Mapping the Metabolic Characteristics and Perturbation of Adult Casper Zebrafish by Ambient Mass Spectrometry Imaging.

Casper, a type of transparent mutant-line zebrafish, was generated to overcome the opaque trunk of an adult zebrafish for tumor modeling to realize real-time visualization of transplanted cells in vivo. However, the molecular information at the metabolic level has not received much attention. Herein, a spatially resolved metabolomics method based on an airflow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) system for whole-body zebrafish was used to investigate small molecules and the distribution of adult casper (Mitfaw2/w2, roya9/a9) and the differences from wild-type zebrafish. Finally, the spatial distribution information of more than 1500 endogenous ions was obtained in positive and negative detection modes, and 186 metabolites belonging to a variety of structural categories were identified or annotated. Compared with wild-type samples, 85 variables, including 37 known metabolites, were screened out. In addition, the disordered metabolic pathways caused by the genetic mutation were excavated, involving downregulation of purine metabolism and arachidonic acid metabolism, upregulation of glycerophospholipid metabolism, and biosynthesis of unsaturated fatty acids. All these results were observed in the most intuitive way through MSI. This study revealed important metabolic characteristics of and perturbation in adult casper zebrafish, and provides indispensable fundamental knowledge for tumor research based on it.

Targeted chemical profiling for p-HAP glycosides by using molecular networking and comparative analysis of their contents between Artemisia japonica and Artemisia capillaris.

A total of 65 phenolic acid compounds were annotated or identified by UHPLC-MS/MS method, among them, 17 p-HAP (p-hydroxyacetophenone) glycosides were firstly targeted profiled based on molecular networking. Their characteristic product ions of MS/MS spectra were found and examined on the guideline of targeted isolation. As a result, a new p-HAP glycoside was thus obtained and determined as 2'-O-caffeoyl-p-HAP-4-O-ß-D-glucopyranoside (33) based on 1D and 2D NMR data. Besides, multicomponents quantitative analysis indicated the distinct regional variability in chemicals distribution of A. japonica, and meanwhile, the contents of p-HAP glycosides from A. japonica were higher than those in A. capillaris as a whole, which further suggested the potential medicinal value of A. japonica.

On-tissue chemical derivatization-enhanced spatially resolved lipidomics reveals abnormal metabolism in type 2 diabetic rat brain.

Neurologic disorders are often accompanied by alterations in lipids and oxylipins in the brain. However, the complexity of the lipidome in the brain and its changes during brain damage caused by diabetes remain poorly understood. Herein, we developed an enhanced spatially resolved lipidomics approach with the assistance of on-tissue chemical derivatization to study lipid metabolism in the rat brain. This method enabled the spatially resolved analysis of 560 lipids and oxylipins in 19 brain microregions in coronal and sagittal sections and remarkably improved the coverage of lipidome detection. We applied this method to lipidomic studies of the diabetic rat brain and found that lipid dysregulation followed a microregion-specific pattern. Carnitines and glycerolipids were mainly elevated in the corpus callosum (midbrain) and pineal gland regions, respectively. In addition, most oxylipins, including fatty aldehydes and oxo fatty acids, were significantly upregulated in nine brain microregions. We produced a spatially resolved analysis of lipids and oxylipins, providing a novel analytical tool for brain metabolism research.

Liquid chromatography-mass spectrometry-based metabolomics and fluxomics reveals the metabolic alterations in glioma U87MG multicellular tumor spheroids versus two-dimensional cell cultures.

