Attempts to correlate protein abundance with mRNA expression levels have had variable success. We review the results of these comparisons, focusing on yeast. In the process, we survey experimental techniques for determining protein abundance, principally two-dimensional gel electrophoresis and mass-spectrometry. We also merge many of the available yeast protein-abundance datasets, using the resulting larger 'meta-dataset' to find correlations between protein and mRNA expression, both globally and within smaller categories.

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Comparing protein abundance and mRNA expression levels on a genomic scale

Extraction and Solubilization of Proteins for Proteomic Studies Richard M. Leimgruber Preparation of Bacterial Samples for 2-D PAGE Brian Berg Vandahl, Gunna Christiansen, and Svend Birkelund Preparation of Yeast Samples for 2-D PAGE Joakim Norbeck Preparation of Mammalian Tissue Samples for Two-Dimensional Electrophoresis Frank A. Witzmann Differential Detergent Fractionation of Eukaryotic Cells Melinda L. Ramsby and Gregory S. Makowski Serum or Plasma Sample Preparation for Two-Dimensional Gel Electrophoresis Anthony G. Sullivan, Stephen Russell, Henry Brzeski, Richard I. Somiari, and Craig D. Shriver Preparation of Plant Protein Samples for 2-D PAGE David W. M. Leung Laser-Assisted Microdissection in Proteomic Analyses Darrell L. Ellsworth, Stephen Russell, Brenda Deyarmin, Anthony G. Sullivan, Henry Brzeski, Richard I. Somiari, and Craig D. Shriver Purification of Cellular and Organelle Populations by Fluorescence-Activated Cell Sorting for Proteome Analysis William L. Godfrey, Colette J. Rudd, Sujata Iyer, and Diether Recktenwald Purification of Nucleoli From Lymphoma Cells and Solubilization of Nucleolar Proteins for 2-DE Separation Regis Dieckmann, Yohann Coute, Denis Hochstrasser, Jean-Jacques Diaz, and Jean-Charles Sanchez Prefractionation of Complex Protein Mixture for 2-D PAGE Using Reversed-Phase Liquid Chromatography Volker Badock and Albrecht Otto Fractionation of Complex Proteomes by Microscale Solution Isoelectrofocusing Using ZOOM(TM) IEF Fractionators to Improve Protein Profiling Xun Zuo, Ki-Boom Lee, and David W. Speicher Large-Format 2-D Polyacrylamide Gel Electrophoresis Henry Brzeski, Stephen Russell, Anthony G. Sullivan, Richard I. Somiari, and Craig D. Shiver Analysis of Membrane Proteins by Two-Dimensional Gels MichaelFountoulakis 2-D PAGE of High-Molecular-Mass Proteins Masamichi Oh-Ishi and Tadakazu Maeda Using Ultra-Zoom Gels for High-Resolution Two-Dimensional Polyacrylamide Gel Electrophoresis Sjouke Hoving, Hans Voshol, and Jan van Oostrum NEpHGE and pI Strip Proteomic 2-D Gel Electrophoretic Mapping of Lipid-Rich Membranes Steven E. Pfeiffer, Yoshihide Yamaguchi, Cecilia B. Marta, Rashmi Bansal, and Christopher M. Taylor Silver Staining of 2-D Gels Julia Poland, Thierry Rabilloud, and Pranav Sinha Zn2+ Reverse Staining Technique Carlos Fernandez-Patron Multiplexed Proteomics Technology for the Fluorescence Detection of Glycoprotein Levels and Protein Expression Levels Using Pro-Q(R) Emerald and SYPRO(R) Ruby Dyes Birte Schulenberg and Wayne F. Patton Multiplexed Proteomics Technology for the Fluorescence Detection of Phosphorylation and Protein Expression Levels Using Pro-Q(R) Diamond and SYPRO(R) Ruby Dyes Birte Schulenberg, Terrie Goodman, Thomas H. Steinberg, and Wayne F. Patton Sensitive Quantitative Fluorescence Detection of Proteins in Gels Using SYPRO(R) Ruby Protein Gel Stain Birte Schulenberg, Nancy Ahnert, and Wayne F. Patton Rapid, Sensitive Detection of Proteins in Minigels With Fluorescent Dyes: Coomassie Fluor Orange, SYPRO(R) Orange, SYPRO Red, and SYPRO Tangerine Protein Gel Stains Thomas H. Steinberg, Courtenay R. Hart, and Wayne F. Patton Differential In-Gel Electrophoresis in a High-Throughput Environment Richard I. Somiari, Stephen Russell, Stella B. Somiari, Anthony G. Sullivan, Darrell L. Ellsworth, Henry Brzeski, and Craig D. Shriver Statistical Analysis of 2-D Gel Patterns Francoise Seillier-Moiseiwitsch 2-DE Databases on the World Wide Web Christine Hoogland, Khaled Mostaguir, and Ron D. Appel Computer Analysis of 2-D Images Patricia M. Palagi,

