Article pubs.acs.org/JAFC
Metabolomic Strategy for the Detection of Metabolic Effects of Spermine Supplementation in Weaned Rats Guangmang Liu,*,†,‡ Tingting Fang,†,‡ Tao Yan,†,‡ Gang Jia,†,‡ Hua Zhao,†,‡ Zhiqing Huang,†,‡ Xiaoling Chen,†,‡ Jing Wang,§ and Bai Xue†,‡ †
Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, Sichuan, China Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Chengdu 611130, Sichuan, China § Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, Sichuan, China ‡
ABSTRACT: The purpose of this study is to examine the effects of spermine supplementation on weaned rat metabolism. A metabolomic strategy employing high-resolution 1H NMR spectroscopy and multivariate data analysis was used to investigate rat biological responses to spermine ingestion. Rats received intragastric administration of either 0.2 or 0.4 μmol/g body weight of spermine or saline for 3 days. Plasma samples taken 48 h after the last spermine ingestion were analyzed. Spermine supplementation significantly increased the plasma levels of 1-methylhistidine, 3-hydroxybutyrate, alanine, glutamate, glycerolphosphocholine, phosphorylcholine, myo-inositol, phenylalanine, lysine, glutamine, trimethylanine, tyrosine, valine, formate, glucose, and lipids. These results suggest that spermine ingestion can alter common systemic metabolic processes, including cell membrane metabolism, lipid metabolism, glucose−alanine cycle metabolism, amino acid metabolism, and gut microbiota metabolism. This study also shows the important role of spermine administration in modulating the metabolism of weaned rats. KEYWORDS: spermine, metabolism, metabolomics, weaning stress, plasma
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INTRODUCTION Weaned animals are subjected to multiple stresses such as maternal and littermate separations, abrupt changes from a diet of milk to a solid diet, commingling with unfamiliar compatriots, and establishment of a new social hierarchy.1 Weaning stress in animals is a critical factor in metabolic disorders, gastrointestinal dysfunction, impaired mucosal barrier function and immune function, imbalanced intestinal microbiota, dyspepsia and diarrhea, and increased susceptibility to disease, which are responsible for the impaired growth and health of animals.2−4 Previous studies have demonstrated that problems related to weaning stress in animals can be alleviated by nutritional modulation.5,6 Previous experiments have shown that spermine can alleviate intestinal dysfunction and promote immune function in animals.7,8 The oral administration of spermine to neonatal rats precociously induces structural and biochemical changes in the small intestine, which are characteristic of natural postnatal intestinal maturation. This maturation is embodied by morphological, enzymatic, and physiological modifications that match those observed at weaning.9 Spermine-induced intestinal maturation is a two-step event. The first step, fast and transient, is to eliminate immature enterocytes located at the tip of the villus. The second step is longer than the first step and involves the replacement of immature cells by adult-type enterocytes.10 A time course analysis of the biochemical and histological modifications that occur after the ingestion of a single dose of spermine demonstrates that spermine dramatically alters mucosa integrity without disrupting the epithelium from 4 to 10 h after administration.11 The function of the mucosa is also impaired by a decrease in lactase-specific © 2014 American Chemical Society
activities and maltase-specific activities owing to cell loss by apoptosis.12,13 The intestinal weight is significantly decreased by spermine supplementation.12 Between 30 and 40 h after spermine ingestion, intestinal weight and maltase-specific activities recover and sucrose-specific activities can be observed in the jejunum and ileum.12 Histological studies demonstrate that the mucosa has entirely regenerated 48 h after spermine treatment. The large supranuclear vacuoles vanish from the ileum.11 Metabolomics is a powerful top-down systems biological tool that can identify the consequences of nutritional intervention and can help in understanding how metabolic balances are influenced by interventions. For example, a recent metabolomic study found that