This study aimed to investigate the mechanism of Xihuang Pills in improving hyperplasia of mammary gland(HMG) in rats based on urine metabolomics using ultra-performance liquid chromatography-quadrupole-Orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS). The HMG rat model was established by intramuscular injection of estradiol benzoate solution(0.5 mg·kg~(-1), 25 days) followed by progesterone injection(5 mg·kg~(-1), 5 days). UPLC-Q-Orbitrap-MS technology was used to establish the endogenous small-molecule metabolic profiles in urine samples of rats in the blank group, the HMG model group, and Xihuang Pills group. Multivariate statistical analysis was performed for pattern recognition, t test and variable importance in the projection(VIP) were used to screen potential biomarkers. The significantly changed differential metabolites were identified using the online database Human Metabolome Database(HMDB). Metabolic pathway enrichment analysis was conducted using the MetaboAnalyst 5.0 database. The results showed that 90 differential metabolites with significant changes(P<0.05) were identified between the blank group and the HMG model group using the HMDB. Among them, 48 metabolites significantly reverted(P<0.05) after administration of Xihuang Pills, which may be related to the regulatory effect of Xihuang Pills. Thirteen metabolic pathways significantly associated with HMG were identified when the differential metabolites were imported into the MetaboAnalyst 5.0 database, and Xihuang Pills could modulate seven of these pathways. These metabolic pathways mainly involved histidine metabolism, arginine and proline metabolism, β-alanine metabolism, glycine, serine and threonine metabolism, tryptophan metabolism, pyrimidine metabolism, and amino sugar and nucleotide sugar metabolism. This study utilized UPLC-Q-Orbitrap-MS and urine metabolomics technology to analyze the mechanism of Xihuang Pills in improving HMG, laying the foundation for further in-depth research.
Humans ; Rats ; Animals ; Chromatography, High Pressure Liquid/methods* ; Hyperplasia ; Metabolomics/methods* ; Metabolome ; Biomarkers/urine*

This study aims to explore the molecular regulation mechanism of the differential accumulation of flavonoids in the leaves and roots of Sarcandra glabra. Liquid chromatography-mass spectrometry(LC-MS) and high-throughput transcriptome sequencing(RNA-seq) were employed to screen out the flavonoid-related differential metabolites and differentially expressed genes(DEGs) encoding key metabolic enzymes. Eight DEGs were randomly selected for qRT-PCR verification. The results showed that a total of 37 flavonoid-related differential metabolites between the leaves and roots of S. glabra were obtained, including pinocembrin, phlorizin, na-ringenin, kaempferol, leucocyanidin, and 5-O-caffeoylshikimic acid. The transcriptome analysis predicted 36 DEGs associated with flavonoids in the leaves and roots of S. glabra, including 2 genes in the PAL pathway, 3 genes in the 4CL pathway, 2 genes in the CHS pathway, 4 genes in the CHI pathway, 2 genes in the FLS pathway, 1 gene in the DFR pathway, 1 gene in the CYP73A pathway, 1 gene in the CYP75B1 pathway, 3 genes in the PGT1 pathway, 6 genes in the HCT pathway, 2 genes in the C3'H pathway, 1 gene in the CCOAOMT pathway, 1 gene in the ANR pathway, 1 gene in the LAR pathway, 2 genes in the 3AT pathway, 1 gene in the BZ1 pathway, 2 genes in the IFTM7 pathway, and 1 gene in the CYP81E9 pathway. Six transcription factors, including C2H2, bHLH, and bZIP, were involved in regulating the differential accumulation of flavonoids in the leaves and roots of S. glabra. The qRT-PCR results showed that the up-or down-regulated expression of the 8 randomly selected enzyme genes involved in flavonoid synthesis in the leaves and roots of S. glabra was consistent with the transcriptome sequencing results. This study preliminarily analyzed the transcriptional regulation mechanism of differential accumulation of flavonoids in the leaves and roots of S. glabra, laying a foundation for further elucidating the regulatory effects of key enzyme genes and corresponding transcription factors on the accumulation of flavonoids in S. glabra.
Metabolome ; Gene Expression Regulation, Plant ; Flavonoids ; Gene Expression Profiling ; Transcriptome ; Transcription Factors/metabolism*

