Analysis of urinary lipid biomarker candidates from tuberculosis patients by multiple reaction monitoring

Master Thesis


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Background: Tuberculosis (TB) is an aggressive disease and is the leading cause of death by infectious disease in South Africa. With early diagnosis and correct treatment, almost all TB cases can be cured. The main diagnostic tests in South Africa are limited for people living in rural areas, require sputum which cannot be produced by very ill patients, and have low sensitivity in immune compromised individuals. There is an urgent need for a non-invasive and robust diagnostic test which uses an easily accessible biofluid and can be performed at the point-of-care. Urine has shown promise as a diagnostic biofluid for biomarker investigation. Full scan mass spectrometry is the gold standard for the unbiased discovery of biomarker candidates, and targeted multiple reaction monitoring (MRM) is the method of choice for subsequent validation of biomarker candidates. A list of candidate urinary biomarkers has previously been generated which can discriminate between latent and active TB infection using MS1 mass spectrometry, but these biomarkers have not yet been verified by targeted mass spectrometry. Aims and Objectives: The aim of this project is to verify a list of biomarker candidates using MRM assays by: 1) developing MRM assays for known fatty acid standards, and 2) developing MRM assays for unidentified urinary lipid biomarker candidates de novo, which can be applied to clinical cohorts for future validation. Methods: Fatty acid standards were initially assessed using direct infusion full-scan MS1 mass spectrometry on an orbitrap mass analyser. They were then optimised for fragmentation by compound optimisation on a triple-quadrupole mass analyser, the data from which was used to build MRM assays. Liquid chromatography was optimised for these lipids and the MRMs were validated by spiking the lipid standards into a complex mixture. For the second part of the project, lipid extract (containing unidentified biomarker candidates) from patient derived urine samples were analysed by data-dependent acquisition with inclusion lists on an orbitrap mass analyser. From this experiment MS/MS data was acquired for biomarker candidates which were then compiled into MRM assays and verified using a triple-quadrupole mass analyser. Results: From six fatty acid standards, reliable MRM assays were generated for five of them. The biomarker candidates formed a list of 70 molecules which were further refined to 10 molecules which were reproducibly measured by MRM assay. Discussion and Conclusions: From this work the fatty acid standards can be used as internal retention time predictors for future lipidomic work and quality checks, as they eluted across a wide retention time range. The biomarker candidates have been verified using MRM assays and can be validated in larger clinical cohorts in the future. The end-goal is to use these biomarker candidates as part of a panel which represents a unique biosignature according to the disease state of the patient.