High-Coverage Strategy for Multi-Subcellular Metabolome Analysis Using Dansyl-Labeling-Based LC-MS/MS.

Subcellular compartmentalization ensures orderly and efficient intracellular metabolic activities in eukaryotic life. Investigation of the subcellular metabolome could provide in-depth insight into cellular biological activities. However, the sensitive measurement of multi-subcellular metabolic profiles is still a significant challenge. Herein, we present a comprehensive subcellular fractionation, characterization, and metabolome analysis strategy. First, six subcellular fractions including nuclei, mitochondria, lysosomes, peroxisomes, microsomes, and cytoplasm were generated from a single aliquot of liver homogenate. Then, a dansyl-labeling-assisted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for measuring 151 amino/phenol- or carboxyl-containing metabolites in the subcellular fractions was established and validated. Last, the strategy was applied to a rat model of carbon tetrachloride (CCl4)-induced acute liver injury (ALI). The metabolic profile of individual organelles was compared with that of the liver. Interestingly, many unique changes were observed specifically in organelles, while the liver failed to capture these changes. This result indicates that metabolic investigation at the tissue level might lead to erroneous results due to the leveling effect. Our study demonstrates a feasible approach for the broad-spectrum-targeted metabolic profiling of multi-subcellular fractions, which can be of great use in driving our further understanding of intracellular metabolic activities in various physical and pathological conditions.

Absolute Quantification of Acylcarnitines Using Integrated Tmt-PP Derivatization-Based LC-MS/MS and Quantitative Analysis of Multi-Components by a Single Marker Strategy.

Acylcarnitines (ACs) play important roles in the fatty acid ß-oxidation and are considered as diagnostic markers for many diseases. Accurate determination of ACs remains challenging due to their low abundance, high structure diversity, and limited availability of standard compounds. In this study, microwave-assisted Tmt-PP (p-[3,5-(dimethylamino)-2,4,6-triazine] benzene-1-sulfonyl piperazine) derivatization was utilized to facilitate the liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) determination of ACs. The result indicated that Tmt-PP labeling enables the prediction of the retention time and MS response of ACs and enhances their MS response up to 4 times. The introduction of the microwave during the derivatization procedure greatly improved the reaction efficiency, demonstrated by the shortened reaction time from 90 to 1 min. Furthermore, we applied a strategy named quantitative analysis of multi-components by a single marker (QAMS) for the assay of 26 ACs with only 5 AC standards, solving the standard availability issue to a large extent. The established workflow was applied to discover dysregulated ACs in xenograft colon cancer mice, and the quantification results were highly comparable with traditional methods where there were the corresponding standards for each AC. Our study demonstrated that chemical derivatization-based LC-MS/MS integrated with the QAMS strategy is robust for the identification and quantification of ACs and has great potential in targeted metabolomics study.

Tryptophan Pathway-Targeted Metabolomics Study on the Mechanism and Intervention of Cisplatin-Induced Acute Kidney Injury in Rats.

Cisplatin is a chemotherapeutic agent widely employed in the treatment of various solid tumors. However, its use is often restricted by acute kidney injury (AKI) which is the dose-limiting adverse effect of cisplatin. While numerous studies aiming to alleviate the AKI have been conducted, there are no effective remedies in clinical practice. In this paper, a targeted metabolomics study was performed to reveal the potential relationship between tryptophan metabolism and cisplatin-induced AKI. A chemical derivatization integrated liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) approach was utilized to quantify 29 metabolites in the tryptophan pathway in rat kidney medulla and cortex after cisplatin administration. Results showed that tryptophan metabolism was remarkably disturbed both in the medulla and cortex after cisplatin administration. We also found that the tryptophan pathway in the medulla was more sensitive to cisplatin exposure compared with the cortex. Among these metabolites, indoxyl sulfate was focused for further study because it accumulated most significantly in the kidney cortex and medulla in a dose-dependent manner. A function verification study proved that chlormethiazole, a widely used CYP2E1 inhibitor, could reduce the production of indoxyl sulfate in the liver and attenuate cisplatin-induced AKI in rats. In conclusion, our study depicted the tryptophan pathway in cisplatin-induced AKI for the first time and demonstrated tryptophan metabolism is closely associated with the renal toxicity caused by cisplatin, which can be of great use for the discovery of renal toxicity attenuating remedies.

