Methodologies proteome analysis

The combination of this top-down proteomics approach, which generates information on the structure of the intact protein, with a bottom-up approach for protein identification (using MS/MS data of tryptic peptides from the collected fractions) has been particularly useful for identifying posttranslational modifications, cotransla-tional processing, and proteolytic modifications in a number of proteins. Examples from our work will be shown to illustrate this hybrid methodology for proteomics analysis. 

The proteomic analysis of the brain has certain limitations that are related either to the sample and/or analytical approach. In the analysis of the brain, many factors may be involved, such as differences among individuals, differences in age and sex, possible other diseases, treatment with medicines, as well as technical factors, disease-unrelated factors, such as postmortem time, improper treatment of the samples, etc., all of which can affect a clear discrimination between healthy and diseased states of interest. The technical limitations involve inefficient detection of low-abundance gene products, hydrophobic proteins (they do not enter the IPG strips), and acidic, basic, high-, and low-molecular mass proteins. All these protein classes are underrepresented in 2-D gels (Lubec et al., 2003 Fountoulakis, 2004). A combination of proteomics methods with protein separation, enriching techniques, and alternative methodologies for detection will improve the detection of additional differences between AD and control brains. Such differences may be essential in the discovery of early disease markers and therapeutic approaches. 

The analysis of a proteome, described as the ensemble of the proteins expressed by a genome in a given tissue, for a given organism at a given time, requires to use and to combine a number of procedures, both experimental (wet-lab experiments) and bioinformatics (dry-lab experiments). Due to the chemical and physical complexity of proteomes, various methodological approaches have to be considered. Nevertheless, a consensus principle of proteome analysis can be described as in Figure 4.1. This linear pathway includes most of the wet- and dry-lab steps required for the complete analysis of a proteome. 

The shear amount of methodologies in the field of proteomics can be grasped by the fact that a topic search using the search words such as proteomics or proteome or proteomic in the Web of Science database returns 12081 publications (search done 2005-10-27). The huge amount of publications does by no means imply that there is no room for improvement. The application of microfluidics to proteomics analysis is still in its infancy and as the detection technologies becomes even more sensitive the ability to handle minute sample amounts will become paramount for continued progress. 

Von Haller, P.D., Yi, E., Donohoe, S., Vaughn, K., Keller, A., Nesvizhskii, A.I., Eng, J., Li, X.J., Goodlett, D.R., Aebersold, R., Watts, J.D. (2003). The Application of New Software Tools to Quantitative Protein Profiling Via Isotope-coded Affinity Tag (ICAT) and Tandem Mass Spectrometry II. Evaluation of Tandem Mass Spectrometry Methodologies for Large-Scale Protein Analysis, and the Application of Statistical Tools for Data Analysis and Interpretation. Mol. Cell. Proteomics 2, 428 -42. 

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