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用于准确无标记蛋白质定量的自动化选择反应监测软件。

Automated selected reaction monitoring software for accurate label-free protein quantification.

机构信息

Protein Technology, Department of Immunotechnology, Lund University, BMC D13, 22184 Lund, Sweden.

出版信息

J Proteome Res. 2012 Jul 6;11(7):3766-73. doi: 10.1021/pr300256x. Epub 2012 Jun 14.

Abstract

Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.

摘要

选择反应监测 (SRM) 是一种质谱方法,具有使用标记参考肽准确且可重复地定量蛋白质的记录能力。然而,如果目标是大量肽,并且希望在选择肽时具有高度灵活性,那么使用标记参考肽就变得不切实际了。我们开发了一种无标记定量 SRM 工作流程,该工作流程依赖于一种新的自动化算法 Anubis,用于准确的峰检测。Anubis 可以有效地从污染肽中去除干扰信号,以估计目标肽的真实信号。我们在已发表的多站点数据集上评估了该算法,并获得了与手动数据分析一致的结果。在化脓性链球菌全蛋白消化物的复杂肽混合物中,我们在整个蛋白质组丰度范围内实现了 6.5-19.2%的技术变异性,这明显低于整个生物学样本的总变异性。我们的结果表明,具有自动化数据分析的无标记 SRM 工作流程适用于大规模的生物学研究,为定量蛋白质组学和系统生物学开辟了新的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7623/3426189/150939f728ee/pr-2012-00256x_0001.jpg

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