Metabolomic estimation of the diagnosis of hepatocellular carcinoma based on ultrahigh performance liquid chromatography coupled with time-of-flight mass spectrometry

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS

Introduction

Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy.

Methods

Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS.

Results

A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy.

Discussion

This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

Molecular and Metabolic Phenotyping of Hepatocellular Carcinoma for Biomarker Discovery: A Meta-Analysis

Identifying and translating hepatocellular carcinoma (HCC) biomarkers from bench to bedside using mass spectrometry-based metabolomics and lipidomics is hampered by inconsistent findings. Here, we investigated HCC at systemic and metabolism-centric multiomics levels by conducting a meta-analysis of quantitative evidence from 68 cohorts. Blood transcript biomarkers linked to the HCC metabolic phenotype were externally validated and prioritized. In the studies under investigation, about 600 metabolites were reported as putative HCC-associated biomarkers; 39, 20, and 10 metabolites and 52, 12, and 12 lipids were reported in three or more studies in HCC vs. Control, HCC vs. liver cirrhosis (LC), and LC vs. Control groups, respectively. Amino acids, fatty acids (increased 18:1), bile acids, and lysophosphatidylcholine were the most frequently reported biomarkers in HCC. BAX and RAC1 showed a good correlation and were associated with poor prognosis. Our study proposes robust HCC biomarkers across diverse cohorts using a data-driven knowledge-based approach that is versatile and affordable for studying other diseases.

Mass spectrometry-based metabolomics for discovering active ingredients and exploring action mechanism of herbal medicine

Natural products derived from herbal medicine are a fruitful source of lead compounds because of their structural diversity and potent bioactivities. However, despite the success of active compounds derived from herbal medicine in drug discovery, some approaches cannot effectively elucidate the overall effect and action mechanism due to their multi-component complexity. Fortunately, mass spectrometry-based metabolomics has been recognized as an effective strategy for revealing the effect and discovering active components, detailed molecular mechanisms, and multiple targets of natural products. Rapid identification of lead compounds and isolation of active components from natural products would facilitate new drug development. In this context, mass spectrometry-based metabolomics has established an integrated pharmacology framework for the discovery of bioactivity-correlated constituents, target identification, and the action mechanism of herbal medicine and natural products. High-throughput functional metabolomics techniques could be used to identify natural product structure, biological activity, efficacy mechanisms, and their mode of action on biological processes, assisting bioactive lead discovery, quality control, and accelerating discovery of novel drugs. These techniques are increasingly being developed in the era of big data and use scientific language to clarify the detailed action mechanism of herbal medicine. In this paper, the analytical characteristics and application fields of several commonly used mass spectrometers are introduced, and the application of mass spectrometry in the metabolomics of traditional Chinese medicines in recent years and its active components as well as mechanism of action are also discussed.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Therapeutic effect and mechanism of danshensu on coronary heart disease using liquid chromatography combined with mass spectrometry metabolomics

Metabolomics can discover the biomarkers and metabolic pathways, provides the possibility for insights into the pharmacological action and mechanism of natural products. The therapeutic effect and mechanism of danshensu (DSS) on total metabolic pathways has not been well investigated. The aim of this study was to explore the disturbed endogenous biomarkers and metabolic pathways reflecting the pharmacological activity of DSS, and mechanism of action of DSS using comprehensive metabolome analysis based on high-throughput metabolomics technology combined with ultra-high performance liquid chromatography (UPLC) coupled with quadrupole tandem time-of-flight mass spectrometry (Q-TOF-MS) and pattern recognition method. Through the changes of the overall metabolic profile and the related biomarkers, the intervention effect of natural product danshensu (DSS) treatment on CHD model rats was revealed. The results showed that after the model replication was established, the metabolic profile was clearly separated, and a total of 26 potential biomarkers were screened out, and involving 8 metabolic pathways. After different doses of DSS solution were given, a total of 20 biomarkers could be significantly regulated, mainly involving primary bile acid biosynthesis, glycerophospholipid metabolism, and lipid metabolism. It showed UPLC-MS-based metabolomics can be used for discovering potential biomarkers and metabolic pathways of CHD, and to further understand and dissecting pharmacological effects and mechanisms of natural products via metabolomics techniques.

