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.

Multi-Channel Metabolomics Analysis Identifies Novel Metabolite Biomarkers for the Early Detection of Fatty Liver Disease in Dairy Cows

Fatty liver disease, a type of metabolic disorder, frequently occurs in dairy cows during the parturition period, causing a high culling rate and, therefore, considerable economic losses in the dairy industry owing to the lack of effective diagnostic methods. Here, metabolite biomarkers were identified and validated for the diagnosis of metabolic disorders. A total of 58 participant cows, including severe fatty liver disease and normal control groups, in the discovery set (liver biopsy tested, n = 18), test set (suspected, n = 20) and verification set (liver biopsy tested, n = 20), were strictly recruited and a sample collected for their feces, urine, and serum. Non-targeted GC-MS-based metabolomics methods were used to characterize the metabolite profiles and to screen in the discovery set. Eventually, ten novel biomarkers involved in bile acid, amino acid, and fatty acid were identified and validated in the test set. Each of them had a higher diagnostic ability than the traditional serum biochemical indicators, with an average area under the receiver operating characteristic curve of 0.830 ± 0.0439 (n = 10) versus 0.377 ± 0.182 (n = 9). Especially, combined biomarker panels via different metabolic pipelines had much better diagnostic sensitivity and specificity than every single biomarker, suggesting their powerful utilization potentiality for the early detection of fatty liver disease. Intriguingly, the serum biomarkers were confirmed perfectly in the verification set. Moreover, common biological pathways were found to be underlying the pathogenesis of fatty liver syndrome in cattle via different metabolic pipelines. These newly-discovered and non-invasive metabolic biomarkers are meaningful in reducing the high culling rate of cows and, therefore, benefit the sustainable development of the dairy industry.

Metabolic Profiling Analysis of the Effect and Mechanism of Gushiling Capsule in Rabbits With Glucocorticoid-Induced Osteonecrosis of the Femoral Head

Gushiling capsule (GSLC) is an effective traditional Chinese medicine for the treatment of glucocorticoid-induced osteonecrosis of the femoral head (GIONFH). This study established the serum metabolite profiles of GSLC in rabbits and explored the metabolic mechanism and effect of GSLC on GIONFH. Seventy-five Japanese white rabbits were randomly divided into the control, model, and GSLC groups. The rabbits in the model group and the GSLC group received injection of prednisolone acetate. Meanwhile, rabbits in the GSLC group were treated by gavage at a therapeutic dose of GSLC once a day. The control group and the model group received the same volume of normal saline gavage. Three groups of serum samples were collected at different time points, and the changes in the metabolic spectrum were analyzed by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The resulting data set was analyzed using multivariate statistical analysis to identify potential biomarkers related to GSLC treatment. The metabolic pathway was analyzed by MetaboAnalyst 4.0 and a heatmap was constructed using the HEML1.0.3.7 software package. In addition, histopathological and radiography studies were carried out to verify the anti-GIONFH effects of GSLC. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) score plots revealed a significant separation trend between the control group and the model group and the GSLC group (1-3 weeks), but there were no significant differences in the GSLC group (4-6 weeks). Orthogonal PLS-DA (OPLS-DA) score plots also revealed an obvious difference between the model and the GSLC groups (4-6 weeks). Ten potential metabolite biomarkers, mainly phospholipids, were identified in rabbit serum samples and demonstrated to be associated with GIONFH. Hematoxylin and eosin staining and magnetic resonance imaging indicated that the pathological changes in femoral head necrosis in the GSLC group were less than in the model group, which was consistent with the improved serum metabolite spectrum. GSLC regulated the metabolic disorder of endogenous lipid components in GIONFH rabbits. GSLC may prevent and treat GIONFH mainly by regulating phospholipid metabolism in vivo.

Effect of synbiotic yogurt fortified with monk fruit extract on hepatic lipid biomarkers and metabolism in rats with type 2 diabetes

Monk fruit extract (MFE) is widely used as a sweetener in foods. In this study, the effects of the consumption of MFE-sweetened synbiotic yogurt on the lipid biomarkers and metabolism in the livers of type 2 diabetic rats were evaluated. The results revealed that the MFE-sweetened symbiotic yogurt affected the phosphatidylcholines, phosphatidylethanolamines, phosphatidylglycerol, lysophosphatidic acids, lysophosphatidylcholines, lysophosphatidylethanolamines, lysophosphatidylglycerols, lysophosphatidylinositols, lysophosphatidylserines, and fatty acid-hydroxy fatty acids biomarkers in the livers of type 2 diabetic rats. In addition, the consumption of the MFE-sweetened synbiotic yogurt significantly altered 12 hepatic metabolites, which are involved in phenylalanine metabolism, sphingolipid metabolism, bile secretion, and glyoxylate and dicarboxylate metabolism in the liver. Furthermore, a multiomics (metabolomic and transcriptomic) association study revealed that there was a significant correlation between the MFE-sweetened synbiotic yogurt and the metabolites and genes involved in fatty acid biosynthesis, bile secretion, and glyoxylate and dicarboxylate metabolism. The findings of this study will provide new insights on exploring the function of sweeteners for improving type 2 diabetes mellitus liver lipid biomarkers.

Elucidation of the Reinforcing Spleen Effect of Jujube Fruits Based on Metabolomics and Intestinal Flora Analysis

Jujube (Ziziphus jujuba Mill.) fruit (JF) is widely consumed as food in Asian countries due to its potential effects for human health. As a traditional Chinese medicine, JF is often used to treat anorexia, fatigue and loose stools caused by spleen deficiency syndromes in China, but the mechanism underlying this effect has not been thoroughly elucidated. In this study, a rat model of spleen deficiency syndromes was adopted to investigate the therapeutic effect of JF extract and its possible mechanism by metabolomics analyses of plasma and urine as well as the intestinal flora analysis. The results showed that the changes in plasma and urine metabolites caused by spleen deficiency were reversed after administration of JF, and these changed endogenous metabolites were mainly involved in retinol metabolism, pentose and glucuronate interconversions, nicotinate and niacinamide metabolism pathways. The 16S rDNA sequencing results showed that JF could regulate intestinal flora imbalance caused by spleen deficiency. The covariance analysis of intestinal flora structure and metabolome indicated that Aerococcus may be a candidate strain for predicting and treating the metabolic pathways of spleen deficiency and related disorders. In summary, it can be revealed that spleen deficiency, which alters metabolic profiles and the intestinal flora, could be alleviated effectively by JF extract.

