Chinmedomics: a potent tool for the evaluation of traditional Chinese medicine efficacy and identification of its active components

As an important part of medical science, Traditional Chinese Medicine (TCM) attracts much public attention due to its multi-target and multi-pathway characteristics in treating diseases. However, the limitations of traditional research methods pose a dilemma for the evaluation of clinical efficacy, the discovery of active ingredients and the elucidation of the mechanism of action. Therefore, innovative approaches that are in line with the characteristics of TCM theory and clinical practice are urgently needed. Chinmendomics, a newly emerging strategy for evaluating the efficacy of TCM, is proposed. This strategy combines systems biology, serum pharmacochemistry of TCM and bioinformatics to evaluate the efficacy of TCM with a holistic view by accurately identifying syndrome biomarkers and monitoring their complex metabolic processes intervened by TCM, and finding the agents associated with the metabolic course of pharmacodynamic biomarkers by constructing a bioinformatics-based correlation network model to further reveal the interaction between agents and pharmacodynamic targets. In this article, we review the recent progress of Chinmedomics to promote its application in the modernisation and internationalisation of TCM.

Metabolomics analysis of urine from patients with alcohol-associated liver disease reveals dysregulated caffeine metabolism

Excess alcohol intake causes millions of deaths annually worldwide. Asymptomatic early-stage, alcohol-associated liver disease (ALD) is easily overlooked, and ALD is usually only diagnosed in more advanced stages. We explored the possibility of using polar urine metabolites as biomarkers of ALD for early-stage diagnosis and functional assessment of disease severity by quantifying the abundance of polar metabolites in the urine samples of healthy controls (n = 18), patients with mild or moderate liver injury (n = 21), and patients with severe alcohol-associated hepatitis (n = 25). The polar metabolites in human urine were first analyzed by untargeted metabolomics, showing that 209 urine metabolites are significantly changed in patients, and 17 of these are highly correlated with patients' model for end-stage liver disease (MELD) score. Pathway enrichment analysis reveals that the caffeine metabolic pathway is the most affected in ALD. We then developed a targeted metabolomics method and measured the concentration of caffeine and its metabolites in urine using internal and external standard calibration, respectively. The described method can quantify caffeine and its 14 metabolites in 35 min. The results of targeted metabolomics analysis agree with the results of untargeted metabolomics, showing that 13 caffeine metabolites are significantly decreased in patients. In particular, the concentrations of 1-methylxanthine, paraxanthine, and 5-acetylamino-6-amino-3-methyluracil are markedly decreased with increased disease severity. We suggest that these three metabolites could serve as functional biomarkers for differentiating early-stage ALD from more advanced liver injury.NEW & NOTEWORTHY Our study using both untargeted and targeted metabolomics reveals the caffeine metabolic pathway is dysregulated in ALD. Three caffeine metabolites, 1-methylxanthine, paraxanthine, and 5-acetylamino-6-amino-3-methyluracil, can differentiate the severity of early-stage ALD.

Metabolomics Analysis Coupled With UPLC/MS on Therapeutic Effect of Jigucao Capsule Against Dampness-Heat Jaundice Syndrome

Dampness-heat Jaundice Syndrome (DHJS) is a complex Chinese medicine syndrome, while Jigucao capsule (JGCC) is an effective compound preparation of Chinese medicine for the treatment of DHJS about liver and gallbladder, but its mechanism is not clear yet. The purpose of this study is to clarify the pathogenesis of DHJS and the treatment mechanism of JGCC. We used ultra-high performance liquid chromatography/mass spectrometry (UPLC/MS) combined with pattern recognition, accompanied the advanced software and online database for the urine metabolomics of rats. The potential biomarkers disturbing metabolism were identified and the metabolic pathway was analyzed. We investigated the callback of biomarkers after treatment with JGCC. Finally, A total of 25 potential urine biomarkers were identified, including Arachidonic acid, Phenylpyruvic acid, L-Urobilin and so on, and 14 related metabolic pathways were disturbed. After treatment with JGCC, the clinical biochemical indexes and histopathological were significantly improved, and the disturbed biomarkers were also obviously adjusted. It is proved that JGCC has remarkable effect on the treatment of DHJS.

Determination of metabolic phenotype and potential biomarkers in the liver of heroin addicted mice with hepatotoxicity

BACKGROUND

Heroin is a semi-synthetic opioid that is commonly abused drugs in the world. It can cause hepatic injury and lead to multiple organs dysfunction to its addicts. Only a few reports exist on the metabolic changes and mechanisms in the liver of heroin-addicted mice with hepatic injury.

