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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2020, Vol. 14 Issue (3) : 335-356    https://doi.org/10.1007/s11684-019-0705-9
RESEARCH ARTICLE
Chinmedomics facilitated quality-marker discovery of Sijunzi decoction to treat spleen qi deficiency syndrome
Qiqi Zhao1, Xin Gao1, Guangli Yan1, Aihua Zhang1, Hui Sun1, Ying Han1, Wenxiu Li1, Liang Liu2, Xijun Wang1,2,3()
1. National Chinmedomics Research Center, Sino-America Chinmedomics Technology Collaboration Center, National TCM Key Laboratory of Serum Pharmacochemistry, Laboratory of Metabolomics, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin 150040, China
2. State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China
3. National Engineering Laboratory for the Development of Southwestern Endangered Medicinal Materials, Guangxi Botanical Garden of Medicinal Plant, Nanning 530023, China
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Abstract

Sijunzi decoction (SJZD) is a Chinese classical formula to treat spleen qi deficiency syndrome (SQDS) and has been widely used for thousands of years. However, the quality control (QC) standards of SJZD are insufficient. Chinmedomics has been designed to discover and verify bioactive compounds of a variety of formula rapidly. In this study, we used Chinmedomics to evaluate the SJZD’s efficacy against SQDS to discover the potential quality-markers (q-markers) for QC. A total of 56 compounds in SJZD were characterized in vitro, and 23 compounds were discovered in vivo. A total of 58 biomarkers were related to SQDS, and SJZD can adjust a large proportion of marker metabolites to normal level and then regulate the metabolic profile to the health status. A total of 10 constituents were absorbed as effective ingredients that were associated with overall efficacy. We preliminarily determined malonyl-ginsenoside Rb2 and ginsenoside Ro as the q-markers of ginseng; dehydrotumulosic acid and dihydroxy lanostene-triene-21-acid as the q-markers of poria; glycyrrhizic acid, isoglabrolide, and glycyrrhetnic acid as the q-markers of licorice; and 2-atractylenolide as the q-marker of macrocephala. According to the discovery of the SJZD q-markers, we can establish the quality standard that is related to efficacy.

Keywords traditional Chinese medicine      Sijunzi decoction      spleen qi deficiency syndrome      Chinmedomics      quality-marker     
Corresponding Authors: Xijun Wang   
Just Accepted Date: 08 August 2019   Online First Date: 26 November 2019    Issue Date: 08 June 2020
 Cite this article:   
Qiqi Zhao,Xin Gao,Guangli Yan, et al. Chinmedomics facilitated quality-marker discovery of Sijunzi decoction to treat spleen qi deficiency syndrome[J]. Front. Med., 2020, 14(3): 335-356.
 URL:  
http://academic.hep.com.cn/fmd/EN/10.1007/s11684-019-0705-9
http://academic.hep.com.cn/fmd/EN/Y2020/V14/I3/335
Fig.1  Model evaluation of spleen qi deficiency syndrome. (A) Body weight between the CON and MOD groups. (B) Spleen and thymus indices between the CON and MOD groups. (C) General state of model rats during model replication period. (D) Gastric food remnant and small intestine propulsive rates between the CON and MOD groups. (E) Gastric and small intestinal mucosa from the MOD group showed disorderly epithelial cells, unclearly muscular layer, slight erosion and exudation. (F) Serum D-xylose level and amylase level between CON and MOD groups. (G) GAS and MOT level between CON and MOD groups. *P<0.05 and **P<0.01 compared with the CON group.
Fig.2  SJZD efficacy evaluation on spleen qi deficiency syndrome. (A) Body weight of the control, model, and SJZD groups. (B) Spleen and thymus indices of the control, model, and SJZD groups. (C) Gastric food remnant and small intestine propulsive rates of the control, model, and SJZD groups. (D) GAS and MOT level of the control, model, and SJZD groups. (E) Gastric and small intestinal mucosa from the SJZD group showed improved epithelial cells and tissue lesion. (F) Serum D-xylose level, amylase level, GAS, and MOT level of the control, model, and SJZD groups. *P<0.05 and **P<0.01 compared with the control group; #P<0.05 and ##P<0.01 compared with the model group.
Fig.3  Multivariate analysis in SQDS serum and urine metabolomics study. (A) PCA score plot (above) and OPLS-DA score plot (below) between different groups in serum metabolomics study. (B) Time trajectory of rat urine during the model replication. (C) PCA score plot (left) and OPLS-DA score plot (right) between different groups in urine metabolomics study.
Fig.4  Chemical structure and the mass fragment information of indole-3-carboxylic acid, identified as the SQDS rat urine biomarker in positive ion mode. The precise molecular mass and the fragments were detected by a mass spectrometer (UPLC-Q-TOF-MS) and determined within a reasonable degree of measurement error (<5 mDa).