This study used nasal lavage fluid for metabolomics to explore its feasibility, and applied it to the clinical metabolomics study of Xiaoqinglong Decoction in the treatment of allergic rhinitis(AR), aiming to investigate the molecular mechanism of Xiaoqing-long Decoction in the treatment of AR through differential changes in local nasal metabolism. AR patients were selected as the research subjects, and nasal lavage fluid was collected as the sample. Metabolomics analysis using liquid chromatography-mass spectrometry was performed on normal group, AR group, and Xiaoqinglong Decoction group. The differences in metabolic profiles among the groups were compared using principal component analysis and partial least squares discriminant analysis, and differential metabolites were identified and subjected to corresponding metabolic pathway analysis. The results showed that Xiaoqinglong Decoction significantly improved the symptoms of AR patients. The metabolomics analysis revealed 20 differential metabolites between AR group and Xiaoqinglong Decoction group. The core metabolite with a trending return in comparison to normal group was trimethyladipic acid. The metabolites were involved in multiple pathways, including β-alanine metabolism, glutathione metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. The feasibility of applying nasal lavage fluid in nasal metabolomics was preliminarily demonstrated. Differential metabolites and enriched pathways in the treatment of AR patients with Xiaoqinglong Decoction were identified, indicating that it may improve rhinitis symptoms through the regulation of various metabolites, including antioxidant effects and correction of Th1/Th2 imbalance.
Humans ; Nasal Lavage Fluid ; Rhinitis, Allergic/drug therapy* ; Metabolomics/methods* ; Metabolome

OBJECTIVE: Arsenic (As) and fluoride (F) are two of the most common elements contaminating groundwater resources. A growing number of studies have found that As and F can cause neurotoxicity in infants and children, leading to cognitive, learning, and memory impairments. However, early biomarkers of learning and memory impairment induced by As and/or F remain unclear. In the present study, the mechanisms by which As and/or F cause learning memory impairment are explored at the multi-omics level (microbiome and metabolome). METHODS: We stablished an SD rats model exposed to arsenic and/or fluoride from intrauterine to adult period. RESULTS: Arsenic and/fluoride exposed groups showed reduced neurobehavioral performance and lesions in the hippocampal CA1 region. 16S rRNA gene sequencing revealed that As and/or F exposure significantly altered the composition and diversity of the gut microbiome，featuring the Lachnospiraceae_NK4A136_group, Ruminococcus_1, Prevotellaceae_NK3B31_group, [Eubacterium]_xylanophilum_group. Metabolome analysis showed that As and/or F-induced learning and memory impairment may be related to tryptophan, lipoic acid, glutamate, gamma-aminobutyric acidergic (GABAergic) synapse, and arachidonic acid (AA) metabolism. The gut microbiota, metabolites, and learning memory indicators were significantly correlated. CONCLUSION Learning memory impairment triggered by As and/or F exposure may be mediated by different gut microbes and their associated metabolites.
Rats ; Animals ; Arsenic/toxicity* ; Fluorides ; RNA, Ribosomal, 16S/genetics* ; Rats, Sprague-Dawley ; Metabolome ; Microbiota

Through the non-targeted metabolomics study of endogenous substances in the liver and serum of hyperlipidemia rats, the biomarkers related to abnormal lipid metabolism in hyperlipidemia rats were found, and the target of ginsenoside Rb_1 in improving hyperlipidemia was explored and its mechanism was elucidated. The content of serum biochemical indexes of rats in each group was detected by the automatic biochemical analyzer. The metabolite profiles of liver tissues and serum of rats were analyzed by HPLC-MS. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to compare and analyze the metabolic data in the normal group, the hyperlipidemia group, and the ginsenoside Rb_1 group, and screen potential biomar-kers. The related metabolic pathways were further constructed by KEGG database analysis. The results showed that hyperlipemia induced dyslipidemia in rats, which was alleviated by ginsenoside Rb_1. The non-targeted metabolomics results showed that there were 297 differential metabolites in the liver tissues of hyperlipidemia rats, 294 differential metabolites in the serum samples, and 560 diffe-rential metabolites in the hyperlipidemia rats treated by ginsenoside Rb_1. Perillic acid and N-ornithyl-L-taurine were common metabolites in the liver and serum samples, which could be used as potential biomarkers for ginsenoside Rb_1 in the improvement of hyperlipidemia. As revealed by pathway enrichment in the liver and serum, ginsenoside Rb_1 could participate in the metabolic pathway of choline in both the liver and serum. In addition, ginsenoside Rb_1 also participated in the ABC transporter, alanine, aspartic acid, and glutamate metabolism, protein digestion and absorption, β-alanine metabolism, taurine and hypotaurine metabolism, caffeine metabolism, valine, leucine, and isoleucine biosynthesis, arachidonic acid metabolism, and methionine and cysteine metabolism to improve dyslipidemia in rats.
Rats ; Animals ; Hyperlipidemias/drug therapy* ; Metabolome ; Ginsenosides/metabolism* ; Lipid Metabolism ; Metabolomics/methods* ; Liver/metabolism* ; Biomarkers ; Taurine

