Combined systems pharmacology and fecal metabonomics to study the biomarkers and therapeutic mechanism of type 2 diabetic nephropathy treated with Astragalus and Leech.

In our study, systems pharmacology was used to predict the molecular targets of Astragalus and Leech, and explore the therapeutic mechanism of type 2 diabetic nephropathy (T2DN) treated with Astragalus and Leech. Simultaneously, to reveal the systemic metabolic changes and biomarkers associated with T2DN, we performed 1H NMR-based metabonomics and multivariate analysis to analyze fecal samples obtained from model T2DN rats. In addition, ELISA kits and histopathological studies were used to examine biochemical parameters and kidney tissue, respectively. Striking differences in the Pearson's correlation of 22 biomarkers and 9 biochemical parameters were also observed among control, T2DN and treated rats. Results of systems pharmacology analysis revealed that 9 active compounds (3,9-di-O-methylnissolin; (6aR,11aR)-9,10-dimethoxy-6a,11a-dihydro-6H-benzofurano[3,2-c]chromen-3-ol; hirudin; l-isoleucine; phenylalanine; valine; hirudinoidine A-C) and 9 target proteins (l-serine dehydratase; 3-hydroxyacyl-CoA dehydrogenase; tyrosyl-tRNA synthetase; tryptophanyl-tRNA synthetase; branched-chain amino acid aminotransferase; acetyl-CoA C-acetyltransferase; isovaleryl-CoA dehydrogenase; pyruvate dehydrogenase E1 component alpha subunit; hydroxyacylglutathione hydrolase) of Astragalus and Leech were closely associated with the treatment of T2DN. Using fecal metabonomics analysis, 22 biomarkers were eventually found to be closely associated with the occurrence of T2DN. Combined with systems pharmacology and fecal metabonomics, these biomarkers were found to be mainly associated with 6 pathways, involving amino acid metabolism (leucine, valine, isoleucine, alanine, lysine, glutamate, taurine, phenylalanine, tryptophan); energy metabolism (lactate, succinate, creatinine, α-glucose, glycerol); ketone body and fatty acid metabolism (3-hydroxybutyrate, acetate, n-butyrate, propionate); methylamine metabolism (dimethylamine, trimethylamine); and secondary bile acid metabolism and urea cycle (deoxycholate, citrulline). The underlying mechanisms of action included protection of the liver and kidney, enhancement of insulin sensitivity and antioxidant activity, and improvement of mitochondrial function. To the best of our knowledge, this is the first time that systems pharmacology combined with fecal metabonomics has been used to study T2DN. 6 metabolites (n-butyrate, deoxycholate, propionate, tryptophan, taurine and glycerol) associated with T2DN were newly discovered in fecal samples. These 6 metabolites were mainly derived from the intestinal flora, and related to amino acid metabolism, fatty acid metabolism, and secondary bile acid metabolism. We hope the results of this study could be inspirational and helpful for further exploration of T2DN treatment. Meanwhile, our results highlighted that exploring the biomarkers of T2DN and therapeutic mechanisms of Traditional Chinese Medicine (TCM) formulas on T2DN by combining systems pharmacology and fecal metabonomics methods was a promising strategy.

Chen R ，Liao C ，Guo Q ，Wu L ，Zhang L ，Wang X ... -  《RSC Advances》

Fecal metabonomics combined with 16S rRNA gene sequencing to analyze the changes of gut microbiota in rats with kidney-yang deficiency syndrome and the intervention effect of You-gui pill.