RATIONALE: Multicellular tumor spheroids (MCTSs) that reconstitute the metabolic characteristics of in vivo tumor tissue may facilitate the discovery of molecular biomarkers and effective anticancer therapies. However, little is known about how cancer cells adapt their metabolic changes in complex three-dimensional (3D) microenvironments. Here, using the two-dimensional (2D) cell model as control, the metabolic phenotypes of glioma U87MG multicellular tumor spheroids were systematically investigated based on static metabolomics and dynamic fluxomics analysis. METHODS: A liquid chromatography-mass spectrometry-based global metabolomics and lipidomics approach was adopted to survey the cellular samples from 2D and 3D culture systems, revealing marked molecular differences between them. Then, by means of metabolomic pathway analysis, the metabolic pathways altered in glioma MCTSs were found using 13 C6 -glucose as a tracer to map the metabolic flux of glycolysis, the tricarboxylic acid (TCA) cycle, de novo nucleotide synthesis, and de novo lipid biosynthesis in the MCTS model. RESULTS: We found nine metabolic pathways as well as glycerolipid, glycerophospholipid and sphingolipid metabolism to be predominantly altered in glioma MCTSs. The reduced nucleotide metabolism, amino acid metabolism and glutathione metabolism indicated an overall lower cellular activity in MCTSs. Through dynamic fluxomics analysis in the MCTS model, we found that cells cultured in MCTSs exhibited increased glycolysis activity and de novo lipid biosynthesis activity, and decreased the TCA cycle and de novo purine nucleotide biosynthesis activity. CONCLUSIONS: Our study highlights specific, altered biochemical pathways in MCTSs, emphasizing dysregulation of energy metabolism and lipid metabolism, and offering novel insight into metabolic events in glioma MCTSs.

Database-Driven Spatially Resolved Lipidomics Highlights Heterogeneous Metabolic Alterations in Type 2 Diabetic Mice.

Spatially resolved lipidomics is pivotal for detecting and interpreting lipidomes within spatial contexts using the mass spectrometry imaging (MSI) technique. However, comprehensive and efficient lipid identification in MSI remains challenging. Herein, we introduce a high-coverage, database-driven approach combined with air-flow-assisted desorption electrospray ionization (AFADESI)-MSI to generate spatial lipid profiles across whole-body mice. Using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), we identified 2868 unique lipids in the serum and various organs of mice. Subsequently, we systematically evaluated the distinct ionization properties of the lipids between LC-MS and MSI and created a detailed MSI database containing 14 123 ions. This method enabled the visualization of aberrant fatty acid and phospholipid metabolism across organs in a diabetic mouse model. As a powerful extension incorporated into the MSIannotator tool, our strategy facilitates the rapid and accurate annotation of lipids, providing new research avenues for probing spatially resolved heterogeneous metabolic changes in response to diseases.

Identification of Diagnostic Metabolic Signatures in Thyroid Tumors Using Mass Spectrometry Imaging.

"Gray zone" thyroid follicular tumors are difficult to diagnose, especially when distinguishing between benign follicular thyroid adenoma (FTA) and malignant carcinoma (FTC). Thus, proper classification of thyroid follicular diseases may improve clinical prognosis. In this study, the diagnostic performance of metabolite enzymes was evaluated using imaging mass spectrometry to distinguish FTA from FTC and determine the association between metabolite enzyme expression with thyroid follicular borderline tumor diagnosis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFAIDESI-MSI) was used to build a classification model for thyroid follicular tumor characteristics among 24 samples. We analyzed metabolic enzyme marker expression in an independent validation set of 133 cases and further evaluated the potential biological behavior of 19 thyroid borderline lesions. Phospholipids and fatty acids (FAs) were more abundant in FTA than FTC (p < 0.001). The metabolic enzyme panel, which included FA synthase and Ca2+-independent PLA2, was further validated in follicular thyroid tumors. The marker combination showed optimal performance in the validation group (area under the ROC, sensitivity, and specificity: 73.6%, 82.1%, and 60.6%, respectively). The findings indicate that AFAIDESI-MSI, in combination with low metabolic enzyme expression, could play a role in the diagnosis of thyroid follicular borderline tumors for strict follow-up.

Spatiotemporal pharmacometabolomics based on ambient mass spectrometry imaging to evaluate the metabolism and hepatotoxicity of amiodarone in HepG2 spheroids.

Three-dimensional (3D) cell spheroid models combined with mass spectrometry imaging (MSI) enables innovative investigation of in vivo-like biological processes under different physiological and pathological conditions. Herein, airflow-assisted desorption electrospray ionization-MSI (AFADESI-MSI) was coupled with 3D HepG2 spheroids to assess the metabolism and hepatotoxicity of amiodarone (AMI). High-coverage imaging of >1100 endogenous metabolites in hepatocyte spheroids was achieved using AFADESI-MSI. Following AMI treatment at different times, 15 metabolites of AMI involved in N-desethylation, hydroxylation, deiodination, and desaturation metabolic reactions were identified, and according to their spatiotemporal dynamics features, the metabolic pathways of AMI were proposed. Subsequently, the temporal and spatial changes in metabolic disturbance within spheroids caused by drug exposure were obtained via metabolomic analysis. The main dysregulated metabolic pathways included arachidonic acid and glycerophospholipid metabolism, providing considerable evidence for the mechanism of AMI hepatotoxicity. In addition, a biomarker group of eight fatty acids was selected that provided improved indication of cell viability and could characterize the hepatotoxicity of AMI. The combination of AFADESI-MSI and HepG2 spheroids can simultaneously obtain spatiotemporal information for drugs, drug metabolites, and endogenous metabolites after AMI treatment, providing an effective tool for in vitro drug hepatotoxicity evaluation.

