Metabolomics Strategy Research Articles

Dissection of Targeting Molecular Mechanisms of Aristolochic Acid-induced Nephrotoxicity via a Combined Deconvolution Strategy of Chemoproteomics and Metabolomics.

Aristolochic acid (AA), mainly derived from herbal Aristolochia and Asarum plants, was listed as a human carcinogen class I in 2002. Aristolochic acid nephropathy (AAN) is a rapidly progressive tubulointerstitial nephritis and urothelial cancer caused by AA. However, the targeting molecular mechanisms of AAs-induced nephrotoxicity are largely unclear. This study aims to dissect targeting molecular mechanisms of AA-induced nephrotoxicity. Activity-based protein profiling (ABPP) in combination with cellular thermal shift assay (CETSA) was performed to identify the AAs binding target proteins. Our data indicated that several key enzymes in the metabolic process and mitochondrial respiration including IDH2 and MDH2 (Krebs cycle), PKM and LDH (aerobic respiration), FASN (fatty acid beta-oxidation), HK2 (glucose metabolism), and ATP synthase were identified as directly binding targets of AAs. Metabolomics and oxygen consumption rate (OCR) experiments further confirmed that AAs targeting proteins disrupted metabolic biosynthesis processes and impaired mitochondrial functions. Ultimately, AAs induced renal cells apoptosis by disturbing various biological processes. Cumulatively, AAs may directly bind to key proteins involved in the metabolic process and mitochondrial homeostasis, and finally induce aristolochic acid nephropathy. Our findings provide novel insight into underlying mechanisms of AAs-induced kidney toxicity, which may help to develop therapeutic strategies for AAN.

A non-targeted metabolomic strategy for characterization of the botanical origin of honey samples using headspace gas chromatography-ion mobility spectrometry.

In this work, characterization of the botanical origin of honey was carried out using headspace gas chromatography coupled to ion mobility spectrometry (HS-GC-IMS). The proposed methodology was applied for the analysis of 89 samples from ten different botanical origins. A total of 15 volatile compounds could be identified, namely, 3-methyl-1-butanol, heptanal, valeraldehyde, octanal, trans-2-hexenal, nonanal, hexanal, benzaldehyde, 2-heptanone, 2-butanone, 2-hexanone, 6-methyl-5-hepten-2-one, 2-pentanone, ethyl acetate and linalool. The analytical method was characterized in terms of limits of detection and quantification, and precision, in order to quantify the identified compounds. Compounds were quantified using the sum of the protonated monomer and proton-bound dimer and logarithmic regression (R2 > 0.98), although the establishment of a concentration threshold that would allow creation of classification rules was not possible since there was variability within the group. Consequently, the establishment of chemometric models was necessary. A non-targeted strategy using 275 features is proposed. Orthogonal partial least squares-discriminant analysis (OPLS-DA) allowed the differentiation of five botanical origins: thousand flowers, rosemary, albaida, orange blossom, and "others" (rest of the investigated botanical origins, since a limited number of samples was available). A success validation rate of 100% allowed the classification of 14 honeys with unknown botanical origin.

Screening of Small Molecular Biomarker Candidates Using Untargeted Metabolomics Strategy in Peripheral Blood from Rats with Neuroinflammatory Injury Induced by Whole-Brain Irradiation

Screening of Small Molecular Biomarker Candidates Using Untargeted Metabolomics Strategy in Peripheral Blood from Rats with Neuroinflammatory Injury Induced by Whole-Brain Irradiation

Innovative Approaches to Assess Intermediate Cardiovascular Risk Subjects: A Review From Clinical to Metabolomics Strategies.