Therapeutic Effect and Mechanism of Si-Miao-Yong-An-Tang on Thromboangiitis Obliterans Based on the Urine Metabolomics Approach

Si-Miao-Yong-An-Tang (SMYAT) is a classic prescription for the treatment of thromboangiitis obliterans (TAO). However, the effect and mechanism are still unclear. This experiment aims to evaluate the therapeutic effect and mechanism of SMYAT on sodium laurate solution induced thromboangiitis obliterans model rats using urine metabolomics. The therapeutic effect of SMYAT was evaluated by histopathology, hemorheology and other indexes. The urine metabolomic method, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used for clustering group and discriminant analysis to screen urine differential metabolic biomarkers, and explore new insight into pathophysiological mechanisms of SMYAT in the treatment of TAO. SMYAT has significant antithrombotic and anti-inflammatory effects, according to the results of urine metabolomic analysis, and regulate the metabolic profile of TAO rats, and its return profile is close to the state of control group. Through metabolomics technology, a total of 35 urine biomarkers of TAO model were characterized. Among them, SMYAT treatment can regulate 22 core biomarkers, such as normetanephrine and 4-pyridoxic acid. It is found that the therapeutic effect of SMYAT is closely related to the tyrosine metabolism, vitamin B6 metabolism and cysteine and methionine metabolism. It preliminarily explored the therapeutic mechanism of SMYAT, and provided a scientific basis for the application of SMYAT.

Serum Metabonomics Reveals Risk Factors in Different Periods of Cerebral Infarction in Humans

Studies of key metabolite variations and their biological mechanisms in cerebral infarction (CI) have increased our understanding of the pathophysiology of the disease. However, how metabolite variations in different periods of CI influence these biological processes and whether key metabolites from different periods may better predict disease progression are still unknown. We performed a systematic investigation using the metabonomics method. Various metabolites in different pathways were investigated by serum metabolic profiling of 143 patients diagnosed with CI and 59 healthy controls. Phe-Phe, carnitine C18:1, palmitic acid, cis-8,11,14-eicosatrienoic acid, palmitoleic acid, 1-linoleoyl-rac-glycerol, MAG 18:1, MAG 20:3, phosphoric acid, 5α-dihydrotestosterone, Ca, K, and GGT were the major components in the early period of CI. GCDCA, glycocholate, PC 36:5, LPC 18:2, and PA showed obvious changes in the intermediate time. In contrast, trans-vaccenic acid, linolenic acid, linoleic acid, all-cis-4,7,10,13,16-docosapentaenoic acid, arachidonic acid, DHA, FFA 18:1, FFA 18:2, FFA 18:3, FFA 20:4, FFA 22:6, PC 34:1, PC 36:3, PC 38:4, ALP, and Crea displayed changes in the later time. More importantly, we found that phenylalanine metabolism, medium-chain acylcarnitines, long-chain acylcarnitines, choline, DHEA, LPC 18:0, LPC 18:1, FFA 18:0, FFA 22:4, TG, ALB, IDBIL, and DBIL played vital roles in the development of different periods of CI. Increased phenylacetyl-L-glutamine was detected and may be a biomarker for CI. It was of great significance that we identified key metabolic pathways and risk metabolites in different periods of CI different from those previously reported. Specific data are detailed in the Conclusion section. In addition, we also explored metabolite differences of CI patients complicated with high blood glucose compared with healthy controls. Further work in this area may inform personalized treatment approaches in clinical practice for CI by experimentally elucidating the pathophysiological mechanisms.

High-throughput metabolomics using UPLC/Q-TOF-MS coupled with multivariate data analysis reveals the effect and mechanism of syringin against ovariectomized osteoporosis

Osteoporosis is an increasing public health problem in the worldwide and has caused socioeconomic burden. Natural products as candidates have the potential to promote bone formation and suppress bone resorption for osteoporosis treatment. Previously, syringin has showed the potent anti-osteoporosis activity, however the detailed mechanism of syringin against osteoporosis is still unclear. This study aimed to reveal the pharmacological effect and mechanism of syringin through the high-throughput metabolomics. In this study, metabolomics techniques were used to explore the metabolic biomarkers and profiles provides deep insights into the pharmacological effects and mechanism of syringin against osteoporosis. The metabolite biomarkers were monitored based on the high-resolution mass spectrometry. By the integration analysis of metabolomics technology, a total of 23 metabolic biomarkers were discovered and we found the highly relevant pathway involved in glycine and serine metabolism, butyrate metabolism, methionine metabolism, catecholamine biosynthesis, tyrosine metabolism, etc. Interestingly, synthesis and degradation of ketone bodies, phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, tyrosine metabolism, glycine, serine and threonine metabolism, butanoate metabolism, was related with efficacy of syringin. The present work showed that the metabolomics technology can provide novel strategies for revealing insights into the metabolic effects and action mechanism of drug.

13C Metabolic Flux Analysis Indicates Endothelial Cells Attenuate Metabolic Perturbations by Modulating TCA Activity

Disrupted endothelial metabolism is linked to endothelial dysfunction and cardiovascular disease. Targeted metabolic inhibitors are potential therapeutics; however, their systemic impact on endothelial metabolism remains unknown. In this study, we combined stable isotope labeling with ¹³C metabolic flux analysis (¹³C MFA) to determine how targeted inhibition of the polyol (fidarestat), pentose phosphate (DHEA), and hexosamine biosynthetic (azaserine) pathways alters endothelial metabolism. Glucose, glutamine, and a four-carbon input to the malate shuttle were important carbon sources in the baseline human umbilical vein endothelial cell (HUVEC) ¹³C MFA model. We observed two to three times higher glutamine uptake in fidarestat and azaserine-treated cells. Fidarestat and DHEA-treated HUVEC showed decreased ¹³C enrichment of glycolytic and TCA metabolites and amino acids. Azaserine-treated HUVEC primarily showed ¹³C enrichment differences in UDP-GlcNAc. ¹³C MFA estimated decreased pentose phosphate pathway flux and increased TCA activity with reversed malate shuttle direction in fidarestat and DHEA-treated HUVEC. In contrast, ¹³C MFA estimated increases in both pentose phosphate pathway and TCA activity in azaserine-treated cells. These data show the potential importance of endothelial malate shuttle activity and suggest that inhibiting glycolytic side branch pathways can change the metabolic network, highlighting the need to study systemic metabolic therapeutic effects.

