Label-free absolute protein quantification with data-independent acquisition
Label-free absolute protein quantification with data-independent acquisition
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DOI：
10.1016/j.jprot.2019.03.005
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发表时间：
2019-05-30
影响因子：
3.3
通讯作者：
Zhu, Hao-Jie
中科院分区：
文献类型：
--
作者：
He, Bing;Shi, Jim;Zhu, Hao-Jie
尽管数据独立采集（data-independent acquisition， DIA）越来越多地用于蛋白质的相对定量，但基于DIAbased的无标记绝对定量方法尚未完全建立。在这里，我们提出了一种新的DIA方法，使用TPA算法（DIA-TPA）来绝对定量人肝微粒体和S9样品中的蛋白质表达。为了验证该方法，对36个人肝微粒体和S9样本进行了数据依赖采集（data-dependent acquisition， DDA）和DIA实验。基于ms2的DIA-TPA能够量化大约两倍于基于ms1的DDA-TPA方法的蛋白质，而两种方法测定的蛋白质浓度是可比的。为了评估DIA-TPA方法的准确性，我们使用已建立的基于SILAC内标准的蛋白质组学分析绝对定量人肝脏S9组分中羧酸酯酶1的浓度；SILAC结果与DIA-TPA分析结果一致。最后，我们在DIA-TPA中采用了一种独特的算法，将共享肽的MS信号分配到单个蛋白质或同种异构体上，并成功地将该方法应用于人肝微粒体中几种药物代谢酶的绝对定量。综上所述，DIA-TPA方法不仅可以对整个蛋白质组和特定蛋白质进行绝对定量，而且具有对具有共享肽的蛋白质进行定量的能力。意义：数据独立采集（Data independent acquisition， DIA）已经成为在整个蛋白质组水平上进行相对蛋白质定量的一种强有力的方法。然而，基于dia的无标签绝对蛋白定量（APQ）方法尚未完全建立。在本研究中，我们提出了一种新的基于dia的无标签APQ方法，命名为DIA-TPA，具有绝对定量具有共享肽的蛋白质的能力。通过将DIA-TPA的定量结果与基于稳定同位素标记的内标蛋白组学分析结果进行比较，验证了该方法的有效性。
Despite data-independent acquisition (DIA) has been increasingly used for relative protein quantification, DIAbased label-free absolute quantification method has not been fully established. Here we present a novel DIA method using the TPA algorithm (DIA-TPA) for the absolute quantification of protein expressions in human liver microsomal and S9 samples. To validate this method, both data-dependent acquisition (DDA) and DIA experiments were conducted on 36 individual human liver microsome and S9 samples. The MS2-based DIA-TPA was able to quantify approximately twice as many proteins as the MS1-based DDA-TPA method, whereas protein concentrations determined by the two approaches were comparable. To evaluate the accuracy of the DIA-TPA method, we absolutely quantified carboxylesterase 1 concentrations in human liver S9 fractions using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-TPA analysis. Finally, we employed a unique algorithm in DIA-TPA to distribute the MS signals from shared peptides to individual proteins or isoforms and successfully applied the method to the absolute quantification of several drug-metabolizing enzymes in human liver microsomes. In sum, the DIA-TPA method not only can absolutely quantify entire proteomes and specific proteins, but also has the capability quantifying proteins with shared peptides.Significance: Data independent acquisition (DIA) has emerged as a powerful approach for relative protein quantification at the whole proteome level. However, DIA-based label-free absolute protein quantification (APQ) method has not been fully established. In the present study, we present a novel DIA-based label-free APQ approach, named DIA-TPA, with the capability absolutely quantifying proteins with shared peptides. The method was validated by comparing the quantification results of DIA-TPA with that obtained from stable isotope-labeled internal standard-based proteomic assays.