Systemic responses of weaned rats to spermine against oxidative stress revealed by a metabolomic strategy

Abstract

Many factors can induce oxidative stress in livestock production. Such stress results in damage to cellular antioxidant defense, suboptimal livestock health conditions, and decrease in production efficiency. Spermine supplementation is known to have the potential to mitigate the effects of oxidative stress. However, the systematic changes in metabolic biochemistry associated with oxidative stress and spermine intervention remain largely unknown. This study aims to investigate the effects of oxidative stress and spermine supplementation on the metabolism of weaned rats. Rats received intragastric administration of either 0.4 μmol g⁻¹ body weight of spermine or saline solution for 3 days. The rats in each treatment were then intraperitoneally injected with diquat at 12 mg kg⁻¹ body weight or sterile solution. The 24 h urine and 48 h plasma samples after the last spermine ingestion were analyzed by using nuclear magnetic resonance-based metabolomics. Spermine supplementation and diquat injection can change common systemic metabolic processes, including lipid metabolism, glucose and energy metabolism, amino acid metabolism, as well as gut microbiota functions. Moreover, diquat can induce oxidative stress and alter bile acid metabolism. Under oxidative stress, spermine supplementation could partially counteract the metabolite changes induced by oxidative stress, including amino acid metabolism and lipid metabolism. This study demonstrates the importance of spermine supplementation in regulating the metabolism of weaned rats.

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Introduction

Oxidative stress, defined as the imbalance between the amount of reactive oxygen species (ROS) and the intra- and extracellular antioxidant systems, can disrupt the normal mechanisms of cellular signaling and is believed to be involved in the development of such diseases as atherosclerosis, cardiovascular disorders, and cancer. The effects of oxidative stress depend on the size of disruptions because a cell can overcome small perturbations and revert to the original state. However, more severe oxidative stress can result in cell death, and even moderate oxidation can trigger apoptosis, whereas more intense stresses may cause necrosis.¹ For newborn and weaned animals, numerous factors, including environmental factors, weaning, and infection, cause oxidative stress and could result in growth retardation, disease, and even death.^2,3

Previous experiments have shown that spermine can stabilize nucleic acids,⁴ control cell growth and differentiation,⁵ stabilize cell membranes,⁶ stimulate such membrane enzymes as cytochrome P-450,⁷ regulate membrane transport,⁸ stimulate the ADP/ATP from mitochondrial inner membranes,⁹ prevent loss of respiratory control in ageing mitochondria,¹⁰ and regulate calcium-related events and signal transduction.^6,11 Spermine has been receiving considerable attention as a free radical scavenger,¹² biologically important antioxidant,¹³ and anti-inflammatory agent.¹³ Some mechanisms have suggested that spermine can protect DNA against the strand breakage induced by singlet oxygen.⁴ Therefore, spermine has potential functions against oxidative stress. However, the metabolic changes associated with oxidative stress and spermine intervention are largely unknown. Pro-oxidants, such as diquat, are widely employed to induce oxidative stress in different animal models.

Alterations in physiological status can disrupt homeostasis, resulting in perturbations in the levels of endogenous biochemicals in relation to key metabolic processes in the cells and tissues.¹⁴ To maintain homeostasis and regulate the changes in tissue biochemistry, the composition of biofluids is consequently altered to acquire different and dynamic “metabolic profiles” Thus, monitoring perturbations in biofluid composition can generate valuable information to understand the molecular mechanisms and obtain novel insights into the changes in the physiological status of biological systems.¹⁵ Metabolic profiles are comprehensively characterized by employing high-throughput analytical tools, such as proton nuclear magnetic resonance (¹H NMR) spectroscopy. ¹H NMR spectroscopy of urine, plasma, or tissue yields comprehensive biochemical profiles of low-molecular-weight metabolites that are regulated in response to various stimuli to maintain homeostasis. Metabolomics facilitates the understanding of the global changes in metabolites in animals or humans caused by modifications in nutrition, genetics, environment, and gut microbiota.^14–16 For example, metabolic effects of spermine supplementation on weaned rats have been reported, and certain systemic metabolic processes were found to be associated with spermine supplementation.¹⁷ A recent metabolomic study found that sweet potato fiber and residue have systemic metabolism and health-promoting effects.¹⁸ Moreover, arginine supplementation can partially counteract the changes in metabolites induced by weaning stress.¹⁹ In above-mentioned studies, metabolomics was demonstrated to be important for exploring the complex relationship between nutritional intervention and metabolism to elaborate the function of dietary components in maintaining health and in disease development. Thus, metabolomics can be considered as an emerging and promising field of science with a level of information that outweighs traditional approaches in terms of clarifying biochemical responses to diet and their unrecognized mechanisms. However, the systematic changes in metabolic biochemistry associated with oxidative stress and spermine intervention remain largely unknown.

The metabolic profiles of oxidative stress and spermine intervention in rats can provide a theoretical basis for developing spermine as a stress-resistant component in feeds and offer insights into the correlation between the metabolite and biochemical mechanisms of oxidative stress and spermine. The method is also potentially useful for studies on spermine administration and health or disease risk. The present study would help in determining the effects of metabolic modifiers and refining nutritional requirements to enable better formulation of nutritional support for growth and health. In this study, NMR spectroscopy coupled with appropriate multivariate data analysis techniques was used to examine the effect of oxidative stress and spermine administration on the urine and plasma compositions of rats.

Materials and methods

Animal experiment and sample collection

The animal experiment was approved by the Animal Care and Use Committee of the Animal Nutrition Institute of Sichuan Agricultural University and was performed according to the Guide for the Care and Use of Laboratory Animals of the National Research Council. Forty-four 20-day-old male Sprague-Dawley rats weighing 42 g to 60 g were placed in individual metabolic cages and were allowed to acclimatize for 1 day. The rats received intragastric administration of either 0.4 μmol g⁻¹ body weight of spermine (Sigma Chemical Co., St. Louis, MO, USA) or saline (control) once a day for 3 days. Following this, the rats in each treatment (23-day-old rats, 08:00 hours) were intraperitoneally injected with diquat (Sigma Chemical Co., St. Louis, MO, USA) at 12 mg kg⁻¹ body weight or sterile 0.9% NaCl solution of the same amount. Eleven rats were assigned to each group (i.e., spermine, diquat, spermine + diquat, and control groups). Rats were allowed free access to food and drinking water. Temperatures between 22 °C and 25 °C, a cycle of 12 h light/12 h dark, and humidity ranging from 50% to 70% were maintained throughout the duration of the study. Clinical observations were carried out during the whole experimental period. Urine samples were collected in ice-cooled vessels, including 30 μL of sodium azide solution (1.0% w/v) from day 4 to day 5 of the first treatment period (24 h). Blood samples were collected (9:00 a.m.) from the eye after anesthesia with ether and subsequently placed in Eppendorf tubes containing sodium heparin 48 h after the last spermine ingestion. Whole blood samples were centrifuged at 3500g for 10 min at 4 °C to obtain plasma. All urine and plasma samples were stored at −80 °C until NMR analysis was performed. The dosage selected for this study was on the basis of the results of a previous experiment.^17,20

Analyses in clinical chemistry

Clinical chemistry measurements were executed by using an automatic biochemical analyzer (AUTOLAB PM 4000; AMS Corporation, Rome, Italy), which included total protein (TP), albumin (ALB), triglycerides (TG), total cholesterol, glucose, blood urea nitrogen (BUN), creatinine (CRE), aspartate aminotransferase (AST), and alanine aminotransferase (ALT).

