Nature Communications ( IF 14.7 ) Pub Date : 2023-02-02 , DOI: 10.1038/s41467-023-36269-7
Qing Yu 1 , Xinyue Liu 1 , Mark P Keller 2 , Jose Navarrete-Perea 1 , Tian Zhang 1 , Sipei Fu 1 , Laura P Vaites 1 , Steven R Shuken 1 , Ernst Schmid 3 , Gregory R Keele 4 , Jiaming Li 1 , Edward L Huttlin 1 , Edrees H Rashan 2 , Judith Simcox 2 , Gary A Churchill 4 , Devin K Schweppe 5 , Alan D Attie 2 , Joao A Paulo 1 , Steven P Gygi 1
Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis.
中文翻译:
基于样本多重的靶向途径蛋白质组学与实时分析揭示了遗传变异对蛋白质表达的影响
靶向蛋白质组学通过测量扰动后与功能、疾病或类别相关的蛋白质组的细胞表达,实现假设驱动的研究。在这里,我们提出了一种以通路为中心的方法和分析构建器资源,用于针对从 >10,000 个表达蛋白中选出的多达 200 个蛋白的整个通路,以直接测量它们的丰度,利用样本复用将通量提高 16 倍。该策略称为 GoDig,仅需要单次 LC-MS 分析、约 1 µg 组合肽材料、多达 200 种蛋白质的列表以及实时分析,即可触发对数百种分析物的多达 16 个样品进行同时定量。我们应用 GoDig 来量化遗传变异对高脂肪饮食小鼠蛋白质表达的影响。我们创建了几种 GoDig 检测来量化 480 只全基因型 Diversity Outbred 小鼠中多个蛋白质家族(激酶、脂质代谢和脂滴相关蛋白质)的表达,揭示蛋白质数量性状位点并建立特定蛋白质和脂质稳态之间的潜在联系。