The metabolomics responses of Chinese mitten-hand crab (Eriocheir sinensis) to different dietary oils

The metabolomics responses of Chinese mitten-hand crab (Eriocheir sinensis) to different dietary oils

Aquaculture 479 (2017) 188–199 Contents lists available at ScienceDirect Aquaculture journal homepage: www.elsevier.com/locate/aquaculture The meta...

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Aquaculture 479 (2017) 188–199

Contents lists available at ScienceDirect

Aquaculture journal homepage: www.elsevier.com/locate/aquaculture

The metabolomics responses of Chinese mitten-hand crab (Eriocheir sinensis) to different dietary oils

MARK

Qian-Qian Maa, Qing Chena, Zhen-Hua Shena, Dong-Liang Lia, Tao Hanb, Jian-Guang Qinc, Li-Qiao Chena,⁎, Zhen-Yu Dua,⁎ a b c

Laboratory of Aquaculture Nutrition and Environmental Health (LANEH), School of Life Sciences, East China Normal University, Shanghai 200241, China Department of Aquaculture, Zhejiang Ocean University, Zhoushan 316022, China School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia

A R T I C L E I N F O

A B S T R A C T

Keywords: Eriocheir sinensis Dietary oils GC–MS Metabolomics Metabolic pathway

Nutritional values of animal diets depend on the type of oil in the feed ingredient, but the underlying metabolic mechanisms of dietary oil in animal feed have not been thoroughly studied in aquatic animals, especially in crustaceans. In the present study, we conducted assays on GC–MS-based metabolomics and nutritional parameters to investigate the metabolic mechanisms between juvenile Chinese mitten crabs (Eriocheir sinensis) fed olive oil containing 69% oleic acid (OA) and perilla oil containing 56% linolenic acid (LNA). Crab fed OA displayed faster growth, lower concentrations of hepatic glycogen, triglycerides and peroxidation products than those fed LNA. In the metabolomics assay, among 222 peaks isolated, 69 peaks were identified in serum. Among 13 significantly different metabolites between OA and LNA groups, six metabolites related to glycolysis and TCA (tricarboxylic acid) cycle (pyruvate, succinic acid, lactose, malic acid, D-glyceric acid and threitol), methionine, 2-keto-isovaleric acid (intermediate for valine and leucine synthesis) and 2-hydroxybutanoic acid (intermediate for glutathione synthesis) were higher in the OA group than in the LNA group. Only glutaconic acid (intermediate of ketogenic amino acids breakdown) was higher in the LNA group. This study indicates that crab in the OA group increased degradation of glucose and lipids to provide energy for growth as compared with crab in the LNA group. This is the first metabolomics study to identify the key pathways and crucial metabolites as biomarkers to differentiate the metabolic mechanisms of crustaceans fed contrasting dietary oils.

1. Introduction Dietary lipid supplies energy and essential fatty acids (EFA) to maintain metabolic and other physiological functions in animals (Watanabe, 1982; Willett, 1997; Arts et al., 2001; Douglas, 2003; Boglino et al., 2012; Norambuena et al., 2013; Stinkens et al., 2015; Hixson et al., 2017). The composition of fatty acids (FAs) can regulate the metabolic pathways and affect cellular physiology (Rivellese et al., 2002; Scoditti et al., 2014; Felson and Bischoffferrari, 2015). So far, nutritional evaluations of lipids and FAs on cellular metabolism have been mainly focused on terrestrial animals (Krisetherton et al., 2003; Hulbert et al., 2005; Oikari et al., 2008; Poudyal et al., 2013; Stinkens et al., 2015) and some aquatic vertebrates such as fish (González-Félix et al., 2002; Bell et al., 2003; Hu et al., 2011), which have improved diet quality and animal production. However, in aquatic invertebrates, only a few studies have addressed the effects of dietary lipids on the growth and body composition of some crustaceans, but none of these



Corresponding authors. E-mail addresses: [email protected] (L.-Q. Chen), [email protected] (Z.-Y. Du).

http://dx.doi.org/10.1016/j.aquaculture.2017.05.032 Received 8 December 2016; Received in revised form 24 May 2017; Accepted 25 May 2017 Available online 31 May 2017 0044-8486/ © 2017 Elsevier B.V. All rights reserved.

studies investigates the variation of metabolic mechanism and growth performance associated with dietary lipids (González-Félix et al., 2002; Hu et al., 2011). In recent years, metabolomics assays have been widely used in biological and medical research. As high-throughput screening technology can identify metabolites with small molecular weight that participate in biochemical and metabolic reactions in organisms (Jablonski, 2015), metabolomics analysis provides a large amount of information related to physiological and biochemical processes at cellular level (Harrigan and Goodacre, 2002). In the studies of human food and nutrition, metabolomics has been a key toolset as it establishes the target, mechanism and dietary program to personalized diet requirement and health need (Liu et al., 2015). More importantly, metabolomics analysis could provide understanding of the underlying metabolic mechanisms in farmed animals (Saleem et al., 2012; MetzlerZebeli et al., 2014; Sun et al., 2015; Sun et al., 2016). However, in nutrition research of aquatic invertebrates, the use of metabolomics