Spatially Resolved Metabolomics Method for Mapping the Global Molecular Landscape of Whole-Body Zebrafish (Danio rerio) Using Ambient Mass Spectrometry Imaging.

Zebrafish (Danio rerio) represent an effective model biological material for human disease research, even for personalized precision medicine. Thus, it is necessary to fully characterize their molecular information in order to obtain a global metabolic profile. Here, a spatially resolved metabolomics method for whole-body zebrafish analysis was established based on an air-flow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) system. Using the optimized experimental conditions, the method provided high-quality visual distribution information for >1000 functional metabolites, thereby organ-specific metabolites characterizing nine regions were obtained comprehensively, including the eyes, brain, gill, heart, liver, kidney, intestine, muscle, and spinal cord. Then, combined with metabolic pathway analysis, a global metabolic network with in situ information on zebrafish was mapped for the first time. We also tried to use the recently published MSI database to annotate the metabolites in this study; however, the annotation rate was only 33.7 and 10.4% in positive and negative modes, respectively. This further demonstrated the necessity of establishing a suitable AFADESI-MSI method for zebrafish samples. These results offer comprehensive and in-depth molecular information about zebrafish at the metabolic level, which facilitates the use of zebrafish models to understand metabolic reprogramming in human diseases and the development of zebrafish disease models.

Chemical profiling and quantitative analysis on the aqueous extract of Pimpinella anisum fruit by liquid chromatography-tandem mass spectrometry.

Anise fruit (Aniseed) has been used for many years as a traditional medicine in various countries throughout the world; however, the chemical material basis of Aniseed water extract (AWE) has not been examined in detail, limiting our understanding of its pharmacological mechanism and methods for practical quality control. A high-efficiency and high-sensitivity LC-triple time-of-flight tandem mass spectrometry (MS/MS) analysis method using data processing method combined with product ion and neutral loss filtering for systematic screening and identification of the constituents of AWE was established. A quantitative method was established by using LC-MS/MS with multiple reaction monitoring for 10 min to determine the concentration of 17 representative constituents. A total of 89 compounds were discovered in AWE, of which 31 were confirmed by the reference standards, while 24 were found in Aniseed for the first time. The qualification analysis results showed that chlorogenic acids and luteolin derivatives were the major compounds. The linearity, sensitivity, precision, stability, repeatability, and accuracy of the method were verified, which demonstrated that the method could meet the requirements for quantification. This work contributes to a better understanding of the chemical material basis of Aniseed and assists in the development of effective analytical methods for natural medicines.

Spatiotemporally resolved metabolomics and isotope tracing reveal CNS drug targets.

Deconvolution of potential drug targets of the central nervous system (CNS) is particularly challenging because of the complicated structure and function of the brain. Here, a spatiotemporally resolved metabolomics and isotope tracing strategy was proposed and demonstrated to be powerful for deconvoluting and localizing potential targets of CNS drugs by using ambient mass spectrometry imaging. This strategy can map various substances including exogenous drugs, isotopically labeled metabolites, and various types of endogenous metabolites in the brain tissue sections to illustrate their microregional distribution pattern in the brain and locate drug action-related metabolic nodes and pathways. The strategy revealed that the sedative-hypnotic drug candidate YZG-331 was prominently distributed in the pineal gland and entered the thalamus and hypothalamus in relatively small amounts, and can increase glutamate decarboxylase activity to elevate γ-aminobutyric acid (GABA) levels in the hypothalamus, agonize organic cation transporter 3 to release extracellular histamine into peripheral circulation. These findings emphasize the promising capability of spatiotemporally resolved metabolomics and isotope tracing to help elucidate the multiple targets and the mechanisms of action of CNS drugs.

