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MSRC Proteomics Lab

2D-DIGE

2-D Difference Gel Electrophoresis and Mass Spectrometry (DIGE/MS)

Difference Gel Electrophoresis (DIGE) technology enables quantification with statistical confidence for 2D gel experiments, where thousands of proteins are resolved by charge (using isoelectric focusing) and apparent molecular mass (using SDS-PAGE). DIGE analyses are typically used for differential-display proteomics on a global scale, sometimes testing a specific hypothesis, but often used to generate new hypotheses.

In some cases, it can be used to analyze relative stochiometry and/or post-translational modifications (that resolve into differentially-charged isoforms) of proteins in defined complexes (e.g., immunopurified complexes).

Protein samples are differentially labeled using three cyanine fluorescent dyes (Cy2, Cy3 and Cy5; Amersham Biosciences) prior to gel electrophoresis. Groups of labeled samples are then resolved together on the same gel and imaged separately using mutually-exclusive excitation/emission spectra, allowing for direct quantitative measurements without distortion from gel-to-gel variation.

In most cases, a pooled-sample internal standard is present on each gel, allowing for quantification of multiple (and repetitive) samples across multiple DIGE gels with statistical confidence (Student's t-test, ANOVA). The pooled-sample internal standard represents every protein present across all samples in an experiment. Each protein in the experiment therefore has an unique signal in the internal standard, which is used for direct quantitative comparisons within each gel, and also to match patterns and normalize quantitative abundance values for each protein between gels.

After proteins of interest have been flagged using DIGE, mass spectrometry and database interrogation are used for protein identification. Matrix-assisted laser desorption/ionization, time-of-flight mass spectrometry (MALDI-TOF MS) and data-dependent TOF/TOF tandem MS are used to acquire peptide ion masses (peptide mass mapping/fingerprinting) and individual peptide ion fragmentation patterns to provide candidate protein matches with statistical confidence from selected databases.

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