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approach is limited, resulting in poor understanding of metabolic mechanisms of nutrient utilization. Chinese mitten-handed crab, Eriocheir sinensis, is one of the most important economic crustacean species cultivated in China (Ying et al., 2006). Recently, the requirements of key nutrients including protein and lipid have been evaluated on this species (Wu et al., 2007; Lin et al., 2010; Luo et al., 2011; Sui et al., 2011; Wu et al., 2011; Jiang et al., 2013; Cai et al., 2014; Chen et al., 2014; Cui et al., 2017). The research consensus is that Chinese mitten-handed crab requires high dietary protein to maintain rapid growth (Lin et al., 2010; Jiang et al., 2013; Cui et al., 2017). However, excess dietary protein level not only increases dietary cost but also causes high nitrogen excretion to the environment (Koshio et al., 1993; Rosas et al., 1996). A number of studies have demonstrated that appropriate use of dietary lipid would efficiently provide physiological energy to spare dietary protein in animal nutrition (Steffens, 1996; Budge et al., 2011; Ljubojević et al., 2015). Therefore, there is a need to identify the appropriate sources of lipid and fatty acid supply for efficient energy production in aquatic animals. In mammalian studies, dietary oleic acid (OA) as a monounsaturated acid can be easily oxidized for energy supply and has beneficial effects to prevent cardio-vascular diseases (Becker et al., 1985; Kris-Etherton et al., 1999; Covas, 2007; Arapostathi et al., 2011; Guasch-Ferré et al., 2014). In comparison, linolenic acid (LNA) is a preferred substrate for β-oxidation to supply energy (Leyton et al., 1987; Clouet et al., 1989; Delany et al., 2000). However, the nutritional functions and the underlying metabolic mechanisms of both FAs in aquatic invertebrates have not been fully investigated. In this study, the Chinese mitten-handed crab was chosen as a representative of economically important species of crustacean to compare the underlying metabolic mechanisms of OA and LNA as a source of dietary lipid in animal nutrition. The olive oil and perilla oil respectively containing a high amount of OA and α-linolenic acid (LNA) were the main dietary lipid source in this study. At the end of the 8week feeding trial, the growth performance and biochemical composition were quantified, and the serum metabolites were identified by GC–MS-depended metabolomics assays to explicate the possible metabolic mechanisms for the lipid-dependent effect on the growth of Chinese mitten-handed crab.

Table 1 Composition of the experimental diets. Experimental diets Ingredients (g kg− 1 diet)

OA

LNA

Casein Gelatin Oil mixa Lecithin Cholesterol Corn starch Vitamin mixb Mineral mixc Attractantcd CMCe Choline chloride Cellulose Proximate composition (g kg Moisture Protein Lipid Ash

400 80 60 5 5 250 40 30 30 20 5 75

400 80 60 5 5 250 40 30 30 20 5 75

138 410 62 45

140 413 65 38

−1

)

a Oil mixture: OA represents 90% olive oil, 10% purified fish oil (34.29% DHA, 48.75% EPA); LNA represents 90% perilla seed oil, 10% purified fish oil. b Vitamin mixture (kg− 1 mixture): vitamin A, 350,000 IU; vitamin D3, 450,000 IU; vitamin E, 20 g; menadione, 7.5 g; thiamin, 10 g; riboflavin, 10 g; pyridoxamine, 12 g; cobalamin, 20 mg; nicotinamide, 40 mg; folic acid, 3 g; calcium pantothenate, 30 g; biotin, 100 mg; ascorbic acid, 60 g; inositol, 60 g (Hangzhou Minsheng Bio-Tech, Hangzhou, China). c Mineral mixture (g kg − 1 diet): NaH2PO4, 3; KH2PO4, 6.45; Ca(H2PO4)2·2H2O, 7.95; CaCO3, 3.15; calcium lactate, 4.95; MgSO4· 7H2O, 3; AlCl3·2H2O, 0.36; ZnSO4·7H2O, 0.153; ferric citrate, 0.018; MnSO4·4H2O, 0.043; KI, 0.017; CuCl2, 0.015; CoCl2 ·6H2O, 0.053; KCl, 0.84. d Attractant: (kg− 1 diet): 6 g glycine; 6 g glutamic acid; 6 g alanine; 12 g betaine. e CMC: carboxymethylcellulose sodium.

Table 2 Fatty acids (FA) composition of olive oil and perilla oil.

2. Materials and methods 2.1. Diets In order to avoid the influences of other fatty acids which are included in natural ingredients, we made two isolipidic and isonitrogenous purified diets to test the role of lipid type in crab metabolism. The mixtures of refined fish oil and olive oil (1:9) or refined fish oil and perilla oil (1:9) were used as the dietary lipid sources at 6% in the both diets. The ingredients of the two diets are shown in Table 1. All the dry ingredients were thoroughly mixed in a Hobart-type mixer. Lipid and water were finally added. Cold-extruded pellets (1-mm diameter) were produced and air-dried, sealed in vacuum-packed bags and frozen at − 20 °C prior to use. The proximate FA compositions of the two experimental diets are shown in Table 2. A generally similar concentration of n-3 HUFA and n-6 HUFA fatty acids was found both in OA and in LNA treatments. The percentage of oleic acid (C18:1n-9) in the OA group was nearly four times more than that in the LNA group (69.6% vs 13.8%), while linolenic acid (C18:3n-3) in the LNA group was nearly 70 times more than that in the OA group (56.3% vs 0.79%).

Fatty acid(%)

Olive oil

Perilla oil

C16:0 C16:1 C18:0 C18:1n9c C18:2n6c C20:0 C20:1n9 C18:3n3 C20:4n6 C20:5n3 C22:5n3 C22:6n3

12.829 0.544 3.132 69.631 6.085 0.316 0.212 0.795 0.863 2.912 0.236 1.885

6.635 0.171 2.079 13.849 14.520 0.093 0.090 56.252 0.178 3.158 0.255 2.013

2 weeks prior to the formal feeding trial. After acclimation, healthy crabs with similar body weight (5.924 ± 0.083 g) were randomly divided into two dietary groups with 6 tanks per group (30 crabs per tank). The experiment lasted 8 weeks. During the trial, the crabs were fed to apparent satiation twice daily at 09:00 and 17:00 h respectively. Continuous aeration was provided to each tank, and the value of temperature, pH, ammonia nitrite and dissolved oxygen was 28 ± 3 °C, 7.6–7.8, ≤ 0.05 mg/l, and ≥ 7.7 mg/l, respectively. To avoid variation due to circadian rhythms, at the end of the feeding trial, crabs in each tank were individually weighed and calculated for growth performance parameters after fasting overnight. The following parameters were used for evaluating growth performance:

2.2. Animals and feeding trial

Survival = Nt × 100 N0

Juvenile Chinese mitten crabs were obtained from the commercial crab hatchery (Chongming Island, Shanghai, China) and distributed into 300-L white rectangle plastic tanks. Crabs were acclimatized by feeding a commercial diet (9812, Shanghai Harmony Feed Co., Ltd.) for

Weight gain = 100 × (Wt − W0) W0 where, Wt and W0 were the final and initial crab weight respectively; Nt and N0 were the final and initial crab number in each tank respectively; 189

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flow rate through the column was 20 ml/min. The initial temperature of the column was kept at 50 °C for 1 min, then increased to 330 °C at a rate of 10 °C min− 1, and remained at 330 °C for 5 min. The injection, transfer line, and ion source temperatures were 280, 280, and 220 °C respectively. The energy was − 70 eV in the electron impact mode. The mass spectrometry data were acquired in full-scan mode with a mass-tocharge ratio (m/z) range of 85–600 at a rate of 20 spectra per second after a solvent delay of 366 s.

t is the experimental duration in days. In the sampling, six crabs in each tank with similar weights, which were close to the average body weight of the crabs in the corresponding tank, were selected. Hemolymph and hepatopancreas from these crabs were collected from the third pereiopod and then mixed as pooled hemolymph or hepatopancrea sample, respectively. The pooled serum samples for blood lipid and metabolomics measurements were prepared from six pooled hemolymph samples (n = 6) by centrifuging at 2800 × g for 20 min at 4 °C. The pooled hepatopancrea samples were also collected for the biochemical assays (n = 6). All samples were stored at − 80 °C prior to analysis. All experiments were conducted under the Guidance of the Care and Use of Laboratory Animals in China. This research was approved by the Committee on the Ethics of Animal Experiments of East China Normal University.

2.6. Data analysis Chroma TOF 4.3X software (LECO Corporation, USA) and LECOFiehn Rtx5 Metabolomics Library were used for raw peaks extracting. The data baselines filtering and calibration, peak alignment, deconvolution analysis, peak identification and integration of the peak area were performed as previously described (Kind et al., 2009). The missing values of the original data were filled up by half of the minimum value through the interquartile range denoising method. For the depth analysis of following data, filtering data through an interquartile range noise removal was conducted. Then, the filtered data were standardized by internal standard normalization methods. The similarity value for evaluating of the accuracy of the discriminating compound identification was obtained from the LECO/Fiehn Metabolomics Library to identify the compounds. If the similarity is > 700, it indicates that the metabolite identification is reliable. It is defined as an “analyte” if its similarity was < 200. A compound with a similarity between 200 and 700 was considered a putative annotation. The retention time index (RI) method was used for peak identification, and the RI tolerance was 5000. The normalized data were imported into SIMCA-P+ 13.0 software package (Umetrics, Umea, Sweden) which was used for multivariate statistical calculation. All variables were scaled with unit variance (UV) prior to principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). PCA was used to observe clustering trends simultaneously to identify and exclude outliers in the data. PLS-DA was used for building a discriminant model. Model validity and potential over-fitting of the PLS-DA model were checked by performing 200 permutation tests and visualized using a validation plot. The R2 value, including R2X and R2Y, was recorded to describe the goodness of fit. It ranged between 0 and 1 with the value of 1 indicating a model of perfect fit. The predictive ability was indicated by Q2. Differential metabolites were extracted according to their variable importance in the projection (VIP) values in the PLS-DA model. To generate a list of potential discriminant metabolites, the VIP cut-off value was set at 1.00. The Student's t-test was then used to compare means of these potential discriminant metabolites between the two serum groups at P ≤ 0.05. Then the same data were converted into orthogonal partial least squares discriminant analysis (OPLS-DA) for better identification and interpretation of discriminant metabolites between OA and LNA serum samples. The fold change (FC) value of each metabolite was calculated by comparing mean value of peak area obtained from the OA group to that from the LNA group. Furthermore, online databases, including National Institute of Standards and Technology (NIST) (http://www.nist.gov/index.html), Chemical Entities of Biological Interest (ChEBI) (http://www.ebi.ac.uk/ chebi/init.do) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (http://www.genome.jp/kegg/) were used for metabolite identification, biological role explanation and pathway construction. The KEGG pathway analysis of different metabolites (SDMs) was performed by Metabo Analyst 3.0 (http://www.metaboanalyst.ca/MetaboAnalyst/). For the growth and biochemical data, results are expressed as mean ± SEM. Significant differences (P < 0.05) of each variable were firstly detected using the one-way ANOVA test, followed by t-test. All analyses were conducted using the IBM SPSS Statistics 21 (IBM, USA).

