Analysis of the Proteomes in Human Tissues by In-Gel Isoelectric Focusing and Mass Spectrometry
Francesco Giorgianni, Šárka Beranová-Giorgianni
- 发表年份
- 2005
- 引用次数
- 2
摘要
The mammalian proteomes are inherently complex, and therefore a global analysis of these proteomes presents a great technical challenge. It is recognized that there is no single method today that is able to probe an entire human proteome, and that a combination of several methodological approaches provides the most flexible strategy (1). To date, the most widely used methodology for proteome analysis involves a combination of two-dimensional gel electrophoresis (2-DE), mass spectrometry, and bioinformatics tools. Although this “classical” approach has been successfully applied in many studies, it suffers from a number of limitations, such as incomplete proteome coverage, low throughput, and so on (2). In order to overcome these limitations, a number of modifications of the 2-DE-based approach have been introduced, such as new strategies for sample pre-fractionation, introduction of medium- and narrow-range immobilized pH gradient (IPG) strips, development of fluorescent protein stains and differential gel electrophoresis, and design of new robotics systems for protein processing. In addition to modifications in the 2-DE-based proteomics, new methodologies were developed that utilize only one of the dimensions of 2-DE, i.e., isoelectric focusing (IEF) or sodium dodecyl sulfate (SDS)-polyacrylamide gel electrophoresis (PAGE). For example, several strategies that combine in-gel IEF with mass spectrometry (MS) were described, such as direct mass spectrometric characterization of intact proteins in IEF gels (3,4), or identification of proteins in selected regions of IEF gels via proteolytic digestion and mass spectrometry (5–7). Furthermore, in-solution IEF has been also been used for protein fractionation, and new devices for liquid IEF have been designed (8–12).
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992