High-Throughput Metabolomics Integrated Network Pharmacology Reveals the Underlying Mechanism of Paeoniae Radix Alba Treating Rheumatoid Arthritis

Objective: The mechanism of action and potential targets of Paeoniae RadixAlba (Baishao, B) in the treatment of adjuvant-induced arthritis (AIA) rats are explained using metabolomics and network pharmacology techniques, and the research evidence for the development of anti-rheumatoid arthritis (RA) drugs is enriched. Methods: The rats were injected with Freund’s complete adjuvant (CFA) to induce arthritis. We then measured the general physical characteristics, examined their X-rays and histopathology to evaluate the pathological condition of the inflammation models, and conducted metabolomics studies on the change in urine metabolism caused by CFA. The lyophilized powder of B at a dose of 2.16 g/kg was orally administered to the rats continuously for 28 days, and the therapeutic effect was evaluated. Network pharmacology prediction shows that B contains the target action of the ingredient, and the simulation of the target molecular docking, in combination with the metabolomics analysis results, shows that B has a potential role in the treatment of AIA rats. Results: B can reduce the paw swelling and pathological changes in rats caused by CFA, reverse the levels of 12 urine biomarkers, and regulate histidine metabolism, phenylalanine metabolism, arginine, proline metabolism, pyrimidine metabolism, etc. The prediction of the active ingredient target in B indicates that it may act as an inflammatory signaling pathway in anti-RA, among them being paeoniflorin, palbinone, beta-sitosterol, kaempferol, and catechin, which are the significant active ingredients. Conclusion: The metabolomics results revealed the markers and metabolic mechanisms of urinary metabolic disorders in rats with AIA, demonstrated the efficacy of the therapeutic effect of B, and identified the key ingredients in B, providing theoretical support for the subsequent development and utilization of B.

Artificial intelligence in cancer target identification and drug discovery

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as cancer. Here, we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover drugs. First, we describe the scope of artificial intelligence biology analysis for novel anticancer target investigations. Second, we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence algorithms. Finally, we showcase the applications of artificial intelligence approaches in cancer target identification and drug discovery. Taken together, the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer, thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.

High-Throughput Chinmedomics Strategy Discovers the Quality Markers and Mechanisms of Wutou Decoction Therapeutic for Rheumatoid Arthritis

Wutou decoction (WTD) is a traditional Chinese medicine prescription for the treatment of rheumatoid arthritis (RA), and this study systematically analyzed the metabolic mechanism and key pharmacodynamic components of WTD in RA rats by combining untargeted metabolomics and serum pharmacochemistry of traditional Chinese medicine to enrich the evidence of WTD quality markers (Q-markers) studies. WTD prevented synovial edema in RA rats and reduced tumor necrosis factor-alpha and interleukin 6 levels in rat serum, according to the results of an enzyme-linked immunosorbent examination and histopathological inspection. In model rats, pattern recognition and multivariate statistical analysis revealed 24 aberrant metabolites that disrupted linoleic acid metabolism, arachidonic acid metabolism, arginine and proline metabolism, etc. However, continued dosing of WTD for 28 days reversed 13 abnormal metabolites, which may be an important therapeutic mechanism from a metabolomic perspective. Importantly, 12 prototypical components and 16 metabolites from WTD were characterized in RA rat serum. The results of Pearson correlation analysis showed that aconitine, L-ephedrine, L-methylephedrine, quercetin, albiflorin, paeoniflorigenone, astragaline A, astragaloside II, glycyrrhetic acid, glycyrrhizic acid, licurazide, and isoliquiritigenin are the key pharmacological components that regulate the metabolism of RA rats, and they are identified as Q-markers. In sum, utilizing metabolomics and serum pharmacochemistry of traditional Chinese medicine, the metabolic mechanisms and Q-markers of WTD therapy in RA rats were revealed, providing a theoretical basis for the quality control investigation of WTD.

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.

