Xiaohang Zhou

An integrated chinmedomics strategy for discovery of effective constituents from traditional herbal medicine

Traditional natural product discovery affords no information about compound structure or pharmacological activities until late in the discovery process, and leads to low probabilities of finding compounds with unique biological properties. By integrating serum pharmacochemistry-based screening with high-resolution metabolomics analysis, we have developed a new platform, termed chinmedomics which is capable of directly discovering the bioactive constituents. In this work, the focus is on ShenQiWan (SQW) treatment of ShenYangXu (SYX, kidney-yang deficiency syndrome) as a case study, as determined by chinmedomics. With serum pharmacochemistry, a total of 34 peaks were tentatively characterised in vivo, 24 of which were parent components and 10 metabolites were detected. The metabolic profiling and potential biomarkers of SYX were also investigated and 23 differential metabolites were found. 20 highly correlated components were screened by the plotting of correlation between marker metabolites and serum constituents and considered as the main active components of SQW. These compounds are imported into a database to predict the action targets: 14 importantly potential targets were found and related to aldosterone-regulated sodium reabsorption and adrenergic signaling pathways. Our study showed that integrated chinmedomics is a powerful strategy for discovery and screening of effective constituents from herbal medicines.

Phenotypic characterization of nanshi oral liquid alters metabolic signatures during disease prevention

This paper was designed to investigate the phenotypic characterization of Nanshi Oral Liquid (NOL) alters metabolic signatures of the ‘Kidney Yang Deficiency syndrome’ (KYDS). Urine metabolites were profiled by UPLC-ESI-Q-TOF-HDMS. The significantly changed metabolites such as xanthurenic acid, 4,8-dihydroxyquinoline, 3-methyldioxyindole, 4,6-dihydroxyquinoline, kynurenic acid, hippuric acid, taurine, tyramine, and 3-metanephrine, had been identified, and were related to the disturbance in tyrosine metabolism, steroid hormone biosynthesis, taurine and hypotaurine metabolism, tryptophan metabolism, phenylalanine metabolism and lysine degradation, which were helpful to further understanding the KYDS and intervention mechanism of NOL. The biochemical result showed that NOL can alleviate the kidney impairment induced by KYDS. Metabolomics results indicated the significantly changed metabolites were found to be reasonable in explaining the action mechanism of NOL. Interestingly, the effectiveness of NOL against KYDS was proved using the established metabolomics method and regulated the biomarkers as well as adjusted the metabolic disorder pathways. NOL had potentially pharmacological effect through regulating multiple perturbed pathways to normal state. This work showed that the metabolomics method was a powerful approach for studying the phenotypic characterization of disease’s syndrome during disease prevention and its intervention mechanism.

Serum metabolomics strategy for understanding pharmacological effects of ShenQi pill acting on kidney yang deficiency syndrome.

Kidney yang deficiency syndrome, a diagnostic pattern in Chinese medicine, is similar with clinical features of the glucocorticoid withdrawal syndrome. The aim of this present study was to explore low molecular mass differentiating metabolites between control group and model group of kidney yang deficiency rats induced with corticosterone as well as the therapeutic effect of Shen Qi Pill, a classic traditional Chinese medicine formula for treating Kidney yang deficiency syndrome in China. This study utilized ultra-performance liquid chromatography coupled with electrospray ionization synapt quadrupole time-of-flight high definition mass spectrometry (UPLC/ESI-SYNAPT-QTOF-HDMS) to identify the underlying biomarkers for clarifying mechanism of Shen Qi Pill in treating Kidney yang deficiency syndrome based on metabolite profiling of the serum samples and in conjunction with multivariate and pathway analysis. Meanwhile, blood biochemistry assay and histopathology were examined to identify specific changes in the model group rats. Distinct changes in the pattern of metabolites were observed by UPLC-HDMS. The changes in metabolic profiling were restored to their baseline values after treatment with Shen Qi Pill according to the combined with a principal component analysis (PCA) score plots. Altogether, the current metabolomics approach based on UPLC-HDMS and orthogonal projection to latent structures discriminate analysis (OPLS-DA) demonstrated 27 ions (18 in the negative mode, 9 in the positive mode, 17 ions restored by Shen Qi Pill). These results indicated that effectiveness of Shen Qi Pill in Kidney yang deficiency syndrome rats induced a substantial change in the metabolic profiles by regulating the biomarkers and adjusting the metabolic disorder. It suggested that the metabolomics approach was a powerful approach for elucidation of pathologic changes of Chinese medicine syndrome and action mechanisms of traditional Chinese medicine.

