Extraction, determination and metabolic profiling of alkaloids in traditional chinese medicines by modern analytical techniques

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Extraction, determination and metabolic profiling of alkaloids in traditional chinese medicines by modern analytical techniques

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EXTRACTION, DETERMINATION AND METABOLIC PROFILING OF ALKALOIDS IN TRADITIONAL CHINESE MEDICINES BY MODERN ANALYTICAL TECHNIQUES JIANG ZHANGJIAN (B Sc., Soochow University) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF CHEMISTRY NATIONAL UNIVERSITY OF SINGAPORE 2009 Acknowledgements Acknowledgements Foremost, I express my most sincere gratitude to my supervisor, Professor Sam Fong Yau Li, for his long-term guidance, support and patience during my PhD study I wish to extend my thanks to all the kind staffs for their patient support for my projects, in particular to Dr Eng Shi Ong in Department of Department of Epidemiology and Public Health, Ms Frances Lim in Department of Chemistry I would like to thank all of my colleagues in Prof Li’s group, who have helped me in various ways: Dr Hua Tao Feng, Dr Lin Lin Yuan, Dr Li Jun Yu, Dr Yan Xu, Dr Xin Bing Zuo, Dr Hua Nan Wu, Dr Wai Siang Law, Dr Ma He Liu, Miss Hiu Fung Lau, Ms Junie Tok, Miss Elaine Teng Teng Tay, Miss Gui Hua Fang, Ms Grace Birungi, Miss Feng Liu, Miss Ai Ping Chew, Mr Jon Ashely, Miss Pei Pei Gan and Mr Jun Yu Lin I sincerely appreciate the National University of Singapore for providing me the financial support during my research Finally, a million thanks to my parents for their selfless love and unfailing support I Table of Contents Table of Contents Acknowledgements Table of Contents Summary I II VIII List of Tables XI List of Figures XII List of Abbreviations XV Chapter Introduction 1.1 Traditional Chinese Medicine (TCM) 1.2 Separation and Analysis of TCM 1.2.1 Separation Technology 1.2.1.1 Headspace Extraction Techniques 1.2.1.1.1 Headspace Solid-phase Microextraction (HS-SPME) 1.2.1.1.2 Headspace Liquid-phase Microextraction (HS-LPME)5 1.2.1.2 Supercritical-fluid Extraction (SFE) 1.2.1.3 Ultrasonic Extraction (UE) 1.2.1.4 Microwave-assisted Extraction (MAE) 1.2.1.5 Pressurized-Liquid Extraction (PLE) 1.2.1.6 Microwave Distillation (MD) 1.2.2 Analysis of TCMs by Chromatographic Techniques 10 1.2.2.1 Analysis of TCMs by GC 11 1.2.2.2 Analysis of TCMs by LC 12 II Table of Contents 1.2.2.3 Analysis of TCMs by Capillary Electrophoresis (CE) 15 1.3 Metabonomics of TCMs 18 1.3.1 Metabonomics 18 1.3.2 Metabonomics Samples 19 1.3.3 Metabonomics Analysis Technologies 19 1.3.3.1 NMR Spectroscopy 20 1.3.3.2 Mass Spectrometry 21 1.3.4 Metabonomics Data Analysis 22 1.4 Research Scope 23 References 26 Part I: Isolation and Determination of Pyrrolizidine Alkaloids in Traditional Chinese Medicine with Modern Analytical Techniques 41 Chapter Determination of Senkirkine and Senecionine in Tussilago Farfara using Microwave Assisted Extraction and Pressurized Hot Water Extraction with Liquid Chromatography Tandem Mass Spectrometry 42 2.1 Introduction 42 2.2 Experimental 45 2.2.1 Chemicals and reagents 45 2.2.2 Preparation of reference standards 45 2.2.3 Extraction 46 2.2.3.1 Microwave-assisted Extraction 46 2.2.3.2 Pressurized Hot Water Extraction 46 III Table of Contents 2.2.3.3 Heating under reflux 47 2.2.4 LC and LC/ESI-MS analyses of MAE Extracts 47 2.2.5 LC/ESI-MS analyses of PHWE Extracts 49 2.3 Results and Discussion 2.3.1 HPLC separation of MAE extract 49 49 2.3.1.1 HPLC separation with UV detector 49 2.3.1.2 Optimization of MAE 51 2.3.1.3 LC/ESI-MS analysis for MAE 53 2.3.2 HPLC analysis for PHWE 57 2.3.2.1 LC/ESI-MS analysis for PHWE 57 2.3.2.2 Optimization of PHWE 57 2.3.3 Matrix-induced interference 61 2.4 Conclusion 62 References 63 Chapter Preconcentration and Separation of Toxic Pyrrolizidine Alkaloids in Herbal Medicines by Non-aqueous Capillary Electrophoresis (NACE) 67 3.1 Introduction 67 3.2 Experimental Section 70 3.2.1 Materials 70 3.2.2 Instruments and methods 71 3.2.3 Standard sample and running buffer preparation 72 3.2.4 Extraction of PAs in herbal