The proteomics protocols handbook

Here, we propose a new model for understanding the Warburg effect in tumor metabolism. Our hypothesis is that epithelial cancer cells induce the Warburg effect (aerobic glycolysis) in neighboring stromal fibroblasts. These cancer-associated fibroblasts, then undergo myo-fibroblastic differentiation, and secrete lactate and pyruvate (energy metabolites resulting from aerobic glycolysis). Epithelial cancer cells could then take up these energy-rich metabolites and use them in the mitochondrial TCA cycle, thereby promoting efficient energy production (ATP generation via oxidative phosphorylation), resulting in a higher proliferative capacity. In this alternative model of tumorigenesis, the epithelial cancer cells instruct the normal stroma to transform into a wound-healing stroma, providing the necessary energy-rich micro-environment for facilitating tumor growth and angiogenesis. In essence, the fibroblastic tumor stroma would directly feed the epithelial cancer cells, in a type of host-parasite relationship. We have termed this new idea the "Reverse Warburg Effect." In this scenario, the epithelial tumor cells "corrupt" the normal stroma, turning it into a factory for the production of energy-rich metabolites. This alternative model is still consistent with Warburg's original observation that tumors show a metabolic shift towards aerobic glycolysis. In support of this idea, unbiased proteomic analysis and transcriptional profiling of a new model of cancer-associated fibroblasts (caveolin-1 (Cav-1) deficient stromal cells), shows the upregulation of both (1) myo-fibroblast markers and (2) glycolytic enzymes, under normoxic conditions. We validated the expression of these proteins in the fibroblastic stroma of human breast cancer tissues that lack stromal Cav-1. Importantly, a loss of stromal Cav-1 in human breast cancers is associated with tumor recurrence, metastasis, and poor clinical outcome. Thus, an absence of stromal Cav-1 may be a biomarker for the "Reverse Warburg Effect," explaining its powerful predictive value.

The reverse Warburg effect: Aerobic glycolysis in cancer associated fibroblasts and the tumor stroma

Fluorescent labeling of biomolecules with organic probes.

Integrated Genomic and Proteomic Analyses of Gene Expression in Mammalian Cells

Fluorescence two-dimensional differential gel electrophoresis (2-D DIGE*) is a new development in protein detection for two-dimensional gels. Using mouse liver homogenates (control and paracetamol (N-acetyl-p-aminophenol, APAP)-treated), we have determined the quantitative variation in the 2-D DIGE process and established statistically valid thresholds for assigning quantitative changes between samples. Thresholds were dependent on normalised spot volume, ranged from approximately 1.2 fold for large volume spots to 3.5 fold for small volume spots and were not markedly affected by the particular cyanine dye combination or by multiple operators carrying out the dye labelling reaction. To minimise the thresholds, substantial user editing was required when using ImageMaster 2D-Elite software. The difference thresholds were applied to the test system and quantitative protein differences were determined using replicate gels of pool samples and single gels from multiple individual animals (control vs treated in each gel). Throughout, the differences revealed with a particular cyanine dye combination were mirrored almost without exception when the dye combination was reversed. Both pool and individual sample analyses provided unique data to the study. The inter-animal response variability in inbred mice was approximately nine times that contributed by the 2-D DIGE process. A number of the most frequently observed protein changes resulting from APAP-treatment were identified by mass spectrometry. Several of these can be rationalised based on available data on the mechanism of APAP hepatotoxicity but others cannot, indicating that proteomics can provide further insights into the biochemical basis of APAP toxicity.