Sample preparation and NMR spectroscopy

Urine samples (550 μL) were mixed with 55 μL of phosphate buffer (1.5 M NaH₂PO₄/K₂HPO₄, pH 7.4, 100% v/v D₂O) containing 0.1% NaN₃ as bacterial growth inhibitor and 5.0 mM 2,2-dimethyl-2-silapentane-5-sulfonate-d₆ (DSS) as chemical shift reference (δ0.00 ppm). After centrifugation (4 °C) at 12 000 rpm for 10 min, the supernatant was pipetted into 5 mm NMR tubes for the NMR test. Plasma samples were prepared by mixing 200 μL of plasma with 400 μL of saline solution containing 75% D₂O as a field frequency lock. After vortexing and centrifugation at 12 000g for 10 min at 4 °C, approximately 550 μL of samples was then transferred into 5 mm NMR tubes.

The proton NMR spectra of the urine and plasma samples were performed 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 a broadband-observe probe. A standard water-suppressed one-dimensional NMR spectrum was derived from urine by employing the first increment of the gradient-selected NOESY pulse sequence (recycle delay–90°–t₁–90°–t_m–90°–acquire data) with recycle delay of 2 s, t₁ of 3 μs, mixing time (t_m) of 100 ms, and 90° pulse length of 13.70 μs. A total of 128 transients were collected into 49 178 data points using a spectral width of 9590 Hz and an acquisition time of 2.56 s. For plasma, a water-presaturated Carr–Purcell–Meiboom–Gill pulse sequence [recycle delay–90°–(τ–180°–τ)_n–acquisition] was employed 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. Typically, 90° pulse was set to 13.7 μs, and 32 transients were acquired into 49 178 data points for each spectrum with a spectral width of 15 ppm. Other acquisition parameters were the same as described above. Metabolites were usually assigned by considering the chemical shifts, coupling constants, and relative intensities as in previous reports and additional ¹H–¹H correlation spectroscopy and ¹H–¹H total correlation spectroscopy were recorded for selected samples (data not shown).

NMR spectroscopic processes and analysis

Prior to Fourier transformation, the free induction decays were multiplied by an exponential window function with a 1 Hz line-broadening factor. All ¹H NMR spectra were then phase- and baseline-corrected manually employing Mestrenova 8.1.2 software (Mestrelab Research S.L., Spain). The plasma spectral region ranging from δ0.5 to δ9.0 was integrated into bins with the bucket-width of 0.002 ppm, and the urinary spectral region δ0.5 to δ9.5 was bucketed into regions with an equal width of 0.005 ppm using Mestrenova 8.1.2 software (Mestrelab Research S.L., Spain). Plasma and urine chemical shifts were referenced to the peak of the methyl proton of L-lactate at δ1.33 and the peak of DSS at δ0.00, respectively. Chemical shifts for urinary citrate was corrected manually because its signals had large inter-sample variations. To obtain only the endogenous metabolite changes induced by treatment, ethanol signals from the process of blood collection were carefully excluded along with the regions containing H₂O and urea signals. This treatment helps avoid any contributions of ethanol, urea and H₂O to intergroup differentiations. In the plasma spectra, the discarded regions include δ4.30 to 5.10 for H₂O, δ5.45 to δ6.50 for urea, and δ1.16 to 1.19 and δ3.60 to 3.62 for ethanol. The excluded regions in the urine spectra contained δ4.50 to δ5.30 for H₂O, as well as δ5.5 to δ6.0 for urea. Afterward, each integral region was normalized to the total sum of all integral regions for each spectrum before pattern recognition analysis.

Multivariate data analysis was achieved on normalized NMR data sets with the software package SIMCA-P+ (version 11.0, Umetrics, Sweden). Principal component analysis (PCA) was performed on the mean-centered data to examine group clustering and to identify possible outliers. Results were observed in the form of score plots, in which each point represented an individual sample, and loading plots, in which 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 achieved by employing the NMR datascaled to unit variance as the X-matrix and the class information as the Y-matrix.²¹ The quality of the model was evaluated by such model parameters as R²X, which indicates the total explained variation, and Q², which represents the model predictability. The models were validated by using two methods: a seven-fold cross validation method and a permutation test.^22,23 The OPLS-DA loading models were generated using MATLAB (The Mathworks Inc.; Natwick, USA. version 7.1) following back-transformation, with signals color-coded with coefficient values (r) to reveal significantly altered metabolites.²² In this study, appropriate correlation coefficients were employed as cutoff values (depending on the number of animals used for each group) for statistical significance on the basis of discrimination significance (P < 0.05). The coefficients were determined by employing Pearson's product-moment correlation coefficient. In the loading plots, the warm-colored (e.g., red) variables contributed more to intergroup differentiation than the cold-colored (e.g., blue) variables.²²

Statistical analysis

The conventional plasma biochemical parameters were analyzed statistically by two-way ANOVA by using the general linear model procedure of SPSS 17.0 software (SPSS Inc., Chicago, IL). Model main effects included spermine levels (0, 0.4 μmol per g per BW) and diquat levels (0, 12 mg per kg per BW). Data were presented as mean ± SEM. The level of significance used was P < 0.05.

Results

Conventional biochemical analysis

Clinical chemistry assays (Table 1) showed that the spermine group showed a decreasing BUN trend and significantly increased TG levels (P < 0.05) compared with the control group. Compared with the control group, the diquat group demonstrated significantly increased ALB, TP, and creatinine levels but decreased AST and BUN levels (P < 0.05).

