Development and Application of Chemical Isotope Labeling Methods and Metabolite Identification Solution for Liquid Chromatography-Mass Spectrometry-Based Metabolomics

• Author / Creator

  Zhao, Shuang

• Metabolomics, the comprehensive analysis of small molecules in biological specimens, has become an emerging and indispensable tool for systems biology and clinical research. Liquid chromatography-mass spectrometry (LC-MS) is a dominant analytical platform for metabolomics, featuring high metabolite detectability, accurate quantification ability and good versatility. However, quantitative metabolomic analysis with very high coverage is still a challenge due to great diversity of metabolites and their wide concentration ranges. Traditional approach of increasing coverage is to combine lists of metabolites detected by several complementary analytical methods (e.g., combined use of reversed phase LC and hydrophilic interaction LC). Alternatively, chemical isotope labeling (CIL) LC-MS method has been developed to improve the overall analytical performance for metabolomics.
  My research focuses on 1) improving CIL LC-MS analysis power to eventually realize high-performance and comprehensive profiling of the entire metabolome and 2) enhancing high-confidence metabolite identification for metabolomics.
  In the first part of my thesis, three novel CIL LC-MS methods for comparative metabolomics study were developed targeting hydroxyl submetabolome (Chapter 2), carbonyl submetabolome (Chapter 3) and carboxyl submetabolome (Chapter 4), respectively. These labeling methods significantly increased metabolite detection sensitivity and improved LC separation efficiency. Using a pair of isotope reagents, very accurate and precise relative quantification could be achieved. The application of these methods was validated in the analysis of urinary submetabolomes. To perform positive metabolite identification, labeled standard libraries were constructed for each reaction. Each method, used alone, should enable in-depth analysis of the corresponding submetabolome. In combination with other CIL LC-MS methods, high-coverage metabolome profiling could be carried out.
  In the second part, the idea that using multiple CIL LC-MS methods to perform high-coverage near-complete metabolome profiling was validated (Chapter 5) and applied for biomarker discovery (Chapter 6). The newly developed methods were integrated with previously reported CIL LC-MS methods to form a multichannel labeling technique. In Chapter 5, human plasma metabolome was analyzed to demonstrate the high performance of this technique. In Chapter 6, the technique was applied in differential biomarker discovery of Alzheimer's disease and cerebral amyloid angiopathy. The method successfully differentiated disease groups from healthy controls. A panel of metabolites was selected as biomarker candidates for each disease and between diseases, showing good discriminative ability. It demonstrated that multichannel CIL LC-MS approach is a powerful tool for metabolome profiling and biomarker discovery.
  Lastly, to improve the metabolite identification in metabolomics, in Chapter 7, a high-resolution MS/MS-retention time (RT) library was constructed using 825 human endogenous metabolites. Based on the library, a convenient metabolite identification solution was developed for real world sample analysis. The performance and portability were validated by analyzing various biological samples in different laboratories. The approach was proved to be a useful and powerful tool for endogenous metabolite identification with high confidence.

• Subjects / Keywords

  • Liquid chromatography-mass spectrometry
  • Chemical isotope labeling
  • Metabolomics

• Graduation date

  Fall 2018

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3PC2TR3V

• License

  Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.