A Hypothesis From Metabolomics Analysis of Diabetic Retinopathy: Arginine-Creatine Metabolic Pathway May Be a New Treatment Strategy for Diabetic Retinopathy

Diabetic retinopathy is one of the serious complications of diabetes, which the leading causes of blindness worldwide, and its irreversibility renders the existing treatment methods unsatisfactory. Early detection and timely intervention can effectively reduce the damage caused by diabetic retinopathy. Metabolomics is a branch of systems biology and a powerful tool for studying pathophysiological processes, which can help identify the characteristic metabolic changes marking the progression of diabetic retinopathy, discover potential biomarkers to inform clinical diagnosis and treatment. This review provides an update on the known metabolomics biomarkers of diabetic retinopathy. Through comprehensive analysis of biomarkers, we found that the arginine biosynthesis is closely related to diabetic retinopathy. Meanwhile, creatine, a metabolite with arginine as a precursor, has attracted our attention due to its important correlation with diabetic retinopathy. We discuss the possibility of the arginine-creatine metabolic pathway as a therapeutic strategy for diabetic retinopathy.

Dimethyl phthalate damages Staphylococcus aureus by changing the cell structure, inducing oxidative stress and inhibiting energy metabolism

Dimethyl phthalate (DMP), used as a plasticizer in industrial products, exists widely in air, water and soil. Staphylococcus aureus is a typical model organism representing Gram-positive bacteria. The molecular mechanisms of DMP toxicology in S. aureus were researched by proteomic and transcriptomic analyses. The results showed that the cell wall, membrane and cell surface characteristics were damaged and the growth was inhibited in S. aureus by DMP. Oxidative stress was induced by DMP in S. aureus. The activities of succinic dehydrogenase (SDH) and ATPase were changed by DMP, which could impact energy metabolism. Based on proteomic and transcriptomic analyses, the oxidative phosphorylation pathway was enhanced and the glycolysis/gluconeogenesis and pentose phosphate pathways were inhibited in S. aureus exposed to DMP. The results of real-time reverse transcription quantitative PCR (RT-qPCR) further confirmed the results of the proteomic and transcriptomic analyses. Lactic acid, pyruvic acid and glucose were reduced by DMP in S. aureus, which suggested that DMP could inhibit energy metabolism. The results indicated that DMP damaged the cell wall and membrane, induced oxidative stress, and inhibited energy metabolism and activation in S. aureus.

Network pharmacology combined with metabolomics approach to investigate the protective role and detoxification mechanism of Yunnan Baiyao formulation

BACKGROUND

Yunnan Baiyao (YNBY) is a traditional Chinese medicine formulae, which has the functions of hemostasis, activating blood circulation and removing blood stasis, anti-inflammation, etc. Although the presence of Caowu (CW, Aconiti Kusnezoffii Radix), the detoxification mechanism of YNBY is still unclear.

PURPOSE

In current study, network pharmacology, toxicological methods and metabolomics technique were applied to explore YNBY in attenuating toxicity of CW.

METHODS

Prediction of targets and pathways of CW were carried out by commonly used network pharmacological method. Simultaneously, SD rats were orally administrated with CW, processed CW (ZCW), YNBY, and YNBY which lack of CW (QCW) for 15 days. Tissue samples were observed with histopathology. Urine samples were analyzed with ultra-performance liquid chromatography-mass spectrometry to screen differential metabolites and related metabolic pathways associated with toxicity of CW. Furthermore, by comparing the changes of the metabolite contents, focused the attenuated metabolic pathway. Finally, the network pharmacological and experimental data were integrated to investigate detoxification mechanism of YNBY.

