early fat deposition partly through modification of m(6)A RNA methylation in neonatal piglets. Cell Stress Chaperones 24, 635645.CrossRefGoogle ScholarPubMed
Tan, P, Dong, X, Xu, H, et al. (2017) Dietary vegetable oil suppressed non-specific immunity and liver antioxidant capacity but induced inflammatory response in Japanese sea bass (Lateolabrax japonicus). Fish Shellfish Immunol 63, 139146.CrossRefGoogle ScholarPubMed
Ji, R, Xiang, X, Li, X et al. (2020) Effects of dietary curcumin on growth, antioxidant capacity, fatty acid composition and expression of lipid metabolism-related genes of large yellow croaker fed a high-fat diet. Br J Nutr 126, 345354.CrossRefGoogle ScholarPubMed
Hyder, MA, Hasan, M & Mohieldein, AH (2013) Comparative levels of ALT, AST, ALP and GGT in liver associated diseases. Eur J Exp Biol 3, 280284.Google Scholar
Podaza, EA, Echarte, SM & Chisari, AN (2015) A low maternal protein diet during pregnancy and lactation induce liver offspring damage, in the rat. Ann Nutr Disord Ther 2, 1020.Google Scholar
Bruce, KD, Cagampang, FR, Argenton, M, et al. (2009) Maternal high-fat feeding primes steatohepatitis in adult mice offspring, involving mitochondrial dysfunction and altered lipogenesis gene expression. Hepatology 50, 17961808.CrossRefGoogle ScholarPubMed
Lesser, MP (2011) Oxidative Stress in Tropical Marine Ecosystems. Chichester: John Wiley & Sons, Ltd.CrossRefGoogle Scholar
Del Rio, D, Stewart, AJ & Pellegrini, N (2005) A review of recent studies on malondialdehyde as toxic molecule and biological marker of oxidative stress. Nutr Metab Cardiovasc Dis 15, 316328.CrossRefGoogle ScholarPubMed
Resende, AC, Emiliano, AF, Cordeiro, VS, et al. (2013) Grape skin extract protects against programmed changes in the adult rat offspring caused by maternal high-fat diet during lactation. J Nutr Biochem 24, 21192126.CrossRefGoogle ScholarPubMed
Vanhees, K, van Schooten, FJ, van Doorn-Khosrovani, SBV, et al. (2013) Intrauterine exposure to flavonoids modifies antioxidant status at adulthood and decreases oxidative stress-induced DNA damage. Free Radic Biol Med 57, 154161.CrossRefGoogle ScholarPubMed
Barden, AE, Mori, TA, Dunstan, JA, et al. (2004) Fish oil supplementation in pregnancy lowers F 2-isoprostanes in neonates at high risk of atopy. Free Radic Res 38, 233239.CrossRefGoogle Scholar
Wischhusen, P, Larroquet, L, Durand, T, et al. (2020) Oxidative stress and antioxidant response in rainbow trout fry exposed to acute hypoxia is affected by selenium nutrition of parents and during first exogenous feeding. Free Radic Biol Med 155, 99113.CrossRefGoogle ScholarPubMed
Luo, L, Wei, HC, Ai, LC, et al. (2019) Effects of early long-chain n-3HUFA programming on growth, antioxidant response and lipid metabolism of Siberian sturgeon (Acipenser baerii Brandt). Aquaculture 509, 96103.CrossRefGoogle Scholar
Vanhees, K, Vonhogen, IG, van Schooten, FJ, et al. (2014) You are what you eat, and so are your children: the impact of micronutrients on the epigenetic programming of offspring. Cell Mol Life Sci 71, 271285.CrossRefGoogle ScholarPubMed
Thompson, LP & Al-Hasan, Y (2012) Impact of oxidative stress in fetal programming. J Pregnancy 2012, 582748.CrossRefGoogle ScholarPubMed
Milagro, FI, Mansego, ML, De Miguel, C, et al. (2013) Dietary factors, epigenetic modifications and obesity outcomes: progresses and perspectives. Mol Aspects Med 34, 782812.CrossRefGoogle Scholar
Figure 0

Fig. 1. Experimental design. FO or VO dietary stimulus was applied to large yellow croaker larvae for 30 d, and then juveniles were fed the commercial diet for 90 d. Subsequently, juveniles were fed to a 30 d challenge test with a FO or VO diet.

Figure 1

Table 1. Formulation and proximate composition of the experimental diets

Figure 2

Table 2. Survival and growth rate of fish during each of the three nutritional phases(Mean values with their standard errors of the mean, n 3)

Figure 3

Fig. 2. Feed utilisation of juvenile large yellow croaker in the challenge phase. FI, feed intake; FER, feed efficiency ratio; ADCD, apparent digestibility coefficients of dry matter; ADCL, apparent digestibility coefficients of lipid. Values are means (n 3), with their standard errors represented by vertical bars. Bars bearing the same letters were not significantly different (P > 0·05, Tukey’s test).

Figure 4

Table 3. Body composition, liver and muscle lipid content in fish during each of the three nutritional phases(Mean values with their standard errors of the mean, n 3)

Figure 5

Table 4. Fatty acid composition of whole larvae in the stimulus phase†(Mean values with their standard errors of the mean, n 3)

Figure 6

Table 5. Fatty acid composition in the liver of juvenile large yellow croaker in the challenge phase*(Mean values with their standard errors of the mean, n 3)

Figure 7

Table 6. Fatty acid composition in the muscle of juvenile large yellow croaker in the challenge phase*(Mean values with their standard errors of the mean, n 3)

Figure 8

Table 7. Serum metabolite profiles of fish in the challenge phase(Mean values with their standard errors of the mean, n 3)

Figure 9

Fig. 3. Expression of lipid metabolism-related genes in the visceral mass of large yellow croaker larvae during the stimulus phase. (a) Lipid lipogenesis and lipolysis; (b) LC-FUFA synthesis and (c) lipid transport. Values are means (n 3), with their standard errors represented by vertical bars. *P < 0·05, significant differences between groups.

Figure 10

Fig. 4. Expression of lipid metabolism-related genes in the liver of large yellow croaker during the growth phase. (a) Lipid lipogenesis and lipolysis; (b) LC-FUFA synthesis and (c) lipid transport. Values are means (n 3), with their standard errors represented by vertical bars. *P < 0·05, significant differences between groups.

Figure 11

Fig. 5. Expression of lipid metabolism-related genes in the liver of large yellow croaker during the challenge phase. (a) Lipid lipogenesis and lipolysis; (b) LC-FUFA synthesis and (c) lipid transport. Values are means (n 3), with their standard errors represented by vertical bars. Bars bearing the same letters were not significantly different (P > 0·05, Tukey’s test).

Figure 12

Fig. 6. Expression of lipid lipogenesis and lipolysis-related proteins in the liver of large yellow croaker during the challenge phase. p-SREBP1c, precursor SREBP1c; m-SREBP1c, mature SREBP1c. Values are means (n 3), with their SE represented by vertical bars. Bars bearing the same letters were not significantly different (P > 0·05, Tukey’s test).

Figure 13

Fig. 7. Liver damage and antioxidant capacity-related parameters of large yellow croaker during the challenge phase. (a) Liver damage: serum ALT, AST and AKP; (b) antioxidant parameters: liver SOD, T-AOC, GSH and MDA and (c) antioxidant genes. Values are means (n 3), with their standard errors represented by vertical bars. Bars bearing the same letters were not significantly different (P > 0·05, Tukey’s test).

Supplementary material: File

Liu et al. supplementary material

Tables S1-S2

Download Liu et al. supplementary material(File)
File 24.2 KB