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采用纳升超高效液相色谱-串联质谱联用技术(NanoUPLC-MS/MS)结合选择反应监测(SRM)对人肝组织中 14 种 UGT1A 和 UGT2B 进行靶向定量蛋白质组学分析。

Targeted quantitative proteomics for the analysis of 14 UGT1As and -2Bs in human liver using NanoUPLC-MS/MS with selected reaction monitoring.

机构信息

Division of Molecular Pharmaceutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599, United States.

出版信息

J Proteome Res. 2013 Oct 4;12(10):4402-13. doi: 10.1021/pr4004213. Epub 2013 Sep 26.

DOI:10.1021/pr4004213
PMID:23977844
Abstract

Targeted quantitative proteomics using heavy isotope dilution techniques is increasingly being utilized to quantify proteins, including UGT enzymes, in biological matrices. Here we present a multiplexed method using nanoLC-MS/MS and multiple reaction monitoring (MRM) to quantify 14 UGT1As and UGT2Bs in liver matrices. Where feasible, we employ two or more proteotypic peptides per protein, with only four proteins quantified with only one proteotypic peptide. We apply the method to analysis of a library of 60 human liver microsome (HLM) and matching S9 samples. Ten of the UGT isoforms could be detected in liver, and the expression of each was consistent with mRNA expression reported in the literature. UGT2B17 was unusual in that ∼30% of liver microsomes had no or little (<0.5 pmol/mg protein) content, consistent with a known common polymorphism. Liver S9 UGT concentrations were approximately 10-15% those of microsomes. The method was robust, precise, and reproducible and provides novel UGT expression data in human liver that will benefit rational approaches to evaluate metabolism in drug development.

摘要

靶向同位素稀释技术的定量蛋白质组学正越来越多地用于定量分析生物基质中的蛋白质,包括 UGT 酶。本文介绍了一种使用纳升液相色谱-串联质谱(nanoLC-MS/MS)和多重反应监测(MRM)技术定量分析肝脏基质中 14 种 UGT1A 和 UGT2B 的方法。在可行的情况下,我们使用每个蛋白的两个或更多的蛋白特征肽段,仅有四个蛋白仅使用一个蛋白特征肽段进行定量。我们应用该方法分析了 60 个人肝微粒体(HLM)和匹配的 S9 样本库。十种 UGT 同工酶可在肝脏中检测到,每种同工酶的表达与文献报道的 mRNA 表达一致。UGT2B17 不同寻常之处在于约 30%的肝微粒体中没有或很少(<0.5 pmol/mg 蛋白)含量,与已知的常见多态性一致。肝脏 S9 UGT 浓度约为微粒体的 10-15%。该方法具有稳健性、精确性和可重复性,并提供了人类肝脏中新型 UGT 表达数据,这将有助于在药物开发中评估代谢的合理方法。

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