RESULTS

A total of 44 potential toxicity biomarkers were identified and 14 related pathways were involved in the toxicity of CW. Furthermore, 5 core toxicity biomarkers (2-keto-6-acetamidocaproate, γ-glutamylleucine, prostaglandin E₃, 4-hydroxy-5-(3'-hydroxyphenyl)-valeric acid-3'-O-sulphate, and 3,4-dihydroxy- phenylglycol O-sulfate) were regulated to normal condition in YNBY group. Lysine degradation was locked as the core metabolic pathway of detoxification of YNBY. Integrating the predicted results of network pharmacology, ACHE, SLC6A3, SLC6A4 might be the target of protective role of other herbs in YNBY.

CONCLUSION

Network pharmacology combined with metabolomics exhibited a powerful mean to investigate the herbal toxicity and probed into the detoxification mechanism of formulae, which contributes to its safety evaluation.

High-throughput metabolomics reveals the perturbed metabolic pathways and biomarkers of Yang Huang syndrome as potential targets for evaluating the therapeutic effects and mechanism of geniposide

High-throughput metabolomics can clarify the underlying molecular mechanism of diseases via the qualitative and quantitative analysis of metabolites. This study used the established Yang Huang syndrome (YHS) mouse model to evaluate the efficacy of geniposide (GEN). Urine metabolic data were quantified by ultraperformance liquid chromatography-tandem mass spectrometry. The non-target screening of the massive biological information dataset was performed, and a total of 33 metabolites, including tyramine glucuronide, aurine, and L-cysteine, were identified relating to YHS. These differential metabolites directly participated in the disturbance of phase I reaction and hydrophilic transformation of bilirubin. Interestingly, they were completely reversed by GEN. While, as the auxiliary technical means, we also focused on the molecular prediction and docking results in network pharmacological and integrated analysis part. We used integrated analysis to communicate the multiple results of metabolomics and network pharmacology. This study is the first to report that GEN indirectly regulates the metabolite "tyramine glucuronide" through its direct effect on the target heme oxygenase 1 in vivo. Meanwhile, heme oxygenase-1, a prediction of network pharmacology, was the confirmed metabolic enzyme of phase I reaction in hepatocytes. Our study indicated that the combination of high-throughput metabolomics and network pharmacology is a robust combination for deciphering the pathogenesis of the traditional Chinese medicine (TCM) syndrome.

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.

Optimising low-dose methotrexate for rheumatoid arthritis-A review

Methotrexate at low doses (5-25 mg/week) is first-line therapy for rheumatoid arthritis. However, there is inter- and intrapatient variability in response, with contribution of variability in concentrations of active polyglutamate metabolites, associated with clinical efficacy and toxicity. Prescribing remains heterogeneous across population groups, disease states and regimens. This review examines current knowledge of dose-response of oral methotrexate in the setting of rheumatoid arthritis, and how this could help inform dosage regimens.

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 for discovering metabolic biomarkers from intestinal tumorigenesis in APC min/+ mice based on liquid chromatography/mass spectrometry

As a major public health concern, colon cancer is one of the most common cancer types, which is also the second cause of cancer death in developed countries and the third most common cancer in other parts of the world. It was reported that patients diagnosed at early stage have a chance to obtain 5-year survival rates at least compared to patients with late stage. Facing the multistep process in intestinal tumorigenesis, there is an urgent need to develop more effective early detection strategies for ameliorating the patient clinical outcome. Metabolomics open up a novel avenue of seeking valuable potential biomarkers for assessing disease severity and prognosticating course by dynamic snapshot of small molecule metabolites. The study aims to provide deeper insights into the discovery, identification and functional pathways analysis of differentially expressed metabolites in intestinal tumorigenesis in APC ^min/+ mice used by the serum metabolomics, and bring about useful information for further effective prevention and treatment of the disease. 17 marker metabolites and related metabolism pathway were identified using non-targeted metabolomics based on liquid chromatography/mass spectrometry (LC/MS) associated with multivariate statistical analysis. The ingenuity pathway analysis platform involved multiple-pathways was applied to metabolic network analysis for further understanding the relationship between functional metabolic pathways and disease.