A myriad of evidence have shown that kidney-yang deficiency syndrome (KYDS) is associated with metabolic disorders of the intestinal microbiota, while TCMs can treat KYDS by regulating gut microbiota metabolism. However, the specific interplay between KYDS and intestinal microbiota, and the intrinsic regulation mechanism of You-gui pill (YGP) on KYDS' gut microbiota remains largely unknown so far. In the present study, fecal metabonomics combined with 16S rRNA gene sequencing analysis were used to explore the mutual effect between KYDS and intestinal flora, and the intrinsic regulation mechanism of YGP on KYDS's gut microbiota. Rats' feces from control (CON) group, KYDS group and YGP group were collected, and metabolomic analysis was performed using 1H NMR technique combined with multivariate statistical analysis to obtain differential metabolites. Simultaneously, 16S rRNA gene sequencing analysis based on the Illumina HiSeq sequencing platform and ANOVA analysis were used to analyze the composition of the intestinal microbiota in the stool samples and to screen for the significant altered microbiota at the genus level. After that, MetaboAnalyst database and PICRUSt software were apply to conduct metabolic pathway analysis and functional prediction analysis of the screened differential metabolites and intestinal microbiota, respectively. What's more, Pearson correlation analysis was performed on these differential metabolites and gut microbiota. Using fecal metabonomics, KYDS was found to be associated with 21 differential metabolites and seven potential metabolic pathways. These metabolites and metabolic pathways were mainly involved in amino acid metabolism, energy metabolism, methylamine metabolism, bile acid metabolism and urea cycle, and short-chain fatty acid metabolism. Through 16S rRNA gene sequencing analysis, we found that KYDS was related to eleven different intestinal microbiotas. These gut microbiota were mostly involved in amino acid metabolism, energy metabolism, nervous, endocrine, immune and digestive system, lipid metabolism, and carbohydrate metabolism. Combined fecal metabonomics and 16S rRNA gene sequencing analysis, we further discovered that KYDS was primarily linked to three gut microbiotas (i.e. Bacteroides, Desulfovibrio and [Eubacterium]_coprostanoligenes_group) and eleven related metabolites (i.e. deoxycholate, n-butyrate, valine, isoleucine, acetate, taurine, glycine, α-gluconse, β-glucose, glycerol and tryptophan) mediated various metabolic disorders (amino acid metabolism, energy metabolism, especially methylamine metabolism, bile acid metabolism and urea cycle, short-chain fatty acid metabolism. nervous, endocrine, immune and digestive system, lipid metabolism, and carbohydrate metabolism). YGP, however, had the ability to mediate four kinds of microbes (i.e. Ruminiclostridium_9, Ruminococcaceae_UCG-007, Ruminococcaceae_UCG-010, and uncultured_bacterium_f_Bacteroidales_S24-7_group) and ten related metabolites (i.e. deoxycholate, valine, isoleucine, alanine, citrulline, acetate, DMA, TMA, phenylalanine and tryptophan) mediated amino acid metabolism, especially methylamine metabolism, bile acid metabolism and urea cycle, short-chain fatty acid metabolism, endocrine, immune and digestive system, and lipid metabolism, thereby exerting a therapeutic effect on KYDS rats. Overall, our findings have preliminary confirmed that KYDS is closely related to metabolic and microbial dysbiosis, whereas YGP can improve the metabolic disorder of KYDS by acting on intestinal microbiota. Meanwhile, this will lay the foundation for the further KYDS's metagenomic research and the use of intestinal microbiotas as drug targets to treat KYDS.

Chen R ，Wang J ，Zhan R ，Zhang L ，Wang X ... -  《-》

Exploring the biomarkers and therapeutic mechanism of kidney-yang deficiency syndrome treated by You-gui pill using systems pharmacology and serum metabonomics.

In this study, systems pharmacology was used to predict the molecular targets of You-gui pill (YGP) and explore the therapeutic mechanism of Kidney-Yang Deficiency Syndrome (KYDS) treated with YGP. On the basis of this, serum samples from control group, KYDS model group and YGP group rats were studied using 1H NMR to verify the results of systems pharmacology from the level of metabonomics. Simultaneously, 1H NMR spectra of serum samples were obtained and statistically assessed using pattern recognition analysis. Biochemical analyses of serums were performed via radioimmunoassays. Furthermore, histopathological studies were conducted on the pituitary, adrenal, and thyroid glands, and testicles of the control, KYDS and YGP rats. Using systems pharmacology to analyze the active components of YGP, 61 active compounds were finally found. These compounds were likely to have an effect on 3177 target proteins and involve 234 pathways. Using metabonomics to analyze serum from KYDS rats treated with YGP, 22 endogenous biomarkers were found. These biomarkers were mainly involved in 10 metabolic pathways. Combining systems pharmacology and metabonomics, we found that the regulation of KYDS was primarily associated with 19 active compounds of 5 Chinese herbal medicines in YGP. These active compounds mainly had an effect on 8 target proteins, including phosphoenolpyruvate carboxykinase, betaine-homocysteine s-methyltransferase 1, alcohol dehydrogenase 1C, etc. These target proteins were primarily involved in 6 overlapping pathways, namely aminoacyl-tRNA biosynthesis, glycolysis/gluconeogenesis, glycine, serine and threonine metabolism, valine, leucine and isoleucine biosynthesis, arginine and proline metabolism, and pyruvate metabolism. In addition, there were 4 non-overlapping pathways, respectively alanine, aspartate and glutamate metabolism, d-glutamine and d-glutamate metabolism, ubiquinone and other terpenoid-quinone biosynthesis, and galactose metabolism. In summary, the therapeutic effects of YGP on KYDS were mainly associated with neuroendocrine regulation, energy metabolism, amino acid metabolism, inflammatory responses, apoptosis, oxidative stress and intestinal flora metabolism. What's more, we also found that YGP possessed the potential to protect liver and kidney function. Our study demonstrated that systems pharmacology and metabonomics methods were novel strategies for the exploration of the mechanisms of KYDS and TCM formulas.