Attenuation of doxorubicin-induced oxidative damage in rat brain by regulating amino acid homeostasis with Astragali Radix.

The nervous system disorders caused by doxorubicin (DOX) are among the severe adverse effects that dramatically reduce the quality of life of cancer survivors. Astragali Radix (AR), a popular herbal drug and dietary supplement, is believed to help treat brain diseases by reducing oxidative stress and maintaining metabolic homeostasis. Here we show the protective effects of AR against DOX-induced oxidative damage in rat brain via regulating amino acid homeostasis. By constructing a clinically relevant low-dose DOX-induced toxicity rat model, we first performed an untargeted metabolomics analysis to discover specific metabolic features in the brain after DOX treatment and AR co-treatment. It was found that the amino acid (AA) metabolism pathways altered most significantly. To accurately characterize the brain AA profile, we established a sensitive, fast, and reproducible hydrophilic interaction chromatography-tandem mass spectrometry method for the simultaneous quantification of 22 AAs. The targeted analysis further confirmed the changes of AAs between different groups of rat brain. Specifically, the levels of six AAs, including glutamate, glycine, serine, alanine, citrulline, and ornithine, correlated (Pearson |r| > 0.47, p < 0.05) with the brain oxidative damage that was caused by DOX and rescued by AR. These findings present that AAs are among the regulatory targets of DOX-induced brain toxicity, and AR is a promising therapeutic agent for it.

Metabolic network-based identification of plasma markers for non-small cell lung cancer.

Metabolic markers, offering sensitive information on biological dysfunction, play important roles in diagnosing and treating cancers. However, the discovery of effective markers is limited by the lack of well-established metabolite selection approaches. Here, we propose a network-based strategy to uncover the metabolic markers with potential clinical availability for non-small cell lung cancer (NSCLC). First, an integrated mass spectrometry-based untargeted metabolomics was used to profile the plasma samples from 43 NSCLC patients and 43 healthy controls. We found that a series of 39 metabolites were altered significantly. Relying on the human metabolic network assembled from Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we mapped these differential metabolites to the network and constructed an NSCLC-related disease module containing 23 putative metabolic markers. By measuring the PageRank centrality of molecules in this module, we computationally evaluated the network-based importance of the 23 metabolites and demonstrated that the metabolism pathways of aromatic amino acids and long-chain fatty acids provided potential molecular targets of NSCLC (i.e., IL4l1 and ACOT2). Combining network-based ranking and support-vector machine modeling, we further found a panel of eight metabolites (i.e., pyruvate, tryptophan, and palmitic acid) that showed a high capability to differentiate patients from controls (accuracy > 97.7%). In summary, we present a meaningful network method for metabolic marker discovery and have identified eight strong candidate metabolites for NSCLC diagnosis.

Dynamic metabolomic analysis of intestinal ischemia-reperfusion injury in rats.

Intestinal ischemia-reperfusion injury (IIR) is a life-threatening abdominal emergency. Compared to traditional steady-state works, we profiled the blood of rats over 72 hr (15 time points) and examined dynamic changes in molecular pathways during IIR. Using a series of methods designed for dynamic datasets analysis (batch effects corrections, metabolomics data reduction, and different features selection), we identified 39 significant different metabolites and discovered the trends of these molecules. Four main patterns were uncovered by a longitudinal pattern recognition method. Furthermore, pathway networks were explored to uncover the possible mechanisms of IIR. We found that IIR is a complex physiological process involved in multiple pathways, such as biosynthesis of amino acids, 2-oxocarboxylic acid metabolism, arginine-related metabolism, and glutathione metabolism. Among which, metabolites related with phenylalanine tyrosine and tryptophan metabolism reached a peak during the early stage of reperfusion, while molecules in biosynthesis of unsaturated fatty acids metabolism declined. Our work provides a feasible scheme to understand dynamic molecule variation and will provide new explications about the effect of intestinal ischemia reperfusion from a dynamic perspective.

Time Series Characteristics of Serum Branched-Chain Amino Acids for Early Diagnosis of Chronic Heart Failure.

