Proteome Features

Although a proteome is defined as the total complanent of a genome or the set of proteins encoded by a genome, the strict definition which describes the proteome as the protein readout of the genome is inadequate because  

Biomacromolecules, by C. Stan Tsai Copyright 2007 John Wiley Sons, Inc. 

The proteome, unlike the genome, is a dynamic entity because it is the product of both gene expression and posttranslational alternations, and varies with different cell types, different stages of development and is greatly affected by the environment. Therefore the first step in the proteomic research lies in optimizing the methods used to analyze and identify the individual proteins. 

Polyacrylamide gel electrophoresis (PAGE) and high performance liquid chromatography (HPLC), which separate, detect, and quantify proteins present in a given system in a manner that also measures the protein s molecular weight, isoelectric point (p7) and other properties, are useful techniques in proteomic research. 

A number of useful computational tools have been developed for predicting the identity of unknown proteins based on the physical and chemical properties of amino acids and vice versa. Many of these tools are available through the Expert Protein Analysis System (ExPASy) at http //www.expasy.org (Gasteiger et al, 2003) and other servers. 

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Fig. 4. Application of bioinformatics tools to 2D-DIGE data analysis. Proteome data consisting of the normalized spot intensity values are exported from the image analysis software and their correlation with clinicopathological data examined. Using informatics tools including clustering algorithms and machine-learning methods, a novel cancer classification based on proteome data is established, and key proteomic features and proteins corresponding to biomarker candidates are identified.

Conrads TP, Fusaro VA, Ross S, et al. High-resolution serum proteomic features for ovarian cancer detection. Endocr Relat Cancer 2004 11(2) 163 178. 

Amann, J.M., Lee, ).-W., Roder, H., et d. (2010) Genetic and proteomic features associated with survival after treatment with erlotinib in first-Une therapy of non-small cell lung cancer in Eastern Cooperative Oncology Group 3503. 

Fig. 4. Complete predicted Proteomes Tool for the NIAID Biodefense Proteomics Research Program (http //pir.geoigetown.edu/pirwww/proteomics/). Tool allows interactive text mining of selected complete proteomes. Features include over 50 fields for Boolean text searches customizable display and export links to master catalog of experimental data from NlAlD Proteomics Research Centers and links to various reports on additional protein information like UniProt, iProClass, BioThesaurus, and PIRSF reports.

Two features of expression profiling make it the most productive approach to study biological systems for the immediate future. First, the present efficiency with which investigators can obtain global and quantitative information with DNA arrays exceeds that of proteomic techniques. Second, RNA expression profiles provide an extremely precise and reproducible signature of the state of the cell that probably reflects albeit indirectly, the functional state of all proteins (Young, 2000, p. 13)-... 

Before we conclude the functions of the elements and the proteome, there is a second general feature of eukaryote cells, much of which evolved from that of the prokaryotes - the types of metal-binding protein. The general supposition is that the number of folds are limited and certainly the number of metal-binding sites for any one metal ion is closely limited (see Section 4.15). We find that there are some general rules for protein-binding centres of metal ions and their geometry, mentioned only in brief in Chapters 5 and 6. 

TOF analyzers are especially compatible with MALDI ion sources and hence are frequently coupled in aMALDI-TOF configuration. Nevertheless, many commercial mass spectrometers combine ESI with TOF with great success. For proteomics applications, the quadrupole TOF (QqTOF) hybrid instruments with their superior mass accuracy, mass range, and mass resolution are of much greater utility than simple TOF instruments.21,22 Moreover, TOF instruments feature high sensitivity because they can generate full scan data without the necessity for scanning that causes ion loss and decreased sensitivity. Linear mode TOF instruments cannot perform tandem mass spectrometry. This problem is addressed by hybrid instruments that incorporate analyzers with mass selective capability (e.g., QqTOF) in front of a TOF instrument. 

Figure 7.5. Simulation results that elucidate how the sensitivity and the selectivity of a proteomics experiment depend on various features (a) The choice of algorithm. The probity algorithm displays better sensitivity and selectivity than an algorithm that ranks strictly based on the number of matches, (b) The search conditions. Increasing the mass window of a search 10 times when searching with data that display small mass errors yields worse sensitivity and selectivitry. (c) The quality of the data. Data with less noise yields better sensitivity and selectivity.

The most prominent field of applications for microchip—MS concerns identification and analysis of large molecules in the field of proteomics according to the reduced separation time compared to conventional approaches such as gel-based methods for protein analysis. High-throughput analyses, with lower contamination and disposability, are other features of microfabricated devices that allow the fast screening of proteomic samples in the clinical field. Applications also include the analysis of low-molecular-weight compounds such as peptides or pharmaceutical samples. 

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