Validation and development of fluorescence two‐dimensional differential gel electrophoresis proteomics technology

Two-dimensional (2D) gel electrophoresis is a powerful technique enabling simultaneous visualization of relatively large portions of the proteome. However, the well documented issues of variation and lack of sensitivity and quantitative capabilities of existing labeling reagents, has limited the use of this technique as a quantitative tool. Two-dimensional difference gel electrophoresis (2D DIGE) builds on this technique by adding a highly accurate quantitative dimension. 2D DIGE enables multiple protein extracts to be separated on the same 2D gel. This is made possible by labeling of each extract using spectrally resolvable, size and charge-matched fluorescent dyes known as CyDye DIGE fluors. 2D DIGE involves use of a reference sample, known as an internal standard, which comprises equal amounts of all biological samples in the experiment. Including the internal standard on each gel in the experiment with the individual biological samples means that the abundance of each protein spot on a gel can be measured relative (i.e. as a ratio) to its corresponding spot in the internal standard present on the same gel. Ettan DIGE is the system of technologies that has been optimized to fully benefit from the advantages provided by 2D DIGE.

The development of the DIGE system: 2D fluorescence difference gel analysis technology.

Comparative proteomic methods are rapidly being applied to many different biological systems including complex tissues. One pitfall of these methods is that in some cases, such as oncology and neuroscience, tissue complexity requires isolation of specific cell types and sample is limited. Laser microdissection (LMD) is commonly used for obtaining such samples for proteomic studies. We have combined LMD with sensitive thiol-reactive saturation dye labelling of protein samples and 2-D DIGE to identify protein changes in a test system, the isolated CA1 pyramidal neurone layer of a transgenic (Tg) rat carrying a human amyloid precursor protein transgene. Saturation dye labelling proved to be extremely sensitive with a spot map of over 5,000 proteins being readily produced from 5 mug total protein, with over 100 proteins being significantly altered at p < 0.0005. Of the proteins identified, all showed coherent changes associated with transgene expression. It was, however, difficult to identify significantly different proteins using PMF and MALDI-TOF on gels containing less than 500 mug total protein. The use of saturation dye labelling of limiting samples will therefore require the use of highly sensitive MS techniques to identify the significantly altered proteins isolated using methods such as LMD.

Comparative proteomic analysis using samples obtained with laser microdissection and saturation dye labelling.

Two-dimensional electrophoresis (2-DE) is the leading tool in proteomics research today, capable of visualising many components of complex proteomes in a single gel (Gorg et al. 2000). This tool separates proteins by pI (isoelectric point) and molecular weight producing a pattern of spots on an SDS-PAGE (polyacrylamide gel electrophoresis) gel, which can be visualised via a range of staining and labelling systems. Protein spot patterns can be compared between different samples of interest, e.g. normal versus diseased, to determine which protein spots demonstrate changes in abundance. The most common 2-DE work system incorporates the analysis/identification of differentially expressed proteins of interest using Mass Spectrometry. Figure 15.1 illustrates a 2-DE workflow from sample preparation to Mass Spectrometry analysis.

Edward Hawkins

Papers

Validation and development of fluorescence two‐dimensional differential gel electrophoresis proteomics technology

The development of the DIGE system: 2D fluorescence difference gel analysis technology.

Comparative proteomic analysis using samples obtained with laser microdissection and saturation dye labelling.

The Quantitative Advantages of an Internal Standard in Multiplexing 2D Electrophoresis