Current Trends and Innovations in Bioanalytical Techniques of Metabolomics

Serum Metabolomics and NF-κB Pathway Analysis Revealed the Antipyretic Mechanism of Ellagic Acid on LPS-Induced Fever in Rabbits

Fever is one of the most common clinical conditions and is characterized by pyrogenic infection, malignancy, inflammation, and tissue damage, among others. Ellagic acid (EA) can inhibit the expression of related proteins on the pathway by blocking the nuclear factor kappa-B(NF-κB) signaling pathway, inhibit the levels of pro-inflammatory factors interleukin-1β(IL-1β), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α), increase the level of anti-inflammatory factor IL-10, and effectively alleviate inflammatory symptoms. In addition, EA can also reduce the levels of malondialdehyde(MDA) and nitric oxide(NO) in the body, increase the activities of superoxide dismutase (SOD), glutathione (GSH), and catalase(CAT), scavenge oxidative free radicals, inhibit lipid oxidation, and achieve antipyretic and anti-inflammatory effects. The purpose of this study was to establish the relationship between EA and various inflammatory markers, such as TNF-α, IL-6, IL-1β, prostaglandin E2(PGE2), and cyclic adenosine monophosphate(cAMP), and clarify the mechanism of the cyclooxidase-2(COX-2)/NF-κB signaling pathway. Combined with the metabolomics analysis, our study revealed the effects of EA on multiple endogenous biomarkers, reflecting the characteristics of a multi-component, multi-target, and multi-pathway mechanism. Compared to lipopolysaccharide (LPS)- treated animals, subsequent administration of EA significantly lowered the LPS-induced rectal temperature increase (p < 0.05 or p < 0.01), significantly increased serum SOD and GSH levels (p < 0.05 or p < 0.01), and significantly decreased serum MDA, IL-1β, IL-6, and TNF-α levels (p < 0.05 or p < 0.01). In addition, compared to LPS-treated animals, subsequent administration of EA significantly decreased cerebrospinal fluid cAMP and PGE2 levels (p < 0.05 or p < 0.01), significantly decreased cAMP, significantly increased 5-HT levels (p < 0.05 or p < 0.01), and significantly down-regulated p-NF-κB p65 and COX-2 protein levels in the hypothalamus. Subsequent gas chromatography mass spectrometry(GC-MS) metabolite analysis indicated that 12 differential metabolites were detected in serum isolated 4 h after LPS treatment, and 10 differential metabolites were detected in serum collected 7 h after LPS treatment. Next, Pearson correlation analysis was used to systematically characterize the relationship between the identified metabolites and TNF-α, IL-6, MDA, SOD, PGE2, and cAMP. The levels of propionic acid, pyridine, and L-valine were up-regulated by EA, which inhibited the expression of MDA, IL-1β, and TNF-α and increased the activity of GSH. The levels of inositol, urea, and 2-monopalmitin were down-regulated by EA, which inhibited the expression of MDA, IL-1β, and TNF-α, increased the activity of SOD and GSH, reduced the inflammatory response, and alleviated the oxidative stress state. Combined with the results of the metabolic pathway analysis, we suggest that the pathways of the galactose metabolism, synthesis and degradation of ketone bodies, as well as ascorbic acid and aldehyde acid metabolism are closely related to the antipyretic and anti-inflammatory effects of EA. Our study established the relationship between EA and various inflammatory markers, such as TNF-α, IL-6, IL-1β, PGE2, and cAMP, and clarified the mechanism of the COX-2/NF-κB signaling pathway. Combined with the metabolomics analysis, our study revealed the effects of EA on multiple endogenous biomarkers, reflecting the characteristics of a multi-component, multi-target, and multi-pathway mechanism.

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.

How Central Carbon Metabolites of Mexican Mint (Plectranthus amboinicus) Plants Are Impacted under Different Watering Regimes

Plants are sessile, and their ability to reprogram their metabolism to adapt to fluctuations in soil water level is crucial but not clearly understood. A study was performed to determine alterations in intermediate metabolites involved in central carbon metabolism (CCM) following exposure of Mexican mint (Plectranthus amboinicus) to varying watering regimes. The water treatments were regular watering (RW), drought (DR), flooding (FL), and resumption of regular watering after flooding (DHFL) or after drought (RH). Leaf cluster formation and leaf greening were swift following the resumption of regular watering. A total of 68 key metabolites from the CCM routes were found to be significantly (p < 0.01) impacted by water stress. Calvin cycle metabolites in FL plants, glycolytic metabolites in DR plants, total tricarboxylic acid (TCA) cycle metabolites in DR and DHFL plants, and nucleotide biosynthetic molecules in FL and RH plants were significantly (p < 0.05) increased. Pentose phosphate pathway (PPP) metabolites were equally high in all the plants except DR plants. Total Calvin cycle metabolites had a significantly (p < 0.001) strong positive association with TCA cycle (r = 0.81) and PPP (r = 0.75) metabolites. Total PPP metabolites had a moderately positive association with total TCA cycle metabolites (r = 0.68; p < 0.01) and a negative correlation with total glycolytic metabolites (r = -0.70; p < 0.005). In conclusion, the metabolic alterations of Mexican mint plants under different watering regimes were revealed. Future studies will use transcriptomic and proteomic approaches to identify genes and proteins that regulate the CCM route.