arginine supplementation can partially counteract the changes in metabolites induced by weaning stress.5 Furthermore, L-glutamine supplementation can lead to changes in the serum metabolome of pigs.14 Psychological and/ or physiological stresses and an enriched long-chain polyunsaturated fatty acid diet intervention have also been used to evaluate the metabolic consequences in rats by a metabolomic approach.15 Thus, metabolomics can be considered an emerging and promising field of science with a level of information that surpasses traditional approaches for elucidating biochemical responses to diet and its unrecognized mechanisms. However, few studies have focused on the Received: Revised: Accepted: Published: 9035
February 19, 2014 August 21, 2014 August 27, 2014 August 27, 2014 dx.doi.org/10.1021/jf500882t | J. Agric. Food Chem. 2014, 62, 9035−9042
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Figure 1. Typical one-dimensional 1H NMR spectra of plasma metabolites taken from the control and spermine (0.2 and 0.4 μmol/g BW) groups. The region of δ 6.0−9.0 was magnified 6 times compared with the corresponding region of δ 0.5−6.0 for clarity. A total of 34 metabolites were unambiguously assigned. The chemical shifts and peak multiplicities of these metabolites are given in Table 1. spermine administration. Centrifugation at 3500g for 10 min at 4 °C was performed on whole blood samples to obtain plasma. All plasma samples were stored at −80 °C pending NMR spectroscopic analysis. The dosage selected for this study was based on a prior experiment.10,16 The rats were allowed ad libitum access to food and drinking water. Temperatures between 22 and 25 °C, a cycle of 12 h light/12 h dark, and humidity from 50 to 70% were maintained throughout the study. Clinical observations were made during the experimental period. Sample Preparation and NMR Spectroscopy. Plasma samples were thawed from −80 °C. Six hundred and thirty microliters of plasma samples was mixed with 70 μL of Anachro certified DSS standard solution containing 99.9% v/v D2O (for field frequency lock purposes), 0.2% w/v NaN3 (for inhibiting bacterial growth), and 4.08 mM DSS as a reference at 0 ppm (Anachro Technology Co., Ltd. Wuhan, China). After vortexing and centrifugation at 12000 rpm for 10 min (4 °C), 550 μL of the samples was placed into 5 mm NMR tubes for NMR analysis. The proton NMR spectra of the plasma samples were achieved at 300 K on a Bruker Avance II 600 MHz spectrometer (Bruker Biospin, Rheinstetten, Germany) operating at a 1H frequency of 600.13 MHz with broadband-observe probe. A water-presaturated Carr−Purcell− Meiboom−Gill pulse sequence (recycle delay−90°−(τ−180°−τ)n− acquisition) was used to attenuate the NMR signals from macromolecules. A spin−spin relaxation delay (2nτ) of 76.8 ms and a spin− echo delay τ of 400 μs were employed. A 90° pulse was set to 13.7 μs with a recycle delay of 2 s and acquisition time of 2.56 s. A total of 32 transients were collected into 49178 data points for each spectrum with a spectral width of 15 ppm. For assignment purposes, 1H−1H correlation spectroscopy and 1H−1H total correlation spectroscopy were acquired for selected samples. NMR Spectroscopic Processes and Analysis. Before Fourier transformation, the free induction decays were multiplied by an exponential window function with a 1 Hz line-broadening factor. All NMR spectra were then manually phase- and baseline-corrected. The plasma spectral region δ 0.5−9.0 was integrated into regions with equal widths of 0.002 ppm by using Mestrenova 8.1.2 software (Mestrelab Research S.L., Spain). Plasma chemical shifts were referenced to the peak of the methyl proton of L-lactate at δ 1.33. The ethanol signals from the process of blood collection were carefully excluded together with the regions containing urea and H2O signals to obtain only the endogenous metabolite changes induced by spermine exposure. This treatment helps avoid any contributions of ethanol, urea, and H2O to intergroup differentiations. In the plasma spectra, the discarded regions contain δ 4.19−5.23 and δ 5.40−6.80 for H2O and urea, and δ 1.16−1.19 and δ 3.60−3.62 for ethanol. Subsequently, each integral region was normalized to the total sum of all integral regions for each spectrum prior to pattern recognition analysis.