Current risk stratification strategies for coronary artery disease (CAD) have low predictive value in asymptomatic subjects classified as intermediate cardiovascular risk. This is relevant because not all coronary events occur in individuals with traditional multiple risk factors. Most importantly, the first manifestation of the disease may be either sudden cardiac death or acute coronary syndrome, after rupture and thrombosis of an unstable non-obstructive atherosclerotic plaque, which was previously silent. The inaccurate stratification using the current models may ultimately subject the individual to excessive or insufficient preventive therapies. A breakthrough in the comprehension of the molecular mechanisms governing the atherosclerosis pathology has driven many researches toward the necessity for a better risk stratification. In this Review, we discuss how metabolomics screening integrated with traditional risk assessments becomes a powerful approach to improve non-invasive CAD subclinical diagnostics. In addition, this Review highlights the findings of metabolomics studies performed by two relevant analytical platforms in current use–mass spectrometry (MS) hyphenated to separation techniques and nuclear magnetic resonance spectroscopy (NMR) –and evaluates critically the challenges for further clinical implementation of metabolomics data. We also discuss the modern understanding of the pathophysiology of atherosclerosis and the limitations of traditional analytical methods. Our aim is to show how discriminant metabolites originated from metabolomics approaches may become promising candidate molecules to aid intermediate risk patient stratification for cardiovascular events and how these tools could successfully meet the demands to translate cardiovascular metabolic biomarkers into clinical settings.

LC-MS-based untargeted metabolomics reveals chemical differences of Cannabis leaves from different regions of China

Cannabis sativa L. is an industrial and medicinal crop that originated in Eurasia. Its female inflorescence is usually used as a drug because of its high content of Δ9-tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD), while the stem and leaf have great potential as sustainable sources of fiber and fuel. In this study, we used an ultra-high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF MS)-based untargeted metabolomics strategy to profile the metabolome differences among those Cannabis leaves collected before flowering from Xinjiang, Qinghai and Sichuan Provinces. Kruskal–Wallis test, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were applied to compare and discover the chemical characterization of the collected samples. Finally, potential high-contribution features were identified as 13 flavonoids (including C-glycoside and O-glycoside) and 1 cannabinoid based on high-resolution MS and MS/MS information, in which 4 flavonoids were unambiguously identified by reference standards. Cannabis leaves from Xinjiang and Qinghai accumulated higher flavonoid glucuronides, while flavonoid glycosides were more abundant in those from Sichuan. However, for the cannabinoids, such as Δ9-THC and CBD, there were no significant differences in leaves, even those samples shown difference genotypes. Our results indicating that flavonoids variation in Cannabis leaves has potential ability of chemotypic marker and geographical marker, and may improve the practical and economic value of Cannabis leaves.

Unraveling Autocrine Signaling Pathways through Metabolic Fingerprinting in Serous Ovarian Cancer Cells.

Focusing on defining metabolite-based inter-tumoral heterogeneity in ovarian cancer, we investigated the metabolic diversity of a panel of high-grade serous ovarian carcinoma (HGSOC) cell-lines using a metabolomics platform that interrogate 731 compounds. Metabolic fingerprinting followed by 2-dimensional and 3-dimensional principal component analysis established the heterogeneity of the HGSOC cells by clustering them into five distinct metabolic groups compared to the fallopian tube epithelial cell line control. An overall increase in the metabolites associated with aerobic glycolysis and phospholipid metabolism were observed in the majority of the cancer cells. A preponderant increase in the levels of metabolites involved in trans-sulphuration and glutathione synthesis was also observed. More significantly, subsets of HGSOC cells showed an increase in the levels of 5-Hydroxytryptamine, γ-aminobutyrate, or glutamate. Additionally, 5-hydroxytryptamin synthesis inhibitor as well as antagonists of γ-aminobutyrate and glutamate receptors prohibited the proliferation of HGSOC cells, pointing to their potential roles as oncometabolites and ligands for receptor-mediated autocrine signaling in cancer cells. Consistent with this role, 5-Hydroxytryptamine synthesis inhibitor as well as receptor antagonists of γ-aminobutyrate and Glutamate-receptors inhibited the proliferation of HGSOC cells. These antagonists also inhibited the three-dimensional spheroid growth of TYKNU cells, a representative HGSOC cell-line. These results identify 5-HT, GABA, and Glutamate as putative oncometabolites in ovarian cancer metabolic sub-type and point to them as therapeutic targets in a metabolomic fingerprinting-based therapeutic strategy.

Study on the Molecular Basis of Huanglian Jiedu Decoction Against Atopic Dermatitis Integrating Chemistry, Biochemistry, and Metabolomics Strategies.

