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Analysis of the Effects of #-Tocopherol (#-TOH) on RAW264.7 and K562 Cells Based on 1H-NMR Metabonomics Yang Lu, Hui Li, and Yue Geng J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b04667 • Publication Date (Web): 09 Jan 2018 Downloaded from http://pubs.acs.org on January 9, 2018
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Journal of Agricultural and Food Chemistry
Analysis of the Effects of δ-Tocopherol (δ-TOH) on RAW264.7 and K562 Cells Based on 1H-NMR Metabonomics Yang Lu, Hui Li, Yue Geng*
Key laboratory of Food Nutrition and Safety of SDNU, Provincial Key Laboratory of Animal Resistant Biology, College of Life Science, Shandong Normal University, Jinan 250014, China * Corresponding author.
E-mail address: Yang Lu (
[email protected]), Hui Li (
[email protected]), Yue Geng (
[email protected]).
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Abstract 1
δ-Tocopherol (δ-TOH) is a form of vitamin E with higher bioactivity. In this
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study, we studied the bioactivity of δ-TOH using the IC50 of δ-TOH on
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RAW264.7 (80 µM) and K562 (110 µM) cells. We compared the differential
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metabolites from the cell lines with and without δ-TOH treatment by 1H-NMR
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metabonomics analysis. It was found that δ-TOH affected the protein
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biosynthesis, betaine metabolism, and urea cycle in various ways in both cell
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lines. Metabolic levels of the cell lines were changed after treatment with
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δ-TOH as differential metabolites were produced. The betaine level in
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RAW264.7 cells was reduced significantly while the L-lactic acid level in K562
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cells was significantly enhanced. The metabolic changes might contribute to
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the switch of the respiration pattern from aerobic respiration to anaerobic
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respiration in K562 cell. These results are helpful in a further understanding
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of the sub-toxicity of δ-TOH.
Keywords: 1H-NMR, metabonomics, δ-TOH, RAW264.7, K562
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1. Introduction
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Vitamin E, as an important nutrient, is necessary for maintaining the
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metabolism and physiological functions of humans. The best way to
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supplement vitamin E is to ingest it from the food such as almonds, hazelnuts,
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soybeans, avocado and so on1. Vitamin E, a fat-soluble vitamin, contains
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tocopherols (TOH)2 and tocotrienols (TT), including their α-, β-, γ- and
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δ-forms. The classification is based on the different number and position of
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methyl groups on the chroman ring. The bioactivity of α-TOH is the largest of
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the different forms of vitamin E, and the bioactivity of γ- and δ-forms are only
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10% and 1%, respectively3. However, the antioxidant capacity of δ-TOH is
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stronger than the antioxidant capacity of α-TOH4. The RAW264.7 cell line has
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usually been used as the common inflammatory model in research studies,
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and K562 cell line has acted as the tumor phenotype, as it can be grown as
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suspension cell cultures in order to conduct research. Parker et al. reported
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that the RAW264.7 cells were incubated with α-TOH, γ-TOH and δ-TOH: Cell
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viability for α-TOH was not affected but for γ-TOH was low and lower still for
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δ-TOH5. Therefore, we decided to study the sub-toxicity of δ-TOH on
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RAW264.7 and K562 cells. As has been established, vitamin E plays a role in
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many types of physiological functions, such as anti-oxidation6, anti-aging7,
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anti-allergic, treating frostbite, protecting blood vessel and plasma
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membranes8 and even signal transduction and gene expression9. Vitamin E
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was reported to alleviate obesity and its metabolic complications through
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regulating many signaling pathways, such as the WNT signaling pathway, the
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Janus Kinase (JAK)-signal transducer and activator of transcription (Stat)
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signaling
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(PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway, all of which are
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involved in the regulation of the bioactivity of tumor10,
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researchers found that γ-TOH had anti-cancer effects by suppressing aerobic
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glycolysis11. It was reported that different forms of vitamin E had distinct
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metabolic pathways in vivo and in vitro1. According to data from the World
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Health Organization12, the Recommended Nutrient Intakes (RNIs) of α-TOH
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is 10 mg for normal adults per day12(145) and the Tolerable Upper Intake
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Level (UL) is 1000 mg12(148). Results of a δ-TOH treatment experiment
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indicated that the IC50 concentration was 55 µM, 47 µM, and 23 µM for
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preneoplastic, neoplastic, and highly malignant mouse mammary epithelial
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cells13. It was reported that a certain dose of vitamin E prevented the mice
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liver primary cells from the toxicity of silver nanoparticles14. An early study
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had demonstrated that vitamin E mitigated leukopenia caused by some
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certain cancer chemotherapy drugs, suggesting that vitamin E might be
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effective in reducing the side-effects of cancer chemotherapy15. Furthermore,
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it was reported that the biological effects of δ-TOH on RAW264.7 cells were
pathway,
and
the
phosphatidylinositol
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3’-kinase
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. Recently,
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greater than of those of α-TOH3. However, there is lack of studies on the
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metabonomics of cells treated with δ-TOH.