Table 1 Data for plasma chemistry of rats from the spermine, diquat, spermine + diquat, and control groups^a

Groups	Spermine (μmol per g BW)	Diquat (mg per kg BW)	ALB (g L^−1)	ALT (U L^−1)	AST (U L^−1)	BUN (mmol L^−1)	Total cholesterol (mmol L^−1)	CRE (μmol L^−1)	Glucose (mmol L^−1)	TG (mmol L^−1)	TP (g L^−1)	AST/ALT	BUN/CRE	ALB/TP
a Data represent the mean ± SEM. Different superscripts (b–d) indicate significant difference (P < 0.05) between groups (group 1, group 2, group3, group4), between spermine (0, 0.4 μmol per g BW, main effects), and between diquat (0, 12 mg per kg BW, main effects) for one of all parameters (ALB, ALT, AST, BUN, total cholesterol, CRE, glucose, TG, TP, AST/ALT,BUN/CRE, ALB/TP), respectively.
1	0	0	30.80 ± 0.39^a	51.55 ± 3.14	304.10 ± 20.41^a^,b	7.30 ± 0.92^a	1.81 ± 0.11	29.27 ± 0.85^a	8.03 ± 0.39^a^,b	0.37 ± 0.01^a	51.09 ± 1.31^a	6.08 ± 0.23^a	0.25 ± 0.03^a	0.60 ± 0.02^a
2	0	12	31.55 ± 0.35^a^,b	43.10 ± 2.60	232.60 ± 11.88^a	4.07 ± 0.31^b	1.81 ± 0.07	32.91 ± 0.96^b	8.70 ± 0.28^b	0.44 ± 0.03^a^,b	74.24 ± 0.42^b	5.45 ± 0.24^a^,b	0.12 ± 0.01^b	0.42 ± 0.01^b
3	0.4	0	30.64 ± 0.43^a	44.36 ± 2.17	278.00 ± 13.13^b	5.18 ± 0.54^b	1.67 ± 0.03	31.73 ± 1.06^a^,b	7.59 ± 0.23^a	0.45 ± 0.04^a^,b	56.58 ± 0.46^c	6.15 ± 0.11^a	0.16 ± 0.01^b	0.54 ± 0.00^c
4	0.4	12	32.86 ± 0.71^b	43.40 ± 3.19	223.73 ± 6.42^a	3.91 ± 0.26^b	1.77 ± 0.07	33.20 ± 1.03^b	8.63 ± 0.32^b	0.51 ± 0.04^b	73.55 ± 2.44^b	5.08 ± 0.39^b	0.12 ± 0.01^b	0.46 ± 0.02^d
Main effects
Spermine	0		31.18 ± 0.35	47.32 ± 1.98	268.35 ± 9.85	5.69 ± 0.40	1.81 ± 0.05	31.09 ± 0.68	8.36 ± 0.22	0.41 ± 0.02^a	62.67 ± 1.06	5.76 ± 0.19	0.19 ± 0.01^a	0.51 ± 0.01
	0.4		31.75 ± 0.34	43.88 ± 1.98	250.86 ± 9.39	4.55 ± 0.40	1.72 ± 0.05	32.46 ± 0.7	8.11 ± 0.22	0.48 ± 0.02^b	65.07 ± 1.01	5.62 ± 0.19	0.14 ± 0.01^b	0.50 ± 0.01
Diquat		0	30.72 ± 0.34^a	47.95 ± 1.93	291.05 ± 9.62^a	6.24 ± 0.40^a	1.74 ± 0.05	30.50 ± 0.68^a	7.81 ± 0.22^a	0.41 ± 0.02	53.84 ± 1.03^a	6.11 ± 0.19^a	0.21 ± 0.01^a	0.57 ± 0.01^a
		12	32.21 ± 0.35^b	43.25 ± 2.03	228.16 ± 9.62^b	3.99 ± 0.40^b	1.79 ± 0.05	33.05 ± 0.70^b	8.67 ± 0.22^b	0.47 ± 0.02	73.90 ± 1.03^b	5.26 ± 0.19^b	0.12 ± 0.01^b	0.44 ± 0.01^b
P value
Spermine			0.25	0.23	0.21	0.05	0.23	0.17	0.42	0.04	0.11	0.59	0.02	0.73
Diquat			0.00	0.10	0.00	0.00	0.56	0.01	0.01	0.08	0.00	0.00	0.00	0.00
Spermine × diquat			0.14	0.19	0.53	0.09	0.50	0.28	0.55	0.86	0.04	0.42	0.04	0.00

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Table 2 ¹H NMR signal assignments for metabolites in rat urine and plasma