Atopic dermatitis (AD) is a common chronic relapsing skin inflammation, which severely affect the quality of life of patients. Inhibiting itching and enhancing immunity to mitigate scratching are key elements in the fight against AD. Huanglian Jiedu decoction (HLJDD) has multiple pharmacological effects in the treatment of AD. However, the effective ingredients and underlying molecular mechanisms have not yet been fully explored. Thus, this study integrates chemistry, biochemistry, and metabolomics strategies to evaluate the active substance basis of HLJDD against AD. First, HLJDD was split to five fractions (CPF, 40AEF, 90AEF, PEF and WEF) and 72 chemical components were identified. NSD (Non-similarity degree) among the different fractions showed significant chemical differences (>81%). Interleukin IL-13, IL-17A, IL-3, IL-31, IL-33, IL4, IL-5, TSLP, IgE, and histamine in the serum, and IL-4Rα, JAK1, and HRH4 levels in skin, participating in inhibiting itching and regulating immunity signaling, were found to be restored to varying degrees in AD treating with HLJDD and its fractions, especially 40AEF and CPF. Untargeted metabolomics analysis demonstrated that forty metabolites were differential metabolites in plasma between the HLJDD-treated group and the AD group, involving in histidine metabolism, arginine biosynthesis, pyrimidine metabolism, and so on. Further, targeted metabolomics analysis revealed that eleven differential metabolites, associating with physiological and biochemical indices, were significant improved in the HLJDD and its fractions groups. In conclusion, HLJDD exhibited anti-AD effects by inhibiting itching and enhancing immunity, which in turn regulating the levels of relative metabolites, and CPF and 40AEF were considered the most important components of HLJDD.

Integrated Metabolomics and Proteomics Dynamics of Serum Samples Reveals Dietary Zeolite Clinoptilolite Supplementation Restores Energy Balance in High Yielding Dairy Cows.

Dairy cows can suffer from a negative energy balance (NEB) during their transition from the dry period to early lactation, which can increase the risk of postpartum diseases such as clinical ketosis, mastitis, and fatty liver. Zeolite clinoptilolite (CPL), due to its ion-exchange property, has often been used to treat NEB in animals. However, limited information is available on the dynamics of global metabolomics and proteomic profiles in serum that could provide a better understanding of the associated altered biological pathways in response to CPL. Thus, in the present study, a total 64 serum samples were collected from 8 control and 8 CPL-treated cows at different time points in the prepartum and postpartum stages. Labelled proteomics and untargeted metabolomics resulted in identification of 64 and 21 differentially expressed proteins and metabolites, respectively, which appear to play key roles in restoring energy balance (EB) after CPL supplementation. Joint pathway and interaction analysis revealed cross-talks among valproic acid, leucic acid, glycerol, fibronectin, and kinninogen-1, which could be responsible for restoring NEB. By using a global proteomics and metabolomics strategy, the present study concluded that CPL supplementation could lower NEB in just a few weeks, and explained the possible underlying pathways employed by CPL.

Protective effects of Fufang Ejiao Jiang against aplastic anemia assessed by network pharmacology and metabolomics strategy