Application of Metabolomics in Diagnosis and Treatment of Chronic Liver Diseases

Chronic liver disease represents stepwise destruction of the liver parenchyma after chronic liver injury, which is often difficult to be diagnosed accurately. Thus, the development of specific biomarkers of chronic liver disease is important. Metabolomics is a powerful tool for biomarker exploration, which enables the exploration of disease pathogenesis or drug action mechanisms at the global metabolic level. The metabolomics workflow generally includes collection, preparation, and analysis of samples, and data processing and bioinformatics. A metabolomics study can simultaneously detect the dysfunctions in the glucose, lipid, amino-acid, and nucleotide metabolisms. Hence, it facilitates the obtaining of a better understanding of the pathogenesis of chronic liver disease and its diagnosis. Many effective drugs could reverse the change of comprehensive biochemical phenotypes induced by chronic liver disease. They can even potentially restore the normal metabolic signatures of patients. Increasingly more researchers have begun to apply metabolomics technologies to diagnose chronic liver disease and investigate the mechanism of action of effective drugs or the variations in drug responses. We are convinced that deepening the understanding of the metabolic alterations could extend their use as powerful biomarkers, promoting the more effective clinical diagnosis and treatment of chronic liver disease in the future.

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.

Identification of the Perturbed Metabolic Pathways Associating With Renal Fibrosis and Evaluating Metabolome Changes of Pretreatment With Astragalus polysaccharide Through Liquid Chromatography Quadrupole Time-Of-Flight Mass Spectrometry

Renal fibrosis is glomerulosclerosis and renal tubulointerstitial fibrosis caused by the increase of interstitial cells and intercellular substances and the accumulation of extracellular matrix, and is a common pathological manifestation of renal disease progressing to end-stage renal failure. It has proved that Astragalus polysaccharide (AP) has curative effect on renal disease; however, its therapeutic mechanism on renal fibrosis is still unclear. Metabolomics approach provides an opportunity to identify novel molecular biomarkers. The purpose of this study is to study the changes of serum metabolic profile of rats with unilateral tubal ligation and replication of renal fibrosis model and the therapeutic effect of AP on it. The blood samples of rats in the control group, renal fibrosis model group, and AP treatment group collected on the 21st day were analyzed by metabolomics method based on UPLC-Q-TOF-MS. Principal component analysis (PCA) showed that clustering was obvious and significantly separated, and paired partial least squares discriminant analysis (OPLS-DA) was used for further analysis. Combined with the network databases such as HMDB and KEGG and a large number of literatures, 32 potential biomarkers related to renal fibrosis were preliminarily screened out and further verified by MS/MS secondary debris information. After pretreatment with AP, 20 biomarkers were significantly regulated, and correlated with phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, etc. It also revealed the metabolic changes of renal fibrosis and intervention effect of AP. These data uncover a link between metabolism and the molecular mechanism with potential implications in the understanding of the intervention effect of AP. Conclusively, UPLC-Q-TOF-MS-based metabolomics can be valuable and promising strategy to understand the disease mechanism and natural drug pretreatment.

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. The Shenqi pill (SQP) is a representative prescription for clinical application in the prevention and treatment of kidney-yang deficiency syndrome (KYDS). However, its effect mechanism is still not clear. This article aims to reveal the intervention effect of SQP on KYDS from the perspective of lipid metabolism. In this study, SQP was used to intervene in the rat model of KYDS, on the foundation of successfully replicating the rat model of KYDS induced by corticosterone. The MetaboAnalyst tool was used for analysis of the serum metabolic profile and pattern recognition of KYDS model, based on UPLC-SYNAPT-G2-Si-HDMS. Finally, twenty-two potential lipid biomarkers related to the KYDS model were characterized, and the effects of SQP on regulating potential lipid markers in serum of KYDS model were analyzed. There were 10 biomarkers and seven metabolic pathways closely related to SQP therapy for KYDS were found. The action mechanism and targets of SQP in treating KYDS were explored based on high-throughput lipidomics. This work could provide valuable data and scientific evidence in subsequent studies for the treatment of KYDS.

