DIGE Analysis of Animal Tissues

Methods Mol Biol. 2018:1664:137-152. doi: 10.1007/978-1-4939-7268-5_12.

Abstract

Two-dimensional difference gel electrophoresis (2D-DIGE) is an acrylamide gel electrophoresis-based technique for protein separation and quantification in complex mixtures. The technique addresses some of the drawbacks of conventional 2D polyacrylamide gel electrophoresis (2D-PAGE), offering improved sensitivity, more limited experimental variation and accurate within-gel matching. DIGE is based on direct labeling of proteins with isobaric fluorescent dyes (known as CyDyes: Cy2, Cy3, and Cy5) prior to isoelectric focusing (IEF). Here, up to two samples and a reference pool (internal standard) can be mixed and loaded onto IEF for first dimension prior to SDS-PAGE separation in the second dimension. After the electrophoretic run, the gel is imaged at the specific excitation wavelength for each dye, in sequence, and gel scans are recorded separately. For each individual protein spot, intensities recorded at the different wavelengths are integrated and the ratio between volumes normalized to that of the internal standard. This provides an immediate appreciation of protein amount variations under the different conditions tested. In addition, proteins of interest can still be excised and identified with conventional mass spectrometry techniques and further analyzed by other biochemical methods. In this chapter, we describe the application of this methodology to separation and quantitation of proteins mixtures from porcine muscle exudate, collected following centrifugation of muscle specimens (centrifugal drip) for the characterization of quality parameters of importance in the meat industry.

Keywords: 2D-DIGE; Centrifugal drip; CyDye DIGE fluor; Image analysis; Internal standard; Isoelectric focusing; Machine learning algorithm; Mass spectrometry; Porcine muscle exudate; SDS-PAGE.

MeSH terms

  • Algorithms
  • Animals
  • Biomarkers
  • Electrophoresis, Polyacrylamide Gel
  • Exudates and Transudates / metabolism
  • Image Processing, Computer-Assisted
  • Isoelectric Focusing
  • Machine Learning
  • Mass Spectrometry
  • Muscles / metabolism
  • Proteomics* / methods
  • Staining and Labeling
  • Swine
  • Two-Dimensional Difference Gel Electrophoresis* / methods

Substances

  • Biomarkers