response of animal or human biological systems to spermine supplementation. To explore the molecular mechanisms of the role of spermine in ameliorating weaning stress, variations in the plasma metabolome were examined by using a metabolomic strategy. Plasma is a complex mixture of many constituents, and the 1H NMR spectra of plasma from animals under similar physiological conditions are reproducible. Each peak in the 1H NMR spectra of plasma is accurately correlated with the hydrogen atom of different metabolic chemicals. The relative signal intensity of each peak represents the contents of each component detected in the samples compared with the control. The metabolic profiles of spermine supplementation in rats can improve the current understanding of the association between metabolites and spermine supplementation, provide clues on the correlation between the metabolite and nutritional biochemical mechanisms of spermine, and create baseline data for future metabolomic experiments on spermine metabolism. This approach is also potentially valuable to the study of spermine metabolism and the search for other relationships between spermine administration and health or disease risk. This study would help define the effects of metabolic modifiers and the refinement of nutritional requirements. This should allow for the better formulation of nutritional support for growth and health. This experiment aims to examine the effect of spermine administration on the plasma compositions of rats by employing an explorative metabolomic approach via 1H NMR spectroscopy and chemometrics.
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MATERIALS AND METHODS
Animal Experiment and Sample Collection. The protocol used in this study was approved by the Animal Care and Use Committee of the Animal Nutrition Institute of Sichuan Agricultural University and was conducted according to the Guide for the Care and Use of Laboratory Animals of the National Research Council. A total of 18 19day-old male Sprague−Dawley rats weighing 38−54 g were habituated in individual metabolic cages and were allowed to acclimatize for 1 day. The rats received intragastric administration of either 0.2 or 0.4 μmol/ g body weight (BW) of spermine (Sigma Chemical Co., St. Louis, MO, USA) or saline (control) once a day for 3 days. Six rats were allocated for each group. Blood samples were collected (9:00 a.m.) from the eye after anesthesia with ether and were placed into Eppendorf tubes that contain sodium heparin 48 h after the last 9036
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metabolite
lipid isoleucine leucine valine propionate ethanol 3-hydroxybutyrate lactate alanine lysine acetate N-acetyl glycoprotein O-acetyl glycoprotein glutamate methionine pyruvate glutamine trimethylamine creatine creatinine malonate choline glycerolphosphocholine phosphorylcholine β-glucose α-glucose myo-inositol glycine allantoin tyrosine 1-methylhistidine phenylalanine 3-methylhistidine formate unknown
key
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
