跨平台的质谱蛋白回归定量和质量控制的参数方法

发布时间：2018-10-30 18:11

【摘要】：各质谱厂商通常使用不同的软件进行蛋白鉴定和定量,导致获得的数据和结果的通用性不佳。另外,目前蛋白质定量的准确性仍有提升空间。因此,开发一个标准化、自动化且定量更准确的蛋白质定量流程具有现实意义。采用肽段保留时间对齐和回归技术,可有效地减少中低丰度肽段鉴定信息缺失带来的影响,提高中低丰度蛋白的定量能力。一个综合考虑信号峰宽分布、保留时间分布以及肽段同位素模式分布等因素的肽段筛选器,可以有效地过滤掉不适宜定量的肽段信号,使肽段离子流色谱(XIC)峰定量面积的计算更为准确。该流程由数据开源转换、保留时间对齐与回归定量、肽段筛选器等模块构成,可准确定量不同平台产出的质谱数据,并明显改善低丰度蛋白的无标定量。经对比,该流程对蛋白质组学动态范围标准蛋白集(UPS2)的定量比MaxQuant和Proteome Discoverer的定量更准确。
[Abstract]:Different mass spectrometry manufacturers usually use different software for protein identification and quantification, which results in poor generality of the obtained data and results. In addition, there is room for improvement in the accuracy of protein quantification. Therefore, it is of practical significance to develop a standardized, automated and more accurate protein quantification process. By using peptide retention time alignment and regression techniques, the effects of missing identification information on low and middle abundance peptide segments can be effectively reduced, and the quantitative ability of low and medium abundance proteins can be improved. A peptide filter which considers the distribution of peak width, retention time and isotopic pattern of peptide segment can effectively filter out unsuitable peptide segment signal. It is more accurate to calculate the quantitative area of (XIC) peak in peptide ion current chromatography. The process is composed of data open source conversion, retention time alignment and regression quantification, peptide screening and so on, which can accurately quantify mass spectrum data from different platforms and improve the non-standard quantification of low abundance protein. By comparison, the quantification of standard protein set (UPS2) in proteomics dynamic range was more accurate than that of MaxQuant and Proteome Discoverer.
【作者单位】：蛋白质组学国家重点实验室北京蛋白质组研究中心军事医学科学院放射与辐射医学研究所;复旦大学生命科学学院;
【基金】：国际科技合作项目《蛋白质组信息学关键技术及分析系统研发》(2014DFB30010) 青年科学基金项目《利用高解析度质谱数据进行中低丰度蛋白质无标定量的研究》(31200992)资助
【分类号】：O629.73;O657.63

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