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Title
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Development of mass spectrometry-based bioanalytical platforms for metabolomics
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Author
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Abstract
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| Metabolomics is the study of small endogenous molecules (<1500 Da) and their interactions in biological systems (cell culture extracts, plasma, urine, or entire organisms). Alterations in genes, RNA transcripts, and proteins, together with environmental changes, are amplified in the metabolome, reflecting the underlying biochemical activity and state of a system. Untargeted metabolomics, the comprehensive analysis of hundreds of metabolites, has proven to be a powerful hypothesis-generating approach in a wide range of applications such as pharmacology, toxicology, food science, and microbial and plant biotechnology. The unbiased nature of untargeted analysis imposes significant challenges for analytical platform development. The goal of this research was 1) to develop an untargeted metabolomics platform for a broad range of polar metabolites and lipids using state-of-the-art liquid chromatography-high resolution mass spectrometry (LC-HRMS), 2) to explore the potential of ion mobility spectrometry (IMS) as an additional dimension of separation and 3) to improve the confidence of compound annotation by implementing in-house multidimensional libraries (e.g., retention time, MS/MS) using open source tools. Since one method cannot simultaneously cover the metabolome and lipidome, two complementary workflows were optimized to increase this coverage for different biological matrices. A platform for polar metabolites was developed, comparing different mixed-mode hydrophilic interaction-based stationary phases, mobile phase composition, and instrumental parameters. Lipids are highly diverse compounds, yet their chemical similarities form an analytical challenge for standard LC-MS platforms. Therefore, an additional technique, IMS, was used in addition to LC-MS analysis. The optimized LC-IM-MS method included the use of IM-derived collision cross section (CCS) values; the platform was successfully applied for high-confidence lipid annotation in biological samples. Further, an easy-to-use workflow for the creation of an in-house metabolite library with curated multidimensional data for 100 metabolite standards was developed using R to generate publicly available data in “.msp” format. Finally, the advantages and current limitations of implementing IMS in LC-HRMS workflows for the analysis of highly isomeric mixtures of oxidized lipids were investigated. The results showed that adding the IM dimension to LC has enormous potential to improve peak capacity. However, a broad dynamic range and fast MS acquisition rates are crucial to separate and annotating isomeric species in biological matrices. |
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Language
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English
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Publication
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Antwerp
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University of Antwerp, Faculty of Pharmaceutical, Biomedical, and Veterinary Sciences, Department of Pharmaceutical Sciences
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2023
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Volume/pages
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256 p.
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Note
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van Nuijs, Alexander L.N. [Supervisor]
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Covaci, Adrian [Supervisor]
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Full text (open access)
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