Proteomic analysis control

Figure 4.10. Proteomic analysis by SILAC. Proteomic analysis by SILAC or stable isotope labeling of amino acids in cell culture utilize de novo metabolic incorporation of stable-isotope-labeled amino acids during protein synthesis. Cells can be cultured with various combinations of stable-isotope-labeled amino acids such as lysine or arginine. Tyrosine has been used in phosphoprotein studies of tyrosine residues. About five or six cell divisions are needed for complete labeling of proteins in cell cultures prior to experimentation. Labeled cells from control and treatment(s) lysates are combined and digested. Quantitation and identification are performed by LC-MS/MS.

The top tier of proteomic analysis categories—proteomic mapping and proteomic profiling—will continue to dominate the field of proteomics because investigators are interested in what proteins are present in their sample and how much. How much is typically a proportion of experimental treatment to control, but proteomic technologies are improving on their abilities to provide amounts and concentrations. Therefore, an important consideration in proteomic analysis is a realistic sense of how much of the proteome can actually be measured with the proteomic platform available in order to best answer the scientific problem at hand. 

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. 

MS is the heart of proteomic analysis and the success of proteomic experiments depends largely on the sensitivity and accuracy of MS equipment used to identify peptide sequences. MS machines have three main components (Figure 2) a source, which generates peptide ions, a mass analyzer, which separates peptide ions based on mass to charge ratio (m/z), and a detector that detects the ion resolved by the mass analyzer. All the modern MS machines are computer controlled and assisted by highly intelligent software. 

In addition to commercially production, a great deal of research and development work on biochips has been going on both in industry and in academia. Genomic analysis of DNA and RNA continues to be the focus of interest, but more and more effort is being spent on proteomic analysis of proteins and peptides. Several enzyme assays and immunoassays designed based on microarray-based systems with simple microfluidic control are close to commercialization. They can be a vital tool in clinic diagnostics, drug discovery, and biomedical research. 

Cell fractionation prior to proteomic analysis has also been explored, as recently illustrated for plasma membranes of breast cancer cells (Adam et al, 2003). Importantly, proteomic analysis from cell cultures can be realized in standardized medium conditions, providing a comparable and controlable status of hormone and growth factor stimulation. In addition, phenotype and behavior of the cells, i.e. proliferation/migration/differentiation/survival, can be experimentaly studied. 

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