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Quantification of Stable Isotope Traces Close to Natural Enrichment in Human Plasma Metabolites Using Gas Chromatography-Mass Spectrometry

机译:使用气相色谱 - 质谱法测量稳定同位素痕量痕量近于人血浆代谢物的天然富集

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摘要

Currently, changes in metabolic fluxes following consumption of stable isotope-enriched foods are usually limited to the analysis of postprandial kinetics of glucose. Kinetic information on a larger diversity of metabolites is often lacking, mainly due to the marginal percentage of fully isotopically enriched plant material in the administered food product, and hence, an even weaker 13C enrichment in downstream plasma metabolites. Therefore, we developed an analytical workflow to determine weak 13C enrichments of diverse plasma metabolites with conventional gas chromatography-mass spectrometry (GC-MS). The limit of quantification was increased by optimizing (1) the metabolite extraction from plasma, (2) the GC-MS measurement, and (3) most importantly, the computational data processing. We applied our workflow to study the catabolic dynamics of 13C-enriched wheat bread in three human subjects. For that purpose, we collected time-resolved human plasma samples at 16 timepoints after the consumption of 13C-labeled bread and quantified 13C enrichment of 12 metabolites (glucose, lactate, alanine, glycine, serine, citrate, glutamate, glutamine, valine, isoleucine, tyrosine, and threonine). Based on isotopomer specific analysis, we were able to distinguish catabolic profiles of starch and protein hydrolysis. More generally, our study highlights that conventional GC-MS equipment is sufficient to detect isotope traces below 1% if an appropriate data processing is integrated.
机译:目前,在稳定同位素的食物消耗后代谢通量的变化通常仅限于葡萄糖后动力学的分析。关于较大多样性代谢物的动力学信息往往缺乏,主要是由于施用食品中完全同位素富含植物材料的边际百分比,因此,下游等离子体代谢物中的甚至较弱的13C富集。因此,我们开发了分析工作流程,以确定具有常规气相色谱 - 质谱(GC-MS)的多样化血浆代谢物的弱13C富集。通过优化(1)来自等离子体的代谢物提取,(2)GC-MS测量,(3)最重要的是,通过优化(1)代谢物提取,增加了定量限度,并且最重要的是,计算数据处理。我们应用了我们的工作流程,以研究三个人类受试者的13个浓麦面包的分解动态。为此目的,我们在用13℃标记的面包和量化13C富集12个代谢物(葡萄糖,乳酸盐,丙氨酸,甘氨酸,丝氨酸,柠檬酸盐,谷氨酸,谷氨酰胺,缬氨酸,异亮氨酸)中收集时间分辨的人血浆样品。 ,酪氨酸和苏氨酸)。基于同位素特异性分析,我们能够区分淀粉和蛋白质水解的分解代谢型材。更一般地,我们的研究突出显示传统的GC-MS设备足以检测在1%以下的同位素迹线,如果集成了适当的数据处理。

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