Objective: To explore the metabolite profile and metabolic pathways of newly diagnosed multiple myeloma (MM). Methods: Gas chromatography-mass spectrometry (GC-MS) was employed for the high-throughput detection and identification of serum samples from 55 patients with MM and 37 healthy controls matched for age and sex from 2016 to 2017 collected at the First Affiliated Hospital of Soochow University. The relative standard deviation (RSD) of quality control (QC) samples was employed to validate the reproducibility of GC-MS approach. The differential metabolites between patients with MM and healthy controls were detected by partial least squares discrimination analysis (PLS-DA), and t-test with false discovery rate (FDR) correction. Metabolomics pathway analysis (MetPA) was employed to construct metabolic pathways. Results: There were 55 MM patients, including 34 males and 21 females. The median age was 60 years old (42-73 years old). There were 30 cases of IgG type, 9 cases of IgA type, 1 case of IgM type, 2 cases of non-secreted type, 1 case of double clone type and 12 cases of light chain type, including 3 cases of kappa light chain type and 9 cases of lambda light chain type. The result of QC sample test showed that the proportion of compounds with the RSD of the relative content of metabolites < 15% was 70.21% obtained by the reproducibility of GC-MS experimental data, which implied that the experimental data were reliable. A total of 17 metabolites were screened differently with the healthy control group, including myristic acid, hydroxyproline, cysteine, palmitic acid, L-leucine, stearic acid, methionine, phenylalanine, glycerin, serine, isoleucine, tyrosine, valine, citric acid, inositol, threonine, and oxalic acid (VIP>1, P<0.05). Metabolic pathway analysis suggested that metabolic disorders in MM patients comprised mainly phenylalanine metabolism, glyoxylic acid and dicarboxylic acid metabolism, phosphoinositide metabolism, cysteine and methionine metabolism, glycerolipid metabolism, glycine, serine, and threonine metabolism. Conclusion: Compared with normal people, patients with newly diagnosed MM have obvious differences in metabolic profiles and metabolic pathways.
Male ; Female ; Humans ; Middle Aged ; Adult ; Aged ; Cysteine ; Multiple Myeloma/diagnosis* ; Reproducibility of Results ; Metabolome ; Metabolomics/methods* ; Metabolic Networks and Pathways ; Methionine ; Serine ; Phenylalanine ; Threonine ; Biomarkers

Objective: To study the changes of serum metabolic profile of occupational people exposed with nanometer titanium dioxide particles (TiO(2)-NPs), and to explore the biomarkers and injury mechanism of TiO(2)-NPs health effects. Methods: From June 2020 to June 2021, a TiO(2)-NPs production enterprise was selected as the research site by a typical sampling method, 64 people in the TiO(2)-NPs exposure group were selected from the enterprise, and 62 people of the logistics administrative staff in the same enterprise were selected as the control group, and blood samples were collected using non-anticoagulant blood collection tubes. After the samples were methanol-precipitated, the untargeted metabolomic data was collected by ultra-high performance liquid chromatography time-of-flight mass spectrometry, and biomarkers were screened and metabolic pathway analysis was performed. Results: 46 different metabolites were screened out by P<0.05 and variable importance projection index (VIP) value >1, mainly including glycerides, sphingomyelin, glycerophospholipid, fatty acyl, etc.; By ROC analysis to determine 3-hydroxy-4, 5-dimethyl-2 (5H) - furanone, 4-aminobiphenyl, heptanoylcarnitine, Hexadecanedioic acid mono-L-carnitine ester, Ibutilide, LysoPA (18∶1 (9Z) /0∶0), LysoPC (18∶0), PC (16∶0/16∶0), PC (16∶0/20: 4 (5Z, 8Z, 11Z, 14Z) ), PC (P-18∶1 (9Z) /P-18∶1 (9Z) ) 10 candidate biomarkers; involving changes in 4 metabolic pathways, namely glycerophospholipid metabolism, sphingolipid metabolism, phenylalanine, tyrosine and tryptophan acid biosynthesis, linoleic acid metabolism. Conclusion: Occupational exposure to TiO(2)-NPs has a significant impact on serum metabolic profiles.
Humans ; Metabolomics ; Metabolome ; Titanium/adverse effects* ; Chromatography, High Pressure Liquid/methods* ; Biomarkers

