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Comparison of a Label-Free Quantitative Proteomic Method Based on Peptide Ion Current Area to the Isotope Coded Affinity Tag Method

机译:基于肽离子流面积的无标记定量蛋白质组学方法与同位素编码亲和标记法的比较

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摘要

Recently, several research groups have published methods for the determination of proteomic expression profiling by mass spectrometry without the use of exogenously added stable isotopes or stable isotope dilution theory. These so-called label-free, methods have the advantage of allowing data on each sample to be acquired independently from all other samples to which they can later be compared in silico for the purpose of measuring changes in protein expression between various biological states. We developed label free software based on direct measurement of peptide ion current area (PICA) and compared it to two other methods, a simpler label free method known as spectral counting and the isotope coded affinity tag (ICAT) method. Data analysis by these methods of a standard mixture containing proteins of known, but varying, concentrations showed that they performed similarly with a mean squared error of 0.09. Additionally, complex bacterial protein mixtures spiked with known concentrations of standard proteins were analyzed using the PICA label-free method. These results indicated that the PICA method detected all levels of standard spiked proteins at the 90% confidence level in this complex biological sample. This finding confirms that label-free methods, based on direct measurement of the area under a single ion current trace, performed as well as the standard ICAT method. Given the fact that the label-free methods provide ease in experimental design well beyond pair-wise comparison, label-free methods such as our PICA method are well suited for proteomic expression profiling of large numbers of samples as is needed in clinical analysis.
机译:最近,几个研究小组已经发表了通过质谱法测定蛋白质组表达谱的方法,而没有使用外源添加的稳定同位素或稳定同位素稀释理论。这些所谓的无标记方法的优点在于,可以独立于所有其他样品获取每个样品上的数据,之后可以在计算机上对其进行比较,以测量各种生物学状态之间蛋白质表达的变化。我们开发了基于直接测量肽离子电流面积(PICA)的无标签软件,并将其与其他两种方法进行了比较,这是一种称为光谱计数的更简单的无标签方法和同位素编码亲和标签(ICAT)方法。通过这些方法对含有已知但浓度不同的蛋白质的标准混合物进行的数据分析表明,它们的表现相似,均方差为0.09。此外,使用不含PICA标签的方法分析掺有已知浓度标准蛋白的复杂细菌蛋白混合物。这些结果表明,在这种复杂的生物样品中,PICA方法以90%的置信度检测了所有水平的标准加标蛋白质。这一发现证实,基于对单个离子电流迹线下面积的直接测量,无标记方法与标准ICAT方法一样有效。鉴于无标记方法提供了易于进行的实验设计,远远超出了成对比较的事实,因此无标记方法(例如我们的PICA方法)非常适合临床分析所需的大量样品的蛋白质组学表达谱分析。

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