The effects of shared peptides on protein quantitation in label-free proteomics by LC/MS/MS
The effects of shared peptides on protein quantitation in label-free proteomics by LC/MS/MS
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DOI：
10.1021/pr0704175
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发表时间：
2008-01-01
影响因子：
4.4
通讯作者：
Miller, John H.
中科院分区：
文献类型：
--
作者：
Jin, Shuangshuang;Daly, Donald S.;Miller, John H.
从所检测的肽的观察特性评估差异蛋白质丰度是基于鸟枪蛋白质组学的蛋白质谱分析的重要部分。然而，观察到的共享肽的丰度可能是由于受到给定处理不同影响的多种蛋白质的贡献。排除共享肽消除了这种模糊性，但可能会显着减少可以获得丰度估计的蛋白质的数量。如果家族成员对治疗有共同的反应，则生物学相关蛋白质家族内的肽共享不会引起歧义。基于这一概念，我们已经开发出一种方法，包括共享的肽在蛋白质谱的差异蛋白质丰度的分析。最近的一项蛋白质组学研究的数据暴露于脂多糖，香烟烟雾，以及这些药物的组合小鼠的肺组织被用来说明我们的方法。从数据库中大约一半的相关蛋白质涉及共享肽的数据开始，基于FASTA注释，将82%的受影响蛋白质分组到家族中，并关闭肽共享。在许多情况下，相对于对照的共同丰度足以解释肽的离子电流峰面积，无论是独特的还是共享的，其鉴定了肽共享封闭组中的生物学相关蛋白质。在这些结果的基础上，我们建议，肽共享封闭组提供了一种方法，包括共享肽的丰度数据在定量蛋白质分析的高通量质谱。
Assessment of differential protein abundance from the observed properties of detected peptides is an essential part of protein profiling based on shotgun proteomics. However, the abundance observed for shared peptides may be due to contributions from multiple proteins that are affected differently by a given treatment. Excluding shared peptides eliminates this ambiguity but may significantly decrease the number of proteins for which abundance estimates can be obtained. Peptide sharing within a family of biologically related proteins does not cause ambiguity if family members have a common response to treatment. On the basis of this concept, we have developed an approach for including shared peptides in the analysis of differential protein abundance in protein profiling. Data from a recent proteomics study of lung tissue from mice exposed to lipopolysaccharide, cigarette smoke, and a combination of these agents are used to illustrate our method. Starting from data where about half of the implicated database protein involved shared peptides, 82% of the affected proteins were grouped into families, based on FASTA annotation, with closure on peptide sharing. In many cases, a common abundance relative to control was sufficient to explain ion-current peak areas for peptides, both unique and shared, that identified biologically related proteins in a peptide-sharing closure group. On the basis of these results, we propose that peptide-sharing closure groups provide a way to include abundance data for shared peptides in quantitative protein profiling by high-throughput mass spectrometry.