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Revista Brasileira de Farmacognosia

Print version ISSN 0102-695XOn-line version ISSN 1981-528X

Rev. bras. farmacogn. vol.28 no.4 Curitiba July/Aug. 2018

https://doi.org/10.1016/j.bjp.2018.05.008 

Original articles

1H NMR-based nontargeted metabonomics study of plasma and urinary biochemical changes in Kudouzi treated rats

Jie Chena  1

Chenxu Zhanga  1

Xiuli Wua  c  d 

Hongyan Jib 

Wei Maa 

Shijie Weib 

Liming Zhanga  c  d  * 

Jing Chena  c  d  * 

aSchool of Pharmacy, Ningxia Medical University, Yinchuan, China

bInstitute of Clinical Pharmacology, General Hospital of Ningxia Medical University, Yinchuan, China

cNingxia Engineering and Technology Research Center for Modernization of Hui Medicine, Yinchuan, China

dKey Laboratory of Hui Ethnic Medicine Modernization, Ministry of Education (Ningxia Medical University), Yinchuan, China


Abstract

Kudouzi (Sophora alopecuroides L., Fabaceae) is an effective folk medicine, but it always causes a hepatic and renal toxicity in clinical therapy. The toxic mechanism remains unclear. This paper detected the urinary and plasma metabolites alteration by 1H NMR-based metabonomics study in Kudouzi-induced rats to evaluate the toxic mechanism for clinical security. The male Sprague-Dawley rats were orally dosed with 0.5 and 1 g Kudouzi/kg weight once per day for consecutive 14 days. Urine samples were collected at day −1 (before treatment), and days 7, 14, and 21 for NMR analysis, respectively. Plasma samples were harvested at day 14 for NMR and biochemical analysis. The metabonomic profiling of Kudouzi-treated rats differed from that of the vehicle. This was confirmed by the biochemistry analysis. The accumulated subacute toxicity of Kudouzi was visible with dosing time, and persisted at day 21 even after the disposal was ended. The observable biochemical pathways alterations included inhibited TCA cycle, activated anaerobic glycolysis, perturbed amino acids metabolism, and disordered gut microbiota. The results evidenced the toxicity mechanism of Kudouzi from a systematic and holistic view.

Keywords: 1H NMR; Metabonomic; Oral subacute toxicity; Kudouzi; Biochemistry analysis

Introduction

Chinese medicine ‘Kudouzi' (Sophora alopecuroides L., Fabaceae) is a plant in the genus Sophora. It is bitter in taste, cold in nature, and possesses various clinical effects such as heat clearing, detoxifying, analgesic, insecticidal, anti-bacterial, and anti-inflammation (Yang and Yu, 1998; Ren, 2000). Hence it has been clinically used to treat the fever, inflammation, edema and pain (Xiao, 1993). However, S. alopecuroides has an extremely strong clinical toxicity; hitherto, the underlying toxic mechanism and potential biomarkers have not yet been recognized, which seriously restricted its clinical application.

Metabonomics is widely used as a powerful tool to investigate the toxicity of Traditional Chinese Medicines (TCM) by tracing the metabolic profiles of biofluids, tissues, and cells, which contain a mixture of metabolites. The abnormal variations of biomolecules in biofluids induced by drugs are rewarding to intensively understand the disease or toxic mechanism (Boudonck et al., 2009a, b). It has been successfully applied to evaluate the toxicity of TCM such as Aconite lateralis (Cai et al., 2013), Pinellia ternate (Zhang et al., 2013), and Ricinus communis (Guo et al., 2014) or some xenobiotics like benalaxyl (Wang et al., 2018), maleic acid (Wu et al., 2017), arsenic (Yin et al., 2017), and 3-MCPD (Ji et al., 2016). Moreover, the obtained results suggested that, for a toxicity evaluation, metabonomics analysis is much more sensitive than traditional toxicological methods (Wang et al., 2018).

Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are superior over other analytical techniques such as Fourier transform infrared (FT-IR) spectroscopy (Corte et al., 2010; Ahmed et al., 2011; Rehman et al., 2012) and high-performance liquid chromatography (HPLC) method (Agnolet et al., 2012) due to high reproducibility of NMR-based techniques and high sensitivity or selectivity of MS-based techniques, and therefore are the most commonly used analytical tools in metabonomics/metabolomics research. NMR-based tools are in general used for nontargeted study and MS can be used for both selective and nonselective (targeted and nontargeted) analysis (Emwas et al., 2015). Although MS is thought to be more sensitive than NMR (Monteiro et al., 2013) and 1H NMR spectroscopy generates spectra with many overlapping signals which leads to uncertainties in the assignment and quantification of many metabolites (Emwas et al., 2015), NMR-based metabonomic analysis still has its own advantages of being relatively robust across many samples and fast (with spectra acquired within a few minutes) in addition to being a non-destructive process (Emwas et al., 2013). Its non-selectivity in detecting the metabolites and capacity of multiple metabolite quantification or minimal sample preparation demanded enables the detection of all soluble proton-containing small-molecular-weight metabolites that are present in concentrations above 10 µM providing both quantitative and structural information (Lei et al., 2008). Moreover, NMR techniques have no limit ion suppression effects as indicated in MS analysis (Scalbert et al., 2009).

In this study, therefore, NMR-based approach was performed to elucidate the toxicity mechanism of S. alopecuroides by hunting the altered toxic metabolites and biochemical pathways in rat plasma and urine after intragastrically administrated with 0.5 and 1 g/kg of S. alopecuroides each per day for successive 14 days. One more week as recovery period after stopping drug treatment was also designed to display if the toxicity effect of S. alopecuroides is reversible. This work will be beneficial to properly analyze and monitor its clinical safety in a system view.

Materials and methods

The wild seeds of Sophora alopecuroides L., Fabaceae, were harvested from the semi-desert area of Ningxia Hui Autonomous Region, China in July, 2015 (coordinates 38°47′N and 106°27′E) and identified by associate Prof. Jianjun Zhao (College of Pharmacy, Ningxia Medical University, China). A voucher specimen (SA-201507) has been deposited in the College of Pharmacy, Ningxia Medical University, for further references.

NaH2PO4, Na2HPO4, and sodium azide solutions were purchased from Yinchuan Wei Bo Xin Biological Co., Ltd. (Ningxia, China). D2O and D2O (TSP) were purchased from Qingdao Tenglong Weibo Technology Co., Ltd. (Shandong, China).

The dried seeds were grinded into the powders and extracted three times for 30 min each time with 65% ethanol (1:8, w/v) at an ambient temperature in an ultrasonic water bath (40 kHz). The filtered solutions were merged and concentrated to dryness on a rotary evaporation apparatus. The extract with yield of 25.1% (w/w, dried extract/crude herb) was redissolved by normal saline to strength of 1 g/ml and stored at 4 °C before use.

Thirty male Sprague-Dawley (SD) rats (180–220 g, 7 weeks old) were purchased from the Laboratory Animal Center of Ningxia Medical University (SCXK N, 2011-0001) and housed at a standard animal experimental laboratory, with a 12 h light/12 h dark cycle, a humidity of 40 ± 5%, and a constant temperature of 25 ± 1 °C. Animals were allowed free access to standard pellets and water for one week prior to the experiment. The experimental protocol was approved by the University Ethics Committee (Ningxia Medical University, China; ethic approval: 2015-013). All procedures involving animals were in accordance with the Regulations of the Experimental Animal Administration, State Committee of Science and Technology, People's Republic of China.

After one-week acclimatization, rats were randomly assigned to three groups (n = 10). S. alopecuroides treated groups were gavaged at dosage of 0.5 and 1 g/kg once per day for sequential 14 days. Control group was subjected to oral administration with normal saline only. The total experiment lasted 21 days, including 14 days of treatment with S. alopecuroides and 7 days of recovery time. Urine samples were collected at day −1 (before treatment), 7, 14 and day 21 with the addition of 50 µl sodium azide solutions (0.1%, w/w) to each tube, respectively. At day 14, five rats of each group were sacrificed to collect plasma for biochemical and NMR analysis. The remaining animals in each group were continued to feed until day 21. All the samples were stored at −80 °C before use.