No. Rt M/Z determined M/Z calculated Adducts Actual_M Proposed composition Postulated identity Trend
1 1.08 136 136 M+ Na 113.05 C5H7NO2 1-Pyrroline-2-carboxylic acid
2 1.09 154 154.1 M+ H 153.04 C7H7NO3 3-Hydroxyanthranilic acid
3 1.68 157.1 157.1 M+ Na 134.07 C4H10N2O3 L-Canaline
4 2.19 201 201 M − H 202.03 C11H6O4 Bergaptol
5 2.54 514.3 514.3 M − H 515.29 C26H45NO7S Taurocholic acid
6 2.81 448.3 448.3 M − H 449.31 C26H43NO5 Chenodeoxyglycocholic acid
7 3.6 315.2 315.2 M − H 316.2 C20H28O3 4-Hydroxyretinoic acid
8 3.64 282.3 282.3 M+ H 281.27 C18H35NO Oleamide
9 3.91 333.2 333.2 M − H 334.21 C20H30O4 Prostaglandin A2
10 3.91 289.2 289.2 M+ H 288.21 C19H28O2 Testosterone
11 3.93 518.3 518.3 M+ H 517.32 C26H48NO7P LysoPC(18:3(9Z,12Z,15Z))
12 4.31 303.2 303.2 M − H 304.24 C20H32O2 Arachidonic acid
13 4.84 255.2 255.2 M − H 256.24 C16H32O2 Palmitic acid
14 4.9 1092 1092 M+ H 1090.7 C56H102N2O18 Ganglioside GA2 (d18:1/9Z-18:1)
15 5.01 295.2 295.2 M − H 296.24 C18H32O3 9,10-Epoxyoctadecenoic acid
16 6.19 552.4 552.4 M+ H 551.4 C28H58NO7P LysoPC(20:0)
17 6.73 780.6 780.6 M+ Na 757.56 C42H80NO8P PC(18:1(11Z)/16:1(9Z))
18 7.02 253.2 253.2 M − H 254.22 C16H30O2 Palmitoleic acid
19 7.13 742.5 742.5 M − H 743.55 C41H78NO8P PC(15:0/18:2(9Z,12Z))
20 7.28 578.4 578.4 M+ H 577.41 C30H60NO7P LysoPC(22:1(13Z))
21 7.42 808.6 808.6 M+ H 807.58 C46H82NO8P PC(20:2(11Z,14Z))
Tab.1  Detailed information of biomarkers tentatively identified by serum metabolomics
No. Rt M/Z
?determined
M/Z
?calculated
Adducts_H+ Adducts_H− Actual_M Proposed ?composition Postulated identity Trend
1 0.68 195.0504 195.0505 195.051 196.0583 C6H12O7 Galactonic acid
2 0.71 114.0661 114.0672 114.067 113.0589 C4H7N3O Creatinine
3 0.76 300.0389 300.0389 300.039 301.0468 C8H15NO9S N-Acetylglucosamine 6-sulfate
4 0.77 203.1508 203.1511 203.15 202.143 C8H18N4O2 Dimethyl-L-arginine
5 0.79 335.0955 339.0961 335.096 334.0907 C17H19ClN2OS Chlorpromazine-N-oxide
6 0.8 243.0973 243.0971 243.098 242.0903 C10H14N2O5 Thymidine
7 0.84 149.0451 149.0445 149.044 150.0528 C5H10O5 β-D-ribopyranose
8 0.89 70.0651 70.0655 70.0654 69.0578 C4H7N 1-Pyrroline
9 0.89 132.0665 132.067 132.066 131.0582 C5H9NO3 4-Hydroxy-L-proline
10 0.9 191.0186 191.0191 191.019 192.027 C6H8O7 Citric acid
11 0.9 173.0079 173.0083 173.008 174.0164 C6H6O6 Trans-aconitic acid
12 1.21 121.065 121.0653 121.065 120.0575 C8H8O Phenylacetaldehyde
13 1.21 138.0915 138.0911 138.092 137.0841 C8H11NO Tyramine
14 1.29 111.0086 111.0081 111.008 112.016 C5H4O3 2-Furoic acid
15 1.29 173.0075 173.0081 173.008 174.0164 C6H6O6 Dehydroascorbic acid
16 1.69 238.0935 238.0929 238.094 237.0862 C9H11N5O3 Dyspropterin
17 1.95 136.0753
?/134.0591
136.0745
?/134.0589
136.076 134.06 135.0684 C8H9NO N-Acetylarylamine
18 2.5 208.0969 208.0971 208.097 207.0895 C11H13NO3 N-Acetyl-L-phenylalanine
19 2.74 220.1183 220.118 220.118 219.112 C10H13N5O Cis-zeatin
20 2.85 279.1335 279.1336 279.134 278.1267 C14H18N2O4 N1-(α-D-ribosyl)-5, 6-?dimethyl-benzimidazole
21 2.94 216.9804 216.981 216.981 217.9885 C7H6O6S 5-Sulfosalicylic acid
22 3.02 162.0561
?/160.0392
162.0555
?/160.0399
162.055 160.039 161.0477 C9H7NO2 Indole-3-carboxylic acid
23 3.23 167.0335 167.0338 167.034 168.0423 C8H8O4 Homogentisic acid
24 3.41 206.0448
?/204.0295
206.0455
?/204.0289
206.045 204.029 205.0375 C10H7NO4 Xanthurenic acid
25 3.74 190.0449 190.0512 190.05 189.0426 C10H7NO3 Kynurenic acid
26 3.95 208.0607 208.0612 208.061 207.0532 C10H9NO4 4-(2-Aminophenyl)-2, 4-?dioxobutanoic acid
27 4.27 178.0492 178.0495 178.05 179.0582 C9H9NO3 Hippuric acid
28 4.57 164.0722
?/162.0558
164.071
?/162.0561
164.071 162.055 163.0633 C9H9NO2 3-Methyldioxyindole
29 4.57 340.1041
?/338.0881
340.1042
?/338.0882
340.104 338.088 339.0954 C15H17NO8 6-Hydroxy-5-methoxyindole ?glucuronide
30 4.8 192.0658 192.0661 192.066 193.0739 C10H11NO3 Phenylacetylglycine
31 5.18 229.143 229.1433 229.143 230.1518 C12H22O4 Dodecanedioic acid
32 5.37 173.0813 173.0809 173.081 174.0892 C8H14O4 Suberic acid