Keys	Metabolites	Moieties	δ ^1H (ppm) and multiplicity	Samples^a
a U, urine; P, plasma; * LDL, low density lipoprotein; VLDL, low density lipoprotein; TMAO, trimethylamine-N-oxide; s, singlet; d, doublet; t, triplet; q, quartet; dd, doublet of doublets; m, multiplet.
1	Bile acids	CH3	0.64(m), 0.75(m)	U
2	α-Hydroxy-n-valerate	CH3, γCH2	0.86(t), 1.31(m)	U
3	α-Hydroxybutyrate	CH3	0.89(t)	U
4	2-Keto-iso-valerate	CH3, CH	0.93(d), 3.03(m)	U
5	α-Hydroxy-iso-valerate	δCH3	0.83(d), 0.97(d)	U
6	Propionate	CH3, CH2	1.06(t), 2.18(q)	U
7	Isobutyrate	CH3	1.14(d)	U, P
8	Ethanol	CH3, CH2	1.19(t), 3.66(q)	U, P
9	Methylmalonate	CH3, CH	1.25(d), 3.75(m)	U
10	Lactate	αCH, βCH3	4.13(q), 1.33(d)	U, P
11	Alanine	αCH, βCH3	3.77(q), 1.47(d)	U, P
12	Citrulline	γCH2, βCH2	1.56(m), 1.82(m)	U
13	Acetate	CH3	1.92(s)	U, P
14	Acetamide	CH3	1.99(s)	U
15	N-Acetylglutamate	βCH2, γCH2, CH3	2.06(m), 1.87(m), 2.03(s)	U
16	Acetone	CH3	2.24(s)	U, P
17	Acetoacetate	CH3	2.28(s)	U, P
18	Pyruvate	CH3	2.37(s)	U, P
19	Succinate	CH2	2.4(s)	U
20	α-Ketoglutarate	βCH2, γCH2	2.45(t), 3.01(t)	U
21	Citrate	CH2	2.54(d), 2.68(d)	U, P
22	Methylamine	CH3	2.61(s)	U, P
23	Dimethylamine	CH3	2.71(s)	U
24	Methylguanidine	CH3	2.81(s)	U
25	Trimethylamine	CH3	2.88(s)	U, P
26	Dimethylglycine	CH3	2.93(s)	U, P
27	Creatine	CH3, CH2	3.05(s), 3.93(s)	U, P
28	Creatinine	CH3, CH2	3.05(s), 4.04(s)	U, P
29	Ornithine	CH2	3.06(t)	U
30	Ethanolamine	CH2	3.11(t), 3.88(m)	U
31	Malonate	CH2	3.15(s)	U
32	Choline	OCH2, NCH2, N(CH3)3	4.07(t), 3.53(t), 3.21(s)	U, P
33	Taurine	–CH2–S, –CH2–NH2	3.27(t), 3.43(t)	U
34	TMAO	CH3	3.3(s)	U, P
35	Glycine	CH2	3.57(s)	U, P
36	Sarcosine	CH2	3.6(s)	U
37	Phenylacetyglycine	2,6-CH, 3,5-CH, 7-CH, 10-CH	7.30(m), 7.36(t), 7.42(dd), 3.67(s)	U
38	Hippurate	CH2, 3,5-CH, 4-CH, 2,6-CH	3.97(d), 7.55(t), 7.63(t), 7.83(d)	U
39	N-Methylnicotinamide	CH3, 5-CH, 4-CH, 6-CH, CH2	4.42(s), 8.21(t), 8.87(d), 8.93(d), 9.24(s)	U
40	β-Glucose	1-CH, 2-CH, 3-CH, 4-CH, 5-CH, 6-CH	4.47(d), 3.25(dd), 3.49(t), 3.41(dd), 3.46(m), 3.73(dd), 3.90(dd)	U, P
41	α-Glucose	1-CH, 2-CH, 3-CH, 4-CH, 5-CH, 6-CH	5.24(d), 3.54(dd), 3.71(dd), 3.42(dd), 3.84(m), 3.78(m)	U, P
42	Allantoin	CH	5.39(s), 6.05(s)	U, P
43	Urea	NH2	5.82(s)	U
44	Homogentisate	6-CH, 5-CH	6.67(d), 6.76(d),	U
45	p-Hydroxyphenylacetate	6-CH, 2-CH, 3,5-CH	3.6(s), 6.85(d), 7.15(d)	U
46	m-Hydroxyphenylacetate	6-CH, 4-CH, 3-CH	6.92(m), 7.04(d), 7.26(d)	U
47	Indoxyl sulfate	CH	7.22(m)	U
48	Nicotinate	2,6-CH, 4-CH, 5-CH	8.6(d), 8.25(d), 7.5(dd)	U
49	4-Aminohippurate	CH2	7.68(d)	U
50	Benzoate	CH	7.87(d)	U
51	Trigonelline	2-CH, 4-CH, 6-CH, 5-CH, CH3	9.09(s), 8.85(m), 8.81(dd), 8.07(m), 4.44(s)	U
52	Formate	CH	8.46(s)	U, P
53	LDL*	CH3(CH2)n	0.84(m)	P
54	VLDL*	CH3CH2CH2C=	0.89(t)	P
55	Isoleucine	αCH, βCH, βCH3, γCH2, δCH3	3.68(d), 1.99(m), 1.01(d), 1.26(m), 1.47(m), 0.94(t)	P
56	Leucine	αCH, βCH2, γCH, δCH3	3.73(t), 1.72(m), 1.66(m), 0.96(t), 0.97(d)	P
57	Valine	αCH, βCH, γCH3	3.62(d), 2.28(m), 0.99(d), 1.04(d)	P
58	3-Hydroxybutyrate	αCH2, βCH, γCH3	2.28(dd), 2.41(dd), 4.13(m), 1.23(d)	P
59	Lipids (triglycerids and fatty acids)	(CH2)n, CH2CH2CO, CH2C=C, CH2CO, C=CCH2C=C	1.28(m), 1.58(m), 2.01(m), 2.14(m), 2.76(m)	P
60	Lysine	αCH, βCH2, γCH2, εCH2	3.76(t), 1.91(m), 1.48(m), 1.72(m), 3.01(m)	P
61	N-Acetyl glycoprotein	CH3	2.04(s)	P
62	O-Acetyl glycoprotein	CH3	2.08(s)	P
63	Glutamate	αCH, βCH2, γCH2	3.78(t), 2.12(m), 2.35(m)	P
64	Methionine	αCH, βCH2, γCH2, S–CH3	3.87(t), 2.16(m), 2.65(t), 2.14(s)	P
65	Glutamine	αCH, βCH2, γCH2	3.78(m), 2.14(m), 2.45(m)	P
66	Asparagine	CH2, CH	2.85(dd), 2.89(dd),3.99(d)	P
67	Phosphorylcholine	N(CH3)3, OCH2, NCH2	3.2(s), 3.35(s), 4.21(t), 3.61(t)	P
68	Glycerolphosphocholine	CH3, βCH2, αCH2	3.22(s), 3.36(s), 3.69(t), 4.33(t)	P
69	myo-Inositol	1,3-CH, 2-CH, 5-CH, 4,6-CH	3.60(dd), 4.06(t), 3.30(t), 3.63(t)	P
70	Betaine	CH2	3.9(s)	P
71	Threonine	αCH, βCH, γCH3	3.58(d), 4.26(m), 1.32(d)	P
72	Phosphoenolpyruvate	CH2	5.18(t), 5.38(t)	P
73	Unsaturated lipids	=CH–CH2C=, –CH=CH–	5.19 (m), 5.30(m)	P
74	Tyrosine	2,6-CH, 3,5-CH	7.19(d), 6.9(d)	P
75	1-Methylhistidine	4-CH, 2-CH	7.06(s), 7.79(s)	P
76	Phenylalanine	2,6-CH, 3,5-CH, 4-CH	7.32(m), 7.42(m), 7.37(m)	P
77	3-Methylhistidine	4-CH, 2-CH	7.07(s), 7.62(s)	P

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¹H NMR spectra of urine and plasma samples

Fig. 1 shows typical ¹H NMR spectra of the urine samples obtained from randomly selected rats in the spermine, diquat, spermine + diquat, and control groups. Fig. 2 demonstrates the representative spectra of rat plasma from spermine, diquat, spermine + diquat, and control groups. NMR signals were assigned to specific metabolites for ¹H resonances Table 2. Forty-five metabolites were unambiguously assigned to urine. The spectra of the urine samples included resonances from several amino acids and organic acids, as well as glucose, allantoin, and choline. Tricarboxylic acid cycle metabolites, such as succinate and citrate, were also detected in the urine samples. The plasma samples mainly included glucose, lactate, lipids, and a series of amino acids.

Fig. 1 Representative one-dimensional ¹H NMR spectra urine metabolites from the (A) control, (B) spermine, (C) diquat, and (D) spermine + diquat groups. The region ranging from δ6.2 to 9.5 was magnified 10 times in comparison with corresponding region ranging from δ0.5 to 6.2 for clarity. The keys for metabolites are shown in Table 2.

Fig. 2 Typical 600 MHz ¹H NMR spectra of plasma metabolites derived from the (A) control, (B) spermine, (C) diquat, and (D) spermine + diquat groups. The region ranging from δ6.0 to 9.0 was magnified 16 times compared with corresponding region ranging from δ0.5 to 6.0. The keys for metabolites are shown in Table 2.