Discovery and verification of the potential targets from bioactive molecules by network pharmacology-based target prediction combined with high-throughput metabolomics

Natural products are an invaluable source for drug candidates. Currently, plasma metabolome has suggested that compounds present in herbs may exert bioactivity. The present investigation employed global metabolome analysis technology to explore the key target and action mechanism of scoparone, a representative ingredient of Yinchenhao (Artemisia capillaris Thunb.). First, we applied different databases for target prediction and focused on the potential targets of scoparone by network pharmacology, which also theoretically characterizes the effectiveness of scoparone on molecular docking. Among them, we selected the top predictions as the potential and crucial target. Then, non-targeted metabolomics technology based on an advanced UPLC-MS instrument coupled with a robust data processing platform was employed to characterize the metabolic profiling of alcoholic liver disease (ALD) rats. Furthermore, the ingenuity pathway analysis platform was used for metabolic network analysis, which mainly involved multiple-pathways, including tyrosine metabolism, glutathione metabolism, and primary bile acid biosynthesis. Interestingly, as a core biomarker, dopaquinone is directly related with target prediction of tyrosinase and finally resulted in a series of disturbances. Moreover, the prediction also validated the target on a metabolic level. The present investigation demonstrated that global metabolome analysis could provide a novel strategy for deciphering the potential drug targets of natural products.

Novel chinmedomics strategy for discovering effective constituents from ShenQiWan acting on ShenYangXu syndrome

Elucidation of the efficacy of traditional Chinese medicine (TCM) is of importance for scientists of modern medicine to understand the value of TCM clinical experience, and it is necessary to have a biological language to scientifically describe the efficacy of TCM. With this background?Chinmedomics has been proposed by our team, which includes integrating serum pharmacochemistry and metabolomics technology, defining theory and research methods for expressing the efficacy of TCMs based on the biomarkers discovery of TCM syndrome and elucidating the efficacy of TCM formulae, discovering effective constituents, and finally elucidating the scientific value of TCM. In the present study, the innovative chinmedomics strategy was conducted to evaluate the therapeutic effects of ShenQiWan (SQW) acting on ShenYangXu (kidney-yang deficiency syndrome, KYDS). We analyzed the urine metabolic trajectory between the model and control groups, and identified the biomarkers by the multivariate analysis. We found that SQW caused significant restoration of abnormal metabolism of KYDs. Using the method of metabolomics, 17 potential urine biomarkers were analyzed through 4 repeated tests in our serial studies on SQW and KYDS. Under the premise of therapeutic efficacy, a total of 56 peaks were tentatively characterized in vivo by the use of serum pharmacochemistry. Correlation analysis between marker metabolites and in vivo constituents of SQW showed that 28 compositions had a close relationship with urine biomarkers of therapeutic effects, whichmight play a key role in the therapeutic effect of SQW. These compounds were imported into an online database to predict their targets. Twenty-three important potential targets were identified, which were related to the metabolism of steroid hormone, tryptophan utilization, and thyroid hormone. In conclusion, chinmedomics is a useful strategy for discovery of potentially effective constituents from complex TCM formulae.

High-throughput chinmedomics-based prediction of effective components and targets from herbal medicine AS1350

This work was designed to explore the effective components and targets of herbal medicine AS1350 and its effect on “Kidney-Yang Deficiency Syndrome” (KYDS) based on a chinmedomics strategy which is capable of directly discovering and predicting the effective components, and potential targets, of herbal medicine. Serum samples were analysed by UPLC-MS combined with pattern recognition analysis to identify the biomarkers related to the therapeutic effects. Interestingly, the effectiveness of AS1350 against KYDS was proved by the chinmedomics method and regulated the biomarkers and targeting of metabolic disorders. Some 48 marker metabolites associated with alpha-linolenic acid metabolism, fatty acid metabolism, sphingolipids metabolism, phospholipid metabolism, steroid hormone biosynthesis, and amino acid metabolism were identified. The correlation coefficient between the constituents in vivo and the changes of marker metabolites were calculated by PCMS software and the potential effective constituents of AS1350 were also confirmed. By using chinmedomics technology, the components in AS1350 protecting against KYDS by re-balancing metabolic disorders of fatty acid metabolism, lipid metabolism, steroid hormone biosynthesis, etc. were deduced. These data indicated that the phenotypic characterisations of AS1350 altering the metabolic signatures of KYDS were multi-component, multi-pathway, multi-target, and overall regulation in nature.

Metabolomics‐proteomics profiles delineate metabolic changes in kidney fibrosis disease

Kidney fibrosis (KF) is a common process that leads to the progression of various types of kidney disease including kidney‐yang deficiency syndrome, however, little is known regarding the underlying biology of this disorder. Fortunately, integrated omics approaches provide the molecule fingerprints related to the disease. In an attempt to address this issue, we integrated metabolomics–proteomics profiles analyzed pathogenic mechanisms of KF based on rat model. A total 37 serum differential metabolites were contributed to KF progress, involved several important metabolic pathways. Using iTRAQ‐based quantitative proteomics analysis, 126 differential serum proteins were identified and provide valuable insight into the underlying mechanisms of KF. These proteins appear to be involved in complement and coagulation cascades, regulation of actin cytoskeleton, MAPK signaling pathway, RNA transport, etc. Interestingly, pathway/network analysis of integrated proteomics and metabolomics data firstly reveals that these signaling pathways were closely related with KF. It further indicated that most of these proteins play a pivotal role in the regulation of metabolism pathways.