33 6.15 255.0671
?/253.0514
255.0665
?/253.0504
255.066 253.05 254.0573 C7H14N2O6S 5-L-Glutamyl-taurine
34 6.23 297.0975 297.0983 297.098 298.1053 C14H18O7 2-Phenylethanol glucuronide
35 6.23 175.0241 175.0235 175.024 176.0321 C6H8O6 D-Glucurono-6,3-lactone
36 7.2 181.0862 181.086 181.086 180.0786 C10H12O3 Coniferyl alcohol
37 8.48 407.2785 407.2793 407.279 408.2876 C24H40O5 Cholic acid
Tab.2  Detailed information of biomarkers tentatively identified by urine metabolomics
Fig.5  Serum and urine biomarker relative measurements before and after SJZD treatment. (A) 37 urine metabolites. (B) 21 serum metabolites. (*P<0.05 and **P<0.01 compared with the control group; #P<0.05 and ##P<0.01 compared with the model group.)
Fig.6  Metabolite profile after orally administrated SJZD and the urine/serum metabolites relative-disordered pathway. (A) Urine metabolite profile. (B) Urine metabolite profile. (C) Urine metabolite relative pathways. 1. Glyoxylate and dicarboxylate metabolism; 2. Pentose and glucuronate interconversions; 3. Folate biosynthesis; 4. Phenylalanine metabolism; 5. Tyrosine metabolism; 6. Citrate cycle (TCA cycle); 7. Pyrimidine metabolism; 8. Starch and sucrose metabolism; 9. Ubiquinone and other terpenoid-quinone biosynthesis; 10. Taurine and hypotaurine metabolism; 11. Ascorbate and aldarate metabolism; 12. Riboflavin metabolism; 13. Tryptophan metabolism; 14. Primary bile acid biosynthesis. (D) Serum metabolite relative pathways. 1. Arachidonic acid metabolism; 2. Glycerophospholipid metabolism; 3. Tryptophan metabolism; 4. Primary bile acid biosynthesis; 5. Steroid hormone biosynthesis; 6. Linoleic acid metabolism; 7. Biosynthesis of unsaturated fatty acids; 8. Taurine and hypotaurine metabolism; 9. α-linolenic acid metabolism; 10. Retinol metabolism; 11. Fatty acid biosynthesis; 12. Arginine and proline metabolism; 13. Fatty acid elongation in the mitochondria.
Fig.7  Reconstructed pathways associated with the biomarkers that are abnormally expressed in SQDS rats. The red script substances are the metabolic markers tentatively identified in this experiment. They are mainly involved in bile acid metabolism, retinoid acid metabolism, fatty acid metabolism, amino acid metabolism, and carbohydrate metabolism.
Fig.8  Chromatograms and multivariate analysis in serum pharmacochemistry analysis. (A) Chromatograms of the SJZD, model group serum, and SJZD-dosed group. (B) PCA score plot between the dosed and model groups. (C) Trend plot of identified absorbed compound 3.117_257.0814.
Fig.9  ES-BPI rat serum chromatogram marked with characterized compounds after orally administrated SJZD. The compounds with yellow arrows were from Ginseng, with purple arrows from poria, with blue arrows from macrocephala, and with green arrows from licorice.
Fig.10  PCMS analysis between serum biomarkers and chemical constituents in the SJZD group. The vertical arrangement is the absorption components, and the transverse arrangement is the biomarkers. Red square: means extremely positive correlation. Black square: means extremely negative correlation. Pink square: means highly positive correlation. Blue square: means highly negative correlation. Green square: means minimal correlation. The absorbed compounds marked in red were the crucial compounds, which we further screened.
Fig.11  PCMS analysis between urine biomarkers and chemical constituents in the SJZD group. The vertical arrangement is the absorption components, and the transverse arrangement is the biomarkers. Red square: means extremely positive correlation. Black square: means extremely negative correlation. Pink square: means highly positive correlation. Blue square: means highly negative correlation. Green square: means minimal correlation. The absorbed compounds marked in red were the crucial compounds, which we further screened.
Fig.12  Research route of Sijunzi decoction’s quality-marker in this experiment.
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