Multivariate data analysis of NMR data

PCA and PLS-DA were initially performed on the plasma spectral data (Fig. 3A and B). Two principal components were calculated for the treatment groups, with 50.3% and 22.6% of the variables being explained by PC1 and PC2, respectively. PCA results show that separations in rats from the spermine, diquat, spermine + diquat, and control groups were absent in their corresponding metabolic plasma profiles. Furthermore, the plasma metabolic changes in the rats from the spermine, diquat, spermine + diquat, and control groups were determined employing OPLS-DA. The corresponding coefficient analysis demonstrated that spermine supplementation significantly increased the plasma levels of phosphorylcholine, choline, glycine, low density lipoprotein (LDL), isobutyrate, glucose, 3-hydroxybutyrate but decreased the plasma levels of lipid, lysine, isoleucine, and lactate compared with the control group (P < 0.05). By contrast, diquat injection significantly increased the plasma levels of 3-hydroxybutyrate, acetoacetate, acetone, choline, creatine, isobutyrate, isoleucine, LDL, leucine, phenylalanine, phosphorylcholine, trimethylamine-N-oxide, and valine but decreased the plasma levels of asparagines, glutamate, lactate, lipid, and lysine compared with control group (P < 0.05, Fig. 4A and B and Table 3). Spermine + diquat significantly increased the plasma levels of glucose, creatine, glutamate, glutamine, lactate, and tyrosine but decreased the plasma levels of 3-hydroxybutyrate, acetone, allantoin, isoleucine, leucine, valine, lipid, lysine, and phenylalanine compared with diquat group (P < 0.05, Fig. 4C and Table 3).

Fig. 3 PCA score plots ((A) R²X = 0.93, Q² = 0.781) and PLS-DA score plots ((B) R²X = 0.197, R²Y = 0.409, Q² = 0.169) on the basis of the ¹H NMR spectra of plasma metabolites derived from the control (black squares), spermine (green triangles), diquat (blue stars), and spermine + diquat groups (red circles). PCA score plots ((C) R²X = 0.817, Q² = 0.354) and PLS-DA score plots ((D) R²X = 0.37, R²Y = 0.317, Q² = 0.0793) based on the ¹H NMR spectra of the urine derived from urinary metabolites obtained from the control (black squares), spermine (green triangles), diquat (blue stars), and spermine + diquat groups (red circles).

Fig. 4 OPLS-DA scores plots (left panel) and the corresponding coefficient loading plots (right panel) of plasma metabolites taken from the control (black squares), spermine (green triangles), diquat (blue stars) and spermine + diquat groups (red circles) ((A) R²X = 17.6%, Q² = 0.413; (B) R²X = 24.5%, Q² = 0.522; (C) R²X = 24.7%, Q² = −0.0743). The color scale in the coefficient plot demonstrates the significance of metabolite variation between the control group, spermine, diquat, and spermine + diquat groups.

Table 3 OPLS-DA coefficients obtained from the NMR data of 48 h plasma metabolites derived from the (A) control group, (B) spermine, (C) diquat, and (D) spermine + diquat groups^a

Metabolite	D (vs. C)	D (vs. B)	C (vs. A)	B (vs. A)
a Metabolite keys were shown in Table 2; correlation coefficients: positive and negative signs denote positive and negative correlation in the concentrations, respectively. The correlation coefficient of |r| > 0.576 was used as the cutoff value. “—” means the correlation coefficient |r| is less than 0.576. LDL: low density lipoprotein.
myo-Inositol(69)	—	−0.617	—	—
Threonine(71)	—	−0.635	—	—
Glycine(35)	—	0.626	—	0.622
Acetoacetate(17)	—	0.685	0.833	—
Trimethylamine-N-oxide(34)	—	0.650	0.774	—
Phosphorylcholine(67)	—	−0.686	0.772	0.743
Choline(32)	—	—	0.734	0.787
LDL(53)	—	—	0.711	0.667
Isobutyrate(7)	—	0.653	0.668	0.663
Asparagine(66)	—	—	−0.645	—
α-Glucose(41)	0.765	—	—	0.633
β-Glucose(40)	0.763	—	—	0.601
Glutamate(63)	0.760	—	−0.651	—
Lactate(10)	0.635	−0.617	−0.78	−0.733
Tyrosine(74)	0.616	—	—	—
Glutamine(65)	0.598	—	—	—
Creatine(27)	0.581	—	0.752	—
Valine(57)	−0.592	—	0.582	—
Lipid(59)	−0.603	—	−0.717	−0.596
Lysine(60)	−0.620	0.618	−0.691	−0.757
3-Hydroxybutyrate(58)	−0.665	0.701	0.862	0.621
Acetone(16)	−0.627	—	0.631	—
Allantoin(42)	−0.637	—	—	—
Phenylalanine(76)	−0.670	—	0.583	—
Leucine(56)	−0.686	—	0.606	—
Isoleucine(55)	−0.693	—	0.720	−0.620

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PCA and PLS-DA were conducted on the urine spectra of the spermine, diquat, spermine + diquat, and control groups. The score plots (Fig. 3C and D) highlighted four clusters corresponding to the four groups. The metabolic profiles of the four groups were compared employing OPLS-DA to further identify the key urine metabolic changes. Multivariate data analysis demonstrated that spermine significantly increased the urine levels of acetone, phenylacetylglycine, p-hydroxyphenylacetate, but decreased the urine levels of choline, hippurate, methylmalonate, N-methylnicotinamide, taurine. By contrast, diquat injection significantly increased the urine levels of 4-aminohippurate, acetamide, acetate, acetone, alanine, benzoate, citrate, citrulline, dimethylglycine, indoxyl sulfate, isobutyrate, methylamine, m-hydroxyphenylacetate, N-acetylglutamate, nicotinate, ornithine, p-hydroxyphenylacetate, succinate, and trigonelline but decreased the urine levels of allantoin, β-glucose, bile acids, choline, creatine, creatinine, hippurate, lactate, methylmalonate, N-methylnicotinamide, phenylacetylglycine, propionate, sarcosine, taurine, and trimethylamine-N-oxide compared with the control group (P < 0.05, Fig. 5A and B and Table 4). The metabolic profile of the spermine + diquat group was also compared with that of the diquat group using OPLS-DA. Urine levels of creatinine and glycine became significantly higher. The urine levels of bile acids, citrate, N-methylnicotinamide, p-hydroxyphenylacetate, and α-ketoglutarate in the spermine + diquat group than in the diquat group were also higher in the spermine + diquat group than the diquat group (P < 0.05, Fig. 5C and Table 4).

Fig. 5 OPLS-DA scores plots (left panel) and the corresponding coefficient loading plots (right panel) of urinary metabolites derived from the control (black squares), spermine (green triangles), diquat (blue stars), and spermine + diquat groups (red circles) ((A) R²X = 35.8%, Q² = −0.118; (B) R²X = 42.8%, Q² = 0.588; (C) R²X = 28.3%, Q² = −0.115). The color scale in the coefficient plot demonstrates the significance of metabolite variation between the control group, spermine, diquat, and spermine + diquat groups.