METHODS

Twelve adult male Kunming mice (30-40 g) were divided into two groups randomly. The mice in the heroin-addicted group were injected subcutaneously in the first ten days with an increased dosage of heroin from 10 mg/kg to 55 mg/kg. The dosage was then stabilized at 55 mg/kg for three days. The control group was injected with the same amount of saline in the same manner. The hepatic injury was confirmed through the combination of histopathological observation and aminotransferase (AST) and alanine aminotransferase (ALT) determination. The withdrawal symptoms were recorded and used for assessment of heroin addiction. Eventually, liver metabolic biomarkers of heroin-addicted mice with hepatotoxicity were measured using UHPLC-MS/MS.

RESULTS

Biochemical analysis and histopathological observation showed that heroin-addicted mice had a liver injury. The liver metabolites of heroin-addicted mice changed significantly. Metabonomics analysis revealed 41 metabolites in the liver of addicted heroin mice as biomarkers involving 34 metabolic pathways. Among them, glutathione metabolism, taurine and hypotaurine metabolism, vitamin B2 metabolism, riboflavin metabolism, and single-carbon metabolism pathways were markedly dispruted.

CONCLUSIONS

Heroin damages the liver and disrupts the liver's metabolic pathways. Glutathione, taurine, riboflavin, 4-pyridoxate, folic acid, and methionine are important metabolic biomarkers, which may be key targets of heroin-induced liver damage. Thus, this study provides an in-depth understanding of the mechanisms of heroin-induced hepatotoxicity and potential biomarkers of liver damage.

Chinmedomics, a new strategy for evaluating the therapeutic efficacy of herbal medicines

Herbal medicines have accumulated valuable clinical experience in thousands of years of applications in traditional Chinese medicine (TCM) or ethnomedicine. The unique multi-target efficacy on complex diseases made herbal medicines gained a global popularity in recent years. However, the characteristic of multi-component acting on multi-target poses a dilemma for the evaluation of therapeutic efficacy of herbal medicines. Advances in metabolomics enable efficient identification of the various changes in biological systems exposed to different treatments or conditions. The use of serum pharmacochemistry of TCM has significant implications for tackling the major issue in herbal medicines development-pharmacodynamic material basis. Chinmedomics integrates metabolomics and serum pharmacochemistry of TCM to investigate the pharmacodynamic material basis and effective mechanisms of herbal medicines on the basis of TCM syndromes and holds the promise of explaining therapeutic efficacy of herbal medicines in scientific language. In this review, the historical development of chinmedomics from concept formation to successful applications was discussed. We also took the systematic research of Yin Chen Hao Tang (YCHT) as an example to show the research strategy of chinmedomics.

Targeted Approaches for In Situ Gut Microbiome Manipulation

The 2019 Dudrick Research Symposium, entitled "Targeted Approaches for In Situ Gut Microbiome Manipulation," was held on March 25, 2019, at the American Society for Parenteral and Enteral Nutrition (ASPEN) 2019 Nutrition Science & Practice Conference in Phoenix, AZ. The Dudrick Symposium honors the many pivotal and innovative contributions to the development and advancement of parenteral nutrition (PN) made by Dr Stanley J. Dudrick, physician scientist, academic leader, and a founding member of ASPEN. As the 2018 recipient of the Dudrick award, Dr Gail Cresci organized and chaired the symposium. The symposium addressed the evolving field of nutrition manipulation of the gut microbiome as a means to mitigate disease and support health. Presentations focused on (1) the role of prebiotics as a means to beneficially support gut microbiome composition and function and health; (2) designer synbiotics targeted to support metabolic by-products altered by ethanol exposure and microbial effectors that manipulate host metabolic outcomes; and, lastly, (3) types of intervention designs used to study diet-gut microbiome interactions in humans and a review of findings from recent interventions, which tested the effects of diet on the microbiome and the microbiome's effect on dietary exposures. New molecular techniques and multiomic approaches have improved knowledge of the structure and functional activity of the gut microbiome; however, challenges remain in establishing causal relationships between changes in the gut microbial-community structure and function and health outcomes in humans.