Side effects of methotrexate therapy for rheumatoid arthritis: A systematic review

Methotrexate (MTX) is used as an anchor disease-modifying anti-rheumatic drugs (DMARDs) in treating rheumatoid arthritis (RA) because of its potent efficacy and tolerability. MTX benefits a large number of RA patients but partially suffered from side effects. A variety of side effects can be associated with MTX when treating RA patients, from mild to severe or discontinuation of the treatment. In this report, we reviewed the possible side effects that MTX might cause from the most common gastrointestinal toxicity effects to less frequent malignant diseases. In order to achieve regimen with less side effects, the administration of MTX with appropriate dose and a careful pretreatment inspection is necessary. Further investigations are required when combining MTX with other drugs so as to enhance the efficacy and reduce side effects at the same time. The management of MTX treatment is also discussed to provide strategies for occurred side effects. Thus, this review will provide scholars with a comprehensive understanding the side effects of MTX administration by RA patients.

Rapid discovery and global characterization of multiple components in corn silk using a multivariate data processing approach based on UHPLC coupled with electrospray ionization/quadrupole time-of-flight mass spectrometry

Corn silk is an important traditional Chinese medicine which has been widely used as diuretic, antilithiasic, uricosuric, antiseptic, etc. for thousands of years. However, it is a pity that the chemical ingredients in corn silk, especially the constituents absorbed into blood, are unclear up to now. The aim of our study was to investigate the multiple components of corn silk in vitro and in vivo. In this present study, a sensitive and rapid method using ultra high performance liquid chromatography coupled with electrospray ionization/quadrupole time-of-flight tandem mass spectrometry and a multivariate data processing approach was established to detect the constituents of corn silk in vitro and in vivo. Consequently, total 41 ingredients in vitro and 19 of them absorbed into blood including luteolin, various C-glycosyl flavones, jasmonic acid, abscisic acid, gibberellin A, etc. were tentatively characterized in sequence. Furthermore, of particular importance, a kind of stable compound named C-glycosyl flavones is a great discovery in vivo, which can point the further pharmacological study target in future. In a word, this is the first serum pharmacochemistry study of corn silk, which played a critical role in exploring the pharmacological and effective data for further research.

Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach

Metabolomics, as a promising and powerful approach, refers to comprehensive assessment and identification of small molecule endogenous metabolites in a biological system which is capable of further understanding the mechanisms of diseases for early diagnosis, effective treatment and prognosis. Acute kidney injury (AKI) induced by contrast is a serious complication in patients undergoing administration of iodinated contrast media. It is becoming a major health concern in clinic, however, the molecular mechanisms of contrast-induced acute kidney injury (CI-AKI) have not been well characterized. In this study, we used serum metabolomics based on liquid chromatography-mass spectrometry (LC-MS) combined with pattern recognition to explore and characterize potential metabolites and metabolic pathway in an experimental model for CI-AKI. Seventeen differentiating metabolites in the serum were identified involving the pivotal metabolic pathways related to tryptophan metabolism, glycerophospholipid metabolism, steroid hormone biosynthesis, pyrimidine metabolism, sphingolipid metabolism, aminoacyl-tRNA biosynthesis. Our study provides novel insight into pathophysiologic mechanisms of AKI by changing biomarkers and pathways.

UPLC-G2Si-HDMS untargeted metabolomics for identification of metabolic targets of Yin-Chen-Hao-Tang used as a therapeutic agent of dampness-heat jaundice syndrome

Yin-Chen-Hao-Tang (YCHT), the classic formulae of traditional Chinese medicine (TCM), is widely used to treat dampness-heat jaundice syndrome (DHJS) and various liver diseases. However, the therapeutic mechanism of YCHT is yet to have an integrated biological interpretation. In this work, we used metabolomics technology to reveal the adjustment of small molecule metabolites in body during the treatment of YCHT. Aim to discover the serum biomarkers which are associated with the treatment of DHJS against YCHT. Pathological results and biochemical indicators showed that the hepatic injury and liver index abnormalities caused by DHJS was effectively improve after treatment with YCHT. On the basis of effective treatment, ultra-high performance liquid chromatography (UPLC-G2Si-HDMS) combined with the multivariate statistical analysis method was utilized to analyze the serum samples. Finally, 22 biomarkers were identified by using mass spectrometry and illuminated the correlative metabolic pathways which play a significant role and as therapeutic targets in the treatment of DHJS. This work demonstrated that mass spectrometry metabolomics provides a new insight to elucidate the action mechanism of formulae.