Metabonomics of white adipose tissue and brown adipose tissue in Tupaia belangeri during cold acclimation

In the present study, liquid chromatography-mass spectrometer (LC-MS) was used to perform untargeted metabolomics analysis of white adipose tissue (WAT) and brown adipose tissue (BAT) in Tupaia belangeri during cold acclimation. Differences in biochemical composition between WAT and BAT were compared. Clarifying how the two adipose tissues respond to the lower temperature in terms of metabolomics, which elucidate the metabolic process and energy homeostasis regulation mechanism in T. belangeri. The results showed that there were 34, 59 and 20 differential metabolites in the WAT, BAT and WAT compared with BAT, respectively. WAT and BAT had significant differences in various metabolic pathways such as sugar metabolism, amino acid metabolism, lipid metabolism, and nucleotide metabolism, which were closely related to the different biological roles of the two tissues. Increasing the concentrations of intermediate products of tricarboxylic acid (TCA) cycle, pyruvic acid, and phosphoenolpyruvic acid (PEP) in WAT and increasing the metabolites in TCA cycle, glyoxylate and dicarboxylate metabolism pathways in BAT, likely to increase the thermogenic capacity in T. belangeri in response to cold stress. There were more differential metabolic pathways in BAT during cold acclimation than that of in WAT. Moreover, compared to WAT, BAT responds to cold stress by adjusting the concentration of nucleotide metabolites.

Untargeted metabolite profiling of liver in mice exposed to 2-methylfuran

Furan, a significant food contaminant, was found in many cooked foods. In most cooked foods, furan has been found to be coexisted with some alkylated derivatives such as 2-methylfuran. 2-methylfuran was found to be potent hepatotoxins. Little toxicological data is available for 2-methylfuran. The objective of this study was to investigate metabolite changes in the liver samples from mice fed with 2-methylfuran by untargeted metabolomic approach. Metabolomic analysis was conducted by using gas chromatography coupled with mass spectrometry (GC-MS). Twenty-four metabolites were identified as differential metabolites. The important metabolic pathway was linoleic acid metabolism, glycine, serine, and threonine metabolism, methane metabolism, ascorbate, and aldarate metabolism, valine, leucine, and isoleucine biosynthesis, arachidonic acid metabolism, alanine, aspartate, and glutamate metabolism, aminoacyl-tRNA biosynthesis, cysteine, and methionine metabolism, inositol phosphate metabolism, and pyruvate metabolism. These newly identified pathways provide evidence for investigating toxic mechanism of 2-methylfuran. PRACTICAL APPLICATION: Furan in foods has caused public health concern for its hepatotoxicity and hepatic carcinogenicity in rodents. The metabolomics method was constructed to find more biomarkers to study underlying hepatotoxic mechanisms of 2-methylfuran. It will offer important information for official limits of 2-methylfuran in foods.

Metabolomics approach based on utra-performance liquid chromatography coupled to mass spectrometry with chemometrics methods for high-throughput analysis of metabolite biomarkers to explore the abnormal metabolic pathways associated with myocardial dysfunction

Ultra-performance liquid chromatography/mass spectrometry-based metabolomics can been used for discovery of metabolite biomarkers to explore the metabolic pathway of diseases. Identification of metabolic pathways is key to understanding the pathogenesis and mechanism of disease. Myocardial dysfunction induced by sepsis (SMD) is a severe complication of septic shock and represents major causes of death in intensive care units; however its pathological mechanism is still not clear. In this study, ultrahigh-pressure liquid chromatography with mass spectrometry-based metabolomics with chemometrics anaylsis and multivariate pattern recognition analysis were used to detect urinary metabolic profile changes in a lipopolysaccharide-induced SMD mouse model. Multivariate statistical analysis including principal component analysis and orthogonapartial least squares discriminant analysis for the discrimination of SMD was conducted to identify potential biomarkers. A total of 19 differential metabolites were discovered by high-resolution mass spectrometry-based urinary metabolomics strategy. The altered biochemical pathways based on these metabolites showed that tyrosine metabolism, phenylalanine metabolism, ubiquinone biosynthesis and vitamin B6 metabolism were closely connected to the pathological processes of SMD. Consequently, integrated chemometric analyses of these metabolic pathways are necessary to extract information for the discovery of novel insights into the pathogenesis of disease.

Agarose hydrogel-enhanced paper spray ionization mass spectrometry for metabolite detection in raw urine

Rapid analysis of metabolites in biofluids is of great importance for disease diagnosis or new-born disease screening. Herein, we introduce an agarose hydrogel conditioning method to enhance the performance of paper spray ionization mass spectrometry. With facile and fast hydrogel conditioning, the signal intensity of therapeutic drugs spiked in urine was 5 to 15 fold higher than that in direct paper spray ionization mass spectrometry analysis. Consequently, the sensitivity of metabolites in urine was improved via hydrogel conditioning, resulting in 9 to 15 fold decrease in the possibility of detection (POD) levels. These results show that agarose hydrogel conditioning coupled with paper spray ionization mass spectrometry could serve as a facile ionization method for ambient mass spectrometry, which might be useful in fast screening of metabolites and therapeutic drugs in raw biofluids.

Comparative metabolomics unveils molecular changes and metabolic networks of syringin against hepatitis B mice by untargeted mass spectrometry

Untargeted metabolomics technology was used to discover the metabolic pathways and biomarkers for revealing the potential biological mechanism of syringin on hepatitis B virus. Serum samples were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS)-based comparative metabolomics coupled with pattern recognition methods and network pathway. In addition, the histopathology, HBV DNA detection of liver tissue, and biochemical indicators of liver function change were also explored for investigating the antiviral effect of syringin. In comparison to the model group, the metabolic profiles of the turbulence in transgenic mice tended to recover to the same as the control group after syringin therapy. A total of 33 potential biomarkers were determined to explore the metabolic disorders in the hepatitis B animal model, of which 25 were regulated by syringin, and 8 metabolic pathways, such as phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism, were involved. Syringin markedly reduced the liver pathology change, inhibited HBV DNA replication, and improved liver function. Amino acid metabolism is a potential target for the treatment of hepatitis B. The hepatoprotective effect of syringin may contribute to ameliorating oxidative stress and preventing protein and DNA replication. Comparative metabolomics is a promising tool for discovering metabolic pathways and biomarkers of the hepatitis B animal model as targets to reveal the effects and mechanism of syringin, which benefits the development of natural products and advances the treatment of diseases.