Table 4 OPLS-DA coefficients obtained from the NMR data of urine metabolites derived from the (A) control group, (B) spermine, (C) diquat, and (D) spermine + diquat groups^a

Metabolite	D (vs. C)	D (vs. B)	C (vs. A)	B (vs. A)
a Metabolite keys were shown in Table 1; correlation coefficients: positive and negative signs denote positive and negative correlation in the concentrations, respectively. The correlation coefficient of |r| > 0.576 was used as the cutoff value. ‘‘—’’ means the correlation coefficient |r| is less than 0.576.
Ethanol(8)	—	0.786	—	—
Formate(52)	—	0.581	—	—
Acetone(16)	—	—	0.848	0.640
N-Acetylglutamate(15)	—	−0.770	0.841	—
Methylguanidine(24)	—	−0.790	0.837	—
Trigonelline(51)	—	0.731	0.814	0.642
m-Hydroxyphenylacetate(46)	—	0.745	0.810	—
Citrulline(12)	—	0.744	0.777	—
Nicotinate(48)	—	0.691	0.769	—
Methylamine(22)	—	0.829	0.761	—
Homogentisate(44)	—	0.748	0.755	—
Alanine(11)	—	0.741	0.722	—
Dimethylamine(23)	—	−0.608	—	—
Ornithine(29)	—	0.699	0.683	—
Benzoate(50)	—	0.649	0.676	—
Indoxyl sulfate(47)	—	—	0.670	—
4-Aminohippurate(49)	—	−0.699	0.654	—
α-Hydroxy-n-valerate(2)	—	—	0.633	—
Succinate(19)	—	0.710	0.629	—
Acetamide(14)	—	—	0.599	—
Acetate(13)	—	0.607	0.591	—
Isobutyrate(7)	—	0.652	0.590	—
Propionate(6)	—	0.706	−0.578	—
Malonate(31)	—	−0.839	−0.581	—
Sarcosine(36)	—	—	−0.596	—
β-Glucose(40)	—	−0.576	−0.605	—
Taurine(33)	—	0.620	−0.617	−0.598
Trimethylamine-N-oxide(34)	—	−0.633	−0.639	—
Choline(32)	—	—	−0.656	−0.619
α-Hydroxy-iso-valerate(5)	—	—	−0.735	—
Allantoin(42)	—	−0.708	−0.746	—
Lactate(10)	—	−0.828	−0.816	—
Hippurate(38)	—	0.816	−0.832	−0.591
Creatinine(28)	0.687	−0.674	−0.843	—
Ethanolamine(30)	—	−0.672	−0.852	−0.628
Phenylacetylglycine(37)	—	−0.700	−0.877	0.658
Methylmalonate(9)	—	—	−0.93	−0.646
Creatine(27)	—	—	−0.704	—
Glycine(35)	0.612	—	—	—
N-Methylnicotinamide(39)	−0.610	−0.807	−0.752	−0.684
p-Hydroxyphenylacetate(45)	−0.590	—	0.702	0.686
Citrate(21)	−0.591	0.658	0.672	—
Bile acids(1)	−0.625	−0.833	−0.807	−0.598
α-Ketoglutarate(20)	−0.655	−0.758	—	—

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Discussion

Effects of spermine supplementation

Spermine supplementation can alter lipid metabolism. In this study, spermine can increase plasma phosphorylcholine levels. Phosphorylcholine is an essential component for the assembly and secretion of very-low-density lipoproteins in the liver. Increased levels of phosphorylcholine can result in high lipid transfer into the blood. The above findings agree with the results of the present study, in which plasma triglyceride levels were significantly increased. Moreover, ketone body production (such as acetone, 3-hydroxybutyrate, and acetoacetate) provides fuel for vital organs (such as the heart and brain), thereby enhancing the chance of survival from metabolic problems. Acetoacetate and 3-hydroxybutyrate are products of fatty acid oxidation in the liver, and their ratios serve as indicators of the mitochondrial redox state. Spermine supplementation was found to increase 3-hydroxybutyrate concentrations, but acetoacetate concentrations in plasma remain unchanged, thereby decreasing the acetoacetate to 3-hydroxybutyrate ratio. The above results show that the oxidized state of cells decreased because of reduced fatty acid oxidation. Furthermore, in this study, spermine supplementation significantly increased plasma low-density lipoproteins and decreased lipid levels. Collectively, spermine supplementation can alter lipid metabolism, which is consistent with the results of our previous study.¹⁷

Spermine intake can change glucose and energy metabolism. The spermine group showed a significant increase in plasma glucose levels when compared with the control group. Glucose is a major energy substrate that has important functions in animal growth and development. The above finding agrees with the results of our previous study.¹⁷ The spermine group exhibited decreased plasma lactate concentrations. Lactate is the end product of compounds associated with energy metabolism. Decreased lactate levels were found to be associated with decreased anaerobic glycolysis. Moreover, decreased plasma lactate levels indicate an increase in gluconeogenesis, as well as carbohydrate and energy metabolism modification. Elevated levels of urinary α-ketoglutarate suggest changes in the tricarboxylic acid cycle. Collectively, the above findings suggest that spermine supplementation can affect glucose and energy metabolism.

Spermine supplementation causes changes in gut microbiota functions. The energy providers for the colon metabolism are SCFAs (such as isobutyrates), which are produced by bacteria in the colon by fermenting unabsorbed dietary fiber. In this study, isobutyrate levels were found to be higher in the spermine group. Thus, exposure to spermine can modify gut microbiota metabolism. Results of this study also show that spermine decreased the urinary excretion of hippurate, which is produced by the renal and hepatic syntheses of glycine and benzoic acid. Hippurate is the product of flavonol degradation acted upon by intestinal microorganisms. As a result, a change in the excretion of this compound suggests alteration in the functional metabolism of the microbiota. Variations in urinary hippurate concentrations have also been linked to changes in the distribution of intestinal microbial colonies.²⁴ Increased levels of gut microbial co-metabolites, such as phenylacetylglycine and p-hydroxyphenylacetate, confirmed the association of spermine supplementation with the gut microbiota disturbance. Phenylacetate was transformed from phenylalanine through gut microbiota action; phenylacetate was then conjugated with glycine to form phenylacetylglycine.²⁴ Results of a previous study suggest that elevated levels of urinary phenylacetylglycine are associated with the abnormal accumulation of phospholipids in the liver of rats, and the elevated levels serve as a surrogate biomarker for associated changes in the gut microbiota.²⁵ Acyl-CoA has an important function in glycine conjugation;²⁶ however, whether Acyl-CoA is regulated by spermine ingestion remains uncertain. p-Hydroxyphenylacetate is a metabolite of tyrosine processed by enteric bacteria. Mammalian metabolism is significantly influenced by interactions with the complex gut microbiota.²⁷ The introduction of spermine ingestion into the mammalian system may displace baseline mammalian-to-microbial behavior, thereby disrupting microbial populations and eventually affecting metabolism. Alterations in these metabolites may be caused by the decreased number and/or altered activity of intestinal microorganisms. Results of an in vitro experiment demonstrated that spermine supplementation can inhibit some microbes, thereby causing a decrease in microbe number and/or metabolic activity.²⁸ A decrease in the number of intestinal bacteria is believed to be linked to decreased fat accretion,²⁹ although the underlying mechanisms remain unknown. Gut microbiota can affect the development and structure of the intestinal epithelium, the digestive and absorptive capabilities of the intestine, and the host immune system.³⁰ Therefore, disturbances in gut microbiota caused by spermine supplementation may affect gut health status, which agrees with the results of our previous study.¹⁷