Chinmedomics Strategy for Elucidating the Pharmacological Effects and Discovering Bioactive Compounds From Keluoxin Against Diabetic Retinopathy

Keluoxin (KLX) is an active agent in the treatment of diabetic retinopathy (DR). However, its mechanism, targets, and effective constituents against DR are still unclear, which seriously restricts its clinical application. Chinmedomics has the promise of explaining the pharmacological effects of herbal medicines and investigating the effective mechanisms. The research results from electroretinography and electron microscope showed that KLX could reduce retinal dysfunction and pathological changes by the DR mouse model. Based on effectiveness, we discovered 64 blood biomarkers of DR by nontargeted metabolomics analysis, 51 of which returned to average levels after KLX treatment including leukotriene D4 and A4, l-tryptophan, 6-hydroxymelatonin, l-phenylalanine, l-tyrosine, and gamma-linolenic acid (GLA). The metabolic pathways involved were phenylalanine metabolism, steroid hormone biosynthesis, sphingolipid metabolism, etc. Adenosine monophosphate-activated protein kinase (AMPK), extracellular signal-regulated protein kinase1/2 (ERK1/2), phosphatidylinositol-3-kinase (PI3K), and protein 70 S6 kinase (p70 S6K) might be potential targets of KLX against DR. This was related to the mammalian target of rapamycin (mTOR) signaling and AMPK signaling pathways. We applied the chinmedomics strategy, integrating serum pharm-chemistry of traditional Chinese medicine (TCM) with metabolomics, to discover astragaloside IV (AS-IV), emodin, rhein, chrysophanol, and other compounds, which were the core effective constituents of KLX when against DR. Our study was the first to apply the chinmedomics strategy to discover the effective constituents of KLX in the treatment of DR, which fills the gap of unclear effective constituents of KLX. In the next step, the research of effective constituents can be used to optimize prescription preparation, improve the quality standard, and develop an innovative drug.

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.

Alterations in the Gut Microbiota and Their Metabolites in Colorectal Cancer: Recent Progress and Future Prospects

Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. The etiology and pathogenesis of CRC remain unclear. A growing body of evidence suggests dysbiosis of gut bacteria can contribute to the occurrence and development of CRC by generating harmful metabolites and changing host physiological processes. Metabolomics, a systems biology method, will systematically study the changes in metabolites in the physiological processes of the body, eventually playing a significant role in the detection of metabolic biomarkers and improving disease diagnosis and treatment. Metabolomics, in particular, has been highly beneficial in tracking microbially derived metabolites, which has substantially advanced our comprehension of host-microbiota metabolic interactions in CRC. This paper has briefly compiled recent research progress of the alterations of intestinal flora and its metabolites associated with CRC and the application of association analysis of metabolomics and gut microbiome in the diagnosis, prevention, and treatment of CRC; furthermore, we discuss the prospects for the problems and development direction of this association analysis in the study of CRC. Gut microbiota and their metabolites influence the progression and causation of CRC, and the association analysis of metabolomics and gut microbiome will provide novel strategies for the prevention, diagnosis, and therapy of CRC.