2.3. Biochemical measurements Commercial kits (Jiancheng Co., Nanjing, China) were used to measure serum concentrations of glucose (Kit number F006), total cholesterol (TC, Kit number F002-1), total triglycerides (TG, Kit number F001-1), free fatty acid (FFA, Kit number A042–1), LDL-C (Kit number A113-1), and HDL-C (Kit number F003-1) using spectrophotometer methods according to the manufacturers' protocols. The concentrations of glycogen (Gn, Kit number A043), TG and methane dicarboxylic aldehyde (MDA, Kit number A003-1) and the activities of SOD (Kit number A001-1) in hapatopancreas were measured using the same kits as described above. 2.4. Preparation of serum for metabolomics Serum has been widely used in metabolism studies to evaluate the systemic metabolism status in a whole organism (Psychogios et al., 2011), therefore, we used serum for metabolic assay in the present study. GC–MS analysis was used for quantifying the concentration of metabolites in Eriocheir sinensis serum samples. Serum metabolites were prepared as previously described with modification (Qiu et al., 2009; Chen et al., 2011). Firstly, serum samples were thawed to room temperature. Serum (200 μl) from three individuals was transferred into a 1.5-ml Eppendorf tube, and 350 μl of 75% methanol and 30 μl of L-2chlorophenylalanine (0.1 mg/ml stock in dH2O, Hengbai Biotech Co Ltd., Shanghai, China) as an internal quantitative standard were added and vortexed for 10 s. The mixture was subsequently centrifuged at 4 °C, 12,000 rpm for 15 min and 0.4 ml supernatant fraction was transferred into a fresh 2 ml GC–MS glass silylated vial and the supernatants were lyophilized in vacuo. Pyridine was dissolved into methoxyamination reagent (60 μl) to reach a final concentration of 20 mg/ ml, and the solution was incubated at 37 °C for 2 h. Subsequently, 80 μl of bis-(trimethylsilyl)-trifluoroacetamide (BSTFA) reagent (containing 1% TCMS, v/v, REGIS Technologies, Morton Grove, IL, USA) was added, followed by incubation at 70 °C for 1 h. When the liquid temperatures reduced close to the room temperature, 10 μl FAMEs (standard mixture of fatty acid methyl esters, C8-C16:1 mg/ml; C18C30:0.5 mg/ml in chloroform) was added to the sample aliquots. Each sample aliquot was prepared prior to GC–MS analysis. 2.5. GC–MS analysis The GC–MS was performed using an Agilent 7890 GC gas chromatograph system (Agilent 7890A, Agilent, USA) equipped with a Pegasus HT time-of-flight mass spectrometer (LECO Chroma TOF PEGASUS HT, LECO, USA). The system was installed with a DB-5MS capillary column (30 m × 250 μm inner diameter, 0.25 μm film thickness; J & W Scientific, Folsom, CA, USA) coated with 95% dimethyl polysiloxane cross-linked with 5% diphenyl. The injection of a 1-μl aliquot derivatized sample was run in a splitless mode, with helium as the carrier gas. The front inlet purge flow was 3 ml per minute, and the constant gas 190

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A

B

C

D

E

F

Fig. 1. Effects of dietary OA and LNA on survival rate, growth rate, biochemical composition and activity of enzyme in the hepatopancreas of juvenile crab Eriocheir sinensis (P < 0.05). No significant difference was found in weight gain and survival rate (A, B). The glycogen (Gn) and TG concentrations in the hepatopancreas of the crabs fed the OA diet were significantly lower than those fed the LNA diet(C, D). The activities of SOD in hepatopancreas were similar, and the concentration of MDA in the hepatopancreas of the LNA group was significantly higher than the OA group (E, F).

3. Results

group was significantly higher than the OA group. The serum FFA concentration in the OA group was lower than in the LNA group, but no significant differences were found in all other parameters (Fig. 2).

3.1. Growth, survival rate and biochemical parameters in hepatopancreas and serum

3.2. Metabolite identification and comparison No significant difference was found in weight gain and survival rate (Fig. 1) while crab in the OA group trended to show better growth performance than in the LNA group (P = 0.072). The glycogen (Gn) and TG concentrations in the hepatopancreas of the crabs fed the OA diet were significantly lower than those fed the LNA diet. Although the activities of SOD in hepatopancreas were similar, the concentration of MDA, a marker of oxidative stress, in the hepatopancreas of the LNA

In total, 303 valid peaks were identified in the serum. A clear discrimination in the abundance of typical peaks highlighted by red arrows was observed between the OA and LNA groups (Fig. 3A). Thus, these TIC chromatograms could directly reflect the difference in metabolite profiles between the serums of two groups. There remained 222 peaks after filtering and denoising. Referring to the LECO-Fiehn Rtx5 191

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A

B

C

D

E

F

Fig. 2. Effects of dietary OA and LNA on serum glucose, FFA and lipid levels of juvenile crab Eriocheir sinensis (P < 0.05). The serum FFA concentration in the OA group was lower than in the LNA group (B), but no significant differences were found in all other parameters (A, CeF).

isovaleric acid (an intermediate for valine and leucine synthesis) and 2hydroxybutanoic acid (an intermediate for glutathione synthesis) were higher in OA than in the LNA group. Only glutaconic acid (an intermediate of ketogenic amino acids breakdown) was higher in LNA group.

Metabolomics Library, most peaks were endogenous metabolites, and a few of these peaks might belong to the derivatives of byproducts. There were altogether 153 metabolites quantified including 39 analytes (similarity > 0). There were 69 metabolites identified by mass spectrum matching with a spectral similarity > 700 (Table 3). The fold-change (FC) value was used to indicate the specific variable quantity in the OA diet compared with the LNA diet. The distribution of metabolites could be visually divided into up-regulation and down-regulation. Among the 69 metabolites, 41 metabolites were up-regulated in the OA group compared to the LNA group, including metabolites such as oxalic acid, fumaric acid, succinic acid and L-Malic acid, all of which participated in energy metabolism in the TCA cycle (Table 3). Furthermore, among all these metabolites, 13 metabolites were significantly different (VIP > 1 and P < 0.05) between OA and LNA groups. Among these 13 metabolites, 11 metabolites owned similarity > 700 and 1 metabolite owned similarity 684 (Table 4). Among them, six metabolites (pyruvate, succinic acid, lactose, malic acid, D-glyceric acid and threitol) linked to carbohydrate and TCA metabolism, methionine, 2-keto-

3.3. Principal component analysis (PCA) The PCA analysis of GC-TOF/MS metabolic profiles of serum showed significantly separated clusters between the OA and LNA groups in 3D-PCA score plot (Fig. 3B). The R2X value of the PCA model representing the explained variance in serum was 0.489. None of the samples from both groups fell outside the Hotelling's T2 tolerance ellipse that denotes 95% confidence limit of the model, indicating that no outlier was present among the samples analyzed. The validation plot for PLS-DA model clearly reveals that the permutation tests of the serum were valid with the R2Y value that was 0.874 and the corresponding Q2 value was 0.504 (Fig. 3C), indicating satisfactory effectiveness of the 192