Chronic heart failure (CHF) is an ongoing clinical syndrome with cardiac dysfunction that can be traced to alterations in cardiac metabolism. The identification of metabolic biomarkers in easily accessible fluids to improve the early diagnosis of CHF has been elusive to date. In this study, we took multidimensional analytical techniques to discover potentially new diagnostic biomarkers by focusing on the dynamic changes of metabolites in serum during the progression of CHF. Using mass-spectrometry-based untargeted metabolomics, we identified 23 cardiac metabolites that were altered in a rat model of myocardial infarction induced CHF. Among these differential metabolites, branched-chain amino acids (BCAAs) in serum, especially leucine and valine, showed a high capability to differentiate between CHF and sham-operated rats, of which area under the receiver operating characteristic curve was greater than 0.75. Combining with targeted analysis of the amino acids and related proteins and genes, we confirmed that BCAA metabolic pathway was significantly inhibited in rat failing hearts. On the basis of the time series data of serum samples, we characterized the fluctuation pattern of circulating BCAAs by the disease progression model. Finally, the time-resolved diagnostic potential of serum BCAAs was evaluated by the machine-learning-based classifier, and high diagnostic accuracy of 93.75% was achieved within 3 weeks after surgery. These findings provide a promising metabolic signature that can be further exploited for CHF early diagnostic development.

Metabolomics-driven identification of adenosine deaminase as therapeutic target in a mouse model of Parkinson's disease.

Neuroinflammation is one of the driving forces of progressive neurodegeneration in Parkinson's disease (PD). The metabolomics approach has been proved highly useful in identifying potential therapeutic targets. Here, to identify inflammation-relevant treatment targets for PD, mass spectrometry-based untargeted metabolomics was applied to characterize metabolic changes in the striatum of mice with double-hit PD induced by lipopolysaccharide plus 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Seven days after the final MPTP administration, metabolites from the purine metabolism pathway, including adenosine, 1-methyladenosine, adenine, inosine, hypoxanthine, xanthine, xanthosine, and guanosine, were found to be significantly dysregulated. The metabolite-protein interaction network and changes in the concentration ratio of these metabolites indicated that adenosine and adenosine deaminase (ADA; EC 3.5.4.4) were the most promising therapeutic targets and adenosine augmentation might be a rational approach to slow PD progression. These findings were then verified in a subacute MPTP-induced PD mouse model treated with ADA inhibition alone or in conjunction with antagonism of adenosine A2A receptors (A2A R). Behavioral, biochemical, and immunohistochemical analysis demonstrated that ADA inhibition significantly ameliorated the MPTP-mediated motor disabilities, dopamine depletion, and dopaminergic cell death. Significantly enhanced neuroprotective effects were further observed when the ADA inhibitor was utilized in conjunction with an A2A R antagonist. Together, our study indicated for the first time that ADA inhibitors protected against neurodegeneration induced by the neurotoxin MPTP, and ADA inhibitors in combination with A2A R antagonists showed additive antiparkinsonian effects.

Integrated Metabolomics and Network Pharmacology Strategy-Driven Active Traditional Chinese Medicine Ingredients Discovery for the Alleviation of Cisplatin Nephrotoxicity.

Renal injury is the main adverse reaction of cisplatin, and many traditional Chinese medicines (TCMs) were proven active against renal toxicity. Here, an integrated metabolomics and network pharmacology strategy was proposed to discover active TCM ingredients for the alleviation of cisplatin nephrotoxicity. First, by interrogating the Human Metabolome Database (HMDB) we collected targets connected to 149 cisplatin nephrotoxicity-related metabolites. Second, targets of kidney damage were obtained from the Therapeutic Target Database (TTD), PharmGKB, Online Mendelian Inheritance in Man (OMIM), and Genetic Association Database (GAD). Common targets of both dysregulated metabolites and kidney damage were then used for TCM active ingredient screening by applying the network pharmacology approach. Eventually, 22 ingredients passed screening criteria, and their antinephrotoxicity activity was assessed in human kidney tubular epithelial (HK2) cells. As a result, 14 ingredients were found to be effective, in which kaempferol showed relatively better activity. Further metabolomics analysis revealed that kaempferol exerted an antinephrotoxicity effect in rats by regulating amino acid, pyrimidine, and purine metabolism as well as lipid metabolism. Collectively, this proposed integrated strategy would promote the transformation of metabolomics research in the field of drug pair discovery for the purpose of reduced toxicity and increased efficiency.

Untargeted Metabolomics Study of the In Vitro Anti-Hepatoma Effect of Saikosaponin d in Combination with NRP-1 Knockdown.