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

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

Altered lipid metabolism is an emerging hallmark of cancers.

Functional metabolomics discover pentose and glucuronate interconversion pathways as promising targets for Yang Huang syndrome treatment with Yinchenhao Tang

Yinchenhao Tang (YCHT), a classic traditional Chinese medicine (TCM) formulae, plays an important role in the treatment of Yang Huang syndrome (YHS). With the emergence of new biomarkers of YHS uncovered via metabonomics, the underlying functional mechanisms are still not clear. Functional metabolomics aims at converting biomarkers derived from metabonomics into disease mechanisms. Here, an integrated non-target metabolomics and IPA strategy were used to investigate the YCHT intervention on YHS. Our metabolomics study has shown that the potential protective effect of YCHT on YHS mice leads to significant changes in the metabolic profile by modulating the biomarkers and regulating the metabolic disorders. Twenty two differential metabolite biomarkers and fifteen involved metabolic pathways were correlated with the regulation of YCHT treatment on YHS. Functional metabolomics identified a core biomarker, d-glucuronic acid in pentose and glucuronate interconversion pathways, which was directly related to the target prediction of UDP-glucuronosyltransferase 1A1 and eventually leaded to a series of disturbances. In conclusion, this study shows that functional metabolomics can discover metabolic pathways as promising targets.

Yinchenhao Tang (YCHT), a classic traditional Chinese medicine (TCM) formulae, plays an important role in the treatment of Yang Huang syndrome (YHS).

Combined systems pharmacology and fecal metabonomics to study the biomarkers and therapeutic mechanism of type 2 diabetic nephropathy treated with Astragalus and Leech

In our study, systems pharmacology was used to predict the molecular targets of Astragalus and Leech, and explore the therapeutic mechanism of type 2 diabetic nephropathy (T2DN) treated with Astragalus and Leech. Simultaneously, to reveal the systemic metabolic changes and biomarkers associated with T2DN, we performed ¹H NMR-based metabonomics and multivariate analysis to analyze fecal samples obtained from model T2DN rats. In addition, ELISA kits and histopathological studies were used to examine biochemical parameters and kidney tissue, respectively. Striking differences in the Pearson's correlation of 22 biomarkers and 9 biochemical parameters were also observed among control, T2DN and treated rats. Results of systems pharmacology analysis revealed that 9 active compounds (3,9-di-O-methylnissolin; (6aR,11aR)-9,10-dimethoxy-6a,11a-dihydro-6H-benzofurano[3,2-c]chromen-3-ol; hirudin; l-isoleucine; phenylalanine; valine; hirudinoidine A–C) and 9 target proteins (l-serine dehydratase; 3-hydroxyacyl-CoA dehydrogenase; tyrosyl-tRNA synthetase; tryptophanyl-tRNA synthetase; branched-chain amino acid aminotransferase; acetyl-CoA C-acetyltransferase; isovaleryl-CoA dehydrogenase; pyruvate dehydrogenase E1 component alpha subunit; hydroxyacylglutathione hydrolase) of Astragalus and Leech were closely associated with the treatment of T2DN. Using fecal metabonomics analysis, 22 biomarkers were eventually found to be closely associated with the occurrence of T2DN. Combined with systems pharmacology and fecal metabonomics, these biomarkers were found to be mainly associated with 6 pathways, involving amino acid metabolism (leucine, valine, isoleucine, alanine, lysine, glutamate, taurine, phenylalanine, tryptophan); energy metabolism (lactate, succinate, creatinine, α-glucose, glycerol); ketone body and fatty acid metabolism (3-hydroxybutyrate, acetate, n-butyrate, propionate); methylamine metabolism (dimethylamine, trimethylamine); and secondary bile acid metabolism and urea cycle (deoxycholate, citrulline). The underlying mechanisms of action included protection of the liver and kidney, enhancement of insulin sensitivity and antioxidant activity, and improvement of mitochondrial function. To the best of our knowledge, this is the first time that systems pharmacology combined with fecal metabonomics has been used to study T2DN. 6 metabolites (n-butyrate, deoxycholate, propionate, tryptophan, taurine and glycerol) associated with T2DN were newly discovered in fecal samples. These 6 metabolites were mainly derived from the intestinal flora, and related to amino acid metabolism, fatty acid metabolism, and secondary bile acid metabolism. We hope the results of this study could be inspirational and helpful for further exploration of T2DN treatment. Meanwhile, our results highlighted that exploring the biomarkers of T2DN and therapeutic mechanisms of Traditional Chinese Medicine (TCM) formulas on T2DN by combining systems pharmacology and fecal metabonomics methods was a promising strategy.

