Targeted and untargeted metabolomic profiling of human serum, urine and brain by liquid chromatography mass spectrometry (LC-MS)

Student thesis: Doctoral Thesis

Abstract

Four projects were undertaken in the current study to apply, and in some cases develop, metabolomic profiling methods based on LC-HRMS for application to different human biofluid and tissue samples.In the first study concerns the potential of metabolic changes to give an indication of physical fitness. Urine samples were collected from ten physically active subjects who underwent two cycling exercise trials. Firstly, their aerobic capacity (VO2max) was determined and the second was a 45 min submaximal exercise test. One hundred and twenty urine samples were collected in total over two days at regular time intervals: on day 1 where there was no exercise intervention; on day 2 where there was an exercise session and on day 3 where there was no exercise intervention.The metabolites affected by the exercise included a range of purine metabolites and several acyl carnitines. Some metabolites including bile acids and several amino acids were subject to diurnal variation during the rest day (day 1). Using OPLS modelling it proved possible to identify a single abundant urinary metabolite provisionally identified as oxo-aminohexanoic acid (OHA) as being strongly correlated with VO2max.Secondly, metabolomic profiling was carried out on 53 post-mortem brain samples from subjects diagnosed with schizophrenia (S), depression (D), bipolar (B), diabetes (Di) and controls (C) in order determine whether or not there were clear metabolites distinguishing these conditions. The most important metabolites producing discrimination were the lipophilic amino acids leucine/isoleucine, proline, methionine, phenylalanine, and tyrosine; the neurotransmitters gamma-aminobutyric acid (GABA) and N-acetyl aspartyl glutamate (NAAG) and sugar metabolites sorbitol, gluconic acid, xylitol, ribitol, arabinotol, and erythritol.For the determination of the sugar polyols it was necessary to develop and new GC-MS method. There appears some commonality between metabolic perturbations resulting from diabetes and from SDB. This study concluded that the changes in sugar alcohol levels which were quantified in physiological fluids confirm the metabolic similarity between mental illness and diabetes. This leads to the question regarding whether or not antidiabetic drugs might have a role in treating mental illness?In a third project a reductive amination method was used in combination with hydrophilic interaction liquid chromatography and high resolution mass spectrometry to analyse the sugars in post-mortem human brain. The samples were collected from six control brain samples and eighteen samples from individuals who had suffered from schizophrenia, depression and bipolar (SDB) disorder. This method was applied to confirm the important role of sugar metabolism through evaluation of relation between the changes in sugar levels and psychiatric.The best separation and quantification of the common hexoses (glucose, fructose, mannose and galactose) by this method was achieved when 2H5-aniline was used as a tagging agent. Additionally, it succeeded in tagging a range of other sugars including pentoses (ribose and xylose) and sugar derivatives (N-acetylneuraminic acid and glucuronic acid). The results highlighted a relationship between the increases in the levels of sugars and psychiatric disorders (SDB). This relation which matched with other studies once again supported our results project 2 suggesting that in that sugar metabolism has an important role in distinguishing the control and SDB brains.Oxidised fatty acids have such as oxylipins and prostaglandins have profound effects on human physiology and are present a low levels in biological fluids. In project 4 a novel tagging method for the analysis of oxidised fatty acids was developed. Fatty acids give a relatively weak response in negative ion ESI-MS. In untargeted metabolomics studies, is important to obtain a good respo
Date of Award1 Nov 2017
LanguageEnglish
Awarding Institution
  • University Of Strathclyde
SupervisorDavid Watson (Supervisor) & Ruangelie Edrada-Ebel (Supervisor)

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