Liquid Chromatograph-Mass Spectrometry-Based Non-targeted Metabolomics Discovery of Potential Endogenous Biomarkers Associated With Prostatitis Rats to Reveal the Effects of Magnoflorine

Magnoflorine (Mag) has multiple pharmacological activities for the prevention and treatment of prostatitis. However, its molecular mechanisms andpharmacological targets are not clear. In this study, the ultra-performance liquid tandem mass spectrometry-based metabolomics method was used to clarify the intervention of Mag against prostatitis and the biological mechanism. A total of 25 biomarkers associated with the prostatitis model were identified by metabolomics, and a number of metabolic pathways closely related to the model were obtained by MetPA analysis. After given Mag treatment, the results of each indicator were shown that Mag alkaloid could inhibit the development of prostatitis effectively. We found that Mag had regulative effects on potential biomarkers of prostatitis model, which can regulate them to the control group. Our results indicated that alkaloids have an effective intervention therapy for prostatitis, and five types of metabolic pathways closely related to prostatitis model were obtained, including phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, tyrosine metabolism, arginine and proline metabolism, glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism. This study has provided the basic experimental data for the development of Mag in the prevention and treatment of prostatitis.

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.

Ultra-Performance Liquid Chromatography/Mass Spectrometry-Based Metabolomics for Discovering Potential Biomarkers and Metabolic Pathways of Colorectal Cancer in Mouse Model (ApcMin/+) and Revealing the Effect of Honokiol

Endogenous metabolites are a class of molecules playing diverse and significant roles in many metabolic pathways for disease. Honokiol (HNK), an active poly-phenolic compound, has shown potent anticancer activities. However, the detailed crucial mechanism regulated by HNK in colorectal cancer remains unclear. In the present study, we investigated the therapeutic effects and the underlying molecular mechanisms of HNK on colorectal cancer in a mouse model (ApcMin/+) by analyzing the urine metabolic profile based on metabolomics, which is a powerful tool for characterizing metabolic disturbances. We found that potential urine biomarkers were involved in the metabolism of compounds such as purines, tyrosines, tryptophans, etc. Moreover, we showed that a total of 27 metabolites were the most contribution biomarkers for intestinal tumors, and we found that the citrate cycle (TCA cycle) was regulated by HNK. In addition, it was suggested that the efficacy of HNK was achieved by affecting the multi-pathway system via influencing relevant metabolic pathways and regulating metabolic function. Our work also showed that high-throughput metabolomics can characterize the regulation of metabolic disorders as a therapeutic strategy to prevent colorectal cancer.

Efficacy of berberine in treatment of rheumatoid arthritis: From multiple targets to therapeutic potential

Rheumatoid arthritis is a systemic autoimmune disorder involved in persistent synovial inflammation. Berberine is a nature-derived alkaloid compound with multiple pharmacological activities in different pathologies, including RA. Recent experimental studies have clarified several determinant cellular and molecular targets of BBR in RA, and provided novel evidence supporting the promising therapeutic potential of BBR to combat RA. In this review, we recapitulate the therapeutic potential of BBR and its mechanism of action in ameliorating RA, and discuss the modulation of gut microbiota by BBR during RA. Collectively, BBR might be a promising lead drug with multi-functional activities for the therapeutic strategy of RA.

Andrographolide Against Lung Cancer-New Pharmacological Insights Based on High-Throughput Metabolomics Analysis Combined with Network Pharmacology

Andrographolide (Andro) has known to treat various illnesses such as colds, diarrhea, fever and infectious diseases. However, the effect mechanism of Andro is still unclear. Therefore, we used high-throughput metabolomics analysis to discover biomarkers, metabolic profiles and pathways to reveal the pharmacological action and effective mechanism of Andro against lung cancer. The metabolic effects of Andro on lung cancer animal was explored by ultra-performance liquid chromatography-triple-time of flight/mass spectrometry (UPLC-TOF/MS) analysis. Our results showed that Andro exhibited significant protective effects against lung cancer. Compared with control group, a total of 25 metabolites biomarkers was identified in urine of model animals, which 18 of them were regulated toward the normal direction after Andro treatment, and network pharmacology analysis showed that they were related with 570 proteins. Biological pathways analysis showed that the 11 metabolism pathways were regulated by Andro treatment in lung cancer mouse, and amino acid metabolism and arachidonic acid metabolism have great potential as target pathways for Andro against lung cancer. It revealed that high-throughput metabolomics combined with network pharmacology analysis provides deeply insight into the therapeutic mechanisms of natural product for promoting medicine development and disease treatment.