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.

Synergistic therapeutic effects of Duzhong Jiangya Tablets and amlodipine besylate combination in spontaneously hypertensive rats using 1 H-NMR- and MS-based metabolomics

Duzhong Jiangya Tablet (DJT) composed of Eucommia ulmoides Oliv. and several other traditional Chinese medicines is a Chinese herbal compound, which is clinically used to treat hypertension. The aim of this study was to evaluate the antihypertensive effect of DJT and amlodipine besylate (AB) on the synergistic treatment of spontaneously hypertensive rats (SHRs), and to explore its antihypertensive mechanism. The synergistic therapeutic effect of DJT in combination with AB on SHR was studied using two metabolomics methods based on mass spectrum (MS) and nuclear magnetic resonance. Metabolomics analysis of plasma, urine, liver, and kidney and the combination of orthogonal partial least squares discriminant analysis was performed to expose potential biomarkers. Then, the overall metabolic characteristics and related abnormal metabolic pathways in hypertensive rats were constructed. Blood pressure measurements showed that DJT combined with AB has better effects in treating hypertension than it being alone. A total of 30 biomarkers were identified, indicating that hypertension disrupted the balance of multiple metabolic pathways in the body, and that combined administration restored metabolite levels better than their administration alone. The changes of biomarkers revealed the synergistic therapeutic mechanism of DJT combined with AB, which provided a reference for the combination of Chinese and Western medicines.

Metabolomics: a promising diagnostic and therapeutic implement for breast cancer

Breast cancer (BC) is the most commonly diagnosed cancer among women and the leading cause of cancer death. Despite the advent of numerous diagnosis and treatment methods in recent years, this heterogeneous disease still presents great challenges in early diagnosis, curative treatments and prognosis monitoring. Thus, finding promising early diagnostic biomarkers and therapeutic targets and approaches is meaningful. Metabolomics, which focuses on the analysis of metabolites that change during metabolism, can reveal even a subtle abnormal change in an individual. In recent decades, the exploration of cancer-related metabolomics has increased. Metabolites can be promising biomarkers for the screening, response evaluation and prognosis of BC. In this review, we summarized the workflow of metabolomics, described metabolite signatures based on molecular subtype as well as reclassification and then discussed the application of metabolomics in the early diagnosis, monitoring and prognosis of BC to offer new insights for clinicians in breast cancer diagnosis and treatment.

Metabolomics profiling of haloperidol and validation of thromboxane-related signaling in the early development of zebrafish

Haloperidol is a common butyrophenone-derivative antipsychotic drug that is used clinically to treat schizophrenia and to control Tourette disorder. Haloperidol has been shown to be an embryonic toxicant and to cause a variety of adverse effects that affect human embryonic development. However, the pathway impaired by haloperidol during the developmental stages remains unclear. To elucidate the innate toxicological pathway of haloperidol, we investigated the lethality of haloperidol during the embryonic development of zebrafish. We observed that haloperidol caused serious morphological changes, with an LD₅₀ of 9.7 x 10^-6 ± 2.4 x 10^-6 μg/L. Next, we established a systematic approach to perform metabolite profiling in embryonic zebrafish with various concentrations of haloperidol and analyzed the metabolites using ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS). A total of 304 metabolites were identified and 86 metabolites were chosen to predict potential pathways. Among the metabolites, we found through prediction that numerous metabolomics-biological pathways are associated with haloperidol, including peroxisome-proliferator-activated receptor (ppar), thromboxane, and mTOR signaling. Quantitative real time-qPCR was then used to validate the gene expression potentially associated with the thromboxane, which is a metabolic product of arachidonic acid and considered to be important for cell proliferation and the inflammatory response. To sum up, analysis of metabolites in the zebrafish model provides a system for mining biomarkers that reflect biological significance and highlight the therapeutic potency in humans. In addition, it may show potential for application to other pharmaceuticals to identify their various activities and clarify functional mechanisms in the future.

