Compartment Modeling for Mammalian Protein Turnover Studies by Stable Isotope Metabolic Labeling

被引:36
作者
Guan, Shenheng [1 ,2 ]
Price, John C. [3 ]
Ghaemmaghami, Sina [3 ,4 ]
Prusiner, Stanley B. [3 ,4 ]
Burlingame, Alma L. [1 ,2 ]
机构
[1] Univ Calif San Francisco, Dept Pharmaceut Chem, San Francisco, CA 94158 USA
[2] Univ Calif San Francisco, Mass Spectrometry Facil, San Francisco, CA 94158 USA
[3] Univ Calif San Francisco, Inst Neurodegenerat Dis, San Francisco, CA 94143 USA
[4] Univ Calif San Francisco, Dept Neurol, San Francisco, CA 94143 USA
关键词
MASS-SPECTROMETRY; DYNAMICS;
D O I
10.1021/ac203330z
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Protein turnover studies on a proteome scale based on metabolic isotopic labeling can provide a systematic understanding of mechanisms for regulation of protein abundances and their transient behaviors. At this time, these large-scale studies typically utilize a simple kinetic model to extract protein dynamic information. Although many high-quality, protein isotope incorporation data are available from those experiments, accurate and additionally useful protein dynamic information cannot be extracted from the experimental data by use of the simple kinetic models. In this paper, we describe a formal connection between data obtained from elemental isotope labeling experiments and the well-known compartment modeling, and we demonstrate that an appropriate application of a compartment model to turnover of proteins from mammalian tissues can indeed lead to a better fitting of the experimental data.
引用
收藏
页码:4014 / 4021
页数:8
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