Exploring lipid biomarkers of coronary heart disease for elucidating the biological effects of gelanxinning capsule by lipidomics method based on LC-MS

High-throughput lipidomics technology was used to explore the potential therapeutic targets and mechanism of action of gelanxinning capsule on rat model with coronary heart disease (CHD). This study attempts to provide a novel method to interpret the molecular mechanism of traditional medicine. The lipid markers of CHD were determined by full-scan analysis based on ultra-performance liquid chromatography-high-definition mass spectrometry. Then, the metabolic changes associated with gelanxinning capsule treatment via the modulation of lipid biomarkers and pathway in rats were characterized. After gelanxinning treatment, the metabolic profile tended to recover compared with the model group. A total of 26 potential biomarkers were identified to represent the disorders of lipid metabolism in CHD animal model, of which 19 were regulated by gelanxinning capsule administration, and four metabolic pathways such as glycerophospholipid metabolism, sphingolipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, and glycerolipid metabolism were involved. From the pathway analysis, it was found that glycerophospholipid metabolism and sphingolipid metabolism with significant differences have the potential to be regarded as new targets for the treatment of CHD. Gelanxinning capsule with its good therapeutic effect protects against CHD by regulating lipid biomarkers and pathway from lipidomics-guided biochemical analysis.

Dissecting Efficacy and Metabolic Characteristic Mechanism of Taxifolin on Renal Fibrosis by Multivariate Approach and Ultra-Performance Liquid Chromatography Coupled With Mass Spectrometry-Based Metabolomics Strategy

Taxifolin (TFN) is an important natural compound with antifibrotic activity; however, its pharmacological mechanism is not clear. In this study, our aim is to gain insight into the effects of TFN and its potential mechanisms in unilateral ureteral obstruction (UUO) animal model using metabolomics approach to identify the metabolic biomarkers and perturbed pathways. Serum metabolomics analysis by UPLC-Q-TOF/MS was carried out to discover the changes in the metabolic profile. It showed that TFN has a significant protective effect on UUO-induced renal fibrosis and a total of 32 potential biomarkers were identified and related to RF progression. Of note, 27 biomarkers were regulated by TFN treatment, which participate in eight metabolic pathways, including phenylalanine, tyrosine and tryptophan biosynthesis, and phenylalanine metabolism. It also showed that metabolomics was a promising strategy to better dissect metabolic characteristics and pharmacological mechanisms of natural compounds by multivariate approach and ultra-performance liquid chromatography coupled with mass spectrometry.

High-throughput metabolomics discovers metabolite biomarkers and insights the protective mechanism of schisandrin B on myocardial injury rats

Schisandrin B has been proved to possess anti-inflammatory and anti-endoplasmic effects, could improve cardiac function, inhibit apoptosis, and reduce inflammation after ischemic injury. However, the detailed metabolic mechanism and potential pathways of Schisandrin B effects on myocardial injury are unclear. Metabolomics could yield in-depth mechanistic insights and explore the potential therapeutic effect of natural products. In this study, the preparation of doxorubicin-induced myocardial injury rat model for evaluation of Schisandrin B on viral myocarditis sequelae related pathological changes and its mechanism. The metabolite profiling of myocardial injury rats was performed through ultra-high performance liquid chromatography combined with mass spectrometry combined with pattern recognition approaches and pathway analysis. A total of 15 metabolites (nine in positive ion mode and six in negative ion mode) were considered as potential biomarkers of myocardial injury, and these metabolites may correlate with the regulation of Schisandrin B treatment. A total of six metabolic pathways are closely related to Schisandrin B treatment, including glycerophospholipid metabolism, sphingolipid metabolism, purine metabolism, etc. This study revealed the potential biomarkers and metabolic network pathways of myocardial injury, and illuminated the protective mechanism of Schisandrin B on myocardial injury.