Plasma biochemical analysis was performed by the Laboratory Biochemistry Assessments Center of Ningxia Medical University on an Olympus AU 400 automatic analyzer (Olympus optical Co., Ltd, Japan). Alanine aminotransferase (ALT), aspartate aminotransferase (AST), urea nitrogen (BUN), glucose (GLU), and creatinine (CREA) were assayed. Data were statistically analyzed using SPSS16.0 software with significance at p < 0.05 and 0.01.

The frozen urine samples were thawed, and a total 500 µl of urine sample was mixed with 100 µl of phosphate buffer (0.2 mol/l of Na2HPO4/NaH2PO4, pH 7.4) to minimize variations in the pH of the urine samples and then centrifuged (14,000 × g, 4 °C, 10 min) to remove any precipitates. The supernatant was transferred into 5 mm NMR tube. An aliquot of 100 µl of D2O, containing 0.05% sodium 3-trimethylsilyl-(2,2,3,3-2H4)-1-propionate (TSP), was finally added. Plasma samples were thawed and centrifuged (14,000 × g, 4 °C, 10 min), then transferred into 5 mm NMR tubes, respectively. Also, 100 µl of D2O was added into each tube.

1H NMR spectra of urinary and plasma samples were collected at 298 Kona Bruker Avance 500 MHz spectrometer equipped with a Bruker inverse probe (Bruker Biospec, Erlangen, Germany). The NMR spectrum was recorded using the water-presaturated standard one-dimensional Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence (recycle delay-9° (τ-180°-τ) n-acquisition), which eliminated the interference by macromolecules. The plasma and urine free induction decays (FID) were collected with 128 or 64 transient into 32 k data points using a spectral width of 10 kHz with a relaxation delay of 3 s, and relaxation time (2 nτ) of 100 ms. All the FID were multiplied by an exponential function with a line-broadening factor of 0.3 Hz before Fourier transformation.

All the spectra were manually phased and baseline corrected, bucketed and then automatically integrated with a self-developed automation routine in software MestreNova as recommended in the literature (Emwas et al., 2018). The chemical shifts were referenced to the methyl group of TSP at δ 0.00. Each spectrum was segmented into regions with a width of 0.04 ppm between δ 9.2 and δ 0.5 using MestReNova 2.0 (Mestre-lab Research SL). The δ 4.60–6.20 region in urine spectra and δ 4.70–5.20 region in serum spectra were excluded prior to statistical analysis to remove the variation in water suppression efficiency. All remaining regions of the spectra were then normalized to the total sum of the integrated spectral area to reduce any significant concentration differences (Holmes et al., 1994).

All 1H NMR spectra were submitted to Principal Components Analysis (PCA) in the Simca-P+11.0 software (Umetrics, Umeá, Sweden) for an unsupervised pattern recognition analysis to identify general metabolic trends and possible outliers. The orthogonal partial least squared discriminant analysis (OPLS-DA) algorithm at Pareto scaling approach was always used to find the main changing metabolites related to drug exposures (Liu et al., 2015). Subsequently, the distinguishable peak area of the selected metabolites from the NMR was extracted (normalized to the total spectra area) to further evaluate the time- and dose-dependence of S. alopecuroides related metabolite variations.

Results and discussion

As displayed in Table 1, aspartate aminotransferase (AST) was enhanced to 114.98 ± 5.75 and 123.8 ± 13.06 IU/l by SA-treatment at doses of 0.5 and 1 g/kg when compared with control (106.34 ± 4.18 IU/l). Also, both creatinine (CREA) and blood urea nitrogen (BUN) increased significantly. AST is the pivotal biochemical index of hepatic diseases. An increased AST might indicate lesions or diseases in the liver induced by toxins (Liao et al., 2007). Blood urea nitrogen (BUN) is the product of amino acids and creatinine (CREA) is the ultimate product of creatine metabolism in skeletal muscle. Up-regulated BUN and CREA are important indicators of renal dysfunction (Sun et al., 2012). Therefore, it hinted that S. alopecuroides treatment might cause liver and kidney dysfunction of rats.