Microbiome as a therapeutic target in alcohol-related liver disease

Alcohol-related liver disease is associated with significant changes in gut microbial composition. The transmissibility of ethanol-induced liver disease has been demonstrated using faecal microbiota transfer in preclinical models. This technique has also led to improved survival in patients with severe alcoholic hepatitis, suggesting that changes in the composition and function of the gut microbiota are causatively linked to alcohol-related liver disease. A major mechanism by which gut microbiota influence the development of alcohol-related liver disease is through a leaky intestinal barrier. This permits translocation of viable bacteria and microbial products to the liver, where they induce and promote inflammation, as well as contribute to hepatocyte death and the fibrotic response. In addition, gut dysbiosis is associated with changes in the metabolic function of the intestinal microbiota, bile acid composition and circulation, immune dysregulation during onset and progression of alcohol-related liver disease. Findings from preclinical and human studies will be used to demonstrate how alcohol causes intestinal pathology and contributes to alcohol-related liver disease and how the latter is self-perpetuating. Additionally, we summarise the effects of untargeted treatment approaches on the gut microbiota, such as diet, probiotics, antibiotics and faecal microbial transplantation in alcohol-related liver disease. We further discuss how targeted approaches can restore intestinal homeostasis and improve alcohol-related liver disease. These approaches are likely to add to the therapeutic options for alcohol-related liver disease independently or in conjunction with steroids.

Targeting regulation of tryptophan metabolism for colorectal cancer therapy: a systematic review

Colorectal cancer (CRC) is one of the most malignant cancers resulting from abnormal metabolism alterations. As one of the essential amino acids, tryptophan has a variety of physiological functions, closely related to regulation of immune system, central nervous system, gastrointestinal nervous system and intestinal microflora. Colorectal cancer, a type of high-grade malignancy disease, stems from a variety of factors and often accompanies inflammatory reactions, dysbacteriosis, and metabolic disorders. Colorectal cancer accompanies inflammation and imbalance of intestinal microbiota and affects tryptophan metabolism. It is known that metabolites, rate-limiting enzymes, and ARH in tryptophan metabolism are associated with the development of CRC. Specifically, IDO1 may be a potential therapeutic target in colorectal cancer treatment. Furthermore, the reduction of tryptophan amount is proportional to the poor quality of life for colorectal cancer patients. This paper aims to discuss the role of tryptophan metabolism in a normal organism and investigate the relationship between this amino acid and colorectal cancer. This study is expected to provide theoretical support for research related to targeted therapy for colorectal cancer. Furthermore, strategies that modify tryptophan metabolism, effectively inhibiting tumor progression, may be more effective for CRC treatment.

Colorectal cancer (CRC) is one of the most malignant cancers resulting from abnormal metabolism alterations.

Pan-cancer analysis of transcriptional metabolic dysregulation using The Cancer Genome Atlas

Understanding metabolic dysregulation in different disease settings is vital for the safe and effective incorporation of metabolism-targeted therapeutics in the clinic. Here, using transcriptomic data for 10,704 tumor and normal samples from The Cancer Genome Atlas, across 26 disease sites, we present a novel bioinformatics pipeline that distinguishes tumor from normal tissues, based on differential gene expression for 114 metabolic pathways. We confirm pathway dysregulation in separate patient populations, demonstrating the robustness of our approach. Bootstrapping simulations were then applied to assess the biological significance of these alterations. We provide distinct examples of the types of analysis that can be accomplished with this tool to understand cancer specific metabolic dysregulation, highlighting novel pathways of interest, and patterns of metabolic flux, in both common and rare disease sites. Further, we show that Master Metabolic Transcriptional Regulators explain why metabolic differences exist, can segregate patient populations, and predict responders to different metabolism-targeted therapeutics.

Mass spectrometry-driven drug discovery for development of herbal medicine

Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high-throughput technology for advancing drug discovery from HM in the post-genomic era. It is essential to develop an efficient, high-quality, high-throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics-guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high-throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes.

Intestinal dysbiosis and permeability: the yin and yang in alcohol dependence and alcoholic liver disease

Alcohol dependence and alcoholic liver disease represent a major public health problem with substantial morbidity and mortality. By yet incompletely understood mechanisms, chronic alcohol abuse is associated with increased intestinal permeability and alterations of the gut microbiota composition, allowing bacterial components, bacteria, and metabolites to reach the portal and the systemic circulation. These gut-derived bacterial products are recognized by immune cells circulating in the blood or residing in remote organs such as the liver leading to the release of pro-inflammatory cytokines which are considered important mediators of the liver-gut-brain communication. Although circulating cytokines are likely not the sole factors involved, they can induce liver inflammation/damage and reach the central nervous system where they favor neuroinflammation which is associated with change in mood, cognition, and drinking behavior. In this review, the authors focus on the current evidence describing the changes that occur in the intestinal microbiota with chronic alcohol consumption in conjunction with intestinal barrier breakdown and inflammatory changes sustaining the concept of a gut-liver-brain axis in the pathophysiology of alcohol dependence and alcoholic liver disease.