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The field of metabolism has become more and more important in a many of
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aspects, such as cancer treatment16 and research on traditional Chinese
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medicine, depending on the basis of the molecule changed. With the
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development of metabonomics, the metabolic differences between normal
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cells and cancer cells have been increasingly characterized17-19. Recently, it
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was reported that hematopoietic stem cell transplantation leading to the lethal
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therapy-related myelodysplasia syndrome or acute myeloid leukemia. This
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process includes regulation in metabolic pathways involving alanine and
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aspartate
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phenylalanine metabolism, the citrate acid cycle, and aminoacyl-tRNA
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biosynthesis20. Meanwhile, research on metabonomics of RAW264.7 cells
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was relatively more than K562 cells. Most of existing studies are focused on
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the effects of α-TOH and γ-TOH on macrophages8, 21, 22. The other reason for
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studying these two cell lines is that the RAW264.7 cell is adherent cell
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whereas the K562 cell is the suspension cell. Hence, we decided to search
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the key metabolites and pathways involved in the effect of δ-TOH on
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RAW264.7 and K562 cells. In this study, we investigated the effect of δ-TOH
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on RAW264.7 and K562 cells by 1H-NMR metabonomics. Our study may
metabolism,
glyoxylate
and
dicarboxylate
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metabolism,
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provide useful information on the sub-toxicity and biological capacity of
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δ-TOH.
2. Materials and methods
2.1. Reagents and instruments 76
δ-TOH (≥98%) (Tauto Biotech, Shanghai, China); D2O containing 0.1% TSP,
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DMEM culture medium, and RPMI 1640 culture medium (Sigma-Aldrich, St.
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Louis, MO); dimethyl sulphoxide (DMSO) and 3-(4,5-dimethylthiazol-2-yl)-
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2,5-diphenyltetrazolium bromide (MTT) (Solarbio, Beijing, China); penicillin,
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streptomycin, and L-glutamine (M&C Gene Technology Ltd., Bejing, China);
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fetal calf serum (FBS) (Zhejiang Tianhang Biotechnology Co., Ltd.,
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Hangzhou, China).
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Stat Fax-2000 Microplate Reader (Awareness Technology, Palm City, FL);
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LabServ CO2 incubator (Thermo Fisher, Waltham, MA); Epsilon 2-4 LSCplus
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freeze dryer (Christ, Osterode, Germany); Centrifuge 5804R (Eppendorf,
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Hamburg, Germany); SB-1000 (Eyela, Tokyo, Japan); VC 130PB (Sonic
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Material Inc., Newtown, CT); AVANCE III 600 MHz (Bruker Biospin, Zurich,
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Switzerland).
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2.2. Cell culture 89
RAW264.7 cells were purchased from the Chinese Type Culture Collection
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(CTCC, Shanghai, China), incubated in DMEM supplement with 100 units/mL
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of penicillin, 100 µg/mL of streptomycin 10 µL/mL of L-glutamine, and 10%
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FBS. This cell line was macrophage-originated from the ascites in the
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leukemia virus-induced tumor Abelson murine. The K562 cells were
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purchased from the Chinese Type Culture Collection (CTCC, Shanghai,
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China), cultured in RPMI 1640 supplemented with 100 units/mL of penicillin,
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100 µg/mL of streptomycin, 10 µL/mL of L-glutamine, and 10% FBS. The
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cells were cultured at 37 ˚C with 5% CO2 and at 95% humidity. The K562 cell
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is a cell line derived from a 53-year-old female chronic myelogenous
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leukemia patient in blast crisis. δ-TOH was dissolved in ethanol before being
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added to culture medium (the final concentration of ethanol was 0.5%).
2.3. Cell viability assay 101
To test the effects of δ-TOH on cell viability, the MTT experiment could be
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utilized. Cells in suspension were placed in 96-well plates at 1×105 cells /well,
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incubated for 8 h at 37 ˚C. Then, the old culture medium was removed and
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fresh culture medium containing δ-TOH with different concentrations (20, 40,
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50, 80 and 100 µM) was added. The cells were incubated for 48 h at 37 ˚C.
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Then 20 µL of MTT was added to cells in each well of the 96-well plates and
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incubated for 4 h at 37 ˚C. The culture medium in each well was then
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removed and 150 µL/well of DMSO was added followed by incubation for 20
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min with shaking at room temperature. The plates were centrifuged with 4 ˚C
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and 1,000 rpm for 10 min before removing medium for K562 cells. The
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absorbance of the cell suspension was measured at 492 nm with the
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Microplate Reader.