Metabolic Perturbation Score-Based Mass Spectrometry Imaging Spatially Resolves a Functional Metabolic Response.

Metabolic perturbation score-based mass spectrometry imaging (MPS-MSI) is proposed to reveal the spatially resolved functional metabolic response associated with disease progression or drug action including metabolism pathways, species, biofunction, or biotransformation. The MPS-MSI enables the exploration of therapeutic or adverse effects, regional heterogeneous responses to drug treatment, possible molecular mechanisms, and even drug potential targets. MPS-MSI was demonstrated to be a promising molecular imaging tool not only for efficacy and safety evaluation but also for molecular mechanism investigation at the early stage of drug research and development.

Comparison of Local Metabolic Changes in Diabetic Rodent Kidneys Using Mass Spectrometry Imaging.

Understanding the renal region-specific metabolic alteration in different animal models of diabetic nephropathy (DN) is critical for uncovering the underlying mechanisms and for developing effective treatments. In the present study, spatially resolved metabolomics based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) was used to compare the local metabolic changes in the kidneys of HFD/STZ-induced diabetic rats and db/db mice. As a result, a total of 67 and 59 discriminating metabolites were identified and visualized in the kidneys of the HFD/STZ-induced diabetic rats and db/db mice, respectively. The result showed that there were significant region-specific changes in the glycolysis, TCA cycle, lipid metabolism, carnitine metabolism, choline metabolism, and purine metabolism in both DN models. However, the regional levels of the ten metabolites, including glucose, AMP, eicosenoic acid, eicosapentaenoic acid, Phosphatidylserine (36:1), Phosphatidylserine (36:4), Phosphatidylethanolamine (34:1), Phosphatidylethanolamine (36:4), Phosphatidylcholine (34:2), Phosphatidylinositol (38:5) were changed in reversed directions, indicating significant differences in the local metabolic phenotypes of these two commonly used DN animal models. This study provides comprehensive and in-depth analysis of the differences in the tissue and molecular pathological features in diabetic kidney injury in HFD/STZ-induced diabetic rats and db/db mice.

On-Tissue Chemical Oxidation Followed by Derivatization for Mass Spectrometry Imaging Enables Visualization of Primary and Secondary Hydroxyl-Containing Metabolites in Biological Tissues.

On-tissue chemical derivatization combined with mass spectrometry imaging (MSI) can effectively visualize low-abundance and poorly ionizable molecules in biological tissues. Owing to the lack of an effective chemical reaction environment on the tissue surface, the development of direct one-step derivatization reactions is challenging. Herein, we present a two-step reaction involving on-tissue chemical oxidation followed by derivatization combined with airflow-assisted desorption electrospray ionization-MSI, enabling the visualization of primary and secondary hydroxyl-containing metabolites (PSHMs) within the tissue sections. This method indirectly achieved on-tissue derivatization by combining two reactions. Hydroxyl was converted to carbonyl using chemical oxidants, and subsequently, carbonyl was derived using Girard's P reagent. Using this methodology, 169 PSHMs, including hydroxy fatty acids (OH-FAs), fatty alcohols (FOHs), and sterol lipids, were detected and imaged in the tissues of rat brain, kidney, and liver. Moreover, we found that the abundant PSHMs, fatty aldehydes, and oxo fatty acids were significantly dysregulated in the liver and kidney tissues of type 2 diabetic rats; in particular, OH-FAs and FOHs were remarkably up-regulated in the diabetic rat liver tissues. The aberrations of these oxidative metabolites provide insights into the understanding of the molecular pathological mechanism of diabetes. This study demonstrates a novel, two-step reaction strategy for on-tissue derivatization with the analysis of previously inaccessible molecules using MSI.

Mapping of Fatty Aldehydes in the Diabetic Rat Brain Using On-Tissue Chemical Derivatization and Air-Flow-Assisted Desorption Electrospray Ionization-Mass Spectrometry Imaging.