In our study, systems pharmacology was used to predict the molecular targets of Astragalus and Leech, and explore the therapeutic mechanism of type 2 diabetic nephropathy (T2DN) treated with Astragalus and Leech.

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.

Serum metabolomics strategy for understanding the therapeutic effects of Yin-Chen-Hao-Tang against Yanghuang syndrome

Yin-Chen-Hao-Tang (YCHT), a classic Chinese herbal formula, is characterized by its strong therapeutic effects of liver regulation and relief of jaundice, especially Yanghuang syndrome (YHS). YHS is a type of jaundice with damp-heat pathogenesis, and it is considered a complicated Chinese medicine syndrome (CMS). The accurate mechanism for healing YHS has not yet been completely reported. The purpose of the current research is to investigate the expression of endogenous biomarkers in YHS mice and evaluate the clinical therapeutic effect of YCHT. Serum samples were analyzed using UPLC-Q/TOF-MS techniques in order to determine differential metabolites to elucidate the functional mechanism of YCHT on YHS through metabolite profiling combined with multivariate analysis. Simultaneously, the exact diversification of YHS mice was elucidated using blood biochemistry indexes and histopathological examination, and the results indicated that YHS is markedly improved by YCHT. Unsupervised principal component analysis (PCA) patterns were constructed to dissect the variances of metabolic profiling. Overall, 22 potential biomarkers were identified using a metabolomics approach based on an accurate MS/MS approach, clustering and distinguishing analysis. The present work demonstrates that the effectiveness of YCHT against YHS prompts distinct discrepancies in metabolic profiles by adjusting biomarkers and regulating metabolic disorders. A total of 15 metabolic pathways were involved in biological disturbance. This demonstrates that metabolomic techniques are powerful means to explore the pathogenesis of CMS and the therapeutic effects of traditional Chinese formulae.

The purpose of the current research is to investigate the expression of endogenous biomarkers in Yanghuang syndrome mice and evaluate the clinical therapeutic effect of Yin-Chen-Hao-Tang.

Advances in mass spectrometry-based metabolomics for investigation of metabolites

Metabolomics is the systematic study of all the metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing over an extensive dynamic range in biological samples. Diverse analytical techniques are needed to achieve higher coverage of metabolites. The application of mass spectrometry (MS) in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques. Significant advances have also occurred in separation-based MS techniques (gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and ion mobility-mass spectrometry), as well as separation-free MS techniques (direct infusion-mass spectrometry, matrix-assisted laser desorption ionization-mass spectrometry, mass spectrometry imaging, and direct analysis in real time mass spectrometry) in the past decades. This review presents a brief overview of the recent advanced MS techniques and their latest applications in metabolomics. The software/websites for MS result analyses are also reviewed.