Effects of diquat injection

Diquat can induce oxidative stress responses. Decreased levels of urinary N-methylnicotinamide and increased levels of nicotinate were found in the diquat group. N-Methylnicotinamide is the methylated metabolite of nicotinamide, which can be yielded during S-adenosylmethionine to S-adenosylhomocysteine conversion in the biosynthesis of cysteine, an essential amino acid in glutathione synthesis.³¹ Moreover, diquat increased the levels of urinary indoxyl sulfate. Indoxyl sulfate is a circulating uremic toxin that increases glomerular sclerosis and interstitial fibrosis. Indoxyl sulfate is one of the most well-known substances of a group of protein-bound uremic retention solutes. Previous studies suggested that indoxyl sulfate is also related to oxidative stress.^32,33 Therefore, the increase in levels of indoxyl sulfate indicates that ROS production may be elevated in rats. Furthermore, plasma m-hydroxyphenylacetate levels were significantly increased. m-Hydroxyphenylacetate is a rutin metabolite and an antioxidant,³² which implies that the increase in m-hydroxyphenylacetate can trigger anti-oxidative responses activated by diquat. Thus, diquat can decrease antioxidant status in rats.

Diquat can alter bile acid and lipid metabolism. Bile acids are formed from cholesterol in the liver and secreted via the bile into the intestine, in which these acids facilitate the formation of micelles. Such formation increases the processing of dietary fat. Bile acids also enhance the biliary excretion of non-metabolized cholesterol into the bile.³² In this study, urinary bile acid levels were decreased by diquat. Diquat supplementation can affect lipid oxidation. Ketone bodies, such as acetone, 3-hydroxybutyrate, and acetoacetate, are the products of β-oxidation of fatty acid in the mitochondria. In this study, the levels of acetone, 3-hydroxybutyrate, and acetoacetate also increased in the diquat group compared with control group, which suggests changes in lipid metabolism. Moreover, 4-aminohippurate is an acyl glycine, a minor metabolite of fatty acids. Previous studies showed that the excretion of certain acyl glycines increased in several inborn errors of metabolism. In certain cases, the assay of these metabolites in body fluids can be applied to diagnose disorders related to mitochondrial fatty acid β-oxidation.^32,33 In this study, 4-aminohippurate levels increased, indicating the development of disorders related to mitochondrial fatty acid β-oxidation. Furthermore, diquat can affect LDL and lipid levels in rats. Finally, choline and phosphorylcholine have important functions in lipid cholesterol transport and metabolism.³⁴ Plasma choline and phosphorylcholine were significantly increased in the diquat group compared with the control group. Therefore, diquat can alter lipid metabolism. Collectively, diquat can alter bile acid and lipid metabolism in rats.

Diquat can change glucose and energy metabolism. Diquat can decrease plasma lactate level in rats. Decreased lactate level is linked to decreased anaerobic glycolysis. Moreover, decreased plasma lactate levels imply the increase in gluconeogenesis and changes in carbohydrate and energy metabolism. Moreover, diquat can increase urinary alanine levels in rats, thereby suggesting that glycogenolysis was decreased. However, the diquat group has significantly lower plasma glucose levels than the control group. This finding suggests that anaerobic glycolysis and glycogenolysis were decreased. Furthermore, succinate, an important intermediate in the tricarboxylic acid cycle (TCA) cycle, was increased in this study. The above results suggest that the TCA cycle is up-regulated by diquat injection, which is also evidenced by increased levels of citrate, another intermediate in the TCA cycle. Several possible explanations include the following: first, increased urinary levels of TCA cycle intermediates may indicate an increase in whole-body oxidative energy metabolism. Second, the urinary excretion of TCA cycle intermediates may signal altered regulation of anaplerosis and cataplerosis pathways, that is, the net synthesis and net removal of TCA cycle intermediates from mitochondria, respectively. These pathways have functions in biosynthesis routes, such as fatty acid biosynthesis in liver, gluconeogenesis in liver and kidney cortex, and glyceroneogenesis in adipose tissue,³⁵ as well as in insulin secretion stimulation.³⁶ Third, increased TCA cycle activity may indicate changes in liver and kidney functions³⁷ because the identified chemical shifts were indicative of components involved in cellular metabolism. Finally, the obtained results also showed that the levels of all branched-chain amino acids were increased by diquat possibly because increases in oxidative stress-induced energy expenditure can result in elevated consumptions of amino acids, such as alanine, valine, and isoleucine, to provide energy.³³ Therefore, diquat can affect glucose and energy metabolism in rats.

Diquat can alter amino acid metabolism. In this study, plasma total proteins were increased by diquat injection, which implies that diquat inhibits protein synthesis. The above results agree with those of a previous study, which found that diquat can reduce protein synthesis in cells.³⁸ As a result, amino acids decreased during protein synthesis and thus caused decreased levels of the amino acids present in plasma. In this study, levels of plasma glutamate, and lysine were decreased, consistent with the function of diquat in reducing the protein synthesis in rats. In addition, urinary citrulline and N-acetylglutamate levels were increased by diquat. Citrulline is an amino acid produced from ornithine and carbamoyl phosphate in one of the central reactions in the urea cycle. Citrulline is derived from arginine as a by-product of the reaction catalyzed by the NOS family. In this reaction, arginine is first oxidized into N-hydroxyl-arginine and then oxidized further to citrulline in conjunction with the release of nitric oxide.³² Urea has a crucial function in the metabolism of nitrogen-containing compounds. N-Acetylglutamate is needed for the normal function of the urea cycle, and variations in N-acetylglutamate concentrations affect urea production rate and other substrates for urea synthesis.³⁹ Compared with the control group, the diquat group can decrease BUN. In this work, diquat can increase urinary N-acetylglutamate levels compared with the control group. A decrease in BUN was observed along with an increase in N-acetylglutamate, indicating that urea production is modulated by N-acetylglutamate. Furthermore, diquat increased plasma albumin and creatinine levels, thereby suggesting that diquat can affect amino acid metabolism in rats.