High-throughput metabolomics method based on liquid chromatography-mass spectrometry: Insights into the underlying mechanisms of salinity-alkalinity exposure-induced metabolites changes in Barbus capito

It is critical to investigate the adaptive development and the physiological mechanism of fish in external stimulation. In this study, the response of Barbus capito to salinity-alkalinity exposure was explored by high-throughput nontargeted and liquid chromatography-mass spectrometry-based metabolomics to investigate metabolic biomarker and pathway changes. Meanwhile, the biochemical indexes of Barbus capito were measured to discover the chronic impairment response to salinity-alkalinity exposures. A total of 29 tissue metabolites were determined to deciphering the endogenous metabolic changes of fishes during the different concentration salinity-alkalinity exposures environment, which were mainly involved in the key metabolism including the phenylalanine, tyrosine, and tryptophan biosynthesis, arachidonic acid metabolism, pyruvate metabolism, citrate cycle, and glycerophospholipid metabolism. Finally, we found the amino acid metabolism as key target was associated with the endogenous metabolites and metabolic pathways of Barbus capito to salinity-alkalinity exposures. In conclusion, metabolomics is a potentially powerful tool to reveal the mechanism information of fish in various exposure environments.

Functional Metabolomics Analysis Elucidating the Metabolic Biomarker and Key Pathway Change Associated With the Chronic Glomerulonephritis and Revealing Action Mechanism of Rhein

Chronic glomerulonephritis (CGN) as the culprit of kidney failure can increase the mortality of critically ill patients and seriously threatens people’s health all over the world. This study using metabolomics strategy is to reveal the potential therapeutic mechanism-related targets to evaluate the effects of rhein (RH) on CGN rats. Changes of serum metabolites and pathways were analyzed by non-targeted metabolomic method based on liquid chromatography-mass spectrometry (LC-MS) combined with ingenuity pathway analysis. In addition, the levels of biochemical indicators were also detected. A total of 25 potential biomarkers were identified to express serum metabolic turbulence in CGN animal model, and then 16 biomarkers were regulated by RH trending to the normal states. From metabolite enrichment and pathway analysis, pharmacological activity of RH on CGN were mainly involved in six vital metabolic pathways including phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, tricarboxylic acid cycle (TCA cycle), alanine, aspartate, and glutamate metabolism, arginine and proline metabolism. It suggested CGN treatment with RH, which may be mediated via interference with metabolic pathway such as amino acid metabolism, arachidonic acid metabolism, and TCA cycle to regulating inflammation, oxidation response and immune regulation against CGN. It showed that metabolomics method offer deeply insight into the therapeutic mechanisms of natural product.

High-Throughput Metabolomics Method for Discovering Metabolic Biomarkers and Pathways to Reveal Effects and Molecular Mechanism of Ethanol Extract From Epimedium Against Osteoporosis

Metabolomics is an effective strategy to explore the molecular mechanism of herbal medicine. Epimedium, a traditional Chinese herb from the Epimedium brevicornu Maxim., has a therapeutic effect on osteoporosis (OP), however the molecular mechanism of the anti-OP effect is uncle\ar. Therefore, we investigated the pharmacological effect and action mechanism of ethanol extract of epimedium (Ext-epi) onOP rat model. The serum of OP rats was analyzed utilized UPLC-Q-TOF/MS metabolomics, and the potential biomarkers were screened and identified using multivariate data analysis systems and network databases. To further appraise the influence of Ext-epi on biological markers and metabolic pathways, and reveal the potential mechanism of Ext-epi on OP treatment. The results showed that 46 potential biomarkers were screened out and after intervention with Ext-epi extracts solution, 16 potential biomarkers were significantly recalled. Further pathway experiments showed that key pathway analysis include sarachidonic acid metabolism, glycerolphospholipid metabolism as potential targets which is related with the efficacy of Ext-epi protect against OP. These results explain the correlation between metabolites and molecular mechanisms, which is of great significance for understanding the intervention of Ext-epi on OP. In short, based on UPLC-Q-TOF/MS metabolomics may provide effective strategies for understanding the pathogenesis of diseases and evaluating the intervention effect of natural products.