Untargeted metabolomics technology was used to discover the metabolic pathways and biomarkers for revealing the potential biological mechanism of syringin on hepatitis B virus.

Exploring the metabolic biomarkers and pathway changes in crucian under carbonate alkalinity exposure using high-throughput metabolomics analysis based on UPLC-ESI-QTOF-MS

The aims of this study is to explore the metabolomic biomarker and pathway changes in crucian under carbonate alkalinity exposures using high-throughput metabolomics analysis based on ultra-performance liquid chromatography-electrospray ionization-quadrupole time of flight-tandem mass spectrometry (UPLC-ESI-QTOF-MS) for carrying out adaptive evolution of fish in environmental exposures and understanding molecular physiological mechanisms of saline–alkali tolerance in fishes. Under 60 day exposure management, the UPLC-ESI-QTOF-MS technology, coupled with a pattern recognition approach and metabolic pathway analysis, was utilized to give insight into the metabolic biomarker and pathway changes. In addition, biochemical parameters in response to carbonate alkalinity in fish were detected for chronic impairment evaluation. A total of twenty-seven endogenous metabolites were identified to distinguish the biochemical changes in fish in clean water under exposure to different concentrations of carbonate alkalinity (CA); these mainly involved amino acid synthesis and metabolism, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism, pyruvate metabolism and the citrate cycle (TCA cycle). Compared with the control group, CA exposure increased the level of blood ammonia; TP; ALB; Gln in the liver and gills; GS; urea in blood, the liver and gills; CREA; CPS; Glu and LDH; and decreased the level of weight gain rate, oxygen consumption, discharge rate of ammonia, SOD, CAT, ALT, AST and Na⁺/K⁺-ATPase. At low concentrations, CA can change the normal metabolism of fish in terms of changing the osmotic pressure regulation capacity, antioxidant capacity, ammonia metabolism and liver and kidney function to adapt to the CA exposure environment. As the concentration of CA increases, various metabolic processes in crucian are inhibited, causing chronic damage to the body. The results show that the metabolomic strategy is a potentially powerful tool for identifying the mechanisms in response to different environmental exposomes and offers precious information about the chronic response of fish to CA.

We explore the metabolic biomarker and pathway changes accompanying the adaptive evolution of crucian subjected to carbonate alkalinity exposure, using UPLC-ESI-QTOF-MS, in order to understand the molecular physiological mechanisms of saline–alkali tolerance.

Integration of metabolomics and proteomics to reveal the metabolic characteristics of high-intensity interval training

Metabolomics and proteomics were integrated to research the molecular characterization of high-intensity interval training, revealing changes in biological pathways.

Ultra-performance liquid chromatography-mass spectrometry-based metabolomics reveals Huangqiliuyi decoction attenuates abnormal metabolism as a novel therapeutic opportunity for type 2 diabetes

Background: As a typical chronic metabolic disease, type 2 diabetes mellitus causes a heavy health-care burden to society. In this study, we applied the metabolomics strategy to explore the potential molecular mechanism of the Huangqiliuyi decoction (HQLYD) for type-2 diabetes (T2D). Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) combined with pattern recognition methods was utilized to select specific metabolites closely associated with HQLYD. Biomarker pathway analysis and biological network were utilized to uncover the therapeutic effect and action mechanism related to HQLYD. A total of twenty-five biomarkers were identified in the animal model, in which sixteen biomarkers are associated with HQLYD treatment for T2D. They attenuated the abnormalities of metabolic pathways such as phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, and the citrate cycle. HQLYD also significantly elevated the serum FINS and SOD, GSP-x level in the liver and kidney, and reduced the serum TC, TG, HDL, LDL, urea, Scr, AST, ALT, FBG, IRS, MDA, and CAT level. We found that the therapeutic mechanism of HQLYD against T2D affected amino acid metabolism, glucose metabolism and lipid metabolism. Metabolomics revealed that the Huangqiliuyi decoction attenuates abnormal metabolism as a novel therapeutic opportunity for type 2 diabetes.

Untargeted metabolomics using liquid chromatography coupled with mass spectrometry for rapid discovery of metabolite biomarkers to reveal therapeutic effects of Psoralea corylifolia seeds against osteoporosis

Liquid chromatography coupled with mass spectrometry has been used as metabolomics profiling tool to discover and identify the metabolites in metabolic diseases. Osteoporosis (OP) syndrome is a chronic metabolic disease characterized by bone mass reduction and changes in bone microstructure. Psoralea corylifolia Linn. seeds (PCS) have a therapeutic effect on osteoporosis, but their action mechanism and therapeutic target are still unclear. This study aims to explore the metabolic changes of the urine profile in glucocorticoid-induced OP model rats and the therapeutic effect of PCS. High-throughput metabolomics based on the liquid chromatography coupled with mass spectrometry quadrupole time-of-flight mass spectrometry and multivariate data analysis were used to analyze the urine metabolites. The results showed that has an obvious separation between model and control groups. OPLS-DA was used to further analyze and discover substances that contributed to the separation. 42 potential biomarkers and 12 related metabolic pathways were identified in combination with network databases. After the intervention of PCS, 24 biomarkers were significantly regulated, mainly with glycone, serine and threonine metabolism, glutathione metabolism and purine metabolism and other metabolic pathways are related and discovered. This study has proved that PCS has therapeutic effect against OP by regulating that metabolic pathways disturbed in the OP. It provided a basis for the research and future development of new drugs for OP treatment.

Liquid chromatography coupled with mass spectrometry has been used as metabolomics profiling tool to discover and identify the metabolites in metabolic diseases.

