Pharmacokinetics, Dynamics and Metabolism (A.V., E.K., A.D.R., M.V.S.V.) and Discovery Sciences (C.N., F.B.), Medicine Design, Pfizer Worldwide R&D, Groton, Connecticut; IQ Proteomics, Cambridge, Massachusetts (B.K.E., R.C.K.); and MS Bioworks, Ann Arbor, Michigan (R.J.).
Pharmacokinetics, Dynamics and Metabolism (A.V., E.K., A.D.R., M.V.S.V.) and Discovery Sciences (C.N., F.B.), Medicine Design, Pfizer Worldwide R&D, Groton, Connecticut; IQ Proteomics, Cambridge, Massachusetts (B.K.E., R.C.K.); and MS Bioworks, Ann Arbor, Michigan (R.J.)
Drug Metab Dispos. 2018 May;46(5):692-696. doi: 10.1124/dmd.117.079285. Epub 2018 Feb 8.
Targeted protein quantification using liquid chromatography-tandem mass spectrometry with stable isotope-labeled standards is recognized as the gold standard of practice for protein quantification. Such assays, however, can only cover a limited number of proteins, and developing targeted methods for larger numbers of proteins requires substantial investment. Alternatively, large-scale global proteomic experiments along with computational methods such as the "total protein approach" (TPA) have the potential to provide extensive protein quantification. In this study, we compared the TPA-based quantitation of seven major hepatic uptake transporters in four human liver tissue samples using global proteomic data obtained from two multiplexed tandem mass tag experiments (performed in two independent laboratories) to the quantitative data from targeted proteomic assays. The TPA-based quantitation of these hepatic transporters [sodium-taurocholate cotransporting polypeptide (NTCP/SLC10A1), organic anion transporter 2 (OAT2/SLC22A7), OAT7/SLC22A9, organic anion-transporting polypeptide 1B1 (OATP1B1/SLCO1B1), OATP1B3/SLCO1B3, OATP2B1/SLCO2B1, and organic cation transporter (OCT1/SLC22A1)] showed good-to-excellent correlations (Pearson = 0.74-1.00) to the targeted data. In addition, the values were similar to those measured by targeted proteomics with 71% and 86% of the data sets falling within 3-fold of the targeted data. A comparison of the TPA-based quantifications of enzyme abundances to available literature data showed that the majority of the enzyme quantifications fell within the reference data intervals. In conclusion, these results demonstrate the capability of multiplexed global proteomic experiments to detect differences in protein expression between samples and provide reasonable estimations of protein expression levels.
基于稳定同位素标记标准的液相色谱-串联质谱的靶向蛋白质定量被认为是蛋白质定量的金标准。然而,这种测定方法只能覆盖有限数量的蛋白质,而开发针对更多数量蛋白质的靶向方法需要大量投资。或者,大规模的全局蛋白质组学实验以及计算方法(如“总蛋白方法”(TPA))有可能提供广泛的蛋白质定量。在这项研究中,我们比较了基于 TPA 的四种人类肝组织样本中七种主要肝摄取转运蛋白的定量,这些数据来自于两个串联质量标签实验(在两个独立实验室中进行)的全局蛋白质组学数据,以及靶向蛋白质组学测定的定量数据。这些肝转运蛋白[牛磺胆酸钠共转运多肽(NTCP/SLC10A1)、有机阴离子转运蛋白 2(OAT2/SLC22A7)、OAT7/SLC22A9、有机阴离子转运多肽 1B1(OATP1B1/SLCO1B1)、OATP1B3/SLCO1B3、OATP2B1/SLCO2B1 和有机阳离子转运体(OCT1/SLC22A1)]的 TPA 定量与靶向数据显示出良好到极好的相关性(Pearson=0.74-1.00)。此外,这些值与靶向蛋白质组学测量的值相似,71%和 86%的数据落在靶向数据的 3 倍以内。将 TPA 定量的酶丰度与可用的文献数据进行比较,结果表明大多数酶的定量值都在参考数据区间内。总之,这些结果表明,多重全局蛋白质组学实验能够检测样品之间蛋白质表达的差异,并提供蛋白质表达水平的合理估计。