Organismal metabolomes may represent the lowest and arguably most tractable level of control in complex biological systems. Metabolomics or the characterization and study of organismal small molecule end products from physiological process has great promise for aiding researchers in uncovering the latent properties of complex multiparametric biological states. However to reap its potential benefits select challenges in metabolomic analyses need to be addressed. The work herein describes a subset of the many challenges faced by metabolomic researchers in the context of targeted lipidomic analyses or the quantitative characterization of lipid reporters from physiological processes (i.e. sterol esters, triglycerides, phospholipids, fatty acids, oxylipins and endocannabinoids), Chapter 1. Improvements in analytical methodologies are discussed and a targeted lipidomic platform is developed and validated for the quantitative analysis of sterol ester, triglyceride and phospholipid, lipid class-esterified, fatty acids and oxylipins, Chapter 2. Challenges in the areas of metabolomic data analysis and biological interpretation are addressed through the development of a graphical user interface for multivariate data analysis and visualization, Chapter 3. The quantitative characterization of plasma free fatty acids, oxylipins and endocannabinoids is used to develop a mechanistic biological interpretation for the observed type 2 diabetes-dependent changes in lipids fuel and signaling metabolisms, Chapter 4. The work contained in the following 4 Chapters was carried out to advance the application of targeted lipidomics for the study of nutrition and disease. These goals were achieved through (1) the development and validation of a quantitative lipidomic platform for the analysis of lipid class-esterified fatty acids and oxylipins, which was used to characterize the dietary omega-3 fatty acid-induced changes in the esterified components of the sterol ester, triglyceride and phospholipid pools in the adipose and liver tissues of a hamster animal model; (2) the development of a multivariate data analysis and visualization frame work, imDEV, which links multivariate statistical algorithms with intuitive multidimensional visualizations which aid the biological interpretation of metabolomic experimental results; (3) the application of a targeted metabolomic approach to study the effects of type 2 diabetes on plasma free fatty acids, oxylipins and endocannabinoids, which was used to develop reporters for diabetes-associated changes in fatty acid metabolism and identify markers for nonalcoholic fatty liver disease.
|Advisor:||Newman, John W.|
|Commitee:||Adams, Sean H., Newman, John W., Rocke, David M.|
|School:||University of California, Davis|
|Department:||Agricultural and Environmental Chemistry|
|School Location:||United States -- California|
|Source:||DAI-B 74/02(E), Dissertation Abstracts International|
|Subjects:||Analytical chemistry, Nutrition, Bioinformatics|
|Keywords:||Disease, Endocannabinoids, Fatty acids, Nutrition, Oxylipins|
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