ObjectiveTo elucidate the mechanisms underlying the therapeutic effects of Fufang Ejiao Jiang (复方阿胶浆, FFEJJ) on aplastic anemia (AA) using integrated network pharmacology and serum metabolomics. MethodsTraditional Chinese Medicine Systems Pharmacology (TCMSP), Pubmed, integrative pharmacology-based research platform of traditional Chinese medicine (TCMIP), and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-TCM) were used to identify the constituents and putative targets of FFEJJ. GeneCards and DisGeNET databases were used to identify AA-associated targets. We constructed a herb-component-target network and analyzed the protein-protein interaction (PPI) network. Potential mechanisms were determined using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. In addition, an AA model was established using acetylphenylhydrazine (APH) and cetylphenylhydrazine (CTX). Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS)-based serum metabolomics was applied to screen potential metabolites and the related pathways associated with AA and the potential anti-anemic effects of FFEJJ. ResultsA total of 30 active components of FFEJJ and 24 targets were related to AA. PPI network analysis showed that VEGFA, AKT1, IL-6, CASP3, and ICAM1 were key nodes overlapping with proteins known to be related to AA. KEGG pathway enrichment analysis revealed that the presumed targets of FFEJJ were mainly associated with pathways linked to the promotion of hematopoiesis and improvement of the hematopoietic microenvironment. A total of 423 metabolite biomarkers were identified between the control and AA models, which are involved in the development of AA. In contrast, FFEJJ reversed the 79 differential metabolites altered by AA. Pathway analysis suggested that the synergistic effects of FFEJJ were mainly enriched in 24 metabolic pathways. Among them, sphingolipid metabolism, glycerophospholipid metabolism, and arachidonic acid metabolism were related to promoting hematopoiesis and improving the hematopoietic microenvironment, which partially conforms with network pharmacology. The interaction network formed by three key differential metabolites, including hydroxy-eicosatetraenoic acid (HETE), sphingosine 1-phosphate (S1P), and lysophosphati-dylcholine (lysoPC), and three predicted network targets (VEGFA, CASP3, and ICAM1) may be the potential mechanism underlying the anti-AA action of the multi-component of FFEJJ. ConclusionFFEJJ could be an alternative treatment option for AA. It acts by promoting hematopoiesis and improving the hematopoietic microenvironment. Network pharmacology-integrated metabolomics makes it possible to analyze TCMs from a systems perspective and at the molecular level.

Plasma metabolomics in the perioperative period of defect repair in patients with pulmonary arterial hypertension associated with congenital heart disease.

The quality of life and survival rates of patients with pulmonary arterial hypertension associated with congenital heart disease (CHD-PAH) have been greatly improved by defect-repair surgery and personalized treatments. However, those who survive surgery may remain at risk of persistent PAH, the prognosis may be considerably worse than those unoperated. Dynamic monitoring of clinical measures during the perioperative period of shunt correction is therefore indispensable and of great value. In this study, we explored the plasma-metabolite profiling in 13 patients with CHD-PAH during the perioperative period of defect repair. Plasma was harvested at four time points: prior to cardiopulmonary bypass (CPB) after anesthesia (Pre), immediately after CPB (T0), 24 h (T24), and 48 h (T48) after defect repair. Untargeted metabolomics strategy based on UPLC Q-TOF MS was used to detect the metabolites. A total of 193 distinguishing metabolites were determined at different time points, enriched in pathways such as oxidation of branched-chain fatty acids. We found that 17 metabolite alterations were significantly correlated with the reduction in mean pulmonary arterial pressure (MPAP) at T48 versus Pre. Gradients in diastolic pulmonary arterial pressure (DPAP), bicarbonate in radial artery (aHCO3), bicarbonate in superior vena cava (svcHCO3), and the partial pressure of dissolved CO2 gas in radial artery (aPCO2) were positively correlated with MPAP gradient. Notably, these clinical-measure gradients were correlated with alterations in shunt-correction-associated metabolites. In total, 12 out of 17 identified metabolites in response to defect repair were increased at both T24 and T48 (all P < 0.05, except propionylcarnitine with P < 0.05 at T24). In contrast, galactinol dihydrate, guanosine monophosphate, and hydroxyphenylacetylglycine tended to decline at T24 and T48 (only galactinol dihydrate with P < 0.05 at T48). In conclusion, 17 metabolites that respond to shunt correction could be used as suitable noninvasive markers, and clinical measures, including DPAP, aHCO3, svcHCO3, and aPCO2, would be of great value in disease monitoring and evaluating future therapeutic interventions.

Untargeted Microbial Exometabolomics and Metabolomics Analysis of Helicobacter pylori J99 and jhp0106 Mutant.

Untargeted metabolomic profiling provides the opportunity to comprehensively explore metabolites of interest. Herein, we investigated the metabolic pathways associated with Jhp0106, a glycosyltransferase enzyme in Helicobacter pylori. Through untargeted exometabolomic and metabolomic profiling, we identified 9 and 10 features with significant differences in the culture media and pellets of the wild-type (WT) J99 and jhp0106 mutant (Δjhp0106). After tentative identification, several phosphatidylethanolamines (PEs) were identified in the culture medium, the levels of which were significantly higher in WT J99 than in Δjhp0106. Moreover, the reduced lysophosphatidic acid absorption from the culture medium and the reduced intrinsic diacylglycerol levels observed in Δjhp0106 indicate the possibility of reduced PE synthesis in Δjhp0106. The results suggest an association of the PE synthesis pathway with flagellar formation in H. pylori. Further investigations should be conducted to confirm this finding and the roles of the PE synthesis pathway in flagellar formation. This study successfully demonstrates the feasibility of the proposed extraction procedure and untargeted exometabolomic and metabolomic profiling strategies for microbial metabolomics. They may also extend our understanding of metabolic pathways associated with flagellar formation in H. pylori.