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Fig. 3. Characterization of GC–MS data. A. GC/MS TICs of crab serum samples from the OA group (OA-18 samples) and LNA group (LNA-18 samples). The ordinate shows the relative mass abundance and the abscissa shows the retention time. B. 3D-PCA analysis of GC–MS metabolite profiles. R2X [1] = 0.326, R2X [2] = 0.164, Ellipse: Hotelling's T2 (95%). C. Permutation tests of the serum. R2: green circle; Q2: blue square. The green line represents the regression line for R2 and the blue line for Q2. The intercept: R2 = 0.813, Q2 = 0.129. D. OPLS-DA score plots for pair-wise comparisons between OA and LNA group. R2X [1] = 0.17, R2X [2] = 0.281, Ellipse: Hotelling's T2 (95%). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

A

B

C

D

and phenylalanine metabolism. Compared to the LNA group, the OA group had higher contents of pyruvate, 2-hydroxybutanoic acid, succinic acid, L-malic acid, methionine, D-glyceric acid, lactic acid, lactose, 4-hydroxybutyrate, 3-hydroxypropionic acid, 2-keto-isovaleric, 2-hydroxypyridine, threitol, 6-deoxy-D-glucose and tagatose, while the content of glutaconic acid was down-regulated (Fig. 5, Table 3).

model. The score plots of OPLS-DA model showed that all the samples between the two groups were within the 95% Hotelling T2 ellipse (Fig. 3D). 3.4. KEGG pathway analysis Furthermore, the KEGG pathway analysis of different metabolites (SDMs) was performed by Metabo Analyst 3.0. Functional pathway analysis facilitating further biological interpretation revealed the most relevant pathways such as propanoate metabolism, glyoxylate and dicarboxylate metabolism, galactose metabolism, butanoate metabolism, citrate cycle (TCA cycle), glycolysis or gluconeogenesis, pantothenate and CoA biosynthesis, pentose and glucuronate interconversions, pyruvate metabolism, valine, leucine and isoleucine biosynthesis (Fig. 4, Table 5). The integrated key metabolic pathways were manually linked together based on the results of common key different metabolic pathways and the significantly changed pathways from different metabolites in serum. Three key metabolic pathways were identified including citrate cycle (TCA cycle), glycolysis, propanoate metabolism (Fig. 5). The map illustrates significantly different metabolites in serum and key metabolic pathways including glycolysis/gluconeogenesis, citrate cycle (TCA cycle), propanoate metabolism, tyrosine metabolism

4. Discussion Apart from providing essential fatty acids (Suprayudi et al., 2004), dietary lipid is a major source of energy supply in the diet (Xu and Nan, 1998; Ying et al., 2006). Lipid oxidation capacity is enhanced during starvation (Torstensen et al., 2012), cold acclimatization (Cordiner and Egginton, 1997; Thibault et al., 1997) and reproduction (Xiao et al., 2002) and the increase of lipid in feed may spare dietary protein leaving more protein to support animal growth and development (Mourente et al., 1994; Karalazos et al., 2011; Mozanzadeh et al., 2016). Several studies suggest that there is a substrate preference for saturated and monounsaturated fatty acids over PUFAs in β-oxidation in fish (Kiessling and Kiessling, 1993; Sidell et al., 1995; Henderson, 1996; Stubhaug et al., 2005). As the sustainable alternatives to fish oil, partial or total replacement of fish oil by vegetable oils may not 193

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Table 3 Identification of metabolites with similarity > 700 in serum between the OA and LNA groups. Peak

Similarity

Mass

MEAN-OA

MEAN-LNA

FCa

Levelb

Maleimide N-Acetyl-D-galactosamine Lysine Tyrosine Asparagine 3-Cyanoalanine Citrulline L-Allothreonine Isoleucine Dihydroxyacetone Cycloleucine Maltose Leucine Phenylalanine Oxoproline Ribonic acid, gamma-lactone Stearic acid Serine Oleic acid Ethanolamine Proline Trans-4-hydroxy-L-proline Pyrrole-2-carboxylic acid Valine Methylmalonic acid Threonine D-Talose Ornithine Uric acid Sophorose Glycine Palmitic acid beta-Alanine alpha-Ketoisocaproic acid 1 Conduritol B epoxide Uracil Noradrenaline Methionine sulfoxide Myo-inositol Aminomalonic acid Hydroxylamine Threonic acid D-Arabitol beta-Mannosylglycerate Fucose Methionine Ribose 4-Aminobutyric acid 2-Hydroxypyridine Glucose-1-phosphate Putrescine N-Methyl-DL-alanine Isomaltose D-Glyceric acid Sulfuric acid Threitol Pyruvic acid Urea 3-Hydroxypropionic acid 6-Deoxy-D-glucose Fumaric acid Fructose L-Malic acid Oxalic acid Sorbose Lactose Glycerol 2-Hydroxybutanoic acid Succinic acid

700 945 890 800 885 762 910 962 958 771 734 975 912 948 862 774 838 943 875 972 975 946 745 964 738 925 910 911 787 890 993 943 971 721 710 957 898 714 961 852 950 946 819 919 918 942 939 732 865 738 849 953 890 927 752 787 909 744 905 778 824 753 957 758 930 775 892 981 939

154 87 174 218 100 141 157 117 158 103 156 204 158 218 156 218 117 204 117 174 142 230 240 144 231 117 319 142 87 103 102 117 86 89 217 99 174 128 217 218 146 147 217 147 117 176 103 174 152 217 174 130 204 147 147 103 174 171 177 117 245 103 147 147 103 204 117 131 147

0.0015 0.0098 0.0250 0.0068 0.0030 0.0060 0.0065 0.1065 0.0862 0.0157 0.0005 0.2750 0.1660 0.0275 0.0282 0.0005 0.0029 0.1591 0.0024 0.0367 4.0854 0.0213 0.0009 0.2563 0.0014 0.0113 1.6196 0.0092 0.0019 0.0043 0.0587 0.0148 0.0818 0.0014 0.0114 0.1070 0.0041 0.0030 0.0517 0.0042 0.0160 0.0072 0.0048 0.0155 0.0165 0.1178 0.5096 0.0029 0.1240 0.0610 0.0038 0.0332 0.0024 0.0048 0.0871 0.0028 0.1222 0.5577 0.0026 0.0150 0.0070 0.0169 0.0634 0.0138 0.0314 0.0039 0.6501 0.2064 0.1539