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.

High-Throughput Metabolomics for Identification of Metabolic Pathways and Deciphering the Effect Mechanism of Dioscin on Rectal Cancer From Cell Metabolic Profiles Coupled With Chemometrics Analysis

High-throughput liquid chromatography-mass spectrometry (LC-MS)-based metabolomics can provide the holistic analysis of the low molecular weight endogenous metabolites in cells and reflect the changes of cellular regulation and metabolic pathways. Our study designed to reveal the potentially pharmacological effects of dioscin on SW480 rectal cancer cells using nontargeted metabolomics method to probe into small molecular metabolites and pathway changes. After the cell assay of proliferation, apoptosis, migration, and invasion, the dioscin-treated cell samples were prepared for nontargeted metabolomics analysis based on LC-MS tool to describe the metabolic profiles. Dioscin has prevented cell proliferation and accelerated cell apoptosis, and it also inhibited the SW480 rectal cancer cells' migration and invasion. A total of 22 metabolites were selected as promising biomarkers of pharmacological reaction of dioscin to rectal cancer, and eight highly correlated pathways including D-glutamine and D-glutamate metabolism, pyruvate metabolism, arachidonic acid metabolism, phenylalanine metabolism, tryptophan metabolism, glycolysis or gluconeogenesis, citrate cycle (TCA cycle), and butanoate metabolism were identified. It showed that strategies based on cell metabolomics are helpful tools to discover the small molecular metabolites to elucidate the action mechanism of drug.

Analytical strategies for the discovery and validation of quality-markers of traditional Chinese medicine

BACKGROUND

Quality control of traditional Chinese medicine (TCM) is the basis of clinical efficacy. Due to the complexity of TCM, it is difficult to unify the quality control, and hinders the further implementation of the quality standardization of TCM. As a new concept, quality-marker (Q-marker) plays a powerful role in promoting the standardization of quality control system of TCM.

HYPOTHESIS/PURPOSE

The present review aims to provide reference and scientific basis for further development of Q-marker and assist standardization of quality control of TCM.

METHODS

Extensive search of various documents and electronic databases such as Pubmed, Royal Society of Chemistry, Science Direct, Springer, Web of Science, and Wiley, etc., were used to search scientific contributions. Other online academic libraries, e.g. Google Scholars, Scopus and national pharmacology literature were also been employed to learn more relevant information about Q-marker.

RESULTS

Q-markers play vital role in promoting the standardization of quality control of TCM. The factors that affect the quality of TCM, the advantages and disadvantages of the analytical techniques commonly used in Q-marker research were reviewed, as well as the systematic research strategies, which were verified by practices.

CONCLUSION

The proposal of Q-marker not only provided a new perspective to break through the bottleneck of current quality control, but also can be used in the evaluation of pharmacological efficiency, therapeutic discovery, toxicology, etc. In addition, the Q-marker analysis strategies summarized in this paper is helpful to standardize the quality control of TCM and promote the internationalization of TCM.

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.

High-throughput liquid chromatography mass-spectrometry-driven lipidomics discover metabolic biomarkers and pathways as promising targets to reveal the therapeutic effects of the Shenqi pill

Lipidomics, a branch of metabonomics, could provide a powerful technique for discovery of lipid molecules to reveal disease status and drug efficacy.

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.