Unveiling Metabolic Phenotype Alterations in Anorexia Nervosa through Metabolomics

Anorexia nervosa (AN) is a mental disorder characterized by an intense fear of weight gain that affects mainly young women. It courses with a negative body image leading to altered eating behaviors that have devastating physical, metabolic, and psychological consequences for the patients. Although its origin is postulated to be multifactorial, the etiology of AN remains unknown, and this increases the likelihood of chronification and relapsing. Thus, expanding the available knowledge on the pathophysiology of AN is of enormous interest. Metabolomics is proposed as a powerful tool for the elucidation of disease mechanisms and to provide new insights into the diagnosis, treatment, and prognosis of AN. A review of the literature related to studies of AN patients by employing metabolomic strategies to characterize the main alterations associated with the metabolic phenotype of AN during the last 10 years is described. The most common metabolic alterations are derived from chronic starvation, including amino acid, lipid, and carbohydrate disturbances. Nonetheless, recent findings have shifted the attention to gut-microbiota metabolites as possible factors contributing to AN development, progression, and maintenance. We have identified the areas of ongoing research in AN and propose further perspectives to improve our knowledge and understanding of this disease.

Authentication of Zingiber Species Based on Analysis of Metabolite Profiles.

Zingiber corallinum and Zingiber montanum, which belong to the Zingiberaceae family, are traditional Chinese folk medicinal herbs in Guizhou and Yunnan Province of China. They share great similarities in morphology, chemical constituent, and DNA barcoding sequence. The taxonomy of the two Zingiber species is controversial and discrimination of traditional Chinese medicines directly affects the pharmacological and clinical effects. In the present study, we performed a systemic analysis of “super-barcode” and untargeted metabolomics between Z. corallinum and Z. montanum using chloroplast (cp) genome sequencing and gas chromatography-mass spectrometry (GC-MS) analysis. Comparison and phylogenetic analysis of cp genomes of the two Zingiber species showed that the cp genome could not guarantee the accuracy of identification. An untargeted metabolomics strategy combining GC-MS with chemometric methods was proposed to distinguish the Zingiber samples of known variety. A total of 51 volatile compounds extracted from Z. corallinum and Z. montanum were identified, and nine compounds were selected as candidate metabolic markers to reveal the significant difference between Z. corallinum and Z. montanum. The performance of the untargeted metabolomic approach was verified with unknown Zingiber samples. Although the cp genomes could not be used to identify Zingiber species in this study, it will still provide a valuable genomics resource for population studies in the Zingiberaceae family, and the GC-MS based metabolic fingerprint is more promising for species identification and safe application of Z. corallinum and Z. montanum.

Plasma metabolomics-based reveals the treatment mechanism of ShenGui capsule for application to coronary heart disease in a rat model

Shen Gui capsule (SGC) has been demonstrated to have a significant treatment effect for coronary heart disease (CHD). Nevertheless, the holistic therapeutic mechanism of SGC in vivo remain poorly interpreted. We aimed to systematically explore the preventive effect and mechanism of SGC on CHD rats using plasma metabolomics strategy. Rat CHD model was established by left anterior descending coronary artery ligation (LAD). Echocardiography, histological analyses of the myocardium and biochemical assays on serum were used to confirm the successful establishment of the CHD model and therapeutic effects of SGC. Then, UHPLC-MS/MS-based plasma metabolomics was combined with multivariate data analysis to screen potential pharmaco biomarkers associated with SGC treatment in the LAD-induced rat CHD model. After SGC treatment, 12 abnormal metabolites considered as potiential pharmaco biomarkers recovered to near normal levels. These biomarkers were involved in several metabolic pathways, including fat and protein metabolism, phenylalanine metabolism, neuroactive ligand-receptor interaction, androgen receptor signaling pathway, and estrone metabolism.These results suggested that SGC achieves therapeutic action on CHD via regulating various aspects of the body such as energy metabolism, neurological disturbances and inflammation, and thus plays a significant role in the treatment of CHD and its complications. The study is useful to systematically understand and analyze the mechanism of SGC's “multipie pathways, multiple levels, multiple targets” prevention and treatment of CHD.