Discovering significantly different metabolites between Han and Uygur two racial groups using urinary metabolomics in Xinjiang, China

The main object of the study was to discover the associated significantly different metabolites between Han and Uygur, two main racial groups in Xinjiang, China with urinary metabolomics. Urine samples from 96 Han and 96 Uygur were analyzed using gas chromatography coupled to mass spectrometry (GCMS). Multivariate analysis was used to investigate the effect of race, age and gender on the urinary metabolomic profiles. Totally eight metabolites are identified contributed to the discrimination between Han and Uygur, including phenylacetylglutamine, myoinositol, d-galactose, ribonolactone, octadecanoic acid, galactitol, threonic acid and succinic acid. The metabolic pathways of them are mainly involved in carbohydrate, TCA cycle, fatty acid and mammalian gut microbial-related metabolism. Importantly, three metabolites, being used as biomarkers in clinic, are also differentially expressed in urine samples of two races. It suggests that the race effect should be critically considered prior to make diagnostic result in multi-race coexisted areas to decrease the false positive rate caused by above biomarkers. Moreover, the results show that the age-period and the gender also affect the urinary metabolomics profiles, but with different levels compared to race. We hope that the work can provide some help for developing novel diagnostic tests, understanding the mechanism of disease, designing clinical trials and refining precision medicine in multi-race coexisted areas.

Metabolomics biotechnology, applications, and future trends: a systematic review

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed. Mass spectrometry-based metabolomics has been used in a variety of disease research areas. However, the deep research of metabolites remains a difficult and lengthy process. Fortunately, mass spectrometry is considered to be a universal tool with high specificity and sensitivity and is widely used around the world. Mass spectrometry technology has been applied to various basic disciplines, providing technical support for the discovery and identification of endogenous substances in living organisms. The combination of metabolomics and mass spectrometry is of great significance for the discovery and identification of metabolite biomarkers. The mass spectrometry tool could further improve and develop the exploratory research of the life sciences. This mini review discusses metabolomics biotechnology with a focus on recent applications of metabolomics as a powerful tool to elucidate metabolic disturbances and the related mechanisms of diseases.

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed.

High-throughput untargeted metabolomics and chemometrics reveals pharmacological action and molecular mechanism of chuanxiong by ultra performance liquid chromatography combined with quadrupole-time-of-flight-mass spectrometry

Metabolomics methods can be used to explore the effect mechanisms underlying treatments with traditional medicine. Lung cancer (LC) causes the highest morbidity and mortality among tumors disease, and has become a serious public health problem. Chuanxiong (CX) is a dried rhizome of Ligusticum Chuanxiong Hort., often used in traditional Chinese medicine and has been widely used in the treatment for tumors. However, the pharmacological effect of CX on the metabolism process of LC mice is still unclear. This study used high-throughput untargeted metabolomics aims to discover biomarkers and metabolic pathways of LC as a potential target to provide insight into the pharmacological action and effective mechanism of CX against LC. The precise structural identification of the LC biomarker has been established using ultra performance liquid chromatography (UPLC) combined with quadrupole-time-of-flight-mass spectrometry (Q-TOF-MS) technology. UPLC-Q-TOF-MS and chemometrics methods were used to analyze the blood metabolism of LC model mice, and revealed the intervention effect of CX on LC model mice and potential therapeutic targets. The results showed that the metabolic profile clustering among the groups was obvious, and 31 potential biomarkers were finally locked, involving 7 related metabolic pathways. After treatment with CX, we found that 22 kinds of biomarkers were recalled to the main metabolic pathway which are associated with lipid metabolism. This study provides an effective biomarker reference for early clinical diagnosis of LC, and also provides a foundation for the expansion of new drugs for CX treatment of LC.

Metabolomics methods can be used to explore the effect mechanisms underlying treatments with traditional medicine.

Metabonomics delineates allergic reactions induced by Shuang-huang-lian injection in rats using ultra performance liquid chromatography-mass spectrometry

Shuang-huang-lian Injection (SHLI) is the first successfully developed drug from traditional Chinese medicine (TCM) powder for injection, since its use for the treatment of acute respiratory tract infection, pneumonia, influenza, etc. At the same time, its allergic reactions have also emerged, which limits clinical applications. However, few scholars pay attention to the mechanism of allergic reactions. In this present study, metabonomics technology was used to explore the changes in endogenous metabolites in urine of the rat model of SHLI induced allergic reaction; we and analyzed the metabolites, metabolic pathway, and the mechanism which were closely related to the allergic reactions. The levels of serum histamine and tryptase were examined and changes in histomorphology were also observed. Based on the UPLC-Q-TOF/MS metabonomics, we carried out the pattern recognition analysis, selected potential biomarkers associated with allergic reactions, and explored the pathological mechanism for SHLI induced allergic reaction, which laid the foundation for the safety research of SHLI. Our results showed that SHLI increased the levels of serum histamine and tryptase in rats with allergic reaction; we determined 15 biomarkers in rat allergic reaction model induced by SHLI and found multiple metabolic pathways involved, such as metabolism of linolenic acid, phenylalanine, amino acid, 2-oxo acid, and purine and other metabolic pathways.

Metabolomics Study of the Biochemical Changes in the Plasma of Myocardial Infarction Patients

Myocardial infarction (MI) is a common and multifactorial disease that has the highest morbidity and mortality in the world. Although a number of physiological, pathological, and functional parameters have been investigated, only scarce information regarding the changes of small metabolites in the plasma has been reported, and this lack of information may cause poor MI diagnosis and treatment. In the present study, we aimed to investigate the metabolic profiles of plasma samples from MI patients to identify potential disease biomarkers and to study the pathology of MI. Metabolic profiles of the plasma of 30 MI patients and 30 controls were obtained using ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry. The resulting data were processed using pattern recognition approaches, including principal component analysis and partial least squares-discriminant analysis, to identify the metabolites that differed between the groups. Significant differences in the plasma levels of the following 10 metabolites were observed in the MI patients compared with the controls: phosphatidylserine, C16-sphingosine, N-methyl arachidonic amide, N-(2-methoxyethyl) arachidonic amide, linoleamidoglycerophosphate choline, lyso-PC (C18:2), lyso-PC (C16:0), lyso-PC (C18:1), arachidonic acid, and linoleic acid. The changes in these 10 biomarkers indicated perturbations of energy metabolism, phospholipid metabolism, and fatty acid metabolism in the MI patients. These findings hold promise to advance the treatment, diagnosis, and prevention of MI.