High-throughput metabolomics enables metabolite biomarkers and metabolic mechanism discovery of fish in response to alkalinity stress

High throughput mass spectrometry (MS)-based metabolomics is a popular platform for small molecule metabolites analyses that are widely used for detecting biomarkers in the research field of environmental assessment. Crucian carp (Carassius carassius, CC) is an economically and ecologically important fish in Asia. It can adapt to extremely high alkalinity, providing us with valuable material to understand the adaptation mechanism for extreme environmental stress. However, the information on the metabolite biomarkers and metabolic mechanisms of CC exposed to alkaline stress is not entirely clear. We applied high-throughput UPLC-Q-TOF/MS combined with chemometrics to identify changes in the metabolome of CC exposed to different concentrations of alkalinity for long term effects. Metabolic differences among alkalinity-treated groups were identified by multivariate statistical analysis. Further, 7 differential metabolites were found after exposure to alkaline conditions. In total, 23 metabolic pathways of these differential metabolites were significantly affected. Alkalinity exposure resulted in widespread change in metabolic profiles in the plasma with disruptions in the phenylalanine metabolism, glycine, serine and threonine metabolism, pyruvate metabolism, tyrosine metabolism, etc. The integrated pathway analysis of the associated metabolites showed that tRNA charging, l-cysteine degradation II, superpathway of methionine degradation, l-serine degradation, tyrosine biosynthesis IV, etc. appear to be the most significantly represented functional categories. Overall, this study demonstrated that metabolic changes in CC played a role in adaptation to the highly alkaline environmental stress.

High throughput mass spectrometry (MS)-based metabolomics is a popular platform for small molecule metabolites analyses that are widely used for detecting biomarkers in the research field of environmental assessment.

High-throughput metabolomics used to identify potential therapeutic targets of Guizhi Fuling Wan against endometriosis of cold coagulation and blood stasis

Metabolomics is an emerging and robust discipline and involves the comprehensive evaluation of small molecule endogenous metabolites and enables the exploration of the pathogenesis of diseases. For example, endometriosis – a common disease which mostly occurs in women of childbearing age. A cure for endometriosis of cold coagulation and blood stasis (ECB) is highly sought after. This study was conducted to discover the potential biomarkers of ECB and the effective mechanism undertaken by Guizhi Fuling Wan (GFW) in treating ECB in rats. Urinary metabolomics were performed by using UPLC-Q-TOF-MS with pattern recognition methods to evaluate the changes in metabolic profiles and to identify biomarkers for elucidating the mechanism of the treatment of ECB with GFW. The results showed that urinary metabolism in the two groups were distinctly separated on the 28^th day, and a total of 20 differential biomarkers (16 in the positive mode, 4 in the negative mode) were confirmed involving several key metabolic pathways which included phenylalanine, tyrosine and tryptophan biosynthesis, valine, leucine and isoleucine biosynthesis, glyoxylate and dicarboxylate metabolism, tyrosine metabolism and the citrate cycle. Following the oral administration of GFW, certain pathways were affected; these included the following: phenylalanine, tyrosine and tryptophan biosynthesis, valine, leucine and isoleucine biosynthesis, glyoxylate and dicarboxylate metabolism, tyrosine metabolism, citrate cycle, steroid hormone biosynthesis, tryptophan metabolism, phenylalanine metabolism, primary bile acid biosynthesis, and aminoacyl-tRNA biosynthesis. This study also demonstrated that the administration of GFW affected the levels of urine endogenous metabolites, thereby laying a foundation for further study of the pharmacodynamical mechanism of GFW.

Metabolomics is an emerging and robust discipline and involves the comprehensive evaluation of small molecule endogenous metabolites and enables the exploration of the pathogenesis of diseases.