Table 1 Plasma chemical and biological parameters (mean ± SD, n = 5) at day 14. 

Group Dose (g/kg) Parameters
GLU (mg/dl) CREA (µmol/l) AST (IU/l) ALT (IU/l) BUN (mmol/l)
Control 8.78 ± 1.32 41.62 ± 5.09 106.34 ± 4.18 44.32 ± 6.06 6.90 ± 0.27
SA 0.5 7.74 ± 1.35 50.24 ± 6.24a 114.98 ± 5.75a 46.66 ± 4.22 7.18 ± 0.18
1.0 7.36 ± 0.85 56.52 ± 7.70b 123.8 ± 13.06a 49.12 ± 6.96 7.32 ± 0.29a

aSignificance at p < 0.05 vs. control group.

bSignificance at p < 0.01 vs. control group. Abbreviations: CREA, creatinine; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GLU, glucose; BUN, blood urea nitrogen.

Representative plasma 500 MHz 1H NMR spectra from the control and the groups treated with 0.5 and 1 g/kg of S. alopecuroides at day 14 were displayed in Fig. 1. Resonance and endogenous metabolites assignments were based on chemical shifts reported in the literatures (Li et al., 2008; Zhao et al., 2012). PCA method was applied to determine the extent of differences in the corresponding spectra between the S. alopecuroides treated and control groups. As shown in PCA score plots (Fig. 2A) and corresponding loading plots (Fig. 2B), the scores plot indicated that the metabolites of plasma in S. alopecuroides treatment groups is clearly distinct from those of the vehicle. Variations of the relative integrals from several metabolites were summarized in Table 2 accounting for the differentiation among three groups and listed the data from the statistical analysis. The identified major biochemical changes include increased lactate (δ 1.30, 4.14), pyruvate (δ 2.37), N-acetyl glycoproteins (δ 2.04), and alanine (δ 1.47) along with decreased 3-hydroxybutyrate (δ 1.20) and taurine (δ 3.26, 3.42).

Fig. 1 Representative plasma 500 MHz 1H NMR spectra of SD rats (A, control group; B, 0.5 g/kg of Sophora alopecuroides; C, 1.0 g/kg of S. alopecuroides). 1, lipids; 2, leucine; 3, isoleucine; 4, valine; 5, 3-hydroxy butyrate; 6, lactate; 7, alanine; 8, acetate; 9, N-acetyl glycoproteins; 10, O-acetyl glycoproteins; 11, pyruvate; 12, α-ketoglutarate; 13, dimethylamine; 14, dimethylglycine; 15, creatine; 16, creatinine; 17, choline 18, phosphorylcholine; 19, glycerol phosphorylcholine; 20, trimethylamine oxide/TMAO; 21, betaine; 22, taurine; 23, glycerol; 24, glucose and amino acids; 25, β-glucose; 26, α-glucose; 27, unsaturated lipids; 28, tyrosine; 29, formate. 

Fig. 2 Principal Component Analysis of plasma 1H NMR spectra from control (■), rats treated with 0.5 g/kg of Sophora alopecuroides (♦) and rats treated with 1 g/kg of S. alopecuroides (▲) at day 14. (A) Scores plot; (B) loadings plot. 

Table 2 1H NMR chemical shifts of the metabolites identified from the plasma and urine of rats treated with different doses of SA (mean ± SD, n = 6). 

