Xinru Liu

Metabolomic study of myocardial ischemia and intervention effects of Compound Danshen Tablets in rats using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry.

Myocardial ischemia (MI) is a worldwide epidemic. Compound Danshen Tablets (CDTs), an herbal compound preparation, are widely used to treat MI in China. In this study, we aimed to explore novel biomarkers to increase the understanding of MI and investigate therapeutic mechanisms of CDT by using a metabolomic approach. Plasma extracts from sham, MI model, CDT- and western medicines (isosorbide dinitrate, verapamil, propranolol, captopril, and trimethazine)-treated rats were analyzed by ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). The orthogonal partial least square (OPLS) model was built to find metabolites expressed in significantly different amounts between MI and sham rats. Meanwhile, partial least squares discriminant analysis (PLS-DA) was used to investigate CDTs protective effects. The results showed that CDT presented protective effects on MI by reversing potential biomarkers to sham levels, especially for the four metabolites in the pathway of purine metabolism (hypoxanthine, xanthine, inosine and allantoin).

A metabonomic approach to early prognostic evaluation of experimental sepsis by 1H NMR and pattern recognition

This study proposes an NMR‐based metabonomic approach to early prognostic evaluation of sepsis. Forty septic rats receiving cecal ligation and puncture (CLP) were divided into the surviving group and nonsurviving group on day 6, while 20 sham‐operated rats served as the control group. Serum samples were collected from septic and sham‐operated rats at 12 h after surgery and analyzed using 1H NMR spectroscopy. Orthogonal partial least squares (OPLS) were applied and showed clustering according to predefined groups, indicating that NMR‐based metabolic profiling could reveal pathologic characteristics in the serum of sham‐operated, surviving, and nonsurviving septic rats. In addition, six characteristic metabolites including lactate, alanine, acetate, acetoacetate, hydroxybutyrate, and formate, which are mainly involved in energy metabolism, changed markedly in septic rats, especially in the nonsurvivors. Using these metabolites, a predictive model for prognostic evaluation of sepsis was constructed using a radial basis function neural network (RBFNN) with a prediction accuracy of about 87% by test samples. The results indicated that the NMR‐based metabonomic approach is a potential technique for the early prognostic evaluation of sepsis. Copyright

Characterization of the constituents in rat biological fluids after oral administration of Fufang Danshen tablets by ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry.

An ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry method was established to detect as many constituents in rat biological fluids as possible after oral administration of Fufang Danshen tablets (FDTs). A C18 column (1.8microm particle size) was adopted to separate the samples, and mass spectra were acquired in both negative and positive modes. First, the fingerprints of FDTs were established, resulting in 43 components being detected within 25min. Among these compounds, 37 were tentatively identified by comparing the retention times and mass spectral data with those of reference standards and the reference literature; the other 6 components were tentatively assigned solely based on the MS data. In vivo, 14 components and 8 metabolites of FDT were observed in plasma, and 12 components of FDT were detected in urine. Tanshinaldehyde, danshexinkun B, a glycine conjugate of danshensu and a methylated conjugate of danshexinkun B were newly detected in rat biological fluids. This study developed a high-speed and sensitive method that was successfully utilized for screening the active ingredients of a Chinese medical formula and provided helpful chemical information for further pharmacology and active mechanism research on Chinese medicine.

