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|Title:||Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry: A High-Throughput Platform in Metabolomics for Assessment of Lifestyle Interventions in Human Health|
|Authors:||Kuehnbaum, Naomi L.|
|Keywords:||metabolomics;capillary electrophoresis;mass spectrometry;high throughput;high intensity interval training;diabetes;Analytical Chemistry;Analytical Chemistry|
|Abstract:||<p>Research in this thesis has focused on development and application of novel methodologies that enhance sample throughput and data fidelity when performing untargeted metabolome profiling by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). Metabolomics is a valuable tool in functional genomics research to investigate underlying molecular mechanisms associated with human health since metabolites are “real-world” end-products of gene expression. CE-MS is well-suited for metabolomics because it is a high efficiency microseparation technique that can be used to resolve complex mixtures of polar metabolites in human biofluids without complicated sample workup. In this thesis, a novel CE-MS assay for estrogens and their intact ionic conjugates has been described (<em>Chapter II</em>) to expand metabolome coverage that enables resolution of positional isomers with high selectivity. This is critical for better understanding of underlying perturbations in estrogen metabolism since the biological activity of estrogens are dependent on specific primary and secondary metabolic transformations. MSI-CE-MS has been introduced as a high-throughput approach for large-scale metabolomic studies based on serial injection of multiple segments of sample within a single fused-silica capillary (<em>Chapter III</em>). It reduces analysis times while increasing data quality and confidence in peak assignment together with better quality assurance. An accelerated workflow for metabolomics has also been developed when using MSI-CE-MS, where a dilution trend filter is used as a primary screen to authenticate reproducible sample-derived metabolites from a pooled sample while eliminating spurious artifact and background signals. In this way, complicated time alignment and peak picking algorithms are avoided when processing data in metabolomics to reduce false discoveries. This strategy was subsequently used in two metabolomics applications (<em>Chapters IV</em> and <em>V</em>) to identify plasma markers associated with strenuous exercise and adaptive training responses following a six-week high intensity interval training. The impact of exercise intervention to improve the glucose tolerance of a cohort of overweight/obese yet non-diabetic women was investigated on an individual level when using a cross-over design. Personalized interventions are critical in designing more effective therapies to prevent metabolic diseases due to inter-subject variations in treatment responses, including potential adverse effects. MSI-CE-MS offers a revolutionary approach for biomarker discovery in metabolomics with high sample throughput and high data fidelity, which is critical for validation of safe yet effective lifestyle interventions that promote human health and reduce risk for chronic diseases.</p>|
|Appears in Collections:||Open Access Dissertations and Theses|
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