Samples Metabolites δ1H (ppm) Dose of SA-treatment (g/kg)
0.5 1.0
Plasma Lipid 0.88 (t)
3-Hydroxybutyrate 1.20 (d) a a
Lactate 1.30 (d), 4.14 (q) a a
N-acetyl glycoproteins 2.04 (s) a
O-acetyl glycoproteins 2.14 (s)
Alanine 1.47 (d) a a
Taurine 3.26 (t), 3.42 (t) a a
Pyruvate 2.37 (s) a a
Creatine 3.04 (s), 3.94 (s)
Glycerol 3.56 (dd)
Urine Lactate 1.33 (d), 4.14 (q)
Alanine 1.48 (d), 3.76 (q)
Succinate 2.42 (s) a
α-KG 2.45 (t), 3.02 (t) a a
Citrate 2.54 (d), 2.70 (d) a
Creatine 3.03 (s), 3.94 (s)
Creatinine 3.06 (s), 4.06 (s) a
Taurine 3.26 (t), 3.42 (t) a a
TMAO 3.27 (s), 3.90 (s) a a
Glycine 3.57 (s)
Phenylalanine 7.42 (m)
Hippurate 7.56 (m), 7.62 (m), 7.83 (m) a a

Multiplicity: s, single; d, double; t, triplet; q, quartet; m, multiplet.

aSignificance at p < 0.05 vs. control group. Abbreviations: α-KG, α-ketoglutarate; TMAO, trimethylamine oxide.

Glycolysis is the preliminary and dominating process in glucose metabolism and exists in the cell cytoplasm where one glucose molecule is ultimately catalyzed to produce pyruvate by pyruvate kinase (PK). Pyruvate can be used to produce acetyl-CoA, which enters into tricarboxylic acid cycle (TCA cycle), playing a key role in glucose aerobic oxidation and energy production (Wu et al., 2008). In the ischemic or mitochondrial deficiency cells, pyruvate could be converted to lactate via lactate dehydrogenase (LDH) or to alanine via alanine amino transferase (ALT). In this paper, we observed that the disposal with 0.5 and 1 g SA/kg weight might lead to the glycolysis metabolism disorder and also an activated anaerobic metabolism based on explicitly increased biomarkers such as pyruvate and lactate in rat plasma.

3-HB is the ketone which is produced by lipids degradation through fatty acid oxidation. Mitochondria in the liver are the main sites for fatty acid oxidation, but the process of oxidation is always incomplete. Therefore, a part of the intermediate product named ketones including acetoacetate, 3-HB and acetone will produce. The peripheral tissue with the mitochondria oxidized 3-HB to acetoacetic acid and later to produce acetyl-CoA. And then the energy will be provided for the cells. Hence, down-regulated 3-HB in the plasma from SA-treated rats might suggest a damaged liver, insufficient oxidative capacity, weakened energy supply, and attenuated fatty acid metabolism.

Most of amino acids could be conversed to organic acids through the transamination effect catalyzed by alanine aminotransferase (ALT) and aspartate aminotransferase (AST) and later are decomposed to the substrates of TCA cycle. Alanine, as a non-essential amino acid, is highly concentrated in muscles and is one of the most important amino acids released by muscles. It will produce pyruvate through a reversible transamination effect and generate acetyl CoA into the TCA cycle (Guo et al., 2014). The up-regulated alanine level in the plasma from the SA-treated rats indicated an alanine metabolic pathway disorder.

Moreover, the aminotransferase is an intracellular enzyme. During the process of normal cell renewal, low concentrations of aminotransferase always occur in the plasma. Therefore, elevated aminotransferase concentrations suggest cell damage. The appearance of AST and ALT in the plasma has a special diagnostic value. Almost all liver diseases could lead to an elevated level of AST and ALT in the plasma which might result in an extensive liver cell necrosis (Waterfield et al., 1993; Clayton et al., 2003). Our data (Table 1) demonstrated that S. alopecuroides treatment impaired the liver based on an enhanced AST and ALT in contrast with the vehicle.

We observed a decreased tendency for a key biomarker, taurine, in the plasma from SA-treated rats. Taurine is one of the most abundant free amino acids presented in mammalian tissues with various biological functions (Brown et al., 1993), such as stabilizing cell membranes, scavenging oxygen free radicals, regulating intracellular osmostasis, and maintaining an intracellular Ca2+ concentration (Wang et al., 1996; Condron et al., 2003; Maher et al., 2005). Taurine, therefore, has a hepatoprotective effect against oxidative stress such as lipid peroxidation. Hence, a declined level of taurine indicated an over-consumption to counteract the injury of oxidative stress induced by SA treatment.