Fatty aldehydes (FALs) are involved in various biological processes, and their abnormal metabolism is related to the occurrence and development of neurological diseases. Because of their low ionization efficiency, methods for in situ detection and mass spectrometry imaging (MSI) analysis of FALs remain underreported. On-tissue chemical tagging of hardly ionizable target analytes with easily ionized moieties can improve ionization efficiency and detection sensitivity in MSI experiments. In this study, an on-tissue chemical derivatization-air-flow-assisted desorption electrospray ionization-MSI method was developed to visualize FALs in the rat brain. The method showed high sensitivity and specificity, allowing the use of in situ high-resolution MS3 to identify FALs. The methodology was applied to investigate the region-specific distribution of FALs in the brains of control and diabetic encephalopathy (DE) rats. In DE rats, FALs were found to be significantly enriched in various brain regions, especially in the cerebral cortex, hippocampus, and amygdala. Thus, increased FAL levels and oxidative stress occurred in a region-dependent manner, which may contribute to cognitive function deficits in DE. In summary, we provide a novel method for the in situ detection of FALs in biological tissues as well as new insights into the potential pathogenesis of DE.

Integrated mass spectrometry imaging reveals spatial-metabolic alteration in diabetic cardiomyopathy and the intervention effects of ferulic acid.

Diabetic cardiomyopathy (DCM) is a metabolic disease and a leading cause of heart failure among people with diabetes. Mass spectrometry imaging (MSI) is a versatile technique capable of combining the molecular specificity of mass spectrometry (MS) with the spatial information of imaging. In this study, we used MSI to visualize metabolites in the rat heart with high spatial resolution and sensitivity. We optimized the air flow-assisted desorption electrospray ionization (AFADESI)-MSI platform to detect a wide range of metabolites, and then used matrix-assisted laser desorption ionization (MALDI)-MSI for increasing metabolic coverage and improving localization resolution. AFADESI-MSI detected 214 and 149 metabolites in positive and negative analyses of rat heart sections, respectively, while MALDI-MSI detected 61 metabolites in negative analysis. Our study revealed the heterogenous metabolic profile of the heart in a DCM model, with over 105 region-specific changes in the levels of a wide range of metabolite classes, including carbohydrates, amino acids, nucleotides, and their derivatives, fatty acids, glycerol phospholipids, carnitines, and metal ions. The repeated oral administration of ferulic acid during 20 weeks significantly improved most of the metabolic disorders in the DCM model. Our findings provide novel insights into the molecular mechanisms underlying DCM and the potential of ferulic acid as a therapeutic agent for treating this condition.

Data-Driven Deciphering of Latent Lesions in Heterogeneous Tissue Using Function-Directed t-SNE of Mass Spectrometry Imaging Data.

Mass spectrometry imaging (MSI), which quantifies the underlying chemistry with molecular spatial information in tissue, represents an emerging tool for the functional exploration of pathological progression. Unsupervised machine learning of MSI datasets usually gives an overall interpretation of the metabolic features derived from the abundant ions. However, the features related to the latent lesions are always concealed by the abundant ion features, which hinders precise delineation of the lesions. Herein, we report a data-driven MSI data segmentation approach for recognizing the hidden lesions in the heterogeneous tissue without prior knowledge, which utilizes one-step prediction for feature selection to generate function-specific segmentation maps of the tissue. The performance and robustness of this approach are demonstrated on the MSI datasets of the ischemic rat brain tissues and the human glioma tissue, both possessing different structural complexity and metabolic heterogeneity. Application of the approach to the MSI datasets of the ischemic rat brain tissues reveals the location of the ischemic penumbra, a hidden zone between the ischemic core and the healthy tissue, and instantly discovers the metabolic signatures related to the penumbra. In view of the precise demarcation of latent lesions and the screening of lesion-specific metabolic signatures in tissues, this approach has great potential for in-depth exploration of the metabolic organization of complex tissue.

Metabolomics and integrated network pharmacology analysis reveal that ginkgolides act as potential active anticancer components by regulating one-carbon metabolism.