Chen R ，Wang J ，Liao C ，Zhang L ，Guo Q ，Wang X ... -  《RSC Advances》

Integrated Systems Pharmacology, Urinary Metabonomics, and Quantitative Real-Time PCR Analysis to Uncover Targets and Metabolic Pathways of the You-Gui Pill in Treating Kidney-Yang Deficiency Syndrome.

Chen R ，Wang J ，Zhan R ，Zhang L ，Wang X ... -  《INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES》

Metabonomics study on orthotopic transplantion mice model of colon cancer treated with Astragalus membranaceus-Curcuma wenyujin in different proportions via UPLC-Q-TOF/MS.

Metabolomics, an important part of systems biology, can reveal the complex pathogenesis of many diseases and mechanism of Chinese materia medica (CMM). Astragalus membranaceus-Curcuma wenyujin (AC) was a classic drug pair that has a good clinical effect on gastrointestinal inflammation and many tumors. Our previous research proved that AC can inhibit tumor growth and metastasis especially the colorectal cancer (CRC), also promote the normalization of tumor blood vessels, but its optimal ratio and the specific mechanism is still not clear. In this study, colon cancer mice of orthotopic transplantion model was used to screen the best proportion, UPLC-Q-TOF/MS metabolomics analysis method was established to explore the pathogenesis of colon cancer and the molecular mechanism of AC. The correlation analysis of metabolite changes and tumor growth was analyzed by R language. The result showed that AC at the ratio of 2:1 showed the best effect on inhibiting tumor growth, also the liver and spleen metastasis rate. A total of 23 potential biomarkers were detected in the serum of colon cancer mice by the analysis of Progenesis QI (Version 2.4) software. Among this, 11 metabolites including purines, steroids, phytosphingosine and l-palmitoylcarnitine were up-regulated in CC mice, while 12 metabolites like amino acids, deoxyribose and dihydrobiopterin were down-regulated in CC mice. After the treatment of AC for 15 days, 8 biomarkers were up-regulated, and 9 biomarkers down-regulated. Especially, AC at the ratio of 2:1 showed a significant callback effect on metabolic biomarkers, such as hypoxanthine, xanthosine, 7-methylxanthine, all-trans-retinoic acid, dihomo-γ-linolenic acid. 8 metabolic pathways: Aminoacyl-tRNA biosynthesis, Nicotinate and nicotinamide metabolism, Phenylalanine, tyrosine and tryptophan biosynthesis, Valine, leucine and isoleucine biosynthesis, Phenylalanine metabolism, Caffeine metabolism, Retinol metabolism, Alanine, aspartate and glutamate metabolism were selected as the model group disturbed metabolic pathways after the enrichment of MetaboAnalyst 4.0 online analysis software. And compared with the model group, Valine, leucine and isoleucine biosynthesis, Aminoacyl-tRNA biosynthesis, Caffeine metabolism pathway and Retinol metabolism pathways were altered after the intervention of AC. The correlation analysis results showed that various endogenous metabolites in serum have a strong correlation with tumor weight, such as hypoxanthine, which provides a basis for the selection of clinical markers. The results showed that AC can partially regulate metabolic disorder of CC mice by reversing the changes of metabolites, so as to inhibit the growth and metastasis of colon cancer, especially at the ratio of 2:1. These findings can provide a scientific basis for exploring the diagnostic biomarkers of colon cancer, and for clinical application of AC in the treatment of CRC program.

Sun R ，Gu J ，Chang X ，Liu F ，Liang Y ，Yang X ，Liang L ，Tang D ... -  《-》