The typical 500 MHz 1H NMR spectra of urine samples were also obtained from the control and SA-treated rats (Fig. 3). Endogenous metabolites involved in 1H NMR chemical shift assignments were assigned according to the literatures (Solanky et al., 2003; Coen et al., 2003; Garrod et al., 2005; Ding et al., 2009; Hwang et al., 2009; Zhang et al., 2011; Tang et al., 2004; Li et al., 2015; Wang et al., 2018). From PCA-derived scores plot, the separation of S. alopecuroides treated groups from the control is evident (Fig. 4A). A loadings plot (Fig. 4B) is generated to identify the metabolites responsible for the differentiation in the scores plot. It shows increased levels of taurine (δ 3.26, 3.42), TMAO (δ 3.27, 3.90) and hippurate (δ 7.56, 7.62, and 7.83) along with decreased levels of succinate (δ 2.42), α-KG (δ 2.45, 3.02), citrate (δ 2.54, 2.70), and creatinine (δ 3.06, 4.06) in S. alopecuroides treated groups when compared with control group. The 1H NMR-detected relative integral level of variation metabolites in urine samples of different groups was also summarized in Table 2.

Fig. 3 Representative urine 500 MHz 1H NMR spectra of SD rats (A – Control group; B – 0.5 g/kg of Sophora alopecuroides; C – 1 g/kg of S. alopecuroides). 1, leucine; 2, isoleucine; 3, valine; 4, 3-methy-2-ketovalerate; 5, 2-ketovalerate; 6, lactate; 7, alanine; 8, acetate; 9, N-acetyl glycoproteins; 10, succinate; 11, α-ketoglutarate; 12, citrate; 13, methylamine; 14, trimethylamine; 15, dimethyl glycine; 16, creatine; 17, creatinine; 18, TMAO; 19, betaine; 20, taurine; 21, glucose; 22, glycine; 23, glutamine; 24, hippurate; 25, phenylalanine; 26, formate. 

Fig. 4 Principal component analysis of urine 1H NMR spectra from control (■), rats treated with 0.5 g/kg of Sophora alopecuroides (♦) and rats treated with 1 g/kg of S. alopecuroides (▲) at day 14. (A) Scores plot; (B) loadings plot. 

Acetylcholine (ACh) is the principal neurotransmitter in the parasympathetic nerve. The release of ACh is always accompanied by a variety of physiological activities. It will be hydrolyzed into choline and acetic acid right after releasing under the hydrolysis effect by cholinesterase. The final production of creatine and creatinine by oxidation is the dominating metabolic pathway of choline. In this paper, a decreased level of creatinine in the urine in SA-treated rats suggested that the SA-toxicity caused an information transmission disorder. Creatinine is a waste product formed by a slow spontaneous degradation of creatine-phosphate (Wyss and Kaddurah-Daouk, 2000). Creatine-phosphate functions as an energy conditioner that stores the energy of excess ATP (Ma et al., 2010a, b). As reported (Bell et al., 1991; Zhang et al., 2012), urinary creatinine might be considered as a biomarker of renal function.

Choline can still be decomposed to be methylamine metabolites such as DMA, TMA, and TMAO by gut microbiota (Gullans et al., 1988; Gartland et al., 1989; Foxall et al., 1993; Holmes et al., 1995, 1997; Feng et al., 2002). An up-regulated TMAO level in the urine in S. alopecuroides treated rats indicated that the gut microbiota had a high speed in choline metabolism under the pressure of S. alopecuroides. The metabolic activity of gut microbiota increased the choline metabolism in SA-treated rats, and produced much more methylamine metabolites. The toxicity of S. alopecuroides, therefore, makes a dynamic imbalance of intestinal flora for the rats.