Metabolite Identification Using Infrared Ion Spectroscopy─Novel Biomarkers for Pyridoxine-Dependent Epilepsy.

Untargeted liquid chromatography–mass spectrometry (LC–MS)-based metabolomics strategies are being increasingly applied in metabolite screening for a wide variety of medical conditions. The long-standing “grand challenge” in the utilization of this approach is metabolite identification—confidently determining the chemical structures of m/z-detected unknowns. Here, we use a novel workflow based on the detection of molecular features of interest by high-throughput untargeted LC–MS analysis of patient body fluids combined with targeted molecular identification of those features using infrared ion spectroscopy (IRIS), effectively providing diagnostic IR fingerprints for mass-isolated targets. A significant advantage of this approach is that in silico-predicted IR spectra of candidate chemical structures can be used to suggest the molecular structure of unknown features, thus mitigating the need for the synthesis of a broad range of physical reference standards. Pyridoxine-dependent epilepsy (PDE-ALDH7A1) is an inborn error of lysine metabolism, resulting from a mutation in the ALDH7A1 gene that leads to an accumulation of toxic levels of α-aminoadipic semialdehyde (α-AASA), piperideine-6-carboxylate (P6C), and pipecolic acid in body fluids. While α-AASA and P6C are known biomarkers for PDE in urine, their instability makes them poor candidates for diagnostic analysis from blood, which would be required for application in newborn screening protocols. Here, we use combined untargeted metabolomics–IRIS to identify several new biomarkers for PDE-ALDH7A1 that can be used for diagnostic analysis in urine, plasma, and cerebrospinal fluids and that are compatible with analysis in dried blood spots for newborn screening. The identification of these novel metabolites has directly provided novel insights into the pathophysiology of PDE-ALDH7A1.

Metabolomics Strategy Assisted by Transcriptomics Analysis to Identify Potential Biomarkers Associated with Tuberculosis.

PurposeTo investigate the dysregulated pathways and identify reliable diagnostic biomarkers for tuberculosis using integrated analysis of metabolomics and transcriptomics.MethodsThree groups of samples, untargeted metabolomics analysis of healthy controls (HC), latent tuberculosis infection patients (LTBI), and active tuberculosis patients (TB), were analyzed using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) and ultra-high performance liquid chromatography-quantitative mass spectrometry (UHPLC-QE-MS). Both univariate and multivariate and statistical analyses were used to select differential metabolites (DMs) among group comparison, and LASSO regression analysis was employed to discover potential diagnostic biomarkers. Metabolite set enrichment analysis was performed to identify the altered metabolic pathways specifically in patients with TB. Meanwhile, a transcriptomic dataset GSEG4992 was downloaded from the GEO database to explore the differentially expressed genes (DEGs) between TB and HC identified in significantly enriched pathways. Finally, an integrative analysis of DMs and DEGs was performed to investigate the possible molecular mechanisms of TB.ResultsThirty-three specific metabolites were significantly different between TB and HC, of which 7 (5-hydroxyindoleacetic acid, isoleucyl-isoleucine, heptadecanoic acid, indole acetaldehyde, 5-ethyl-2,4-dimethyloxazole, and 2-hydroxycaproic acid, unknown 71) were chosen as combinational potential biomarkers for TB. The area under the curve (AUC) value of these biomarkers was 0.97 (95% CI: 0.92–1.00). Metabolites set enrichment analysis (MSEA) displayed that there were 3 significantly enriched pathways among all. The genes in 3 significantly enriched pathways were further analyzed, of which 9(ALDH3B1, BCAT1, BCAT2, GLYAT, GOT1, IL4I1, MIF, SDS, SDSL) were expressed differentially. The area under the curve (AUC) values of these DEGs enriched in pathways mostly were greater than 0.8. As a result, a connected network of metabolites and genes in the pathways were established, which provides insights into the credibility of selected metabolites.ConclusionThe newly identified metabolic biomarkers display a high potential to be developed into a promising tool for TB screening, diagnosis, and therapeutic effect monitoring.

