Method Development for Comprehensive Lipidome Profiling of Cells using LC-MS

  • Author / Creator
    Bajwa, Barinder
  • Lipidomics aims to research lipid metabolism inside various samples or biological organisms. Through the research of lipidomics, information regarding the diversity, abundance, and function of lipids can determined. Although lipids can be categorized into 8 lipid classes, the variability between head groups and acyl chains results in over 100,000’s of unique structures. These unique lipids encompass a wide range of biological functions in living organisms such as cell signaling, energy storage, and cell compartmentalization. Mass spectrometry (MS) makes for an ideal analysis technique for lipid research, as it allows for the comprehensive profiling of lipid species from complex matrices as a result of its high sensitivity and ability to be coupled with separation techniques. Additionally, through the employment of tandem MS, the structural identifications of lipid molecules can be determined, helping validate MS results. A fundamental step in the analysis of lipids involves lipid extraction, in which solvents are used to efficiently extract as many lipid classes and species as possible from the biological organism. Due to the structural diversity of lipids, lipids tend to have a wide range of physiochemical properties, making the extraction of all lipid classes impossible. The use of an appropriate extraction protocol is critical, as lipid extraction tends to be one of the preliminary steps in lipidomics research, thus will have a considerable effect on the quality of results obtained from the analysis. Biphasic extraction is often utilized as it incorporates the use of a non-polar organic solvent for lipid extraction, along with a polar solvent for the solubilization of polar contaminants. In chapter 2, a slightly modified version of the Folch and MTBE, along with the original MTBE method were evaluated to determine an optimal extraction protocol for the lipidomics analysis of cell lines. Metrics such as the time for lipid extraction, reproducibility of extraction, ease of extraction, and extraction efficiency were assessed using Saccharomyces cerevisiae cells. Although the MTBE protocol was more efficient at extracting polar lipids, the modified Folch protocol was chosen as the optimal extraction method due to its high reproducibility and short extraction time. Furthermore, it was found that an increased incubation time in the MTBE protocol was detrimental to its reproducibility, based on RSD values and intragroup separation in PCA. Finally, the modified Folch protocol was used for tandem MS of yeast cell extracts in which 401 and 398 features were identified using Metaboscape 4.0 and LipidMatch, respectively. Our tandem MS protocol had applied unique collision energies to specific lipid classes, which resulted in more lipid identifications compared to previous literature that focused on profiling the yeast lipidome. Research into the lipidomes of various cancer cell lines through liquid chromatography mass spectrometry (LC-MS) has increased over the past decade. In particular, MCF-7 breast cancer cells are a useful model for cancer research due to their ability to simulate human breast cancers, and have been successfully used to demonstrate abnormal lipid changes relative to healthy cells. In chapter 3, we first found the optimal cell lysis protocol by evaluating the lysis efficiency between MCF-7 cells disrupted via thermal lysis and bead lysis. Cells subjected to bead lysis were found to have a better cell lysis efficiency, homogenized better in the lysis solvent, and had lower intra-group variability. Additionally, comprehensive lipid profiling of MCF-7 cells was performed through our untargeted tandem MS protocol. After evaluating our identifications against literature, our profiling method was able to identify more lipid species in every lipid class compared, with the exception of phosphatidylserines. Through the employment of our protocol, we can get a better understanding of the MCF-7 lipidome, which could potentially lead to biomarker discovery for breast cancer in the future.

  • Subjects / Keywords
  • Graduation date
    Spring 2021
  • Type of Item
  • Degree
    Master of Science
  • 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.