Nmr spectroscopy for metabolic profiling of plant extracts
Başlık çevirisi mevcut değil.
- Tez No: 401205
- Danışmanlar: DR. ANNA K. JAGER, DR. NILS T. NYBERG
- Tez Türü: Doktora
- Konular: Eczacılık ve Farmakoloji, Pharmacy and Pharmacology
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2012
- Dil: İngilizce
- Üniversite: Københavns Universitet (University of Copenhagen)
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 114
Özet
Özet yok.
Özet (Çeviri)
Metabolic profiling of natural products is used to map correlated concentration of known and unknown secondary metabolites in extracts. NMR spectroscopy in that respect has been demonstrated to be convenient and reproducible technique with the ability to detect a wide range of small organic compounds. NMR spectra provides detailed structural information about all hydrogen containing compounds in the extracts and, with the combination of statistical techniques provides pioneering way of assessing plant metabolome. Metabolic profiling approach typically involves four general steps: sampling, sample preparation, data acquisition and data analysis. The work of this study includes all four steps with the main focus on last three. NMR spectroscopy has been used as the analytical platform for metabolic profiling of Saffron samples and Cinchona bark extracts, which formed the basis of chemometric model and direct extraction protocol developments, respectively. The emphasis of this thesis work has been to develop chemometric methods and use of Statistical Correlation Spectroscopy (STOCSY) aimed at facilitating the interpretation of discriminating metabolites which is puzzling job in the analysis of complex mixtures from plants. Investigation of different preprocessing techniques and multivariate data analytical steps for enhanced information recovery and improve the classification accuracy is a common interest in the works presented in this thesis. The feasibility of 1H NMR fingerprinting for discrimination of authenticity of saffron using cross-validated PCA was explored. The direct extraction of grinded saffron with methanol-d4 quickly provided solutions for NMR analysis with excellent reproducibility. This study also illustrated how feasible it is to employ STOCSY for exploring the discriminating metabolites. Two dimensional J-resolved NMR spectra were used to resolve overlapping signals by separating the effect of J-coupling from the effect of chemical shifts. The use of PARAFAC as a tool to process a set of two dimensional J-resolved spectra with the aim of keeping the J-coupling information intact facilitates the analysis of individual metabolites. PCA analysis of data containing relative concentrations of individual metabolites, provided from PARAFAC enabled the sample comparison. Sample preparation in plant metabolomics is an essential and critical step affecting the accuracy of the results. Thus, in one study the main focus was development of rapid, reproducible and robust extraction protocols allowing direct extraction of Cinchona alkaloids from the barks. PCA model based on 1H NMR spectra of solutions prepared by direct extraction of Cinchona alkaloids assisted to learn the distribution of the different alkaloids and helped the possible determination of sample quality and variability as well as means of unsupervised detection of minor alkaloids. A new approach to aid complex biomixture analysis of plant material that combines component analysis with statistical correlation spectroscopy (STOCSY-CA) has been proposed and its application in the characterization of discriminative metabolites was demonstrated on synthetic data. This approach facilitates the interpretation since it provides pure-loadings according to individual constituents, and enables to find out the distribution of minor metabolites among the samples. This approach preliminary applied to synthetic data set consists of 1H NMR spectra of Quinine and Quinidine alkaloids.
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