Old William M, Meyer-Arendt Karen, Aveline-Wolf Lauren, Pierce Kevin G, Mendoza Alex, Sevinsky Joel R, Resing Katheryn A, Ahn Natalie G
Department of Chemistry and Biochemistry, Howard Hughes Medical Institute, University of Colorado, Boulder 80309-0215, USA.
Mol Cell Proteomics. 2005 Oct;4(10):1487-502. doi: 10.1074/mcp.M500084-MCP200. Epub 2005 Jun 23.
Measurements of mass spectral peak intensities and spectral counts are promising methods for quantifying protein abundance changes in shotgun proteomic analyses. We describe Serac, software developed to evaluate the ability of each method to quantify relative changes in protein abundance. Dynamic range and linearity using a three-dimensional ion trap were tested using standard proteins spiked into a complex sample. Linearity and good agreement between observed versus expected protein ratios were obtained after normalization and background subtraction of peak area intensity measurements and correction of spectral counts to eliminate discontinuity in ratio estimates. Peak intensity values useful for protein quantitation ranged from 10(7) to 10(11) counts with no obvious saturation effect, and proteins in replicate samples showed variations of less than 2-fold within the 95% range (+/-2sigma) when >or=3 peptides/protein were shared between samples. Protein ratios were determined with high confidence from spectral counts when maximum spectral counts were >or=4 spectra/protein, and replicates showed equivalent measurements well within 95% confidence limits. In further tests, complex samples were separated by gel exclusion chromatography, quantifying changes in protein abundance between different fractions. Linear behavior of peak area intensity measurements was obtained for peptides from proteins in different fractions. Protein ratios determined by spectral counting agreed well with those determined from peak area intensity measurements, and both agreed with independent measurements based on gel staining intensities. Overall spectral counting proved to be a more sensitive method for detecting proteins that undergo changes in abundance, whereas peak area intensity measurements yielded more accurate estimates of protein ratios. Finally these methods were used to analyze differential changes in protein expression in human erythroleukemia K562 cells stimulated under conditions that promote cell differentiation by mitogen-activated protein kinase pathway activation. Protein changes identified with p<0.1 showed good correlations with parallel measurements of changes in mRNA expression.
在鸟枪法蛋白质组学分析中,质谱峰强度测量和谱图计数是用于量化蛋白质丰度变化的很有前景的方法。我们介绍了Serac软件,该软件用于评估每种方法量化蛋白质丰度相对变化的能力。使用添加到复杂样品中的标准蛋白质,测试了三维离子阱的动态范围和线性度。在对峰面积强度测量值进行归一化和背景扣除以及对谱图计数进行校正以消除比率估计中的不连续性之后,获得了线性以及观察到的与预期的蛋白质比率之间的良好一致性。用于蛋白质定量的峰强度值范围为10⁷至10¹¹计数,没有明显的饱和效应,并且当样品之间共享≥3个肽/蛋白质时,重复样品中的蛋白质在95%范围(±2σ)内的变化小于2倍。当最大谱图计数≥4个谱图/蛋白质时,可以从谱图计数中高置信度地确定蛋白质比率,并且重复测量显示在95%置信限内的测量值相当。在进一步的测试中,通过凝胶排阻色谱法分离复杂样品,量化不同级分之间蛋白质丰度的变化。对于来自不同级分中蛋白质的肽,获得了峰面积强度测量的线性行为。通过谱图计数确定的蛋白质比率与通过峰面积强度测量确定的蛋白质比率非常一致,并且两者都与基于凝胶染色强度的独立测量结果一致。总体而言,谱图计数被证明是检测丰度发生变化的蛋白质的更灵敏方法,而峰面积强度测量产生了更准确的蛋白质比率估计值。最后,这些方法被用于分析在通过丝裂原活化蛋白激酶途径激活促进细胞分化的条件下刺激的人红白血病K562细胞中蛋白质表达的差异变化。p<0.1时鉴定出的蛋白质变化与mRNA表达变化的平行测量结果具有良好的相关性。