Top References

 
The single most common application of proteomics is protein identification. Most investigators use proteomics approaches to isolate and display proteins based on their own specific criteria and then identify the proteins. Protein identification provides immediate information that will direct subsequent experimentation. For example, the identity of a protein can reveal an expected result, validate a proteomics approach, provide completely unexpected information, or reveal that your biochemical method is not working at all. We feel that the most critical stage of any proteomics approach is the strategic design for the isolation of protein targets. In recent years, as the technology of MS has improved, there has been a de-emphasis on the "front-end" of proteomics experiments compared to data analysis. This can result in the isolation of hundreds of irrelevant proteins for identification, consuming both time and effort. Our general strategy is to devise techniques that enrich for low-abundance proteins and then analyze only the proteins that appear on differential display or are isolated by affinity chromatography. To accomplish this, we use affinity columns and other strategies to select for protein targets. In each case, protein samples are subjected to a series of precolumns and high-stringency washes to remove nonspecific proteins. This reduces the number of irrelevant proteins for analysis.

Many laboratories are now engaged in an effort to characterize protein complexes by MS. Examples include Link et al. utilizing multidimensional LC and MS/MS to identify proteins (95) or Mann and colleagues identifying proteins present after immunoprecipitation of protein complexes (124). Recently, Macara, Haystead, and coworkers used MS to identify interacting proteins with the Cdc42 effector, Borg3 (80). In this case, the "bait" protein, Borg3, was produced as a glutathione S-transferase (GST) fusion in E. coli and then mixed with NIH 3T3 cell lysate. Four interacting proteins were identified by mixed-peptide sequencing: heat shock protein Hsp70 and three septins including Septin6, Cdc10, and Nedd5 (Fig. 11). None of these proteins were present in the GST-only control sample. Although the interaction with Hsp70 was not pursued, it was shown from coimmunoprecipitation studies that endogenous Borg3 interacts with endogenous Cdc10 and Nedd5 (80). Additional proof from expression and structure-function studies confirmed a role for the Borg proteins as regulators of septin organization. It should be noted that although several proteins were quickly identified as Borg3 interactors by the pull-down experiment, it took several more months of work to confirm this interaction.

View larger version (92K): [in this window] [in a new window]   FIG. 11. Identification of novel protein interactions by protein coprecipitation. (A) Pull-down experiment with a control (GST) or target (GST-Borg3) protein using 35S-labeled NIH 3T3 cell lysate. (B) Large-scale affinity purification of GST-Borg3 from the NIH 3T3 lysate. Individual proteins were microsequenced by mixed-peptide sequencing and identified by database searching with the FASTF algorithm (101).

The largest application of proteomics continues to be protein expression profiling. Through the use of two-dimensional gels or novel techniques such as ICAT, the expression levels of proteins or changes in their level of modification between two different samples can be compared and the proteins can be identified. This approach can facilitate the dissection of signaling mechanisms or identify disease-specific proteins.

Expression profiling by two-dimensional electrophoresis. Currently, the majority of protein expression profiling studies are performed by 2-DE. Several diseases have been studied, including heart disease (44) and cancer (30). Cancer cells are good candidates for proteomics studies because they can be compared to their nontransformed counterparts. Analysis of differentially expressed proteins in normal versus cancer cells can (i) identify novel tumor cell biomarkers that can be used for diagnosis, (ii) provide clues to mechanisms of cancer development, and (iii) identify novel targets for therapeutic intervention. Protein expression profiling has been used in the study of breast (121), esophageal (121), bladder (30) and prostate (114) cancer. From these studies, tumor-specific proteins were identified and 2-D protein expression databases were generated. Many of these 2-D protein databases are now available on the World Wide Web (15).

Isotope-coded affinity tags. Recently, a novel method for protein expression profiling was introduced that does not depend on the separation of proteins by 2-DE. This method is known as isotope-coded affinity tags (ICAT) and relies on the labeling of protein samples from two different sources with two chemically identical reagents that differ only in mass as a result of isotope composition (66). Differential labeling of samples by mass allows the relative amount of protein between two samples to be quantitated in the mass spectrometer. An example of the methodology of ICAT is shown in Fig. 12. Cell extract from two different samples is reacted with one of two forms of the ICAT reagent, an isotopically light form in which the linker contains eight hydrogens or a heavy form in which the linker contains eight deuterium atoms. The ICAT reagent reacts with cysteine residues in proteins via a thiol-reactive group and contains a biotin moiety to facilitate purification (Fig. 12). Peptides are recovered on the basis of the biotin tag by avidin affinity chromatography and are then analyzed by MS. The difference in peak heights between heavy and light peptide ions directly correlates with the difference in protein abundance in the cells. Thus, if a protein is present at a threefold higher level in one sample, this will be reflected in a threefold difference in peak heights. Following quantitation of the peptides, they can be fragmented by MS/MS and the amino acid sequence can be obtained. Thus, using this approach, proteins can be identified and their expression levels can be compared in the same analysis.

View larger version (26K): [in this window] [in a new window]   FIG. 12. The ICAT method for measuring differential protein expression. (A) Structure of the ICAT reagent. ICAT consists of a biotin affinity group, a linker region that can incorporate heavy (deuterium) or light (hydrogen) atoms, and a thiol-reactive end group for linkage to cysteines. (B) ICAT strategy. Proteins are harvested from two different cell states and labeled on cysteine residues with either the light or heavy form of the ICAT reagent. Following labeling, the two protein samples are mixed and digested with a protease such as trypsin. Peptides labeled with the ICAT reagent can be purified by virtue of the biotin tag by using avidin chromatography. Following purification, ICAT-labeled peptides can be analyzed by MS to quantitate the peak ratios and proteins can be identified by sequencing the peptides with MS/MS.

 
The single biggest advantage of this method is the elimination of the 2-D gel for protein quantitation. As a result, an increased amount of sample can be used to enrich for low-abundance proteins. Alternatively, the cell lysate can be fractionated prior to reaction with the ICAT reagent. This can allow the enrichment of low-abundance proteins before the analysis begins. The main disadvantages are that currently this method works only for proteins containing cysteine, even though this includes the majority of proteins (68). In addition, peptides must contain appropriately spaced protease cleavage sites flanking the cysteine residues. Finally, the ICAT label is large (500 kDa) and remains with each peptide throughout the analysis. This can make database searching more difficult, especially for small peptides with limited sequence (4, 65). Sensitivity may also be of concern since tagged peptides derived from low-copy proteins are likely to be poorly recovered during the affinity step as a result of nonspecific interactions with avidin-Sepharose. Studies have been performed to optimize the labeling of proteins with the ICAT reagent (151).

Protein arrays. Protein arrays are undergoing rapid development for the detection of protein-protein interactions and protein expression profiling (17, 98, 180, 181). Recently, protein microarrays were created using ordinary laboratory equipment (98). Proteins were immobilized by being covalently attached to glass microscope slides, and the protein microarrays were shown to be capable of interacting with other proteins, small molecules, and enzyme substrates (98). In another report, 5,800 yeast proteins were expressed and printed onto microscope slides. These protein microarrays were used to identify novel calmodulin- and phospholipid-interacting proteins (180). These reports indicate that protein arrays hold great promise for the global analysis of protein-protein and protein-ligand interactions. Undoubtedly, these arrays will improve as the technology for their creation is developed and refined.

上一页  [1] [2] [3] [4] [5] [6] [7] [8] 下一页