Abstract：
Blood plasma is one of the most commonly analyzed and easily accessible biological samples. Here, we describe an automated liquid-liquid extraction platform that generates accurate, precise, and reproducible samples for metabolomic, lipidomic, and proteomic analyses from a single aliquot of plasma while minimizing hands-on time and avoiding contamination from plasticware. We applied mass spectrometry to examine the metabolome, lipidome, and proteome of 90 plasma samples to determine the effects of age, time of day, and a high-fat diet in mice. From 25 μl of mouse plasma, we identified 907 lipid species from 16 different lipid classes and subclasses, 233 polar metabolites, and 344 proteins. We found that the high-fat diet induced only mild changes in the polar metabolome, upregulated apolipoproteins, and induced substantial shifts in the lipidome, including a significant increase in arachidonic acid and a decrease in eicosapentaenoic acid content across all lipid classes.
摘要：
血浆是最常用的分析和容易获得的生物样品之一。这里,我们描述了一个自动的液-液萃取（LLE）平台，产生准确的，精确，和可重现的代谢组学样本，脂质体，和蛋白质组学分析从一个单一的血浆等分试样，同时尽量减少动手时间和避免污染从塑料器皿。我们应用质谱来检查代谢组，脂凝素,和90个血浆样本的蛋白质组，以确定年龄的影响，一天的时间,和老鼠的高脂肪饮食。从25μL小鼠血浆中，我们从16种不同的脂质类别和亚类中鉴定出907种脂质，233极性代谢物，344种蛋白质。我们发现高脂肪饮食仅引起极性代谢组的轻度变化，上调载脂蛋白,并引起脂质组的实质性变化，包括所有脂质类别中花生四烯酸（AA）的显着增加和二十碳五烯酸（EPA）含量的降低。
