Complex Proteomes Analysis Using Label-Free Mass Spectrometry-Based Quantitative Approach Coupled with Biomedical Knowledge
Label-free quantitative proteomics based on mass spectrometry plays an essential role in large-scale analysis of complex proteomes.Meanwhile, quantitative proteomics is not only a way for data processing, but also an important approach for exploring protein functions and interactions in a large-scale manner.An effective method combining quantitation and qualification should be built.To systematically overcome this challenge, we proposed a new label-free quantitative method using spectral counting in the proposed method, the count of shared peptides was considered as an optimized factor to accurately appraise abundance of Isoforms for complex proteomes.Large-scale functional annotations for complex proteomes were extracted by g:Profiler and were assigned to functional clusters.To test the effect of the methods, three groups of mitochondrial proteins including mouse heart mitochondrial dataset, mouse liver mitochondrial dataset and human heart mitochondrial dataset were selected for analysis.According to the biochemical properties of mitochondrial proteins, all functional annotations were assigned to various signalling pathway or functional clusters.We came to draw a conclusion that the strategy with shared peptides overcame inaccurate and overestimated results for low-abundant isoforms to improve accuracy, and quantitative proteomics coupled with biomedical knowledge can thoroughly comprehend functions and relationships for complex proteomes, and contribute to providing a new method for large-scale comparative or diseased proteomics.
Complex Proteomes Label-free Quantitation Mass Spectrometry Biomedical Knowledge
Chao Pan Wenxian Peng Huilong Duan Ning Deng
College of Biomedical Engineering and Instrument Science,Key Laboratory of Biomedical Engineering of Department of Radiology, Zhejiang Medical College, Hangzhou, China
国际会议
8th International Conference on Intelligent Information Processing(2014年IFIP智能信息处理国际会议)
杭州
英文
20-28
2014-10-01（万方平台首次上网日期，不代表论文的发表时间）