Identifying the cardioprotective mechanism of Danyu Tongmai Granules against myocardial infarction by targeted metabolomics combined with network pharmacology

BackgroundDanyu Tongmai Granules (DY), the commercial Chinese medicine, was well-accepted cardiovascular protective actions in clinic. However, the mechanisms underlying the beneficial effects of DY on cardiovascular disease still need largely to be clarified. PurposeTherefore, this study was designed to explore potential mechanisms of DY in myocardial infarction (MI) by integrated strategy of metabolomics and network pharmacology. MethodsCardiomyocytes were subjected to H2O2 induced myocardial injury and rats were induced MI via isoproterenol (ISO) injection. The entire metabolic alterations in serum and heart tissues of experimental rats were profiled by UPLC-MS/MS. Based on the identified differential metabolites, the pathway analysis results were obtained and further validated using the network pharmacology approach. ResultsWe found that DY exerted significant cardioprotective effects in vitro and in vivo, and ameliorated inflammatory cell infiltration and cardiomyocyte apoptosis induced by ISO. The metabolomics data suggested that DY mainly affected the amino acid metabolism (i.e., valine, leucine and isoleucine biosynthesis, arginine biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arginine biosynthesis, glycine, serine, as well as the alanine metabolism, aspartate and glutamate metabolism, etc.). Simultaneously, DY participated in the regulation of the biosynthesis of bile acids and biosynthesis of unsaturated fatty acids. Notably, DY significantly reduced the biosynthesis of valine, leucine and isoleucine to regulating the metabolism of branched chain amino acids (BCAAs) in infarcted myocardium, thus blocking the inflammation via inhibiting the expression of NLRP3 inflammasome in ISO-induced rats. The anti-inflammatory system of DY was further validated with the results of network pharmacology. ConclusionOur study, for the first time, confirmed that DY inhibited inflammation and further exerted significant anti-myocardial infarction effect. Additionally, our work further demonstrated that the myocardial protective effect of DY was contributed to the inhibition of the NLRP3 inflammasome activation by regulating BCAAs in infarcted myocardium using the comprehensive metabolomics, molecular biology and network analysis. Overall, our study gained new insights into the role of the relationship between the metabolic regulation of BCAAs and the NLRP3 inflammasome against MI.

Rapid discovery of potential ADR compounds from injection of total saponins from Panax notoginseng using data-independent acquisition untargeted metabolomics.

Injection of total saponins from Panax notoginseng (ISPN) is a modern preparation derived from traditional Chinese medicine (TCM) and is widely applied in the treatment of cardiovascular, cerebrovascular, ophthalmology, and endocrine system diseases. With the increase in the clinical application of ISPN, its adverse drug reactions (ADRs) and related safety issues have attracted much attention. In the present study, a data-independent acquisition (DIA) strategy was proposed to comprehensively characterize the saponins contained in ISPN based on the ultra-high-performance liquid chromatography/quadrupole-Orbitrap MS (UHPLC/Q-Orbitrap MS) platform. As many as 276 saponins were detected, and 250 compounds were identified or tentatively identified based on the retention times and MS/MS data. Furthermore, a metabolomic strategy was utilized to discover the discriminative saponins between normal and ADR batches. The results showed that six saponins, including ginsenoside Rh4, ginsenoside Rk3, ginsenoside Rg5, ginsenoside Rk1, ginsenoside Rg6, and 20(S)-ginsenoside Rh2, were significantly different between the two groups. According to cytotoxicity analysis and degranulation detection of RBL-2H3 cells, ginsenoside Rg5, ginsenoside Rk1, and 20(S)-ginsenoside Rh2 were considered the potential compounds responsible for clinical ADRs, ultimately. In addition, the quantitative analysis showed that the content of these three compounds in ISPN samples with ADRs was generally higher than that in samples without ADRs. This study demonstrated that it is advisable to screen out potential markers related to ADRs for developing the quality standard of ISPN by the integration of untargeted metabolomic analysis and cell biology study, and thus reduce its ADRs in the clinic.