δ 1H (ppm) and multiplicity 0.84(t), 0.89(t), 1.28(m), 1.58(m), 2.01(m), 2.24(m), 2.76(m), 5.30(m) 3.68(d), 1.99(m), 1.01(d), 1.26(m), 1.47(m), 0.94(t) 3.73(t), 1.72(m), 1.72(m), 0.96(d), 0.97(d) 3.62(d), 2.28(m), 0.99(d), 1.04(d) 1.08(t), 2.18(q) 1.18(t), 3.55(q) 2.28(dd), 2.42(dd), 4.16(m), 1.20(d) 4.13(q), 1.33(d) 3.77(q), 1.48(d) 3.76(t), 1.91(m), 1.48(m), 1.72(m), 3.01(t) 1.92(s) 2.04(s) 2.08(s) 3.75(m), 2.12(m), 2.35(m) 3.87(t), 2.16(m), 2.65(t), 2.14(s) 2.37(s) 3.78(m), 2.14(m), 2.45(m) 2.92(s) 3.04(s), 3.93(s) 3.04(s), 4.05(s) 3.45(s) 4.07(t), 3.53(t), 3.20(s) 3.22(s), 3.69(t), 4.33(t) 3.22(s), 4.21(t), 3.61(t) 4.65(d), 3.25(dd), 3.49(t), 3.41(dd), 3.46(m), 3.73(dd), 3.90(dd) 5.24(d), 3.54(dd), 3.71(dd), 3.42(dd), 3.84(m), 3.78(m) 3.60(dd), 4.06(t), 3.30(t), 3.63(t) 3.58(s) 5.40(s) 7.20(dd), 6.91(d) 7.05(s), 7.78(s) 7.32(m), 7.42(m), 7.37(m) 7.07(s), 7.67(s) 8.46(s) 7.83 (d)
moieties
CH3(CH2)n, CH3CH2CH2C, (CH2)n, CH2CH2CO, CH2CC, CH2CO, CCCH2CC, −CHCH− αCH, βCH, βCH3, γCH2, δCH3 αCH, βCH2, γCH, δCH3 αCH, βCH, γCH3 CH3, CH2 CH3, CH2 αCH2, βCH, γCH3 αCH, βCH3 αCH, βCH3 αCH, βCH2, γCH2, εCH2 CH3 CH3 CH3 αCH, βCH2, γCH2 αCH, βCH2, γCH2, S-CH3 CH3 αCH, βCH2, γCH2 CH3 CH3, CH2 CH3, CH2 CH2 OCH2, NCH2, N(CH3)3 CH3, βCH2, αCH2 N(CH3)3, OCH2, NCH2 1-CH, 2-CH, 3-CH, 4-CH, 5-CH, 6-CH 1-CH, 2-CH, 3-CH, 4-CH, 5-CH, 6-CH 1,3-CH, 2-CH, 5-CH, 4,6-CH CH2 CH 2,6-CH, 3,5-CH 4-CH, 2-CH 2,6-CH, 3,5-CH, 4-CH 4-CH, 2-CH CH
Table 1. 1H NMR Data for Metabolites in Rat Plasma
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Multivariate data analysis was performed on normalized NMR data sets with the software package SIMCA-P+ (version 11.0, Umetrics, Sweden). Principal component analysis (PCA) was performed on the data set to examine group clustering and to find possible outliers. The results were viewed in the form of score plots, where each point represented an individual sample, and loading plots, where each coordinate represented one NMR spectral region. Projection to latent structure−discriminant analysis (PLS-DA) and orthogonal projection to latent structure−discriminant analysis (OPLS-DA) were performed by using the NMR data (scaled to unit variance) as the X-matrix and the class information as the Y-matrix.17 The quality of the model was evaluated by the parameters R2X, representing the total explained variation, and Q2, standing for the model predictability. The models were validated by using a 7-fold cross-validation method and a permutation test.18,19 A model was considered significant if the Q2 value was significant (P < 0.05) through permutation. The OPLS-DA models were interpreted by coefficient-coded loading plots. The loadings were backtransformed in Excel (Microsoft, USA) and plotted with the color-coded absolute coefficient values (|r|) of the variables in MATLAB (The Mathworks Inc., Natwick, MA, USA; version 7.1).18 In these loading plots, the warm-colored (e.g., red) variables contributed more to intergroup differentiation than cool-colored (e.g., blue) variables. In the current study, appropriate correlation coefficients were used as the cutoff values (depending upon the number of animals used for each group) for the statistical significance based on the discrimination significance (P < 0.05). These coefficients were determined by using Pearson’s product-moment correlation coefficient.18
Figure 2. PCA score plots (R2X = 0.865, Q2 = 0.638; A) and PLS-DA score plots (R2X = 0.639, R2Y = 0.987, Q2 = 0.537; B) based on the 1H NMR spectra of 48 h plasma metabolites taken from the sperminetreated groups (0.2 (red circles) and 0.4 μmol/g BW (blue triangles)) and the control group (black squares). One sample from the control group was excluded because of hemolysis.