2.4. Cell extraction 113
Based on the results from the MTT experiment, the half-maximal inhibitory
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concentrations (IC50) of δ-TOH were 80 µM for RAW264.7 cells and 110 µM
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for K562 cells. The cells were cultured in the culture medium with a certain
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amount of δ-TOH for 48 h at 37 ˚C, washing with PBS three times and
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addition of 4 mL of iced methanol was utilized for fixation. The cells were
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removed from the culture dishes with a cell scraper23 and suspended in the
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iced methanol and stored at -4 ˚C. Then, the cell suspensions in methanol
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were then mixed with ultrapure water and trichloromethane at a ratio of
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2.85:4:4 (V:V:V, ultrapure water: methanol: trichloromethane). After vortexing,
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the cell suspension were sonicated to break up cells. Sonication was
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performed in the iced water bath at 1 minute sonication/ break alternations for
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a total of 9 min. The aqueous phase was separated from the organic phase
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by centrifugation at 12,000 rpm, and 4 ˚C for 30 min. After centrifugation, the
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clear aqueous supernatant was collected. The same extraction process was
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repeated three times. The supernatant liquid was combined and stored at
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-80℃.
2.5. Pre-treatment of samples for NMR spectroscopy 129
The aqueous supernatant samples were evaporated at 60℃ and the solid
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compound was dissolved in 900 µL D2O (pH 7.4, containing 0.1% TSP). The
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24 samples were centrifuged at 12,000 rpm and 4 ˚C for 15 min and
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lyophilized. The lyophilized samples were re-dissolved in 700 µL D2O and
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centrifuged under the same conditions above. From the aqueous supernatant,
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600 µL were taken and mixed with 50 µL phosphate buffer solution involving
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D2O (pH 7.4, containing 0.1% TSP). A supernatant in the amount of 550 µL
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was collected into a 5 mm NMR tube for analysis.
2.6. Nuclear magnetic resonance spectroscopy analysis 137
All 1H-NMR spectra were obtained by superconductor shielding flourier
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transform nuclear magnetic resonance spectrometer detection equipped with
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a 13C and 1H double resonance optimization of a 5 mm CPTCI three trans
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detector CryoProbeTM AVANCE 600 Ⅲ (Bruker). Under the conditions as
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follow: 600.104 MHz for proton resonance frequency, zg30 for pulse
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sequence, 12,019.230 Hz for spectral width, number of repetitions was 256,
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number of dummy scans at 298 K was 2, 1 second of relaxation delay, 12
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microsecond of pulse length, and Topspin 3.2 was used to process the
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spectral data.
2.7. Data analysis 146
The NMR spectra were processed with MestReNova 6.11 (Mestrelab
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Research, Santiago de Compostela, Spain). All spectra were added with an
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exponential window function to the spectra and to process manual baseline
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correction. Taking TSP as the standard, the spectra were manually cut off the
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water peak and normalized. Data of the integrated peak was exported into
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numbered groups in Excel files. Next, the data were imported into
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SIMCA-P+12.0 software (Umetrics Inc., Umea, Sweden). The data were
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analyzed
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squares-discriminant analysis (PLS-DA)24, and orthogonal partial least
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squares-discriminant analysis (OPLS-DA). The reliability of the PLS and
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OPLS-DA model were verified by permutation testing and CV-ANOVA25.
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Differential metabolites were identified based on variable importance in
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projection (VIP) and loading weights of primary predictive component. The
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chemical shifts (δ) were selected with the standard of their values of VIP≥1.
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Then, the values of chemical shift were imported into the Biological Magnetic
using
principal components
analysis
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(PCA),
partial
least
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Resonance Bank (BMRB), and the list of possible materials was compiled.
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Based on the list, we identified the substances through matching the
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locations and patterns of peaks in the human metabolome database
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(HMDB)24. In order to quantify the different up and down regulation of
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metabolites, we normalized the peak areas of identified metabolites by the
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sum of the metabolites of the integral area multiplied by 1000 (relative value).
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After distinguishing certain metabolites, we enriched pathways through the
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Kyoto Encyclopedia of Genes and Genomes (KEGG) and MetaboAnalyst
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(MetPA). The metabolites were imported into KEGG to get a list of their
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KEGG ID number. Then, the list was imported into MetPA to match the
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metabolic pathways with two methods. One method is the pathway analysis,
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whose pathway impact characterization of horizontal could coordinate graphs
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by the topological analysis of the importance of the metabolic pathways of the
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computed value, while the ordinated -logP provided significant metabolic
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pathway enrichment analysis. According to P