0.0017 0.1177 0.0636 0.0125 0.0053 0.0096 0.0100 0.1524 0.1223 0.0221 0.0007 0.3584 0.2103 0.0336 0.0340 0.0006 0.0034 0.1863 0.0029 0.0424 4.6550 0.0232 0.0010 0.2702 0.0015 0.0117 1.6417 0.0092 0.0019 0.0043 0.0561 0.0136 0.0750 0.0013 0.0104 0.0963 0.0037 0.0027 0.0456 0.0037 0.0141 0.0062 0.0038 0.0122 0.0127 0.0894 0.3807 0.0022 0.0916 0.0435 0.0027 0.0231 0.0016 0.0031 0.0529 0.0016 0.0721 0.3208 0.0013 0.0072 0.0034 0.0073 0.0268 0.0056 0.0113 0.0014 0.1968 0.0528 0.0379

0.925 0.084 0.394 0.548 0.566 0.625 0.654 0.699 0.705 0.710 0.754 0.767 0.790 0.818 0.829 0.840 0.852 0.854 0.855 0.866 0.878 0.918 0.927 0.949 0.951 0.960 0.987 0.998 1.008 1.014 1.046 1.088 1.090 1.093 1.101 1.112 1.114 1.130 1.132 1.135 1.136 1.155 1.264 1.269 1.297 1.319 1.338 1.350 1.354 1.403 1.425 1.435 1.500 1.540 1.648 1.692 1.696 1.738 2.067 2.076 2.091 2.318 2.368 2.449 2.776 2.846 3.303 3.905 4.062

Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Down Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up

a FC = fold change, mean value of peak area obtained from OA group/mean value of peak area obtained from LNA group. If the FC value is > 1, it means that metabolites in OA are more than in LNA. b Up: an increased in OA group, down: a decrease in OA group.

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Table 4 Identification of significantly different metabolites in serum between the OA and LNA groups. Metabolite name

Similarity

RTa

VIP

P value

FCb

Biological role

2-Keto-isovaleric acid Lactose 6-Deoxy-D-glucose Threitol 2-Hydroxypyridine 3-Hydroxypropionic acid Pyruvic acid D-Glyceric acid Succinic acid Methionine L-Malic acid 2-Hydroxybutanoic acid Glutaconic acid

644 775 778 787 865 905 909 927 939 942 957 981 301

8.04 24.74 15.88 13.34 7.04 8.55 7.19 11.13 10.93 13.6 13.19 8.3 12.6355

1.623 1.672 1.685 1.647 1.592 1.656 1.767 1.612 1.715 1.642 1.708 2.204 1.89493

0.038 0.048 0.033 0.035 0.041 0.036 0.021 0.044 0.045 0.035 0.043 0.004 0.014768

1.842 2.846 2.076 1.692 1.354 2.067 1.696 1.54 4.062 1.319 2.368 3.905 0.30184

A metabolite of valine and leucine An intermediate compound in the metabolism of carbohydrates – A main end product of D-xylose metabolism – A carboxylic acid An intermediate compound in the metabolism of carbohydrates, proteins, and fats A substrate in glycolysis and fructose breakdown A component of the TCA cycle An intermediate in transmethylation reactions and protein synthesis An intermediate of the TCA cycle A product in glutathione synthesis An intermediate of ketogenic amino acids breakdown

a

RT = retention time. FC = fold change, mean value of peak area obtained from OA group/mean value of peak area obtained from LNA group. If the FC value is > 1, it means that metabolites in OA are more than in LNA. b

compromise growth and survival of fish or crustacean (Richard et al., 2006; Morais et al., 2012; Renjie et al., 2012). However, utilization of lipid in aquatic animals depends on oil sources. Senadheera et al. (2011) reported that Murray cod has a preferential order of accumulation for oleic acid (OA; 18:1n-9) over linolenic acid (LNA; 18:3n-3) (Senadheera et al., 2011), indicating that it has a low preference of oleic acid for energy production. This is in contrast with other research in fish where n-9 fatty acids are more easily oxidized than n-3 fatty acids (Stubhaug et al., 2005; Stubhaug et al., 2006). The canola oil diet containing oleic acid can be efficiently oxidized and utilized for ATP synthesis and energy supply in fish tissues (Karalazos et al., 2011; Mozanzadeh et al., 2016). Similarly, rainbow trout has a higher uptake rate of oleic acid compared to linolenic acid (Oxley et al., 2006). In crustaceans, some studies indicated that linseed oil could bring better growth and feed efficiency than peanut oil in Pacific white shrimp (González-Félix et al., 2002), while the growth of Chinese mitten-hand crab would be improved by rapeseed oil rather than linseed oil (Chen et al., 2014). The essential fatty acids of Chinese mitten-hand crabs had

been identified as DHA (22:6n-3) and EPA (20:5n-3), and the requirements were 0.53% and 0.28%, respectively (Cheng et al., 1998; Chen et al., 2000; Xiao, 2001). In the present study, because of the existence of fish oil (10% of the mixed oil added) in the diets, the requirement of DHA and EPA should be satisfied. However, it is pity that the utilizing preference of different fatty acids has not been studied in crustaceans, and this was one of the purposes in the present study. In the current study, the crabs fed the OA diet gained better growth trend and lower hepatic glycogen than the LNA diet. There are a few reports on the effects of dietary lipid source on carbohydrate metabolism (Castro et al., 2015) in aquatic animals. In mammals, the activity of glucose-6-phosphate dehydrogenase (G6PD) that controls the first step and regulates the pentose phosphate pathway (Hodge and Salati, 1997) is inhibited by dietary polyunsaturated fats while monounsaturated fatty acids such as oleate (18:1) do not inhibit G6PD activity (Clarke et al., 1976; Stabile et al., 1998; Salati and Amir-Ahmady, 2001). This suggests that the high amount of LNA as a PUFA in the LNA diet can lower G6PD activity and inhibit pentose phosphate pathway, Fig. 4. The metabolome view map of significant metabolic pathways characterized in serum for crabs fed OA and LNA. This figure illustrates significantly changed pathways based on enrichment and topology analysis. The x-axis represents pathway enrichment, and the y-axis represents pathway impact. Larger sizes and darker colors represent greater pathway enrichment and higher pathway impact values, respectively.