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RESULTS AND DISCUSSION H NMR Spectra of Plasma Samples. Figure 1 demonstrates the representative 1H NMR spectra of rat plasma from the control and spermine-treated groups. NMR signals were assigned to specific metabolites for 1H NMR resonances (Table 1). The spectra of the plasma samples mainly contained resonances from glucose, lactate, lipids, choline metabolites, and a series of amino acids. Multivariate Data Analysis of NMR Data. PCA was initially performed on plasma spectral data. Two principal components were calculated for the treatment groups, with 55.8 and 12.9% of the variables explained by PC1 and PC2, respectively. PCA results (Figure 2A) showed that separation were absent in the metabolic plasma profiles of rats from the treatment and control groups. Moreover, PLS-DA was conducted on the plasma spectra of the spermine-treated and control groups. The score plots clearly highlighted three clusters corresponding to the three groups (Figure 2B). Furthermore, the plasma metabolic changes in the rats from the spermine-treated and control groups were analyzed by using OPLS-DA. The corresponding coefficient analysis demonstrated that spermine (0.2 μmol/g BW) significantly increased the plasma levels of 1-methylhistidine, 3-hydroxybutyrate, alanine, glutamine, glycerolphosphocholine (GPC), phosphorylcholine, myo-inositol, phenylalanine, tyrosine, valine, trimethylanine, and α-glucose compared with the control group (P < 0.05; Table 2 and Figure 3B). Spermine (0.4 μmol/g BW) significantly increased the plasma levels of 1-methylhistidine, alanine, formate, glutamate, glutamine, GPC, phosphorylcholine, lysine, lipid, phenylalanine, tyrosine, trimethylanine, αglucose, and β-glucose compared with the control groups (P < 0.05; Table 2 and Figure 3A). Furthermore, spermine (0.4 μmol/g BW) significantly decreased the plasma levels of 3hydroxybutyrate, acetate, choline, lactate, and myo-inositol and increased the plasma levels of glutamine compared with the 1
spermine-treated (0.2 μmol/g BW) groups (P < 0.05; Table 2 and Figure 3C). Spermine Supplementation Induces Alterations to Cell Membrane Metabolism and Lipid Metabolism. Spermine supplementation can alter cell membrane metabolism. Phosphorylcholine and GPC are essential elements for the structural integrity of cell membranes and play critical roles in cell metabolism and signaling processes.20,21 In this study, plasma phosphorylcholine and GPC levels were increased by spermine ingestion. Spermine supplementation can enhance intestinal maturation (data not shown). Therefore, the structural integrity of the cell membrane is ameliorated. Moreover, spermine supplementation can alter lipid metabolism. GPC synthesis in mammalian and bacterial cells occurs with choline.22 GPC acts as an inhibitor of lysophospholipase, which catalyzes the hydrolysis of physiologically important lysophospholipid substrates (containing lysophosphatidic acid and sphingosine 1-phosphate). These lipids play a critical role in cellular signaling and nutrient metabolism regulation.23 The plasma concentrations of myo-inositol were increased in response to spermine supplementation. This carbocyclic polyol provides the structural basis for many secondary messengers (e.g., inositol phosphates, phosphatidylinositol, and phosphatidylinositol phosphate) in eukaryotic cells.24 Therefore, inositol is linked to the regulation of intracellular calcium (Ca) concentrations, insulin signal transduction, gene expression, and fatty acid oxidation.24,25 This result is in agreement with a previous study that shows that spermine enhances electrogenic Ca2+ uptake and increases mitochondrial Ca2+ retention.26 Phosphorylcholine is an essential component for the assembly and secretion of very-low-density lipoproteins in the liver, and an increased level of phosphorylcholine can cause high lipid transfer into the blood. This result is in agreement with that of 9038
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Table 2. OPLS-DA Coefficients, P Values, and Main Functions Derived from the NMR Data of 48 h Plasma Metabolites Obtained from the (A) Control Group and Spermine-Treated Groups ((A) 0.2 and (B) 0.4 μmol/g BW) metabolite
OPLS-DA coefficient (r)a
P valueb
B (vs A) C (vs A) C (vs B)
B (vs A) C (vs A) C (vs B)
1-methylhistidine (31)
0.912
0.91
−