Insight into the metabolic mechanism of scoparone on biomarkers for inhibiting Yanghuang syndrome

Scoparone (6,7-dimethoxycoumarin) is the representative ingredient of Yinchenhao (Artemisia capillaris Thunb.) which is a famous Chinese medicinal herb and shows favorable efficacy for all kinds of liver disease, specifically for the treatment of Yanghuang syndrome (YHS). The precise molecular mechanism concerning the action of scoparone on YHS is yet to be fully elucidated. The aim of the present study was to determine the mechanism of scoparone and evaluate its efficacy on metabolite levels. The differential expression of metabolites responsible for the pharmacological effects of scoparone was characterized and the protection effect of scoparone against this disease. Using multivariate statistical analysis, 33 biomarkers were identified using precise MS/MS and play an important role in the regulation of key metabolic pathways associated with liver disease. In addition, pathological results also showed consistent changes in the YHS model group and after treatment with scoparone, both the metabolic profile and histopathology resembled that of normal level, which suggesting favorable efficacy over the observed time period. The present work indicated that a metabolomics platform provided a new insight into understanding the mechanisms of action of natural medicines such as scoparone.

Network pharmacology combined with functional metabolomics discover bile acid metabolism as a promising target for mirabilite against colorectal cancer

In this study, a combination of network pharmacology and metabolomics was used to explore the mechanism by which mirabilite regulates bile acid metabolism in the treatment of colorectal cancer. The PharmMapper web server was applied to make preliminary predictions for the treatment targets of mirabilite and to predict the interaction between mirabilite and disease targets using Discovery Studio 2.5. Furthermore, the urine metabolic profile was analyzed by the UPLC-Q-TOF-MS technology. The original data were processed by Progenesis QI software and analyzed by multivariate pattern recognition, which allowed us to reveal the metabolic disturbance in colorectal cancer and explain the therapeutic effect of mirabilite. The network pharmacology results showed that mirabilite can act on the disease targets, and the sites of action include amino acid residues Arg-364 and Asp-533, as well as nucleotides TPC-11, DG-112 and DA-113. Based on metabolomics, potential biomarkers were found to lie in the relevant pathways of bile acid metabolism, such as taurine, chenodeoxycholic acid, cholic acid, and deoxycholic acid. The results showed that mirabilite could regulate the distribution of overall metabolic disturbance, and bile acid metabolism was the main targeted pathway. Additionally, we predicted the upstream targets by ingenuity pathway analysis and found that mirabilite played a significant role in regulating the bile acid-related biomarkers, which allowed comprehensive analysis of the effect of mirabilite on colorectal cancer. This study fully explained the role of mirabilite in inhibiting colorectal cancer, which mainly occurs through bile acid metabolism, via the approach of network pharmacology combined with functional metabolomics.

High-throughput lipidomics reveal mirabilite regulating lipid metabolism as anticancer therapeutics

Altered lipid metabolism is an emerging hallmark of cancers. Mirabilite has a therapeutic effect on colorectal cancer (CRC); however, its metabolic mechanism remains unclear. This study aims to explore the potential therapeutic targets of mirabilite protection against colorectal cancer in APCmin/+ mice model. Oral administration of mirabilite was started from the ninth month, while the same dosage of distilled water was given to both the control group and the model group. Based on lipidomics, we collected serum samples of all mice at the 20th week and used a non-targeted method to identify the lipid biomarkers of CRC. Compared with C57BL/6J mice, the metabolic profile of CRC model mice was significantly disturbed, and we identified that 25 lipid-related biomarkers, including linoleic acid, 2-hydroxybutyric acid, 6-deoxocastasterone, hypoxanthine, PC(16:1), PC(18:4), and retinyl acetate, were associated with CRC. According to the abovementioned results, there were six lipid molecules with significant differences that can be used as new targets for handling of CRC through six metabolic pathways, namely, linoleic acid metabolism, retinol metabolism, propanoate metabolism, arachidonic acid metabolism, biosynthesis of unsaturated fatty acids and purine metabolism. Compared with the model group, the metabolic profiles of these disorders tend to recover after treatment. These results indicated that the lipid molecules associated with CRC were regulated by mirabilite. In addition, we identified seven key lipid molecules, of which four had statistical significance. After administration of mirabilite, all disordered metabolic pathways showed different degrees of regulation. In conclusion, high-throughput lipidomics approach revealed mirabilite regulating the altered lipid metabolism as anticancer therapeutics.