Metabolomics-driven identification of perturbations in amino acid and sphingolipid metabolism as therapeutic targets in a rat model of anorexia nervosa disease using chemometric analysis and a multivariate analysis platform

It is important to explore novel therapeutic targets and develop an effective strategy for the treatment of anorexia nervosa. In this work, serum samples were analyzed using ultra-performance liquid chromatography coupled with quadrupole time-of flight mass spectrometry (UPLC/Q-TOF MS) coupled with chemometric analysis and multivariate analysis to obtain the metabolites and their corresponding pathways. In addition, knock-in and knock-down of the key enzyme in vivo was performed to verify the reliability of the obtained metabolic pathway, which is closely associated with the anorexia nervosa pathomechanism and the potential targets. There were significant differences in the biochemical parameters between the model group and the control group. A total of 26 potential biomarkers were identified to resolve the difference between the control and model rats, which were closely related to amino acid metabolism, sphingolipid metabolism, arachidonic acid metabolism, the citrate cycle, and so forth. According to the ingenuity pathway analysis, we further elucidated the relationship between the gene, protein, and metabolite alteration in anorexia nervosa, which are involved in cellular compromise, lipid metabolism, small molecule biochemistry, cell signaling, molecular transport, nucleic acid metabolism, cell morphology, cellular function and maintenance. Arginosuccinate synthetase (ASS) deficiency was accompanied by a significant downregulation of the β-endorphin and ghrelin in the animal models. The metabolites and pathways obtained using the metabolomics strategy may provide valuable information for the early treatment for anorexia nervosa.

It is important to explore novel therapeutic targets and develop an effective strategy for the treatment of anorexia nervosa.

Functional metabolomics using UPLC-Q/TOF-MS combined with ingenuity pathway analysis as a promising strategy for evaluating the efficacy and discovering amino acid metabolism as a potential therapeutic mechanism-related target for geniposide against alcoholic liver disease

Metabolomics has been used as a strategy to evaluate the efficacy of and potential targets for natural products.

High-throughput lipidomics analysis to discover lipid biomarkers and profiles as potential targets for evaluating efficacy of Kai-Xin-San against APP/PS1 transgenic mice based on UPLC-Q/TOF-MS

Lipid metabolism has a significant function in the central nervous system and Alzheimer's disease (AD) is an age-related senile disease characterized by central nerve degeneration. The pathological development of AD is closely related to lipid metabolism disorders. To reveal the influence of Kai-Xin-San (KXS) on lipid metabolism in APP/PSI transgenic mice and potential therapeutic targets for treating AD, brain tissue samples were collected and analyzed by high-throughput lipidomics based on UPLC-Q/TOF-MS. The collected raw data were processed by multivariate data analysis to discover the potential biomarkers and lipid metabolic profiles. Compared with the control wild-type mouse group, nine potential lipid biomarkers were found in the AD model group, of which seven were up-regulated and two were down-regulated. Orally administrated KXS can reverse the changes in these potential biomarkers. Compared with the model group, a total of six differential metabolites showed a recovery trend and may be potential targets for KXS to treat AD. This study showed that high-throughput lipidomics can be used to discover the perturbed pathways and lipid biomarkers as potential targets to reveal the therapeutic effects of KXS.

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.

Plasma-free amino acid profiles in dogs with hepatocellular carcinoma

BACKGROUND

Metabolomic analysis using blood samples has been suggested to be useful for the early detection of cancer. Among metabolites, plasma-free amino acid (PFAA) profiles are potential diagnostic biomarkers for several diseases including cancer. However, the relationship between PFAA concentrations and liver tumors in dogs remains unknown.

OBJECTIVE

To determine the characteristics of PFAA profiles of dogs with hepatocellular carcinoma (HCC) and correlated clinical features.

ANIMALS

Thirty-four client-owned dogs diagnosed with HCC (n = 26) and benign liver diseases (n = 8) and 11 age-matched healthy dogs.

METHODS

Prospective study using heparinized blood samples from fasted dogs. Plasma was deproteinized, and the concentrations of 21 amino acids were measured using an automated high-performance liquid chromatography amino acid analyzer.