Diquat injection can regulate gut microbiota metabolism. The energy providers for the colon metabolism are SCFAs (such as isobutyrates, propionate, and acetate), which are produced by bacteria in the colon via fermentation of unabsorbed dietary fiber. In this study, levels of plasma and urine isobutyrates, as well as urine acetate, increased. However, urine propionate decreased in the diquat group, which can be attributed to the possibility that gut microbiota can either manufacture or utilize these products. Results of this study also indicate that diquat decreased the urinary excretion of hippurate, which is produced through both renal and hepatic syntheses of glycine and benzoic acid. Hippurate is the degradation product of flavonols acted upon by intestinal microorganisms.⁴⁰ As a result, a change in the excretion of this compound suggests a corresponding change in the functional metabolism of the microbiota. Variations in urinary hippurate concentration have also been associated with the changes in the distribution of intestinal microbial colonies.²⁴ Changes in gut microbial co-metabolites, such as phenylacetylglycine and p-hydroxyphenylacetate, with diquat exposure verified the association of the disturbance to gut microbiota. Through the action of gut microbiota, phenylacetate was transformed from phenylalanine; phenylacetate was then conjugated with glycine to produce phenylacetylglycine.²⁴ p-Hydroxyphenylacetate is a metabolite of tyrosine through the action of enteric bacteria. Mammalian metabolism is significantly affected by the complex gut microbiota. The introduction of diquat into the mammalian system may displace baseline mammalian-to-microbial behavior, thereby disrupting in microbial populations and eventually affecting metabolism. In this study, urinary acetamide levels significantly increased. Acetamide has been shown to exhibit anti-microbial, anti-inflammatory, anti-arthritic, and antibiotic functions.³² Changes in these metabolites are attributed to the decreased number and/or altered activity of intestinal microorganisms. Gut microbiota can significantly affect the development and structure of the intestinal epithelium, the digestive and absorptive capabilities of the intestine, and the host immune system.³⁰ Therefore, the disturbances in gut microbiota caused by the supplementation of diquat can affect gut health status.

Effects of spermine under oxidative stress

Spermine supplementation could partially counteract the changes in metabolites induced by oxidative stress, including the increased levels of glucose, glutamate, glutamine, tyrosine, lactate, as well as the decreased levels of allantoin, branched chain amino acid (BCAA), and 3-hydroxybutyrate. Spermine exhibits antioxidant activity. In this study, spermine supplementation can decrease urinary allantoin levels under oxidative stress. Allantoin is a product of purine metabolism in most mammals. Allantoin in urine can be produced via non-enzymatic means through high levels of ROS. Thus, allantoin can be used as a marker of oxidative stress.^32,33 Moreover, oxidative stress induced by diquat can decrease intestinal development (data not shown). However, spermine can alimorate intestinal development under oxidative stress (data not shown). Decreased levels of urinary N-methylnicotinamide was found in the spermine group under oxidative stress. N-Methylnicotinamide is the methylated metabolite of nicotinamide, which can be generated during the conversion of S-adenosylmethionine to S-adenosylhomocysteine during the biosynthesis of cysteine, an essential amino acid of glutathione synthesis.³¹ The above finding implies that rats may utilize an antioxidative vitamin B₃ to decrease oxidative stress induced by diquat. Collectively, the results indicate that spermine supplementation can reduce the oxidative stress of rats.

Spermine supplementation can also increase lipid oxidation under oxidative stress. In this study, spermine + diquat supplementation decreased the plasma levels of 3-hydroxybutyrate but had no effect on acetoacetate compared with the diquat group. Thus, the acetoacetate/3-hydroxybutyrate ratio also increased, which suggests a more oxidized state of cells. Moreover, in this study, spermine can affect lipid metabolism in rats. Therefore, spermine can alter lipid metabolism under oxidative stress.

Spermine supplementation can also alter glucose and energy metabolism under oxidative stress. The spermine + diquat group can exhibit increased plasma glucose levels when compared with the diquat group. The above finding is consistent with that of our previous study. Lactate concentration was also found to increase in the plasma of the spermine + diquat group compared with the diquat group. Increased lactate level is associated with increased anaerobic glycolysis. The above findings indicate that spermine supplementation can increase glycolysis under oxidative stress. Moreover, the spermine + diquat group can exhibit decreased urinary α-ketoglutarate and citrate levels compared with the diquat group. This result suggests that the tricarboxylic acid cycle was altered in rats. The plasma creatine levels increased in the spermine + diquat group compared with the diquat group. Creatine provides energy to muscles in vertebrates in the form of stored creatine phosphate. Creatine synthesis levels in the animals are de novo from the liver through the use of amino acids, such as arginine, glycine, and methionine. Therefore, spermine supplementation can affect energy metabolism in rats under oxidative stress.

Spermine supplementation can also alter amino acid metabolism under oxidative stress. Amino acids in the intestine increased during protein synthesis to promote intestinal maturation, thereby causing increased levels of amino acids present in plasma. In this study, levels of plasma tyrosine were found to increase upon spermine supplementation under oxidative stress. The above results are consistent with the findings of our previous study, in which spermine supplementation was found to ameliorate protein synthesis.¹⁷ Moreover, an increase in the levels of plasma glutamate and glutamine was observed, which also agrees with the spermine function in increasing protein synthesis in rats.¹⁷ Glutamine can activate signaling pathways to increase protein synthesis, thereby affecting animal growth and development. Glutamine is the principal carrier of nitrogen in the body and is an important energy source for many cells. A significant body of evidence has found an association between glutamine-enriched diets with intestinal effects. Glutamine helps in the maintenance of gut barrier function and intestinal cell proliferation and differentiation, as well as the reduction of septic morbidity and irritable bowel syndrome symptoms.^41–45 The possible explanation for the increase in glutamine is the amelioration of the structural integrity of the cell membrane, which is consistent with the results of our studies showing that spermine can significantly increase intestinal villus height and width under oxidative stress (data not shown). Elevated creatinine levels were also observed to be associated with growth. Creatinine is an index of muscle mass, which also supported our findings. Spermine is known to have important functions in increasing protein synthesis, which results in more amino acids being converted into proteins. Such conversion decreases the levels of amino acids present in plasma. In this study, reduced levels of lysine, phenylalanine, and BCAA were observed in rats, which agree well with the known function of spermine in ameliorating protein synthesis in the rats.¹⁷ Taken together, spermine ingestion can cause changes in amino acid metabolism under oxidative stress.

Conclusion

Oxidative stress and spermine supplementation modify some common systemic metabolic processes, including lipid metabolism, glucose and energy metabolism, protein biosynthesis, and gut microbiota metabolism. Spermine supplementation can partially counteract the metabolic consequences associated with oxidative stress, such as lipid and amino acid metabolism. Results obtained from this study reveal the metabolic consequences related to oxidative stress and spermine supplementation, which has important implications in nutritional research in human and animals. This study emphasizes the potential metabolomic strategy for evaluating nutritional interventions in a mammalian system. To the best of our knowledge, this study is the first to identify systematically the expressed metabolites in urine and plasma from spermine against oxidative stress. Nevertheless, the mechanism on the effects of spermine against oxidative stress in animal tissue intermediary metabolism requires further investigation.

Acknowledgements

We would like to thank all the study participants for their ongoing assistance. This work was supported by the National Natural Science Foundation of China (no. 31301986), Research Foundation of Education Bureau of Sichuan Province (no. 11ZB061), Ministry of Education Chunhui Project of China (no. Z2010092) and Specific Research Supporting Program for Discipline Construction in Sichuan Agricultural University.

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