Saikosaponin d (SSd) is one of the main active ingredients in Radix Bupleuri. In our study, network pharmacology databases and metabolomics were used in combination to explore the new targets and reveal the in-depth mechanism of SSd. A total of 35 potential targets were chosen through database searching (HIT and TCMID), literature mining, or chemical similarity predicting (Pubchem). Out of these obtained targets, Neuropilin-1 (NRP-1) was selected for further research based on the degree of molecular docking scores and novelty. Cell viability and wound healing assays demonstrated that SSd combined with NRP-1 knockdown could significantly enhance the damage of HepG2. Metabolomics analysis was then performed to explore the underlying mechanism. The overall difference between groups was quantitatively evaluated by the metabolite deregulation score (MDS). Results showed that NRP-1 knockdown exhibited the lowest MDS, which demonstrated that the metabolic profile experienced the slightest interference. However, SSd alone, or NRP-1 knockdown in combination with SSd, were both significantly influenced. Differential metabolites mainly involved short- or long-chain carnitines and phospholipids. Further metabolic pathway analysis revealed that disturbed lipid transportation and phospholipid metabolism probably contributed to the enhanced anti-hepatoma effect by NRP-1 knockdown in combination with SSd. Taken together, in this study, we provided possible interaction mechanisms between SSd and its predicted target NRP-1.

Branched-Chain Amino Acids as Predictors for Individual Differences of Cisplatin Nephrotoxicity in Rats: A Pharmacometabonomics Study.

Nephrotoxicity is the dose-limiting adverse effect of cisplatin with large individual differences. Up to now, little has been done on how to recognize and predict the individual differences in either preclinical or clinical research. In the present study, important postdose indicators were screened out first and integrated into a grouping factor, according to which rats were recognized as lowly or highly sensitive individuals. Then, mass-spectrometry-based untargeted metabolomics approach was performed to dissect the metabolic differences in predose serum of the two groups. Eventually, branched-chain amino acids (BCAAs) were found to be most significant with the lowest p value of Mann-Whitney U test and the highest area under receiving operating characteristic curve (AUC-ROC). The findings were further confirmed by absolute quantitation of BCAAs using liquid chromatography-tandem mass spectrometry. Binary logistic regression showed that in the discovery set absolute BCAA contents in rat predose serum could predict cisplatin nephrotoxicity with accuracy of 85%. This result was validated by another two independent external validation sets with accuracy of 81.8 and 78.8%, respectively. This study could provide new insight into cisplatin nephrotoxicity and may help expedite personalized medicine of cisplatin or other antitumor drugs in future clinical studies.

Discovery of Metabolite Biomarkers for Acute Ischemic Stroke Progression.

Stroke remains a major public health problem worldwide; it causes severe disability and is associated with high mortality rates. However, early diagnosis of stroke is difficult, and no reliable biomarkers are currently established. In this study, mass-spectrometry-based metabolomics was utilized to characterize the metabolic features of the serum of patients with acute ischemic stroke (AIS) to identify novel sensitive biomarkers for diagnosis and progression. First, global metabolic profiling was performed on a training set of 80 human serum samples (40 cases and 40 controls). The metabolic profiling identified significant alterations in a series of 26 metabolites with related metabolic pathways involving amino acid, fatty acid, phospholipid, and choline metabolism. Subsequently, multiple algorithms were run on a test set consisting of 49 serum samples (26 cases and 23 controls) to develop different classifiers for verifying and evaluating potential biomarkers. Finally, a panel of five differential metabolites, including serine, isoleucine, betaine, PC(5:0/5:0), and LysoPE(18:2), exhibited potential to differentiate AIS samples from healthy control samples, with area under the receiver operating characteristic curve values of 0.988 and 0.971 in the training and test sets, respectively. These findings provided insights for the development of new diagnostic tests and therapeutic approaches for AIS.

Influences of Normalization Method on Biomarker Discovery in Gas Chromatography-Mass Spectrometry-Based Untargeted Metabolomics: What Should Be Considered?