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suggest that Chinese mitten crab prefers to use oleic acid as an energy source rather than use LNA, and this can cause more lipid accumulation and higher lipid peroxidation in the LNA group. In order to further determine the metabolic characteristics of the Chinese mitten crab fed OA and LNA diets, metabolomics assay was performed in the present study. Metabolomics has been used widely to investigate metabolites in fluids or tissues and intensively explains the underlying metabolic mechanisms. MS-based metabolomics is more sensitive in detecting low-abundance metabolites compared to NMR platform (Scano et al., 2014; Tredwell et al., 2014), and it also permits separation of structurally similar compounds that are difficult to separate by LC (Jiang et al., 2010). Therefore, MS-based metabolomics, including GC/MS and LC/MS, has been widely applied in biological sample analysis (Metzler-Zebeli et al., 2014; Sun et al., 2015). In the present study, we chose GC-TOF/MS based on metabolomics to identify and compare the metabolites in serum from the crabs fed two diets containing different lipid sources. In our study, 222 peaks were detected, but the number of metabolites detected by GC/MS in plasma varies among animal taxa in other studies (Psychogios et al., 2011; Kodama et al., 2014; Zaitsu et al., 2014; Sun et al., 2015). There are 53 metabolites from the serum of tiger puffer fish Takifugu rubripes (Kodama et al., 2014) and 218 metabolites in the serum of cow (Sun et al., 2015). Among 21 significantly different metabolites between two dietary groups, only 11 metabolites (52.4%) have the similarity > 700 (Sun et al., 2015). Although the metabolites in the blood sample are secreted, excreted or discarded from different animal tissues in response to physiological need or stress (Psychogios et al., 2011), and most clinical tests are based on the analysis of blood plasma or serum (Grant and Butt, 1970; Gobbi et al., 1985; Lee et al., 2016), the number of metabolites detected by GC/MS in animal tissues is usually more than those in serum. For example, Xu et al. (2016) identified 565 peaks from the Coilia nasus ovary tissue, but only 72 metabolites (12.7%) shared a similarity > 700 (Xu et al., 2016). In the present study, we detected 222 peaks, but 69 (31.1%) of them had a similarity > 700. Of 13

Table 5 Metabolic pathways identified from the significantly different metabolites (SDMs) from the serum between OA and LNA groups. Metabolic pathway

SDM

Propanoate metabolism

(3.905) (4.062) (2.067) (1.354) (2.368) (4.062) (1.504) (1.696) (2.846) (4.062) (1.696) (2.368) (4.062) (1.696) (1.696) (1.842) (1.696) (1.504) (1.696) (2.368) (1.696) (1.842) (1.696)

Glyoxylate and dicarboxylate metabolism

Galactose metabolism Butanoate metabolism Citrate cycle (TCA cycle)

Glycolysis or gluconeogenesis Pantothenate and CoA biosynthesis Pentose and glucuronate interconversions Pyruvate metabolism Valine, leucine and isoleucine biosynthesis

a

2-Hydroxybutanoic acida, Succinic acid, 3-Hydroxypropionic acid, 2-Hydroxypyridine L-Malic acid, Succinic acid, D-Glyceric acid, Pyruvic acid Lactose Succinic acid, Pyruvic acid L-Malic acid, Succinic acid, Pyruvic acid Pyruvic acid 2-Keto-isovaleric acid, Pyruvic acid D-Glyceric acid, Pyruvic acid L-malic acid, Pyruvic acid 2-Keto-isovaleric acid, Pyruvic acid

The number in parentheses is the value of fold change (OA/LNA).

and thus decrease the utilization of carbohydrate in crab. Conversely, the efficiency of pentose phosphate pathway was not affected by the OA diet. Likewise, the hepatic glycogen concentration in the LNA group was significantly higher than that in the OA group. We also observed that the concentrations of serum FFA and hepatic TG in the LNA group were significantly higher than those in the OA group. In addition, MDA as a lipid peroxidation product in the hepatopancreas of crab fed LNA was significantly increased compared to crab in the OA group. These

Fig. 5. Main Kyoto Encyclopedia of Genes and Genomes pathways.

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these energy-release pathways. These results further reiterate that the activity of energy metabolism for the crabs in the OA group was higher than that in the LNA group. To the best of our knowledge, this study is the first metabolomics study to identify the key pathways and crucial metabolites as biomarkers differentiating the metabolic responses of crustaceans to different dietary lipid sources. However, we should also point out that only several significantly different metabolites in some given pathways actually could not indicate the global metabolic changes caused by different dietary FAs, therefore, more intensive investigations towards these pathways should be performed in future studies. Nevertheless, the metabolomics study could at least provide possible directions for future metabolism studies.