Plasma metabolomics in perioperative period of defect repair in patients with pulmonary arterial hypertension associated with congenital heart disease

Abstract Background The pathophysiological alterations in response to shunt correction in patients with pulmonary arterial hypertension associated with congenital heart disease (CHD-PAH) is still not clear. Purpose To explore the dynamic plasma metabolite profiling and its relationship with clinical characteristics in patients with CHD-PAH during the perioperative period of defect repair. Methods Plasma samples from 13 patients with CHD-PAH were harvested at four time points: before cardiopulmonary bypass (CPB) after anesthesia (Pre), immediately after CPB (T0), 24 h (T24), and 48 h (T48) after defect repair. The untargeted metabolomics strategy based on UPLC Q-TOF MS was used to detect the metabolites. Clinical measures were recorded at indicated time points. Results The sample distribution at four time points was well separated (Figure 1A, B). 193 metabolites were distinguished at different time points according to Variable Important in Projection (VIP) score (Figure 1C), enriched in pathways such as carnitine synthesis, phospholipid biosynthesis and oxidation of branched chain fatty acids (Figure 2A). 17 metabolites alterations were significantly correlated with gradients in mean pulmonary arterial pressure (mPAP) at T48 versus Pre, indicative of the response to defect correction (Figure 2B). Intriguingly, 4 out of the 17 (23.5%) metabolites including propionylcarnitine, butenylcarnitine, isobutyryl-L-carnitine and hexanoylcarnitine were enriched in oxidation of branched chain fatty acids. They were increased at both T24 and T48 (all P&amp;lt;0.05 except propionylcarnitine with P&amp;lt;0.05 at T24) (Figure 2C). Conclusions This is the first study to show the altered metabolic profiles of CHD-PAH patients in perioperative period of defect repair. Metabolites that respond to shunt correction could be a suitable non-invasive marker and would be of great value in disease monitoring and evaluating future therapeutic interventions. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): 13th Five-Year Plan–Precise Medicine–Key Research and Development Program–Clinical Cohort of Rare Disease; National Natural Science Foundation of China Figure 1. Overall analysis of metabolitesFigure 2. Shunt correction associated metabolites

Protective effects of Huang-Lian-Jie-Du Decoction on diabetic nephropathy through regulating AGEs/RAGE/Akt/Nrf2 pathway and metabolic profiling in db/db mice

BackgroundDiabetic nephropathy (DN) is a severe diabetic complication that is the principal cause of end-stage kidney disease worldwide. Huang-Lian-Jie-Du Decoction (HLJDD) is widely used to treat diabetes clinically. However, the nephroprotective effects and potential mechanism of action of HLJDD against DN have not yet been fully elucidated. PurposeThis study aimed to investigate the potential roles of HLJDD in DN and elucidate its mechanisms in db/db mice. MethodsAn integrated strategy of network pharmacology, pharmacodynamics, molecular biology, and metabolomics was used to reveal the mechanisms of HLJDD in the treatment of DN. First, network pharmacology was utilized to predict the possible pathways for DN using the absorbed ingredients of HLJDD in rat plasma in silico. Then, combined with histopathological examination, biochemical evaluation immunohistochemistry/immunofluorescence assay, western blot analysis, and UPLC-Q-Orbitrap HRMS/MS-based metabolomics approach were applied to evaluate the efficacy of HLJDD against DN and its underlying mechanisms in vivo. ResultsIn silico, network pharmacology indicated that the AGEs/RAGE pathway was the most prominent pathway for HLJDD against DN. In vivo, HLJDD exerted protective effects against DN by ameliorating glycolipid metabolic disorders and kidney injury. Furthermore, we verified that HLJDD protected against DN by regulating the AGEs/RAGE/Akt/Nrf2 pathway for the first time. In addition, 22 potential biomarkers were identified in urine, including phenylalanine metabolism, tryptophan metabolism, glucose metabolism, and sphingolipid metabolism. ConclusionThese findings suggest that HLJDD ameliorates DN by regulating the AGEs/RAGE/Akt/Nrf2 pathway and metabolic profiling.