medicines 72 IV Table of Contents 3.2.4.1 Heating under reflux 72 3.2.4.2 Microwave-assisted extraction 72 3.3 Results and discussion 3.3.1 Optimization of NACE conditions 73 73 3.3.1.1 Effect of concentration of acetic acid 73 3.3.1.2 Effect of concentration of ammonium acetate 75 3.3.1.3 Effect of concentration of ACN 76 3.3.1.4 Effect of applied voltage 77 3.3.1.5 Linearity, precision, LODs and LOQs 78 3.3.1.6 Application 81 3.3.2 Optimization of online preconcentration conditions 82 3.3.2.1 Large volume sample stacking (LVSS) 82 3.3.2.2 Field-amplified sample stacking (FASS) 86 3.3.2.2.1 Choice of organic solvent plug 86 3.3.2.2.2 Optimization of sample matrix 87 3.3.2.2.3 Optimization of organic solvent plug injection time 88 3.3.2.2.4 Optimization of sample injection time and injection voltage89 3.3.2.2.5 Linearity, precision, LODs and LOQs 3.3.3 Application to real sample 91 94 3.4 Conclusion 95 References 96 Part II: Metabonomic Study of Natural Alkaloid in Rats 99 V Table of Contents Chapter Metabolic Profiling of Berberine in Rats with gas chromatography/mass spectrometry, liquid chromatography/mass spectrometry and 1H NMR spectroscopy 100 4.1 Introduction 100 4.2 Experimental 103 4.2.1 Chemicals 103 4.2.2 Animal Studies 103 4.2.3 Histopathological Examination 104 4.2.4 Sample preparation for metabonomics profile of rat urine samples 104 4.2.5 Reversed-phased LC/MSMS 104 4.2.6 Analysis of urine samples by 1H NMR 105 4.2.7 Analysis of liver samples by GC/MS 105 4.2.8 Chemometric analysis 106 4.2.9 Statistical analysis 107 4.3 Results and Discussion 4.3.1 Results 4.3.1.1 Body weight and histopathology 107 107 107 4.3.1.2 Determination of metabolites in rat livers samples by GC/MS109 4.3.1.3 Determination of metabolites in rat urine samples by 1H NMR 113 4.3.1.4 Determination of metabolites in rat urine samples by LC/MS 122 4.3.2 Discussion 129 VI Table of Contents 4.4 Conclusion 131 References 132 Appendix for Chapter 137 Chapter Conclusion and Future Work 168 5.1 Summary of Results 168 5.2 Limitation and Future Work 170 List of Publications 172 Conference Papers 173 VII Summary Summary In this dissertation, efforts were dedicated to the study of alkaloids in traditional Chinese medicines (TCMs) Various techniques of separation and determination of natural alkaloids in Chinese herbs have been developed and the metabolic profiling of alkaloid in rat model has been investigated This dissertation is broadly divided into two parts: the first part (chapter and chapter 3) focused on the separation and determination of toxic pyrrolizidine alkaloids (PAs) in Chinese herbal medicine, called Tussilago farfara (Kuan Donghua), and the second part (chapter 4) focused on the metabonomics studies of a commonly used TCM, named berberine, in rat model In chapter 1, TCM was briefly reviewed from various aspects, including the background, separation and analysis and metabonomics of TCMs Two new extraction techniques, microwave-assisted extraction (MAE) and pressurized hot water extraction (PHWE) were applied to the separation of toxic PAs from Tussilago farfara (Kuan Donghua) (Chapter 2) Conditions for MAE and PHWE were optimized It was found that a binary mixture of MeOH:H2O (1:1) acidified using HCl to pH 2–3 was the optimal solvent for the extraction of the PAs in the plant materials The results obtained from MAE and PHWE were compared against heating under reflux LC with UV detection and electrospray ionization mass spectrometry (ESI-MS) in the positive mode were used for the determination and quantitation of PAs in the botanical extract The proposed extraction methods with LC/MS allow for a rapid detection of both the major and VIII Summary the minor PAs in T farfara in the presence of co-eluting peaks With LC/MS, the quantitative analysis of PAs in the extract was done using internal standard calibration and the precision was found to vary from 0.6% to 5.4% (n=6) on different days The limits of detection (LODs) and limits of quantitation (LOQs) for MAE and PHWE were found to be 0.26 to 1.04 µg/g and1.32 to 5.29 µg/g, respectively The method precision of MAE and PHWE were found to