RESULTS

Plasma glutamic acid concentrations were significantly different among groups (P < .0024 after Bonferroni correction). Compared to healthy dogs, dogs with HCC and benign liver diseases had significantly higher concentrations of glutamic acid by post hoc analysis. However, no significant difference in the PFAA profiles of HCC and benign liver diseases were detected. In addition, preoperative and postoperative PFAA profiles of dogs with HCC were not significantly different.

CONCLUSIONS AND CLINICAL IMPORTANCE

Increased glutamic acid concentrations might play a role in the development or be a consequence of liver tumor formation. However, PFAA profiles of HCC could not be differentiated from those of benign lesions. In addition, glutamic acid concentrations did not change after surgical resection. These results indicate that PFAA profiles may not be useful biomarkers for detecting HCC in dogs.

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.

Retracted Article: A high-throughput metabolomics strategy for discovering the influence of differential metabolites and metabolic pathways of huaxian capsules on sepsis-associated Qi deficiency and blood stasis syndrome

High-throughput metabolomics can be used to investigate the therapeutic targets and metabolic mechanisms of traditional Chinese medicine formulae.

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.

High-throughput metabolic profiling, combined with chemometrics and bioinformatic analysis reveals functional alterations in myocardial dysfunction

High-throughput metabolic profiling technology has been used for biomarker discovery and to reveal underlying metabolic mechanisms.

Applications and potential mechanisms of herbal medicines for rheumatoid arthritis treatment: a systematic review

In this review, we systematically discuss the role of traditional Chinese medicine (TCM) in rheumatoid arthritis (RA) disease treatment. TCM classifies the subtypes of RA through its own theoretical method, which is beneficial for more accurate diagnosis and treatment with Chinese herbal medicines (CHMs) that are more suitable for different syndromes. TCM mainly uses a flexible combination of CHMs to play an important role in RA treatment. The main components of these extracts can be subdivided into alkaloids, flavonoids, triterpenes, saponins and other compounds. Using a platform of transgenic and induced arthritis models, we explore the potential mechanisms of TCM against RA with the help of omics analysis techniques and methods. These mechanisms are mainly CHM and its extracts can inhibit RA patients and experimental animal models, including synovitis, vascular proliferation and bone injury; this involves many biological signal exchange targets and pathways. In conclusion, the role of TCM in RA treatment mainly involves reducing the expression and secretion of pro-inflammatory factors, thus decreasing the degree of abnormal immune response.

In this review, we systematically discuss the role of traditional Chinese medicine (TCM) in rheumatoid arthritis (RA) disease treatment.

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.

Non-targeted metabolite profiling and specific targeted discrimination strategy for quality evaluation of Cortex Phellodendri from different varieties

Cortex Phellodendri is derived from two species of Phellodendron amurense Rupr. and Phellodendron chinense Schneid. Traditionally, the two species are utilized interchangeably under the name of “huangbo” in the clinic because they are believed to share the same clinical efficacy. However, the chemical analysis in vitro couldn't directly reflect the pharmacological effects. Therefore, whether the constituents could be absorbed into the blood becomes the uppermost problem to account for the clinical efficacy differences of the two species. Therefore, a rapid and sensitive approach to differentiate the two species of Cortex Phellodendri based on non-targeted metabolite profiling and the specific targeted discrimination strategy was first established. Samples from different cultivars were clearly discriminated by principal component analysis and orthogonal partial least squares discriminant analysis. 17 prototype compounds and 22 metabolites contributing to the group separation were identified and tentatively characterized, three of which were found for the first time. Moreover, six of them were screened out as the chemical markers which contribute most to the differences between the two species. Taken together, the application of the non-targeted metabolite profiling and specific targeted discrimination strategy is suitable for the assessment of Cortex Phellodendri.

Non-targeted metabolite profiling and specific targeted discrimination strategy coupled with pattern recognition to differentiate the two varieties in rats.