A metabonomic approach to early prognostic evaluation of experimental sepsis

OBJECTIVES Early prognostic evaluation of sepsis is an attractive strategy to decrease the mortality of septic patients, but presently there are no satisfactory approaches. Our goal is to establish an early, rapid and efficient approach for prognostic evaluation of sepsis. METHODS Forty-five septic rats, induced by cecal ligation and puncture, were divided into surviving (n=23) and nonsurviving group (n=22) on day 6. Serum samples were obtained from septic and sham-operated rats (n=25) at 12h after surgery. HPLC/MS assays were performed to acquire serum metabolic profiles, and radial basis function neural network (RBFNN) was employed to build predictive model for prognostic evaluation of sepsis. RESULTS Principle component analysis allows a clear discrimination of the pathologic characteristics among rats from surviving, nonsurviving and sham-operated groups. Six metabolites related to the outcome of septic rats were then structurally identified, which included linolenic acid, linoleic acid, oleic acid, stearic acid, docosahexaenoic acid and docosapentaenoic acid. A RBFNN model was built upon the metabolic profile data from rat serum, and a high predictive accuracy over 94% was achieved. CONCLUSIONS HPLC/MS-based metabonomic approach combined with pattern recognition permits accurate outcome prediction of septic rats in the early stage. The proposed approach has advantages of rapid, low-cost and efficiency, and is expected to be applied in clinical prognostic evaluation of septic patients.

Metabolomic analysis of thermally injured and/or septic rats

INTRODUCTION Early diagnosis and treatment for thermal injury with septic complications continue to be a serious clinical problem. In this study, plasma biomarkers of rats in the burn and/or septic models were investigated with a metabolomic method. METHODS Rat plasma samples were analyzed by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Multivariate analysis, the principal components analysis (PCA), was used to validate metabolic changes. In addition, another multivariate method, the orthogonal partial least-squares analysis (OPLS), was used to profile potential biomarkers in models. RESULTS Nine characteristic metabolites, including hypoxanthine, indoxyl sufate, glucuronic acid, gluconic acid, proline, uracil, nitrotyrosine, uric acid, and trihydroxy cholanoic acid were identified in models of thermal injury and/or sepsis. CONCLUSION These biomarkers were mainly involved in oxidative stress and tissue damage, and might supply evidence for distinguishing burned septic patients from non-septic ones.

Metabolomic strategy to study therapeutic and synergistic effects of tanshinone IIA, salvianolic acid B and ginsenoside Rb1 in myocardial ischemia rats

AIM OF THE STUDY Tanshinone IIA (T), salvianolic acid B (S) and ginsenoside Rb1 (G) are the three major active ingredients of Compound Danshen Formula (CDF) for its protective effects on myocardial ischemia (MI). In this study, we aimed to investigate therapeutic and synergistic effects of TSG (combination of T, S and G) on MI rats with metabolomic strategy. MATERIALS AND METHODS MI model were induced in Sprague-Dawley rats by left anterior descending coronary artery ligation. MI rats were respectively administrated T, S, G, TSG and CDF. Plasma was analyzed by ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Partial least squares discriminate analysis (PLS-DA) models were built to evaluate the therapeutic and synergistic effects of TSG at whole level. 22 MI biomarkers in rat plasma were also investigated to explain that. RESULTS TSG brings nearly equal therapeutic effects on MI as CDF and it plays more stable regulated action on those 22 identified metabolites than single compound. CONCLUSIONS Overall, there were few methods for the study of synergistic effects of Chinese medicine. Our results suggested that metabolomics offers a new idea for Chinese medicine research.

Analysis of urinary metabolic profile in aging rats undergoing caloric restriction

Background and aims: While caloric restriction (CR) is associated with a prolonged lifespan in multiple species by regulating metabolism, a comprehensive profile of metabolism under CR conditions remains largely unclear. Therefore, in this study we aimed to characterize the metabolomic profiling associated with CR using a rat model. Methods: Rapid resolution liquid chromatography/electrospray ionization quadrupole-time of flight mass spectrometry (RRLC/ESI-Q-TOFMS) was employed to analyze metabolomic profiling of urine samples from aging rats who underwent caloric restriction (CR; n=7) or were provided a normal diet (N; n=8) for 12 weeks time. Multivariate data analysis was performed on the mass data of metabolomic profiles to uncover the differences between the CR and N groups. Results: CR treatment led to manifest metabolic changes in aging rats, and fifteen urinary metabolites including hypoxanthine, hippurate, dimethylglycine and creatinine were significantly different in the rat groups. Conclusion: Our study demonstrates the high reliability of the HPLC-based metabolomic approach towards the study of anti-aging effects induced by CR, while the urinary metabolites we identified may become potential biomarkers of aging.

