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基于质谱的方法,使用 ATP 探针提高激酶组分析的通量。

Mass spectrometry based method to increase throughput for kinome analyses using ATP probes.

机构信息

Department of Cell Biology, Harvard Medical School, Harvard University, Boston, Massachusetts 02115, United States.

出版信息

Anal Chem. 2013 May 7;85(9):4666-74. doi: 10.1021/ac303478g. Epub 2013 Apr 22.

Abstract

Protein kinases play critical roles in many biological and pathological processes, making them important targets for therapeutic drugs. Here, we desired to increase the throughput for kinome-wide profiling. A new workflow coupling ActivX ATP probe (AAP) affinity reagents with isotopic labeling to quantify the relative levels and modification states of kinases in cell lysates is described. We compared the new workflow to a classical proteomics approach in which fractionation was used to identify low-abundance kinases. We find that AAPs enriched approximately 90 kinases in a single analysis involving six cell lines or states in a single run, an 8-fold improvement in throughput relative to the classical approach. In general, AAPs cross-linked to both the active and inactive states of kinases but performing phosphopeptide enrichment made it possible to measure the phospho sites of regulatory residues lying in the kinase activation loops, providing information on activation state. When we compared the kinome across the six cell lines, representative of different breast cancer clinical subtypes, we observed that many kinases, particularly receptor tyrosine kinases, varied widely in abundance, perhaps explaining the differential sensitivities to kinase inhibitor drugs. The improved kinome profiling methods described here represent an effective means to perform systematic analysis of kinases involved in cell signaling and oncogenic transformation and for analyzing the effect of different inhibitory drugs.

摘要

蛋白激酶在许多生物和病理过程中发挥着关键作用,使其成为治疗药物的重要靶点。在这里,我们希望提高全激酶组分析的通量。我们描述了一种新的工作流程,该流程将 ActivX ATP 探针 (AAP) 亲和试剂与同位素标记相结合,以定量细胞裂解物中激酶的相对水平和修饰状态。我们将新工作流程与经典蛋白质组学方法进行了比较,该方法使用分馏来鉴定低丰度激酶。我们发现,AAP 在单次分析中富集了大约 90 种激酶,涉及六种细胞系或状态,与经典方法相比,通量提高了 8 倍。通常,AAP 交联到激酶的活性和非活性状态,但进行磷酸肽富集使得能够测量位于激酶激活环中的调节残基的磷酸化位点,提供关于激活状态的信息。当我们比较六种细胞系(代表不同的乳腺癌临床亚型)中的激酶组时,我们观察到许多激酶,特别是受体酪氨酸激酶,丰度差异很大,这也许可以解释对激酶抑制剂药物的不同敏感性。这里描述的改进的激酶组分析方法代表了一种有效的方法,可以对参与细胞信号转导和致癌转化的激酶进行系统分析,并分析不同抑制性药物的效果。

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