一种结合生物医学知识的蛋白质组非标记定量分析方法及其应用  

A Mass Spectrometry-based Label-free Quantitative Approach Coupled With Complex Proteome Functional Analysis

作　　者：潘超[1] 苏运聪 杨睿[1] 段会龙[1] 邓宁[1] 

机构地区：[1]浙江大学生物医学工程与仪器科学学院,生物医学工程教育部重点实验室,杭州310027

出　　处：《生物化学与生物物理进展》2015年第1期82-90,共9页Progress In Biochemistry and Biophysics

基　　金：国家自然科学基金(31100592);国家高技术研究发展计划(863)(2012AA02A601;2012AA02A602;2012AA020201);国家科技重大专项(2013ZX03005012);supported by grants from The National Natural Science Foundation of China(31100592);National High Technology Research and Development Programs of China(863 Programs)(2012AA02A601;2012AA02A602;2012AA020201);National Science and Technology Major Project of China(2013ZX03005012)

摘　　要：基于质谱的非标记定量方法能够对复杂蛋白质组进行规模化分析,同时,在定量分析的基础上理解和解释蛋白质组的功能和相互作用关系更有意义.这需要建立一种有效的兼容定量和定性分析结果的方法.针对这一需求,本文首先借鉴了NSAF(normalized spectral abundance factor)算法采用肽段计数对蛋白质组数据进行定量,进一步结合共享肽对该方法进行优化.以此为基础,通过g:Profiler获取海量蛋白质组的功能注释信息,在定量分析的过程中,同步实现了对蛋白质组数据的功能性分析.本文选择来自人心脏、小鼠心脏、小鼠肝脏的三组线粒体蛋白质组数据对该方法进行验证,按照功能性分析将三组数据划分为若干功能组或信号通路,并进行相关性、功能聚类以及电子传递链分析.结果表明,结合共享肽的优化算法克服了对低丰度蛋白质的错误估计,提高了非标记定量的准确性.同时,结合生物医学知识的分析方法解释了蛋白质组的功能和相互作用关系,为差异比较蛋白质组学、疾病蛋白质组学以及功能蛋白质组学等组学研究提供了新的方法.Label-free quantitative approach based mass spectrometry was used for analysis of complex proteomes,meanwhile, a method based on quantitative analysis which is used for explaining functions and interactions in a large-scale manner is of great importance. To systematically overcome this challenge, we should build a method combing with quantitation and qualification. We used Normalized Spectral Abundance Factor（NSAF） based peptide count as starting point for our analysis and proposed a new method with shared peptides to accurately evaluate abundance of Isoforms for complex proteomes. In addition, large-scale functional annotations of complex proteomes were extracted by g：Profiler and analyzed in the process of quantitation. In this paper, three groups of mitochondrial proteins including mouse heart mitochondrial proteins, mouse liver mitochondrial proteins and human heart mitochondrial proteins were selected for analysis. All MS/MS spectra t were searched against the IPI mouse database and IPI human database using the p Find software kit. Detailed search parameters were performed using as follows： partial tryptic digest allowing two missed cleavages; fixed modification of cysteine with carbamidomethylation（57.021 Da） and variable modification of methionine with oxidation（15.995 Da）, the precursor and fragment mass tolerances were set up at 1.5 and 0.5 Da, respectively. Peptides matching the following criteria were used for protein identification： Delta CN ≥0.1; FDR ≤1.0%; peptide mass was 600.0 ～6000.0; peptide length was 6 ～60. According to the biochemical properties of mitochondrial proteins, all functional annotations were assigned to various signaling pathway or functional clusters, such as apoptosis,DNA/RNA/protein synthesis, metabolism, oxidative phosphorylation, protein binding/folding, proteolysis, redox,signal transduction, structure, transport, cell adhesion and cell cycle, and analyzed by correlation analysis,functional clustering and electron transport chain analysis. We found

关 键 词：蛋白质组学 非标记定量分析 生物质谱 生物医学知识 

分 类 号：Q51[生物学—生物化学] Q811.4