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.

UPLC/ESI-QTOF-MS-based metabolomics survey on the toxicity of triptolide and detoxication of licorice

Triptolide (TP) from Tripterygium wilfordii has been demonstrated to possess anti-inflammatory, immunosuppressive, and anticancer activities. TP is specially used for the treatment of awkward rheumatoid arthritis, but its clinical application is confined by intense side effects. It is reported that licorice can obviously reduce the toxicity of TP, but the detailed mechanisms involved have not been comprehensively investigated. The current study aimed to explore metabolomics characteristics of the toxic reaction induced by TP and the intervention effect of licorice water extraction (LWE) against such toxicity. Obtained urine samples from control, TP and TP + LWE treated rats were analyzed by UPLC/ESI-QTOF-MS. The metabolic profiles of the control and the TP group were well differentiated by the principal component analysis and orthogonal partial least squares-discriminant analysis. The toxicity of TP was demonstrated to be evolving along with the exposure time of TP. Eight potential biomarkers related to TP toxicity were successfully identified in urine samples. Furthermore, LWE treatment could attenuate the change in six of the eight identified biomarkers. Functional pathway analysis revealed that the alterations in these metabolites were associated with tryptophan, pantothenic acid, and porphyrin metabolism. Therefore, it was concluded that LWE demonstrated interventional effects on TP toxicity through regulation of tryptophan, pantothenic acid, and porphyrin metabolism pathways, which provided novel insights into the possible mechanisms of TP toxicity as well as the potential therapeutic effects of LWE against such toxicity.

Neurochemical changes in unilateral cerebral hemisphere during the subacute stage of focal cerebral ischemia-reperfusion in rats: An ex vivo 1H magnetic resonance spectroscopy study

Understanding the subacute may shed light on the mechanism of cerebral ischemia. The present study aimed to explore metabolic features underlying subacute stage of ischemia-reperfusion injury and developing effective treatments. Rats were divided into three groups: the permanent middle cerebral artery occlusion (pMCAO), transient cerebral focal ischemia (tMCAO) and sham group. Evaluation of animal models was performed by the neurological deficit, MR images and pathological morphological abnormality. To elucidate metabolic changes, we conducted a comparative analysis of metabolic composition of unilateral brain tissue using ¹H nuclear magnetic resonance spectroscopy. The successful model was observed low signal on T1WI and high signal on T2WI lesions in the left cerebral. Histopathological results confirmed the formation of apparent lesions in the left striatum, hippocampus CA1 and cortex tissues of subacute cerebral ischemia rats and showed that rats with focal cerebral ischemia-reperfusion could alleviate the extent of pathological damage degree. In pMCAO rats 7 days after surgery, decreased levels of N-acetyl aspartate (NAA), γ-aminobutyric acid (GABA), glutamate (Glu) and succinate (Suc) concomitantly with increased levels of glutamine (Gln), myo-inositol (m-Ins) and lactate (Lac) were observed compared to the control. Whereas, increased level of Lac with decreased levels of NAA, GABA, Glu, Suc, creatine (Cre) were observed in the tMCAO rats. This demonstrated that experimental subacute ischemic stroke in rats caused extensive perturbation in energy metabolism, the tricarboxylic acid cycle and GABA shunt, which provided essential information for understanding the pathogenesis of subacute cerebral ischemia-reperfusion and provided guidance in choosing the suitable therapeutic schedule.

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.

1H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli-associated urinary tract infection (UTI)

BACKGROUND

Urinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli, followed by Klebsiella spp. and Proteus spp., cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis.

METHODS

Urine samples from 51 patients with a prior diagnosis of Escherichia coli-associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The ¹H-NMR spectra were acquired and processed. Multivariate statistical models were applied and their performance was validated using permutation test and ROC curve.

RESULTS

Orthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R²Y = 0.76, Q2=0.45, p < 0.001) between UTI caused by Escherichia coli and healthy controls. Acetate and trimethylamine were identified as discriminant metabolites. The concentrations of both metabolites were calculated and used to build the ROC curves. The discriminant metabolites identified were also evaluated in urine samples from patients with other pathogens infections to test their specificity.

CONCLUSIONS

Acetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli-associated UTI using acetate and trimethylamine concentrations.

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.

Distinct urine metabolome after Asian ginseng and American ginseng intervention based on GC-MS metabolomics approach

Ginseng occupies a prominent position in the list of best-selling natural products worldwide. Asian ginseng (Panax ginseng) and American ginseng (Panax quinquefolius) show different properties and medicinal applications in pharmacology, even though the main active constituents of them are both thought to be ginsenosides. Metabolomics is a promising method to profile entire endogenous metabolites and monitor their fluctuations related to exogenous stimulus. Herein, an untargeted metabolomics approach was applied to study the overall urine metabolic differences between Asian ginseng and American ginseng in mice. Metabolomics analyses were performed using gas chromatography-mass spectrometry (GC-MS) together with multivariate statistical data analysis. A total of 21 metabolites related to D-glutamine and D-glutamate metabolism, glutathione metabolism, TCA cycle and glyoxylate and dicarboxylate metabolism, differed significantly under the Asian ginseng treatment; 34 metabolites mainly associated with glyoxylate and dicarboxylate metabolism, TCA cycle and taurine and hypotaurine metabolism, were significantly altered after American ginseng treatment. Urinary metabolomics reveal that Asian ginseng and American ginseng can benefit organism physiological and biological functions via regulating multiple metabolic pathways. The important pathways identified from Asian ginseng and American ginseng can also help to explore new therapeutic effects or action targets so as to broad application of these two ginsengs.