vary from 3.7% to 10.4% on different days The results showed that extraction efficiencies for major and minor PAs extracted using MAE and PHWE were comparable to that by heating under reflux Our results also showed that significant ion suppression was not observed in the LC/MS analysis In chapter 3, a simple and efficient non-aqueous capillary electrophoresis (NACE) method was established for the determination of toxic PAs in Tussilago farfara (Kuan Donghua) firstly Influences from the background electrolyte (BGE) and separation voltage were investigated Then two online preconcentration methods for NACE, named large volume sample stacking (LVSS) and field-amplified sample stacking (FASS), were investigated The stacking conditions, such as the length of sample zone in LVSS, choice of organic solvent plug, organic solvent plug length, sample injection voltage and injection time in FASS, were optimized Under the optimized conditions, the FASS could provide 18 to 89–fold sensitivity enhancements with satisfactory reproducibility, while the LVSS could only provide to 7-fold In chapter 4, methods using gas chromatography/mass spectrometry (GC/MS), IX Chapter Metabolic Profiling of Berberine in Rats with GC/MS, LC/MS and 1H NMR Spectroscopy NO 10 11 12 13 14 15 Metabolites identified in rat urine samples for both control and treatment groups as measured by 1H NMR, day Normalized peak intensitya Metabolite Chemical Shift (ppm) Multiplicity Control Ave ±SD Treated Ave Tryptamine 7.69 d 0.12 0.06 0.16 Tryptamine 7.32 d 0.23 0.07 0.17 Tryptamine 7.24 d 0.21 0.06 0.15 Hippurate* 7.62 t 0.48 0.09 0.29 Hippurate * 7.55 t 1.67 0.33 1.02 Phenylacetylglycine* 7.40 m 0.34 0.08 0.49 Phenylacetylglycine 7.36 m 0.52 0.12 0.66 Tyrosine 7.16 m 0.24 0.06 0.20 Tyrosine ** 6.87 m 0.36 0.12 0.21 Fumurate** 6.53 s 0.27 0.02 0.13 Creatine 3.91 s 0.37 0.07 0.41 Creatinine** 3.08 s 0.19 0.03 0.33 Betaine 3.88 s 0.56 0.07 0.49 Glucose** 3.83 m 0.50 0.07 0.64 Glucose 3.66 m 0.83 0.09 0.99 Glucose * 3.51 m 0.54 0.09 0.67 Methionine 3.76 m 0.75 0.10 0.82 Methionine ** 2.14 m 0.38 0.04 0.63 Methionine ** 2.13 s 0.33 0.04 0.57 Lysine** 3.74 t 0.71 0.10 1.08 Ethanol** 3.64 q 1.04 0.08 1.22 Glycine* 3.52 s 0.51 0.07 0.59 Taurine 3.41 t 3.89 1.16 3.06 Taurine * 3.18 t 0.35 0.05 0.42 Hypotaurine 3.35 t 0.34 0.11 0.37 ±SD 0.07 0.08 0.05 0.19 0.55 0.12 0.22 0.04 0.06 0.06 0.06 0.04 0.06 0.05 0.24 0.05 0.35 0.09 0.06 0.19 0.06 0.04 1.49 0.06 0.10 159 Chapter Metabolic Profiling of Berberine in Rats with GC/MS, LC/MS and 1H NMR Spectroscopy 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 Trimethylamine –N-oxide (TMAO) Creatinine/Creatine** α-Ketoglutarate* α-Ketoglutarate * Dimethylglycine Trimethylamine (TMA) Aspartic Acid Citrate Citrate Citrate Citrate Glutamine** Succinate Pyruvate Glutamate* Glutamate ** Acetoacetate* Arginine** Alanine** Alanine ** Lactate** Lactate ** 3-D-Hydroxybutyrate** Isobutyrate Valine Valine * Leucine Leucine ** 3.25 3.01 3.00 2.43 2.93 2.85 2.84 2.62 2.60 2.60 2.50 2.44 2.42 2.39 2.36 2.33 2.27 1.63 1.49 1.47 1.34 1.32 1.20 1.11 1.04 0.98 1.00 0.94 s s t t s s m d d d d m s s m m s m d d d d d d d d m m 3.19 4.28 2.40 1.99 1.78 0.30 0.52 0.30 0.27 0.28 0.36 3.86 0.84 0.44 0.30 0.49 0.31 0.22 0.23 0.25 0.34 0.29 0.24 0.09 0.09 0.09 0.08 0.31 0.94 1.27 0.67 0.53 0.56 0.16 0.30 0.05 0.08 0.12 0.09 1.12 0.08 0.08 0.13 0.06 0.05 0.04 0.04 0.04 0.06 0.05 0.11 0.05 0.04 0.03 0.04 0.04 3.54 1.58 1.03 1.09 1.61 0.21 0.28 0.19 0.24 0.32 0.41 1.34 0.81 1.01 0.48 0.71 0.36 0.33 0.35 0.39 0.55 0.61 0.36 0.14 0.13 0.14 0.13 0.47 4.14 0.73 0.95 0.87 0.98 0.03 0.07 0.12 0.03 0.08 0.03 0.84 0.16 1.18 0.10 0.09 0.02 0.03 0.08 0.05 0.17 0.10 0.09 0.05 0.03 0.03 0.03 0.14 160 Chapter Metabolic Profiling of Berberine in Rats with GC/MS, LC/MS and 1H NMR Spectroscopy a The relative intensity of metabolites is expressed with their normalized peak area Values are represented as mean ±SD (standard deviation) The statistics are as follows: significance difference between the control group (n=8) and treatment group (n=8) is based on two tailed student t test (* p

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