ETHNOPHARMACOLOGICAL RELEVANCE: Ginkgo biloba L. is a rare tree species unique to China. Ginkgo biloba is a traditional Chinese medicinal with a long history, acting on the heart and lung meridians, and has been reported to have a significant effect on non-small cell lung cancer. However, the mechanism underlying this metabolic effect is poorly understood. AIM OF THE STUDY: To identify the active components of Ginkgo biloba extract that may have effects on non-small cell lung cancer and their mechanisms of metabolic regulation. MATERIALS AND METHODS: In this study, LC-MS/MS was used to investigate the chemical constituents of Ginkgo biloba extract. Network pharmacology was used to identify the active components potentially valuable in the treatment of non-small cell lung cancer. Antitumor activity was evaluated using CCK-8 and apoptosis assays. The mechanisms of metabolic regulation by the active components were further explored using untargeted metabolomics, targeted metabolomics, and western blot experiments. RESULTS: Network pharmacology and component analysis of Ginkgo biloba extract identified four ginkgolides that significantly affect non-small cell lung cancer. Their antiproliferative activity in A549 cells was evaluated using CCK-8 and apoptosis assays. The metabolomics results indicated that the ginkgolides had a significant regulatory effect on metabolic pathways related to one-carbon metabolisms, such as purine metabolism, glutathione metabolism, and the methionine cycle. Further targeted metabolomics analysis on one-carbon metabolism found that the ginkgolides may significantly affect the content of multiple metabolites in A549 cells, including purine, S-adenyl methionine, S-adenylyl homocysteine, and glutathione upregulated, and adenosine, tetrahydrofolate, and 10-Formyl-tetrahydrofolate significantly decreased. Notably, dihydrofolate reductase (DHFR) and methylenetetrahydrofolate dehydrogenases (MTHFR) were found to be altered after the treatment of ginkgolides. CONCLUSION: This in vitro study indicated that ginkgolides might inhibit the growth of A549 cells by targeting one-carbon metabolism. This study also demonstrated that metabolomics combined with network pharmacology is a powerful tool for identifying traditional Chinese medicines' active components and metabolic mechanisms.

Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics.

Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data's median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.

Metabolomics reveals the intervention effect of Zhuang medicine Longzuantongbi granules on a collagen-induced arthritis rat model by using UPLC-MS/MS.

ETHNOPHARMACOLOGICAL RELEVANCE: Rheumatoid arthritis (RA) is known as "Fawang" in Zhuang medical theory. Longzuantongbi granules (LZTBG) is an in-hospital preparation used at the First Affiliated Hospital of the Guangxi University of Chinese Medicine. This medicine is based on traditional Zhuang medicine theory for the treatment of "Fawang", and has an effectiveness of over 86.67%. It comprises eight medicinal materials, including the main drug Toddalia asiatica (L.) Lam. and Kadsura coccinea (Lem.) A.C. Smith, the assisting drugs Alangium chinense (Lour.) Harms, Zanthoxylum nitidum (Roxb.) DC., Sinomenium acutum (Thunb.) Rehd.et Wils., Bauhinia championii (Benth.) Benth., Spatholobus suberectus Dunn, and Ficus hirta Vahl. All of these herbs are commonly used in Zhuang medicine. AIM OF THE STUDY: This study aims to reveal the effect of LZTBG on collagen-induced arthritis (CIA) rats, to discover the potential efficacy-related biomarkers and explore the intervention mechanism of LZTBG from a molecular level, based on metabolomics. MATERIALS AND METHODS: Sprague-Dawley (SD) rats were randomly assigned into a normal group, a CIA model group, a positive control (MTX) group and two different LZTBG treatment groups (5.4 g/kg/d and 2.7 g/kg/d). Body weight, arthritis index (AI), paw swelling, and hematoxylin and eosin (HE) staining experiments were used to evaluate the efficacy of the established model. A metabolomics method based on an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technique was established to analyze plasma taken from the rats, and to explore the interventional mechanism of LZTBG. RESULTS: LZTBG showed a positive effect on the CIA model rats. Thirty-one differential metabolites were screened out, and combined with pathway analysis, 11 potential efficacy-related biomarkers were then mapped in the pathway. These included linoleic acid (LA), phosphatidylcholine (PC), lysophosphatidylcholine (LPC), arachidonic acid (AA), 12-HETE, alpha-linolenic acid (ALA), 13(S)-HOT, 2-oxobutanoate, 3-hydroxybutyric acid, L-Valine, and acetylcholine. Furthermore, it was found that these metabolites may exhibit an intervention effect by means of modulating pathways related to both lipid metabolism and amino acid metabolism to associated with inflammation. CONCLUSION: LZTBG can effectively alleviate symptoms of RA, an effect that can primarily be attributed to the regulation of multiple pathways and multiple targets These results demonstrate that LC-MS/MS-based metabolomics is an advantageous technique for the investigation of the intervention effect and molecular mechanism of traditional compound medicine.