Pathway Analysis and Metabolites Identification by Metabolomics of Etiolation Substrate from Fresh-Cut Chinese Water Chestnut (Eleocharis tuberosa)

Fresh-cut Chinese water chestnuts (CWC) turn yellow after being peeled, reducing their shelf life and commercial value. Metabolomics, the systematic study of the full complement of small molecular metabolites, was useful for clarifying the mechanism of fresh-cut CWC etiolation and developing methods to inhibit yellowing. In this study, metabolic alterations associated with etiolation at different growth stages (0 day, 2 days, 3 days, 4 days, 5 days) from fresh-cut CWC were investigated using LC–MS and analyzed by pattern recognition methods (principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal projection to latent structures-discriminant analysis (OPLS-DA)). The metabolic pathways of the etiolation molecules were elucidated. The main metabolic pathway appears to be the conversion of phenylalanine to p-coumaroyl-CoA, followed by conversion to naringenin chalcone, to naringenin, and naringenin then following different pathways. Firstly, it can transform into apigenin and its derivatives; secondly, it can produce eriodictyol and its derivatives; and thirdly it can produce dihydrokaempferol, quercetin, and myricetin. The eriodictyol can be further transformed to luteolin, cyanidin, dihydroquercetin, dihydrotricetin, and others. This is the first reported use of metabolomics to study the metabolic pathways of the etiolation of fresh-cut CWC.

Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors

Background

To identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population.

Methods and Findings

One thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by ¹H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of Group 3 and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of Group 3 and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine.

Conclusions

The results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors.

Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach

Type 2 diabetic coronary heart disease (T2DM-CHD) is a kind of serious and complex disease. Great attention has been paid to exploring its mechanism; however, the detailed understanding of T2DM-CHD is still limited. Plasma samples from 15 healthy controls, 13 coronary heart disease (CHD) patients, 15 type 2 diabetes mellitus (T2DM) patients and 28 T2DM-CHD patients were analyzed in this research. The potential biomarkers of CHD and T2DM were detected and screened out by (1)H NMR-based plasma metabolic profiling and multivariate data analysis. About 11 and 12 representative metabolites of CHD and T2DM were identified respectively, mainly including alanine, arginine, proline, glutamine, creatinine and acetate. Then the diagnostic model was further constructed based on the previous metabolites of CHD and T2DM to detect T2DM-CHD with satisfying sensitivity of 92.9%, specificity of 93.3% and accuracy of 93.2%, validating the robustness of (1)H NMR-based plasma metabolic profiling to diagnostic strategy. The results demonstrated that the NMR-based metabolomics approach processed good performance to identify diagnostic plasma biomarkers and most identified metabolites related to T2DM and CHD could be considered as predictors of T2DM-CHD as well as the therapeutic targets for prevention, which provided new insight into diagnosing and forecasting of complex diseases.

Serum metabolic biomarkers distinguish metabolically healthy peripherally obese from unhealthy centrally obese individuals

Background

Metabolic abnormalities are more associated with central obesity than peripheral obesity, but the underlying mechanisms are largely unknown. The present study was to identify serum metabolic biomarkers which distinguish metabolically unhealthy centrally obese (MUCO) from metabolically healthy peripherally obese (MHPO) individuals.

Methods

A two-stage case–control study design was employed. In the discovery stage, 20 individuals (10 MHPO and 10 MUCO) were included and in the following validation stage, 79 individuals (20 normal weight (NW), 30 MHPO, 29 MUCO) were utilized. Study groups were matched for age, sex, physical activity and total dietary calorie intake with MHPO and MUCO additionally matched for BMI. Metabolic abnormality was defined as: 1) HOMA-IR > 4.27 (90^th percentile), 2) high-density lipoprotein cholesterol < 1.03 mmol/L in men and < 1.30 mmol/L in women, 3) fasting blood glucose ≥ 5.6 mmol/L, and 4) waist circumference > 102 cm in men and > 88 cm in women. MUCO individuals had all of these abnormalities whereas MHPO and NW individuals had none of them. A targeted metabolomics approach was performed on fasting serum samples, which can simultaneously identify and quantify 186 metabolites.

Results

In the discovery stage, serum leucine, isoleucine, tyrosine, valine, phenylalanine, alpha-aminoadipic acid, methioninesulfoxide and propionylcarnitine were found to be significantly higher in MUCO, compared with MHPO group after multiple testing adjustment. Significant changes of five metabolites (leucine, isoleucine, valine, alpha-aminoadipic acid, propionylcarnitine) were confirmed in the validation stage.

Conclusions

Significantly higher levels of serum leucine, isoleucine, valine, alpha-aminoadipic acid, propionylcarnitine are characteristic of metabolically unhealthy centrally obese patients. The finding provides novel insights into the pathogenesis of metabolic abnormalities in obesity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12986-016-0095-9) contains supplementary material, which is available to authorized users.

Metabolic fingerprinting to understand therapeutic effects and mechanisms of silybin on acute liver damage in rat

BACKGROUND

Metabolic fingerprinting is a rapid and noninvasive analysis, representing a powerful approach for the characterization of phenotypes and the distinction of specific metabolic states due to environmental alterations. It has become a valuable analytical approach for the characterization of phenotypes and is the rapidly evolving field of the comprehensive measurement of ideally all endogenous metabolites in bio-samples. Silybin has displayed bright prospects in the prevention and therapy of liver injury, and we had conducted a preliminary exploration on the molecular mechanism of the hepatoprotective effects of silybin. Because the knowledge on the metabolic responses of an acute liver damage rat to the silybin is still scarce, metabolic fingerprinting can provide relevant information on the intrinsic metabolic adjustments.

MATERIALS AND METHODS

Here, the physiological and metabolic changes in the acute liver damage rat were investigated by performing a metabolic analysis. The phenotypic response was assessed by liquid chromatography/mass spectrometry (LC/MS) combined with pattern recognition approaches such as principal components analysis and partial least squares projection to supervised latent structures and discriminant analysis. Multivariate analysis of the data showed trends in scores plots that were related to the concentration of the silybin.

RESULTS

Results indicate 10 ions (7 upregulated and 3 downregulated) as differentiating metabolites. Key observations include perturbations of metabolic pathways linked to glutathione metabolism, tryptophan metabolism, cysteine and methionine metabolism, etc., Overall, this investigation illustrates the power of the LC/MS combined with the pattern recognition methods that can engender new insights into silybin affecting on metabolism pathways of an acute liver damage rat.

CONCLUSION

The present study demonstrates that the combination of metabolic fingerprinting with appropriate chemometric analysis is a valuable approach for studying cellular responses to silybin drug and can provide additional insight into the mechanisms.