Using high-throughput metabolomics to discover perturbed metabolic pathways and biomarkers of allergic rhinitis as potential targets to reveal the effects and mechanism of geniposide

In this study, we probed the molecular mechanisms of metabolic biomarkers and pathways affected by the bioactive ingredient geniposide (GP), which was shown to protect against experimental allergic rhinitis in mice. The methods used here involved a metabolomics strategy based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-TOF/MS). Using the metabolomics strategy, serum samples of mice in control, model and GP groups were used to explore the differential production of metabolites and pathways related to defense activity of GP towards allergic rhinitis. Allergic symptom, inflammatory factors, and cell populations in the mice spleens were reversed by GP treatment. Seventeen potential biomarkers were discovered in experimental allergic rhinitis mice. GP was shown to have a regulatory effect on 12 of them, which were associated with 8 key metabolic pathways. The ingenuity pathway analysis platform was used to further understand the relationship between metabolic changes and pharmacological activity of GP. The pathways which affected by GP involved cellular growth and proliferation, organismal development, and free radical scavenging. This metabolomics study produced valuable information about potential biomarkers and pathways affected by GP during its effective prevention and therapeutic targeting of allergic rhinitis.

In this study, we probed the molecular mechanisms of metabolic biomarkers and pathways affected by the bioactive ingredient geniposide (GP), which was shown to protect against experimental allergic rhinitis in mice.

Aqueous Humor Analysis Identifies Higher Branched Chain Amino Acid Metabolism as a Marker for Human Leukocyte Antigen-B27 Acute Anterior Uveitis and Disease Activity

PURPOSE

Human leukocyte antigen-B27 (HLA-B27)-positive acute anterior uveitis (AAU) has a higher recurrence rate and shows more anterior chamber cell infiltration compared with HLA-B27-negative patients, suggesting distinct etiologies of these clinically overlapping conditions. To advance our understanding of the biology of AAU, we characterized the metabolic profile of aqueous humor (AqH) of patients with HLA-B27-associated AAU (B27-AAU) and noninfectious idiopathic AAU (idiopathic AAU).

DESIGN

Experimental laboratory study.

METHODS

AqH samples from 2 independent cohorts totaling 30 patients with B27-AAU, 16 patients with idiopathic AAU, and 20 patients with cataracts underwent 2 individual rounds of direct infusion mass spectrometry. Features predicted by direct infusion mass spectrometry that facilitated maximum separation between the disease groups in regression models were validated by liquid chromatography/tandem mass spectrometry-based quantification with appropriate standards.

RESULTS

Partial least square-discriminant analysis revealed metabolite profiles that were able to separate patients with B27-AAU from those with iodiopathic AAU. Pathway enrichment analysis, based on metabolites on which separation of the groups in the partial least square-discriminant analysis model was based, demonstrated the involvement of branched-chain amino acid biosynthesis, ascorbate and aldarate metabolism, the tricarboxylic acid cycle, and glycolysis-diverting pathways (eg, serine biosynthesis) across all investigated cohorts. Notably, the metabolite ketoleucine was elevated in B27-AAU across all 3 runs and moderately-but robustly-correlated with anterior chamber cell count (correlation coefficient range 0.41-0.81).

CONCLUSIONS

These results illustrate metabolic heterogeneity between HLA-B27-positive and HLA-B27-negative AAU, including an increase of branched-chain amino acid biosynthesis, that reflects disease activity in AAU.

Exploring metabolic biomarkers and regulation pathways of acute pancreatitis using ultra-performance liquid chromatography combined with a mass spectrometry-based metabolomics strategy

Acute pancreatitis (AP), as a common kind of pancreas-based inflammatory disease, is accompanied by a serious and abnormal metabolism. However, the specific metabolic process of AP is still unclear. Novel and effective drugs against acute pancreatitis are urgently required. To explore the metabolic biomarkers and regulation pathways of acute pancreatitis, ultra-performance liquid chromatography (UPLC) combined with a mass spectrometry (MS)-based metabolomics strategy was used. Sixteen male adult Sprague-Dawley rats were divided into two groups: a sham operation group (SO) and an AP model group. The AP animal model was induced via the retrograde ductal infusion of 3.5% sodium taurocholate, and rats in the SO group were infused with 0.9% saline. After serum sample collection and sacrifice, a metabolomics strategy based on UPLC-MS was used to detect serum metabolites and metabolic pathways by comparing the SO and AP model groups through full-scan analysis. A total of 19 metabolites were detected in the serum for highlighting the differences between the two groups: l-arabitol, citric acid, isocitric acid, l-phenylalanine, l-tyrosine, dihydroxyacetone, l-valine, succinic acid, 3-hydroxybutyric acid, uric acid, acetylglycine, palmitic amide, homocysteine, d-glutamine, l-arginine, arachidonic acid, N-acetylserotonin, (R)-3-hydroxy-hexadecanoic acid, and d-mannose. Six crucial metabolic pathways, phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism and the citrate cycle, were involved; these have potential to become novel targets for the treatment of AP. The ingenuity pathway analysis (IPA) platform is used to gain insights into the metabolic targets in the system, referring to development disorders, cell-to-cell signaling and interactions, cellular assembly and organization, cell compromise, cell growth and proliferation, carbohydrate metabolism and others. It is suggested that UPLC-MS-based metabolomics is capable of accurately depicting the pathological mechanisms of acute pancreatitis, which can drive new drug development.

