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Optimised spectral processing and lineshape analysis in 2-dimensional J-resolved NMR spectroscopy based metabolomics

Parsons, Helen Michelle (2010)
Ph.D. thesis, University of Birmingham.

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Abstract

NMR spectroscopy is a primary analytical approach of metabolomics. Although 1D 1H NMR spectroscopy is versatile, highly reproducible and widely used, analysis of complex biological samples yields congested spectra with many overlapping signals. This makes metabolite identification and quantification challenging. 1H J-resolved (JRES) experiments spreads this high signal density into a second dimension, simplifying the spectral analysis. This thesis analyses the approaches and suitability of JRES spectroscopy to analyse metabolomics data. Firstly, the robustness of the JRES experiment is investigated. Using spectral relative standard deviation, benchmarks of spectral robustness can be compared between disparate processing techniques, sample types and analytical platforms. JRES spectra were found to be suitable for metabolomics experiments. Secondly, the application of standard metabolomic analysis methods to JRES spectra was examined. Using principal component analysis, the classification accuracy of 1D 1H and JRES spectra were investigated using several data sets. Alongside, three scaling methods were also evaluated. It was found that 2D JRES spectra and the glog transformation could produce 100% classification accuracy. Finally, spectral deconvolution of 2D JRES spectra from line-shape fitting was investigated Here, the mathematical functions describing the JRES line-shape, under several different processing conditions, are derived and used to create a semi-automated metabolite identification and quantification algorithm. Furthermore, possible quantitation errors arising from using JRES spectra are investigated, evaluating effects such as the overlapping of dispersive tails of nearby signals. In conclusion, the JRES experiment is a suitable for use in the field of metabolomics.

Type of Work:Ph.D. thesis.
Supervisor(s):Viant, Mark and Chipman, J. Kevin
School/Faculty:Colleges (2008 onwards) > College of Life & Environmental Sciences
Department:Biosciences
Subjects:QH301 Biology
Institution:University of Birmingham
ID Code:816
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
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