Metabolomic Analysis Using Liquid Chromatography/Mass Spectrometry for Gastric Cancer

Metabolomics is a post-genomics research field for analysis of low molecular weight compounds in biological samples and has shown great potentials for elucidating complex mechanisms associated with diseases. However, metabolomics studies on gastric cancer (GC), which is the second leading cause of cancer death worldwide, remain scarce, and the molecular mechanisms to metabolomics phenotypes are also still not fully understood. This study reports that the metabolic pathways can be exploited as biomarkers for diagnosis and treatment of GC progression as a case study. Importantly, the urinary metabolites and metabolic patterns were analyzed by high-throughput liquid chromatography mass spectrometry (LC-MS) metabolomics strategy coupled with chemometric evaluation. Sixteen metabolites (nine upregulated and seven downregulated) were differentially expressed and may thus serve as potential urinary biomarkers for human GC. These metabolites were mainly involved in multiple metabolic pathways, including citrate cycle (malic acid, succinic acid, 2-oxoglutarate, citric acid), cyanoamino acid metabolism (glycine, alanine), primary bile acid biosynthesis (glycine, taurine, glycocholic acid), arginine and proline metabolism (urea, L-proline), and fatty acid metabolism (hexadecanoic acid), among others. Network analysis validated close association between these identified metabolites and altered metabolic pathways in a variety of biological processes. These results suggest that urine metabolic profiles have great potential in detecting GC and may aid in understanding its underlying mechanisms. It provides insight into disease pathophysiology and can serve as the basis for developing disease biomarkers and therapeutic interventions for GC diseases.

Metabolomics for Biomarker Discovery: Moving to the Clinic

To improve the clinical course of diseases, more accurate diagnostic and assessment methods are required as early as possible. In order to achieve this, metabolomics offers new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has become an important tool in clinical research and the diagnosis of human disease and has been applied to discovery and identification of the perturbed pathways. It provides a powerful approach to discover biomarkers in biological systems and offers a holistic approach with the promise to clinically enhance diagnostics. When carried out properly, it could provide insight into the understanding of the underlying mechanisms of diseases, help to identify patients at risk of disease, and predict the response to specific treatments. Currently, metabolomics has become an important tool in clinical research and the diagnosis of human disease and becomes a hot topic. This review will highlight the importance and benefit of metabolomics for identifying biomarkers that accurately screen potential biomarkers of diseases.

Berberine ameliorates nonbacterial prostatitis via multi-target metabolic network regulation

Metabolomics has been increasingly applied to discovering biomarkers and identifying perturbed pathways. Berberine has been shown to exhibit anti-inflammatory, antioxidant, and anticancer properties, but its mechanisms for treating nonbacterial prostatitis (NBP) remain unclear completely. We developed the untargeted metabolomics approach based on UPLC-Q-TOF-HDMS to profile the metabolite changes in urine samples in order to discover novel potential biomarkers to clarify mechanisms of berberine in treating a rat model of capsaicin-induced nonbacterial prostatitis (NBP). The changes in metabolic profiling were restored to their base-line values after berberine treatment according to the principal component analysis (PCA) score plots. Fourteen different potential biomarkers and five acutely perturbed metabolic pathways contributing to the treatment of NBP were discovered and identified. Specifically, the berberine-treated rats are located closer to the normal group, indicating that the NBP-induced disturbances to the metabolic profile were partially reversed by berberine treatment. After treatment with berberine, the relative contents of 12 potential biomarkers were effectively regulated, which suggested that the therapeutic effects of berberine on NBP may involve regulating disturbances to the metabolism. Our results show that the protective effect of berberine occurs in part through a reversal of the NBP-caused disturbances.

Identification of bile biomarkers of biliary tract cancer through a liquid chromatography/mass spectrometry-based metabolomic method

The incidence and mortality rate of biliary tract cancer have been increasing worldwide; however, its diagnosis and prognosis have not improved in recent years. A novel approach, termed 'metabolomics', may have the potential to be developed as an effective diagnostic tool. The present study prospectively obtained bile samples from 115 individuals, including 32 patients with biliary tract cancer, 61 patients with benign biliary tract diseases and 22 normal controls. A liquid chromatography/mass spectrometry (LC/MS)‑based approach was used to investigate the differences in bile samples between the three groups, followed by multivariate statistical analysis, which included partial least squares projection to latent structures with discriminant analysis (PLS‑DA) and orthogonal projection to latent structures with discriminant analysis (OPLS‑DA). The metabolomic 2D score plot and 3D plot revealed clear separation between the cancer, benign and normal control groups by PLS‑DA. To further address the significant difficulties in clinically differentiating between biliary tract cancer and benign biliary tract diseases, OPLS‑DA was performed to distinguish between the two disease groups and to select potential biomarkers. The cancer and benign groups were well differentiated. The metabolic analysis revealed significantly lower levels of lysophosphatidylcholine, phenylalanine, 2‑octenoylcarnitine, tryptophan and significantly higher levels of taurine‑ and glycine‑conjugated bile acids in the bile from patients with biliary tract cancer compared with those in the bile from patients with benign biliary tract disease. The present study suggested that an LC/MS‑based metabolomic investigation provides a potent and promising approach for discriminating biliary tract cancer from benign biliary tract diseases and the identified specific metabolites may offer potential as novel biomarkers for the early detection of biliary tract cancer.

The application of metabolomics in traditional Chinese medicine opens up a dialogue between Chinese and Western medicine

Metabolomics provides an opportunity to develop the systematic analysis of the metabolites and has been applied to discovering biomarkers and perturbed pathways which can clarify the action mechanism of traditional Chinese medicines (TCM). TCM is a comprehensive system of medical practice that has been used to diagnose, treat and prevent illnesses more than 3000 years. Metabolomics represents a powerful approach that provides a dynamic picture of the phenotype of biosystems through the study of endogenous metabolites, and its methods resemble those of TCM. Recently, metabolomics tools have been used for facilitating interactional effects of both Western medicine and TCM. We describe a protocol for investigating how metabolomics can be used to open up 'dialogue' between Chinese and Western medicine, and facilitate lead compound discovery and development from TCM. Metabolomics will bridge the cultural gap between TCM and Western medicine and improve development of integrative medicine, and maximally benefiting the human.