The environmental gas concentration affects the storage period and quality of fruits and vegetables. High concentration CO₂ treating for a long time will cause damage to fruits, However, the specific molecular mechanism is unclear. To analyze the mechanism of CO₂ injury in apple, high-throughput sequencing technology of Illumina Hiseq 4000 and non-targeted metabolism technology were used to analyze the transcriptome sequencing and metabolomics analysis of browning flesh tissue of damage fruit and normal pulp tissue of the control group. A total of 6 332 differentially expressed genes were obtained, including 4 187 up-regulated genes and 2 145 down regulated genes. Functional analysis of the differentially expressed genes confirmed that the occurrence of CO₂ injury in apple was related to redox process, lipid metabolism, hormone signal transduction process and energy metabolism process. Twenty candidate browning genes were successfully screened, among which grxcr1 (md14g1137800) and gpx (md06g1081300) participated in the reactive oxygen species scavenging process, and pld1_ 2 (md15g1125000) and plcd (md07g1221900) participated in phospholipid acid synthesis and affected membrane metabolism. mdh1 (md05g1238800) participated in TCA cycle and affected energy metabolism. A total of 77 differential metabolites were obtained by metabolomic analysis, mainly organic acids, lipids, sugars and polyketones, including 35 metabolites related to browning. The metabolism of flavonoids was involved in the browning process of apple. Compared with the control tissue, the content of flavonoids such as catechin and quercetin decreased significantly in the damaged apple tissue, the antioxidant capacity of cells decreased, the redox state was unbalanced, and the cell structure was destroyed, resulting in browning. The results of this study further enrich the theoretical basis of CO₂ damage, and provide reference for the practical application of high concentration CO₂ preservation technology.
Carbon Dioxide ; Fruit ; Gene Expression Regulation, Plant ; Malus/genetics* ; Metabolome ; Transcriptome

Objective To obtain the metabolome profiles in liver and serum of mice during normal aging. Methods The liver and serum samples of ten 2-month-old mice and ten 18-month-old C57BL/6J mice under physiological conditions were collected.Metabolites were identified and quantified by liquid chromatography-tandem mass spectrometry.The overall assessment,differential screening,and functional analysis were performed with the filtered high-quality data. Results In the negative-ion mode and positive-ion mode,242 and 399 metabolites were identified in the liver and 265 and 230 in serum,respectively.The difference of metabolome between young and old mice was moderate.The upregulated metabolites identified in aging liver were related to the metabolism of riboflavin,glucose,and arachidonic acid,while the downregulated ones were associated with the metabolism of pyrimidine,purine,glycerophospholipid,glutathione,and nicotinamide.Altered metabolites in serum during aging were involved in a variety of nucleic acid metabolism-related pathways,such as pyrimidine metabolism,purine metabolism,one carbon pool by folate,and amino sugar and nucleotide sugar metabolism. Conclusions The metabolome profiles of mouse liver and serum both revealed dysregulated nucleic acid metabolism pathways during normal aging.This study provides metabolome data for further research on aging-associated mechanism and may support the discovery of intervention methods for aging.
Aging ; Animals ; Liver ; Metabolome ; Metabolomics ; Mice ; Mice, Inbred C57BL

OBJECTIVE: To analyze the metabolic profile and genetic variants for newborns with primary carnitine deficiency (PCD) from Guangxi, China. METHODS: From January 2014 to December 2019, 400 575 newborns from the jurisdiction of Guangxi Zhuang Autonomous Region Newborn Screening Center were subjected to tandem mass spectrometry (MS/MS) analysis. Newborns with positive results for PCD and their mothers were recalled for retesting. Those who were still positive were subjected to sequencing of the SLC22A5 gene. RESULTS: Twenty-two newborns and 9 mothers were diagnosed with PCD, which gave a prevalence rate of 1/18 208. Sequencing of 18 newborns and 4 mothers have identified 14 types of SLC22A5 gene variants, with the common ones including c.51C>G (10/44, 22.7%), c.1195C>T (9/44, 20.5%) and c.1400C>G (7/44, 15.9%), The c.517delC(p.L173Cfs*3) and c.1031C>T(p.T344I) were unreported previously and predicted to be pathogenic (PVS1+PM2_supporting+PM3+PP4) and likely pathogenic (PM1+PM2_supporting+PM3+PP3+PP4) based on the American College of Medical Genetics and Genomics standards and guidelines. CONCLUSION c.51C>G, c.1195C>T and c.1400C>G are the most common variants underlying PCD in Guangxi.
Cardiomyopathies ; Carnitine/deficiency* ; China ; Humans ; Hyperammonemia ; Infant, Newborn ; Metabolome ; Muscular Diseases ; Mutation ; Solute Carrier Family 22 Member 5/genetics* ; Tandem Mass Spectrometry