Acute pancreatitis (AP), as a common kind of pancreas-based inflammatory disease, is accompanied by a serious and abnormal metabolism.

Exploring potential biomarkers of coronary heart disease treated by Jing Zhi Guan Xin Pian using high-throughput metabolomics

Coronary heart disease (CHD) is a relatively complex disease characterized by narrowing of the arterial lumen and reduction of blood flow to the heart. There is no effective early diagnosis and prevention method. Jing Zhi Guan Xin Pian (JZGXP) is a new preparation prepared from the effective extract of Guanxin II. It is made of five components of traditional Chinese medicine and functions by promoting blood circulation and removing blood stasis and is used for the treatment of CHD and angina pectoris. In our study, a CHD rat model was prepared using a high-fat diet combined with intraperitoneal injection of vitamin D3. Clinical biochemical indexes (TG, CHO and HDL-C), histopathology (coronary and myocardial tissue), electrocardiogram and cardiac indexes were used to evaluate the efficacy of JZGXP in the treatment of CHD model rats. UPLC-HDMS-based metabolomics techniques were used to find metabolic profiles, biomarkers and related metabolic pathways in CHD models and to evaluate the effects of JZGXP on them. At the same time, the targets of JZGXP for the treatment of CHD were analyzed. Our study ultimately identified 25 biomarkers associated with CHD models. Further studies found that these 25 biomarkers involved 9 metabolic pathways in the body and found that JZGXP can recall 21 biomarkers in the urine of model rats and these biomarkers involve nine metabolic pathways. Finally, the targets of JZGXP for the treatment of CHD were β-alanine metabolism and tyrosine metabolism, i.e. amino acids metabolism. This study showed that metabolomics technology is effective for exploring potential biomarkers associated with syndromes or diseases and the therapeutic mechanisms of a traditional Chinese medicine formulation.

Coronary heart disease (CHD) is a relatively complex disease characterized by narrowing of the arterial lumen and reduction of blood flow to the heart.

Mass spectrometry is a multifaceted weapon to be used in the battle against Alzheimer's disease: Amyloid beta peptides and beyond

Amyloid-β peptide (Aβ) accumulation and aggregation have been considered for many years the main cause of Alzheimer's disease (AD), and therefore have been the principal target of investigation as well as of the proposed therapeutic approaches (Grasso [2011] Mass Spectrom Rev. 30: 347-365). However, the amyloid cascade hypothesis, which considers Aβ accumulation the only causative agent of the disease, has proven to be incomplete if not wrong. In recent years, actors such as metal ions, oxidative stress, and other cofactors have been proposed as possible co-agents or, in some cases, main causative factors of AD. In this scenario, MS investigation has proven to be fundamental to design possible diagnostic strategies of this elusive disease, as well as to understand the biomolecular mechanisms involved, in the attempt to find a possible therapeutic solution. We review the current applications of MS in the search for possible Aβ biomarkers of AD to help the diagnosis of the disease. Recent examples of the important contributions that MS has given to prove or build theories on the molecular pathways involved with such terrible disease are also reviewed.

Gut microbiota as important modulator of metabolism in health and disease

The human gastrointestinal tract colonizes a large number of microbial microflora, forms a host-microbiota co-metabolism structure with the host to participate in various metabolic processes in the human body, and plays a major role in the host immune response. In addition, the dysbiosis of intestinal microbial homeostasis is closely related to many diseases. Thus, an in-depth understanding of the relationship between them is of importance for disease pathogenesis, prevention and treatment. The combined use of metagenomics, transcriptomics, proteomics and metabolomics techniques for the analysis of gut microbiota can reveal the relationship between microbiota and the host in many ways, which has become a hot topic of analysis in recent years. This review describes the mechanism of co-metabolites in host health, including short-chain fatty acids (SCFA) and bile acid metabolism. The metabolic role of gut microbiota in obesity, liver diseases, gastrointestinal diseases and other diseases is also summarized, and the research methods for multi-omics combined application on gut microbiota are summarized. According to the studies of the interaction mechanism between gut microbiota and the host, we have a better understanding of the use of intestinal microflora in the treatment of related diseases. It is hoped that the gut microbiota can be utilized to maintain human health, providing a reference for future research.

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

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