Data reduction techniques in gas chromatography-mass spectrometry-based untargeted metabolomics has made the following workflow of data analysis more lucid. However, the normalization process still perplexes researchers, and its effects are always ignored. In order to reveal the influences of normalization method, five representative normalization methods (mass spectrometry total useful signal, median, probabilistic quotient normalization, remove unwanted variation-random, and systematic ratio normalization) were compared in three real data sets with different types. First, data reduction techniques were used to refine the original data. Then, quality control samples and relative log abundance plots were utilized to evaluate the unwanted variations and the efficiencies of normalization process. Furthermore, the potential biomarkers which were screened out by the Mann-Whitney U test, receiver operating characteristic curve analysis, random forest, and feature selection algorithm Boruta in different normalized data sets were compared. The results indicated the determination of the normalization method was difficult because the commonly accepted rules were easy to fulfill but different normalization methods had unforeseen influences on both the kind and number of potential biomarkers. Lastly, an integrated strategy for normalization method selection was recommended.

Twin Derivatization Strategy for High-Coverage Quantification of Free Fatty Acids by Liquid Chromatography-Tandem Mass Spectrometry.

Free fatty acids (FFAs) are vitally important components of lipids that modulate biological metabolism in various ways. Although the molecular structures are simple, the analysis of FFAs is still challenging due to their unique properties and wide concentration range. In the present study, a high-coverage liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was established for the quantification of FFAs in serum samples using two structural analogues 5-(dimethylamino)naphthalene-1-sulfonyl piperazine (Dns-PP) and (diethylamino)naphthalene-1-sulfonyl piperazine (Dens-PP) as twin derivatization reagents. The Dns labeling of FFAs could significantly enhance their MS response via the introduction of the easily ionizable moiety of a tertiary amine-containing part and aid fragmentation in the multiple reaction monitoring (MRM) mode. Our results demonstrated that the detection sensitivities of FFAs were increased by 50-1500 fold compared with the nonderivatization method. At the same time, Dens-labeled standards were used as one-to-one internal standards to ensure accurate quantifications. Thirty-eight FFAs, covering short-, medium-, and long-chain, could be quantified in wide dynamic range with the lower limit of quantification (LLOQ) varied from 2 to 20 nM. Using this method, we analyzed serum FFAs in rat models of cisplatin-induced nephrotoxicity and irinotecan-induced gastrointestinal toxicity, respectively. The findings were further compared with those revealed by previous untargeted metabolomics. The results indicate that twin derivatization-based LC-MS provides a more accurate view of global FFA alternation and has great application potential in the fields of targeted metabolomics.

Practical Synthesis of α-Amyrin, ß-Amyrin, and Lupeol: The Potential Natural Inhibitors of Human Oxidosqualene Cyclase.

A practical synthesis of α-amyrin (1), ß-amyrin (2), and lupeol (3) was accomplished in total yields of 32, 42, and 40% starting from easily available ursolic acid (4), oleanolic acid (5), and betulin (6), respectively. Remarkably, these three natural pentacyclic triterpenes exhibited potential inhibitory activity against human oxidosqualene cyclase.

Discovery of Potential Biomarkers with Dose- and Time-Dependence in Cisplatin-Induced Nephrotoxicity Using Metabolomics Integrated with a Principal Component-Based Area Calculation Strategy.

Cisplatin is a potent chemotherapeutic agent. However, its clinical usage is restricted by serious adverse effects, especially nephrotoxicity. For revealing the dose- and time-dependence of cisplatin-induced nephrotoxicity, mass spectrometry-based metabolomics integrated with a principal component-based area calculation (PCAC) strategy was proposed in the present study. Area plots based on the first two principal components of the principal component analysis model were constructed first. Then, the sums of cumulative areas under PC-T curves (AUCPC-T) were calculated. Finally, the fold change of AUCPC-T between experimental and control groups at different time points was calculated and used as an indicative parameter. With the PCAC approach, dose- and time-dependence of cisplatin-induced metabolic change was quantitatively confirmed for the first time. Furthermore, 27 potential biomarkers with dose- and time-dependence related to nephrotoxicity induced by cisplatin were screened out and tentatively identified. Metabolic pathways interrupted by cisplatin mainly included energy, amino acid, and lipid metabolism.

Effect of Phyllanthus amarus Extract on 5-Fluorouracil-Induced Perturbations in Ribonucleotide and Deoxyribonucleotide Pools in HepG2 Cell Line.

