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从基于质谱的蛋白质表达数据计算绝对和相对蛋白质丰度。

Calculating absolute and relative protein abundance from mass spectrometry-based protein expression data.

作者信息

Vogel Christine, Marcotte Edward M

机构信息

Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, 2500 Speedway, MBB 3.210, Austin, Texas 78712, USA.

出版信息

Nat Protoc. 2008;3(9):1444-51. doi: 10.1038/nport.2008.132.

Abstract

Mass spectrometry (MS)-based shotgun proteomics allows protein identifications even in complex biological samples. Protein abundances can then be estimated from the counts of tandem MS (MS/MS) spectra attributable to each protein, provided one accounts for differential MS detectability of contributing peptides. We developed a method, APEX, which calculates Absolute Protein EXpression levels based upon learned correction factors, MS/MS spectral counts and each protein's probability of correct identification. This protocol describes APEX-based calculations in three parts. (i) Using training data, peptide sequences and their sequence properties, a model is built to estimate MS detectability (O(i)) for any given protein. (ii) Absolute protein abundances are calculated from spectral counts, identification probabilities and the learned O(i)-values. (iii) Simple statistics allow calculation of differential expression in two distinct biological samples, i.e., measuring relative protein abundances. APEX-based protein abundances span 3-4 orders of magnitude and are applicable to mixtures of 100s to 1,000s of proteins.

摘要

基于质谱(MS)的鸟枪法蛋白质组学即使在复杂的生物样品中也能实现蛋白质鉴定。如果考虑到组成肽段的质谱检测差异,那么就可以根据归因于每种蛋白质的串联质谱(MS/MS)谱图计数来估计蛋白质丰度。我们开发了一种名为APEX的方法,该方法基于学习到的校正因子、MS/MS谱图计数以及每种蛋白质正确鉴定的概率来计算绝对蛋白质表达水平。本方案分三个部分描述基于APEX的计算方法。(i)利用训练数据、肽段序列及其序列特性,构建一个模型来估计任何给定蛋白质的质谱检测能力(O(i))。(ii)根据谱图计数、鉴定概率和学习到的O(i)值计算绝对蛋白质丰度。(iii)简单的统计方法可以计算两个不同生物样品中的差异表达,即测量相对蛋白质丰度。基于APEX的蛋白质丰度范围跨越3 - 4个数量级,适用于数百到数千种蛋白质的混合物。

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