Proteomics is the science of large-scale analysis of proteins. As proteins are the basis of structural, enzymatic, and many regulatory components of a cell, the direct study of proteins involved in signaling pathways is of great interest. Mass spectrometry has increasingly become the method of choice for the analysis of complex protein samples (Aebersold and Mann 2003; de Hoog and Mann 2004), especially in those cases in which the protein function is not yet fully understood. The success of protein mass spectrometry has been made possible by the development of soft protein ionization methods, such as electrospray ionization (ESI) or matrix-assisted laser desorption/ionization (MALDI), an achievement that has been acknowledged with the Nobel prize in chemistry 2002 to John Fenn and Koichi Tanaka. However, without the information derived from various full genome sequencing projects, and without efficient algorithms for peptide sequence determination from fragmentation spectra (Eng et al. 1994; Pevzner et al. 2001), proteomic experiments would be a great deal more difficult today.
The recent success of mass spectrometry based approaches in the elucidation of protein-protein interactions indicates that the technology has evolved to a crucial tool in signaling biology (Blagoev et al. 2003, 2004; Schulze et al. 2005). The field of mass spectrometry based proteomics is still under fast development; new and better instrumentation is being developed on almost a yearly basis. Thus, each technical breakthrough either allows new kinds of applications or improves the quality or throughput of traditional measurements. However, no method or instrument is capable of identifying and quantifying all the components in a complex protein extract in a single step. Therefore, careful experimental design involving the steps of protein separation, enrichment, and purification is essential for successful interpretation of proteomic datasets.
Among the variety of different technological aspects of mass spectrometry based proteomics, two major workflows have emerged, one involving separation of proteins on two-dimensional gels and subsequent identification of protein spots by mass spectrometry, and the other involving in-solution digestion of a complex protein mixture, subsequent separation of the peptides by one-dimensional or multidimensional liquid chromatography, and online analysis by mass spectrometry. Depending on the nature of the biological question, mixtures of the two major strategies are employed.
Protein mixtures today can routinely be characterized in terms of proteins present in a given sample. However, in order to allow biological interpretation, quantitative analyses are necessary. Peak integration, spectrum counts, or derived indices (Ishihama et al. 2005; Washburn et al. 2001) have been established as a basis for quantitative comparison of protein extracts derived from organisms under different conditions, or in defining a sub-proteome of interest (Andersen et al. 2003). Alternatively, stable isotope labeling strategies, such as metabolic labeling, H218O digest, iTRAQ or ICAT, are used. These techniques allow direct relative comparison of two or more samples in the same LC/MS/MS analysis (Dunkley et al. 2004; Engelsberger et al. 2006; Jones et al. 2006; Nelson et al. 2006). This chapter will give an overview of how quantitative proteomic strategies can be applied to the analysis of signaling pathways, with special respect to protein-protein interactions and protein phosphorylation.
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