The aim of this study was to investigate the antitumor activities of Phyllanthus amarus (PHA) and its potential of herb-drug interactions with 5-Fluorouracil (5-FU). Cell viability, ribonucleotides (RNs) and deoxyribonucleotides (dRNs) levels, cell cycle distribution, and expression of thymidylate synthase (TS) and ribonucleotide reductase (RR) proteins were measured with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, high performance liquid chromatography tandem mass spectrometry (HPLC/MS/MS) method, flow cytometry and Western blot analysis, respectively. Our standardized PHA extract showed toxicity to HepG2 cells at high concentrations after 72 h exposure and induced G2/M cell cycle arrest. Combined use of 5-FU with PHA resulted in significant decreases in ATP, CTP, GTP, UTP and dTTP levels, while AMP, CMP, GMP and dUMP levels increased significantly compared with use of 5-FU alone. Further, PHA could increase the role of cell cycle arrest at S phase induced by 5-FU. Although PHA alone had no direct impact on TS and RR, PHA could change the levels of RNs and dRNs when combined with 5-FU. This may be due to cell cycle arrest or regulation of key enzyme steps in intracellular RNs and dRNs metabolism.

Discrimination of crude and processed rhubarb products using a chemometric approach based on ultra fast liquid chromatography with ion trap/time-of-flight mass spectrometry.

Crude rhubarb subjected to different processing procedures will produce different therapeutic effects that are possibly due to processing-induced variation in chemical composition. In this study, a chemometric approach based on ultra fast liquid chromatography with ion trap/time-of-flight mass spectrometry was established to systematically investigate the chemical variations of rhubarb induced by different processing methods. The approach was validated based on pooled quality-control samples from two perspectives: the individual properties of variables and the bulk properties of samples. Orthogonal partial least squares discriminant analysis was introduced to compare the differences between crude and processed rhubarb products. A total of 20 significantly different markers were screened out and unambiguously/tentatively characterized. This research proved that a chemometric method based on ultra fast liquid chromatography with ion trap/time-of-flight mass spectrometry can comprehensively analyze the chemical variation of herbal medicine and provide evidence for a deeper understanding of the pharmacological activities of processed rhubarb products.

Metabolomics based on liquid chromatography with mass spectrometry reveals the chemical difference in the stems and roots derived from Ephedra sinica.

To better understand different traditional uses of the stems (known as Mahuang) and roots (known as Mahuanggen) of Ephedra sinica, their chemical difference should be investigated. In this study, an ultra-fast liquid chromatography coupled with ion trap time-of-flight mass spectrometry untargeted metabolomics approach was established to reveal global chemical difference between Mahuang and Mahuanggen. Clear separation was observed in scores plots of principal component analysis and orthogonal partial least squares-discriminant analysis. Twenty two chemical markers responsible for such separation were screened out and unambiguously/tentatively characterized. Then chemical markers of pharmacologically important ephedrine and pseudoephedrine were absolutely quantified using liquid chromatography coupled with tandem mass spectrometry under multiple reaction monitoring mode. The results showed that Mahuang was rich in ephedrine-type alkaloids, while Mahuanggen was rich in macrocyclic spermine alkaloids. Additionally, different types of flavan-3-ols and flavones exist in Mahuang and Mahuanggen extracts. This research facilitates a better understanding of different traditional uses of Mahuang and Mahuanggen and provides references for chemical analysis of other medicinal plants.

Determination of corilagin in rat plasma using a liquid chromatography-electrospray ionization tandem mass spectrometric method.

A sensitive and simple liquid chromatography-tandem mass spectrometric (HPLC-MS/MS) method for the determination of corilagin in rat plasma has been developed. Samples were prepared with protein precipitation method and analyzed with a triple quadrupole tandem mass spectrometer. We employed negative electrospray ionization as the ionization source and the analytes were detected in multiple reaction monitoring mode. Separation was achieved on a C8 column eluted with mobile phase consisting of methanol-0.1% formic acid in a gradient mode at the flow rate of 0.3 mL/min. The total run time was 7.0 min.This method was proved to have good linearity in the concentration range of 2.5-1000.0 ng/mL. The lower limit of quantification of corilagin was 2.5 ng/mL. The intra- and inter-day relative standard deviationa across three validation runs for four concentration levels were both <9.8%. The relative error was within ±6.0%. This assay offers advantages in terms of expediency and suitability for the analysis of corilagin in rat plasma. The practical utility of this new HPLC-MS/MS method was confirmed in pilot plasma concentration studies in rats following oral administration.