significantly different metabolites between OA and LNA groups, 11 components (84.6%) showed similarity > 700. The number of metabolites in our study is more than those detected in the plasma of crucian carp (Guo et al., 2014), the ovary tissue of Coilia nasus (Xu et al., 2016), and the serum of cow (Sun et al., 2015) and tiger puffer fish (Kodama et al., 2014). The present study also indicated that the metabolic pathways identified from the significantly different metabolites (SDMs) from crab serum between the OA and LNA groups are in line with classic metabolism and represent the typical characteristics of the dietary or medical intervention on organisms (Rocha et al., 2011; Sun et al., 2015). Metabolomics analyses show that 69 metabolites had similarity > 700, and the concentrations of 41 metabolites were higher in the OA group than in LNA group. Moreover, even among the 13 significantly different metabolites, 12 were higher in OA group than in LNA group except glutaconic acid (Table 4). Most of the metabolites identified with significant difference between two lipid groups participated in energy metabolism, especially in glucose metabolism (pyruvate, succinic acid, lactose, malic acid, D-glyceric acid and threitol). The metabolite with the largest difference between two groups was succinic acid (4.06 fold higher in OA group than in LNA group), which is an important intermediate in TCA cycle. The elevated concentrations of pyruvate and lactate, which are the products of glycolysis, implying the increase of glucose utilization (Rocha et al., 2011). As another biochemical evidence, the amount of hepatic glycogen was also lower in the OA group than in the LNA group. Therefore, the OA group is more likely to have higher activity in carbohydrate metabolism than the LNA group. Except for the metabolites relating to glucose metabolism, we also found higher methionine, 2-keto-isovaleric acid and lower glutaconic acid in the OA group than in the LNA group. As methionine and 2-keto-isovaleric acid are the essential amino acid and metabolite for protein synthesis, and glutaconic acid is an intermediate in the breakdown of some ketogenic amino acids such as L-lysine (Sauer et al., 2015), the metabolomics data suggest that the protein synthesis was probably enhanced and the protein degradation was likely to be lowered in the OA group than in the LNA group. This could partly explain the faster growth trend of crab in the OA group than in the LNA group. In biochemical assay, higher concentrations of hepatic TG and serum FFA were found in the LNA group than in the OA group. In many mammalian lipid metabolism studies, increased lipid contents in tissues and blood are always accompanied with the impaired/decreased lipid catabolism capability (Du et al., 2013; Lei et al., 2016). The similar phenomenon is also observed in Nile tilapia (Ning et al., 2016). Although the intensive lipid metabolism study has not been carried out in crustaceans, it could suggest that lipid catabolism was lowered in the LNA group than in the OA group. Getting together, compared to the OA group, the crabs in the LNA group had lower ability to utilize glucose and lipid and relied more on amino acids for energy supply, causing accumulation of glycogen and lipid in liver and relatively lower growth. Of note, crab in the OA group also had higher 2-hydroxybutanoic acid, which is correlated to the synthesis of glutathione, a well-known antioxidative factor. This could explain why crab in the OA group had lower serum MDA than in the LNA group, indicating that crab in the OA group had lower oxidative stress than in the LNA group. The difference in serum MDA could also be related to the lower hepatic lipid content in the OA group than in the LNA group, because high lipid accumulation would also induce oxidative stress (Du et al., 2008). In order to clearly demonstrate the metabolic response of Chinese mitten crab to OA and LNA diets, the significantly different metabolites are combined with the corresponding metabolic pathways and the comprehensive pathways in data analysis are shown in Table 5, Figs. 4 and 5. According to metabolic pathway analysis, ten important pathways present distinct difference between the two groups. Citrate cycle (TCA cycle), pyruvate metabolism, propanoate metabolism and pentose phosphate pathway are the key different metabolic pathways involved in energy supply, and the values of the OA group were all elevated in

5. Conclusions Oleic acid and linolenic acid are both regarded as good substrates for energy supply in mammals. However, in the Chinese mitten crab, the OA diet resulted higher growth, and lower concentrations of hepatic glycogen, TG and MDA than the LNA diet. By analyzing a number of metabolites in energy metabolism pathways using GS/MS-based metabolomics assay, we found that OA increased the degradation of glucose and lipids to provide energy and caused a “protein sparing effect” to promote protein synthesis as compared with the LNA diet. For the first time, we used metabolomics analysis to elucidate the relationship between nutritional characteristics and lipid sources in crustacean, which may be applicable to nutrition research in other animals. Disclosures No conflicts of interest, financial or otherwise, are declared by the authors. Author contributions Z.Y.D., L.Q.C. and Q.Q.M. designed the research. Q.Q.M., Q.C. and Z.H.S., conducted the research. Q.Q.M., D.L.L. and T.H. analyzed data. Q.Q.M., Z.Y.D., J.G.Q. and L.Q.C. contributed to the final writing of the paper. Q.Q.M. and Z.Y.D. wrote the manuscript. All authors have read and approved the final manuscript. Acknowledgment This research was supported by grants from the Special Fund for Agro-scientific Research in the Public Interest (No. 201203065), National ‘Twelfth Five-Year’ Plan for Science & Technology Support (2012BAD25B03), the National Natural Science Foundation of China (No. 31572629) and Shanghai Technology System for Chinese Mittenhanded Crab Industry. References Arapostathi, C., Tzanetakou, I.P., Kokkinos, A.D., Tentolouris, N.K., Vlachos, I.S., Donta, I.A., Perrea, K.N., Perrea, D.N., Katsilambros, N.L., 2011. A diet rich in monounsaturated fatty acids improves the lipid profile of mice previously on a diet rich in saturated fatty acids. Angiology 62, 636–640. Arts, M.T., Ackman, R.G., Holub, B.J., 2001. “Essential fatty acids” in aquatic ecosystems: a crucial link between. Can. J. Fish. Aquat. Sci. 58, 122–137. Becker, W., Mohammed, A., Slanina, P., 1985. Uptake of radiolabelled α-linolenic, arachidonic and oleic acid in tissues of normal and essential fatty acid-deficient rats – an autoradiographic study. Ann. Nutr. Metab. 29, 65–75. Bell, J.G., Tocher, D.R., Henderson, R.J., Dick, J.R., Crampton, V.O., 2003. Altered fatty acid compositions in Atlantic salmon (Salmo salar) fed diets containing linseed and rapeseed oils can be partially restored by a subsequent fish oil finishing diet. J. Nutr. 133, 2793–2801. Boglino, A., Gisbert, E., Darias, M.J., Estévez, A., Andree, K.B., Sarasquete, C., OrtizDelgado, J.B., 2012. Isolipidic diets differing in their essential fatty acid profiles affect the deposition of unsaturated neutral lipids in the intestine, liver and vascular system of Senegalese sole larvae and early juveniles. Comp. Biochem. Physiol. A Mol. Integr. Physiol. 162, 59–70.

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