Dissect new mechanistic insights for geniposide efficacy on the hepatoprotection using multiomics approach

A multi-omics approach could yield in-depth mechanistic insights. Here, we performed an integrated analysis of miRNAome, proteome and metabolome, aimed to investigate the underlying mechanism of active product geniposide in ethanol-induced apoptosis. We found that integrative meta-analysis identified 28 miRNAs, 20 proteins and 7 metabolites significantly differentially expressed, respectively. Further analysis identified geniposide extensively regulated multiple metabolism pathways and the most important related pathway was citrate cycle (TCA cycle). In addition, geniposide can improve energy metabolism benefits using the Extracellular Flux Analyzer. Of particular significance, miR-144-5p exhibits a high positive correlation with oxoglutaric acid, isocitrate dehydrogenase (IDH) 1 and 2 that involved in the TCA cycle. Furthermore,we discovered that miR-144-5p regulates TCA cycle metabolism through IDH1 and IDH2. Collectively, we describe for the first time the hepatoprotective effect of geniposide decreased miR-144-5p level, capable of regulating TCA cycle by directly targeting IDH1 and IDH2 and promoting functional consequences in cells. Integrating metabolomics, miRNAomics and proteomics approach and thereby analyzing microRNAs and proteins as well as metabolites can give valuable information about the functional regulation pattern and action mechanism of natural products.

Metabolic characterization and pathway analysis of berberine protects against prostate cancer

Recent explosion of biological data brings a great challenge for the traditional methods. With increasing scale of large data sets, much advanced tools are required for the depth interpretation problems. As a rapid-developing technology, metabolomics can provide a useful method to discover the pathogenesis of diseases. This study was explored the dynamic changes of metabolic profiling in cells model and Balb/C nude-mouse model of prostate cancer, to clarify the therapeutic mechanism of berberine, as a case study. Here, we report the findings of comprehensive metabolomic investigation of berberine on prostate cancer by high-throughput ultra performance liquid chromatography-mass spectrometry coupled with pattern recognition methods and network pathway analysis. A total of 30 metabolite biomarkers in blood and 14 metabolites in prostate cancer cell were found from large-scale biological data sets (serum and cell metabolome), respectively. We have constructed a comprehensive metabolic characterization network of berberine to protect against prostate cancer. Furthermore, the results showed that berberine could provide satisfactory effects on prostate cancer via regulating the perturbed pathway. Overall, these findings illustrated the power of the ultra performance liquid chromatography-mass spectrometry with the pattern recognition analysis for large-scale biological data sets may be promising to yield a valuable tool that insight into the drug action mechanisms and drug discovery as well as help guide testable predictions.

Screening the active compounds of Phellodendri Amurensis cortex for treating prostate cancer by high-throughput chinmedomics

Screening the active compounds of herbal medicines is of importance to modern drug discovery. In this work, an integrative strategy was established to discover the effective compounds and their therapeutic targets using Phellodendri Amurensis cortex (PAC) aimed at inhibiting prostate cancer as a case study. We found that PAC could be inhibited the growth of xenograft tumours of prostate cancer. Global constituents and serum metabolites were analysed by UPLC-MS based on the established chinmedomics analysis method, a total of 54 peaks in the spectrum of PAC were characterised in vitro and 38 peaks were characterised in vivo. Among the 38 compounds characterised in vivo, 29 prototype components were absorbed in serum and nine metabolites were identified in vivo. Thirty-four metabolic biomarkers were related to prostate cancer, and PAC could observably reverse these metabolic biomarkers to their normal level and regulate the disturbed metabolic profile to a healthy state. A chinmedomics approach showed that ten absorbed constituents, as effective compounds, were associated with the therapeutic effect of PAC. In combination with bioactivity assays, the action targets were also predicted and discovered. As an illustrative case study, the strategy was successfully applied to high-throughput screening of active compounds from herbal 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.

High-throughput metabolomics approach reveals new mechanistic insights for drug response of phenotypes of geniposide towards alcohol-induced liver injury by using liquid chromatography coupled to high resolution mass spectrometry

Alcohol-induced liver injury (ALD) shows obvious metabolic disorders, categorized by a wide range of metabolite abnormalities.

Exploring potential biomarkers and determining the metabolic mechanism of type 2 diabetes mellitus using liquid chromatography coupled to high-resolution mass spectrometry

Diabetes mellitus has imposed a huge burden on modern society and is a serious threat to human health globally.

Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects

BACKGROUND

Alcohol-dependence (AD) is a ravaging public health and social problem. AD diagnosis depends on questionnaires and some biomarkers, which lack specificity and sensitivity, however, often leading to less precise diagnosis, as well as delaying treatment. This represents a great burden, not only on AD individuals but also on their families. Metabolomics using nuclear magnetic resonance spectroscopy (NMR) can provide novel techniques for the identification of novel biomarkers of AD. These putative biomarkers can facilitate early diagnosis of AD.

OBJECTIVES

To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics.

METHOD

Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC).

RESULTS

The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0).

CONCLUSION

This study revealed that metabolomics analysis of urine using NMR identified AD novel biomarkers which can discriminate AD from social drinkers and controls with high accuracy.