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Development of Chemical Isotope Labeling (CIL) Liquid Chromatography-Mass Spectrometry (LC-MS) for Single-Cell Metabolomics

  • Author / Creator
    Chan, Wan
  • Single-cell metabolomics (SCM) strives to identify, quantify and characterize all metabolites in a single-cell. The study of the metabolome enhances our understanding of the cellular interaction with and in response to environmental influences at the molecular level. As cells are being analyzed individually, this leads to a more accurate representation of cell-to-cell variations that would be masked by bulk population measurements. In this respect, SCM is important for illuminating cellular diversity and heterogeneity, and its development has the potential to shed light on, for example, improving the diagnosis and treatment of cancer, which has been recognized as a heterogeneous disease.
    The most prevalent limit of SCM is the comprehensive analysis of the metabolome in a single-cell. Owing to the fact that metabolites can have very different chemical and physical properties, high coverage metabolic profiling with only one analytical platform is difficult to achieve. It is also worth noting that metabolites amount in a single-cell is extremely limited, additionally, metabolites cannot be amplified. Therefore, a highly sensitive detection method is necessary. Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) provides a way for comprehensive metabolic profiling of single-cell with one platform – positive ion mode reversed phase liquid chromatography mass spectrometry (RPLC-MS). In brief, the metabolome is first being divided into four different groups based on their chemical properties and hydrophobicity. CIL is followed to attach an isotope-mass-encoded tag to metabolites, which has been proved to improve their separation and mitigate ion suppression in RPLC1. Moreover, CIL enables quantification metabolomics in which absolute and relative quantification can be performed.
    In this work, the integration of efficient single-cell preparation and CIL LC-MS method were developed for single-cell metabolomics. Xenopus laevis oocyte is used as the model system. A sample preparation and processing protocol involving cell extraction from the Xenopus laevis and cell lysis to extract metabolites were developed. Dansylation labeling was first used to profile the amines and phenols containing metabolites in cells. The amine and phenol submetabolome of cells were able to be determined comprehensively and quantitatively. At the same time, the behavior of each single-cell was revealed.
    One of the goals in metabolomics is to quantify metabolomics changes induced by one or more effectors, so as to study the perturbations of metabolic networks. Hence, the metabolic responses of cells to heat stress was also studied by applying CIL LC-MS. The short-term and long-term effect of heat stress, as well as the recovery from heat stress were investigated and determined.
    CIL LC-MS was also used to study cells at different locations of the Xenopus laevis ovary comprehensively by applying four labeling chemistries with proper design of sample collection. Cellular amine and phenol, hydroxyl, carbonyl and carboxylic acid submetabolome were studied. And by comparing the metabolome of cells at different locations, I was able to find out some submetabolome of cells have large variations at different points of the ovary, which demonstrates the importance of applying four labeling chemistries to elucidate the metabolome of cells comprehensively and systematically. This study can provide improvements in experimental design using Xenopus oocytes.
    When performing metabolic profiling of single-cell, I understand and realize the importance of expanding the library in metabolite identification. Therefore, I constructed two MS/MS-retention time (RT) libraries including the molecular mass, MS/MS spectrum and RT information. RT calibrants was generated and multipoint RT calibration method was used to transfer RTs from the instrumental setup in one laboratory to the same setup in another laboratory. Moreover, metabolite identification in human urine samples using the two libraries were demonstrated.

  • Subjects / Keywords
  • Graduation date
    Fall 2021
  • Type of Item
  • Degree
    Doctor of Philosophy
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.