Metabolomic evaluation of the response to endocrine therapy in patients with prostate cancer

Timely evaluation of the response to endocrine therapy in patients with prostate cancer (PCa) may optimize treatment regimens and improve long-term prognosis. We used the liquid chromatography-mass spectrometry (LC-MS)-based metabolomic technique to identify serum biomarkers indicative of disease progression and therapeutic benefit. The mean serum levels of seven metabolites, including deoxycholic acid (DCA), glycochenodeoxycholate (GCDC), l-tryptophan, docosapentaenoic acid (DPA), arachidonic acid, deoxycytidine triphosphate, and pyridinoline, differed significantly between untreated PCa patients and healthy controls. In patients who did not develop castration-resistant prostate cancer (CRPC) for at least 2 years (good responders), these metabolite levels reverted to near healthy control levels during endocrine therapy. In contrast, the metabolite levels remained abnormal in patients who developed CRPC within 1 year (poorly responsive patients). Three of these biomarkers (DCA, GCDC, and DPA) are mainly involved in cholesterol metabolism, underscoring the importance of elevated cholesterol to PCa progression. These metabolites may serve as predictive biomarkers for assessing the therapeutic response of PCa patients to endocrine therapy.

A metabonomic approach to chemosensitivity prediction of cisplatin plus 5-fluorouracil in a human xenograft model of gastric cancer

The prediction of chemosensitivity is a challenging problem in the management of cancer. In the present study, a metabonomic approach was proposed to assess the feasibility of chemosensitivity prediction in a human xenograft model of gastric cancer. BALB/c‐nu/nu mice were transplanted with MKN‐45 cell line to establish the xenograft model. The mice were then randomized into treatment group (cisplatin and 5‐fluorouracil) and control group (0.9% sodium chloride), and their plasma were collected before treatment. Metabolic profiles of all plasma samples were acquired by using high‐performance liquid chromatography coupled with a quadrupole time‐of‐flight mass spectrometer (HPLC/Q‐TOF‐MS). Based on the data of metabolic profiles and k‐Nearest Neighbor algorithm, a prediction model for chemosensitivity was developed and an average accuracy of 90.4% was achieved. In addition, a series of endogenous metabolites, including 1‐acyl‐lysophosphatidycholines, polyunsaturated fatty acids and their derivatives, were determined as potential indicators of chemosensitivity. In conclusion, our results suggest that the proposed metabonomic approach allows effective chemosensitivity prediction in human xenograft model of gastric cancer. The approach presents a new concept in the chemosensitivtiy prediction of cancer and is expected to be developed as a powerful tool in the personalized cancer therapy.

Global and targeted metabolomics reveal that Bupleurotoxin, a toxic type of polyacetylene, induces cerebral lesion by inhibiting GABA receptor in mice.

Polyacetylenes are widely distributed in food plants and medicinal herbs, which have been shown to have highly neurotoxic effects. However, there were insufficient studies on the toxicity of these compounds. Thus, a series of experiments was designed to elucidate the toxicity mechanism of bupleurotoxin (BETX) as a representative polyacetylene. First, male BALB/c mice were intragastrically administered 2.5 mg/kg of bodyweight BETX once a day for seven consecutive days. The histopathological results showed that BETX could induce severe morphological damages in the brain hippocampus. We then used metabolomics approaches to screen serum samples from the control and BETX-treated groups. The global metabolomics results revealed 17 metabolites that were perturbed after BETX treatment. Four of these metabolites were then verified by targeted metabolomics. Bioinformatics analysis with the Ingenuity Pathway Analysis (IPA) software found a strong correlation between the GABA receptor signaling pathway and these metabolites. On the basis of these results, a validation test using a rat hippocampal neuron cell line was performed, and the results confirmed that BETX inhibited GABA-induced currents (IGABA) in a competitive manner. In summary, our study illustrated the molecular mechanism of the toxicity of polyacetylenes. In addition, our study was instructive for the study of other toxic medical herbs.