Metabolomics is the systematic study of all the metabolites present within a biological system, supply functional information and has received extensive attention in the field of life sciences.

LC-MS-based plasma metabolomics reveals metabolic variations in ovariectomy-induced osteoporosis in female Wistar rats

Osteoporosis with a reduction in bone mineral density has become one of the most common metabolic bone diseases.

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.

High-throughput system metabolomics method reveals new mechanistic insights of chlorogenic acid by using liquid chromatography coupled to high resolution mass spectrometry

It has increasingly been recognized that metabolism is highly interconnected with disease, and system metabolomics studies have aimed to discover metabolic biomarkers and analyze the pathways of metabolome phenotypes. To better understand the metabolic alteration related with disease, a urine metabolic profile using a high-throughput system metabolomics technology approach was applied to probe the underlying molecular mechanisms of alcohol-induced liver injury and the therapeutic effects of chlorogenic acid (CA). In this study, endogenous low-molecular-weight metabolites were characterized using liquid chromatography coupled with mass spectrometry (LC-MS). The acquired data was parsed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to identify potential biomarkers. A total of 19 biomarkers were identified in a model of alcohol-induced liver injury rats, and it was found that chlorogenic acid had a regulatory effect on 14 of them, associated with multiple metabolic pathways. Comprehensive pathway analysis suggests that CA has the ability to regulate abnormal metabolic states. In addition, accessory examinations such as biochemical analysis and histopathological observations were also performed that showed similar results. As a natural product agent against ethanol-induced liver injury, CA was validated in the rebalancing of a wide range of metabolic disorders. High-throughput system metabolomics represents a powerful approach for revealing new mechanistic insights of natural products.

It has increasingly been recognized that metabolism is highly interconnected with disease, and system metabolomics studies have aimed to discover metabolic biomarkers and analyze the pathways of metabolome phenotypes.

Prediction of the targets of the main components in blood after oral administration ofXanthii Fructus: a network pharmacology study

Xanthii Fructus (XF), a famous traditional Chinese medicine (TCM), has been widely used in the treatment of rhinitis and other diseases. However, the targets of the main XF components found in the blood after oral administration of XF extract are still unclear. In the current study, a feasible systems pharmacology method was developed to predict these targets. In accordance with our previous research, XF components were selected including cleomiscosin A, myristic acid, succinic acid, xanthosine, sitostenone, emodin, apigenin, and chrysophanol. Three components, namely emodin, apigenin, and chrysophanol, failed to be detected with target proteins, thus the other five components, namely cleomiscosin A, myristic acid, succinic acid, xanthosine and sitostenone, were eventually chosen for further systematic analysis. Ninety-nine target proteins and fifty-two pathways were found after a series of analyses. The frequency of some target proteins was much higher than that of others; high frequencies were obtained for P15086, P07360, P07195, MAOM_HUMAN (P23368), P35558, P35520, ACE_HUMAN (P12821), C1S_HUMAN (P09871), PH4H_HUMAN (P00439), FPPS_HUMAN (P14324), P50613, P12724, IMPA1_HUMAN (P29218), HXK1_HUMAN (P19367), P14061, and MCR_HUMAN (P08235). The frequency of eight pathways was also high, including Generic Transcription Pathway, RNA Polymerase II Transcription, Metabolism, Metabolism of steroids, Gene expression (Transcription), Cellular responses to stress, Platelet activation, signaling and aggregation, Signaling by Receptor Tyrosine Kinases, and Cellular Senescence. This study identified a common pathway – the Metabolism pathway – for all five XF components. We successfully developed a network pharmacology method to predict the potential targets of the main XF components absorbed in serum after oral administration of XF extract.

This paper developed a network pharmacology method to predict the potential pathways targeted by oral administration of XF extract.

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

In this study, a combination of network pharmacology and metabolomics was used to explore the mechanism by which mirabilite regulates bile acid metabolism in the treatment of colorectal cancer.