Development of Deuterium Oxide Labeling for Global Omics Relative Quantification for Assessment of Environmental Risks

Abstract

With the high demand for toxicity testing, omics approaches have gained prominence because of their ability to provide rapid and comprehensive molecular-level toxicity endpoints. However, there are a limited number of quantitative methods that can be widely applicable to multiple omics. This thesis extends the application of the previously developed deuterium oxide labeling for global omics relative quantification (DOLGOReQ) regarding biomolecules and sample types. By applying DOLGOReQ, which was originally developed for lipids, to glycans with different elemental compositions and sizes, a new quantitative evaluation metric was developed that can be consistently applied to any isotopic distribution. From the elemental composition of the biomolecule to be quantified, the number of mass isotopomers required for high quantitation was calculated, and features that did not meet this criterion were filtered out; only features with low quantitation accuracy were successfully removed. After enhancing DOLGOReQ’s filtering algorithm to expand the size range of the biomolecules that DOLGOReQ can cover, DOLGOReQ was introduced to a variety of sample models. Applied to a 3D culture system, which is an alternative model to animal experiments, DOLGOReQ provided information on the lipid changes caused by the differentiation of adipocytes and coculture with macrophages. The 3D-cultured adipocytes showed higher reproducibility than 2D-cultured adipocytes. An upregulation of lipolysis and a decrease in triacylglycerol with a very long fatty acyl chain caused by a coculture with macrophages also could be detected. The significance of these results is that DOLGOReQ can provide a comprehensive interpretation of lipid metabolism because it also provides information on changes in the turnover of D2O labeling, which cannot be provided using conventional quantitative methods. This strategy narrows down the possibility of quantitative changes in lipids, allowing for a more in-depth and accurate interpretation. Finally, DOLGOReQ was applied to a human-like mouse model to demonstrate the systemic changes caused by long-term, low-level exposure to microplastics. DOLGOReQ was able to label multiple organs simultaneously, revealing lipid changes in the brain and heart. The whole organism was well labeled by D2O, demonstrating the strength of DOLGOReQ’s ability to simultaneously quantify multiple organs to uncover systemic changes. The method of this study can largely be applied to a variety of biological models and biomolecules with little difficulty and can provide comprehensive quantification for environmental toxicity and biological experiments with an affordable, rapid, and automated platform.