We also found that the biomarker hippurate in the urine was enhanced in S. alopecuroides treated rats. The production of hippuric acid requires the formation of benzoic acid by the decomposition of the phenyl group with the gut microbiota (Phipps et al., 1998; Williams et al., 2002; Nicholls et al., 2003), and then is combined with glycine in the liver under the action of cytochrome. It again demonstrated that S. alopecuroides actually induced a gut microbiota disorder.

Finally, the same PCA strategy was applied to the urinary metabonomic study after S. alopecuroides treatment at doses of 0.5 g and 1 g/kg at four matched time points (days −1, 7, 14, and 21) to reveal the time-related response to SA treatment (Fig. 5). The loading plots indicated the corresponding changes in metabolites during treatment duration and recovery for both two SA treatment groups, such as increased TMAO and taurine as well as decreased succinate and α-KG. The normalized integrals of the changes in these endogenous urinary metabolites were shown in Fig. 5, which demonstrated the time-related response to S. alopecuroides treatment. It comes to reach a conclusion that the toxicity effect of S. alopecuroides might be irreversible.

Fig. 5 Principal component analysis of urine 1H NMR spectra of SD rats treated with 0.5 g/kg of Sophora alopecuroides (A1 and A2, R2 = 86.3%, Q2 = 74.80%) and 1 g/kg of S. alopecuroides at four matched time points (day −1 (■), 7 (●), 14 (♦), and 21 (▲)). 

PCA analysis of 1H NMR metabonomic profiles of plasma and urine samples revealed the potential toxic biomarkers and the altered metabolic pathways induced by S. alopecuroides caused toxicity. The corresponding metabolic pathways included TCA cycle, anaerobic glycolysis, amino acid metabolism, and gut microbe disorder (Fig. 6).

Fig. 6 Schematic diagram of the disturbed metabolic pathways were detected by 1H NMR analysis, showing the interrelationship of the identified metabolic pathways. The words in yellow means increased biomarkers and words in blue means decreased biomarkers. Metabolites with superscript "P" means observed significant level change from plasma; "U" means observed significant level change from urine; "PU" means observed significant level change from both plasma and urine. 

Conclusion

In this study, 1H NMR based metabonomic analysis using plasma and urine samples in conjunction with plasma biochemistry assay was performed to investigate the toxic metabolites biomarkers and abnormal biochemical pathways caused by toxicity of S. alopecuroides. Dose- and time-related changes of endogenous metabolites in S. alopecuroides treated rats included increased lactate, alanine, N-acetyl glycoproteins, creatine, alanine, and pyruvate along with decreased 3-hydroxybutyrate and taurine in plasma samples. Increased taurine, TMAO, and hippurate as well as decreased succinate, α-KG, citrate, and creatinine in urine samples were also discovered. Altered biochemical pathways included energy metabolism, amino acid metabolism and gut microbiota. Toxicity of SA, therefore, is evaluated through a systematic and holistic view.

Ethical disclosures

Protection of human and animal subjects

The authors declare that the procedures followed were in accordance with the regulations of the relevant clinical research ethics committee and with those of the Code of Ethics of the World Medical Association (Declaration of Helsinki).

Confidentiality of data

The authors declare that they have followed the protocols of their work center on the publication of patient data.

Right to privacy and informed consent

The authors declare that no patient data appear in this article.

Acknowledgement

This work was supported by Ningxia Natural Science Foundation (NZ17056).

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Received: January 6, 2018; Accepted: May 25, 2018

* Corresponding authors. E-mails:zhanglm@nxmu.edu.cn (L. Zhang), chenjing@nxmu.edu.cn (J. Chen).

Author's contributions

JC and CZ contributed in running the laboratory work. XW and HJ analyzed the data. WM and SW revised the manuscript critically. LZ and JC designed the study, supervised the laboratory work and contributed to modify the manuscript. All the authors have read the final manuscript and approved its submission.

Conflicts of interest

The authors declare no conflicts of interest.

1

These authors contributed equally to this work.

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