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Identification of protein expression changes in milk in experimental bovine mastitis using difference gel electrophoresis

Published: 2024


  • Funmilola Clara Thomas

  • Eyitayo Solomon Ajibola

  • Allan Scott

  • Richardo Tassi

  • Andre Marcos Santana

  • Tom Nathan McNeilly

  • Ruth Zadoks

  • Hayley Haining

  • Richard Burchmore

  • Peter David Eckersall

Is Part of:

Veterinarski Arhiv, 94, 1, pp11-20


In order to identify the extent of protein changes in milk during mastitis as a guide to detecting markers for prompt management of the disease, milk from cows in which clinical mastitis was experimentally induced were subjected to difference gel electrophoresis (DiGE) analysis. Pooled samples from 6 udders (from 6 cows) were analysed at selected time points: 0, 81 and 312 hours post-challenge with Streptococcus uberis mastitis. These corresponded to samples from the pre-infection, peak and resolution phases of the mastitis challenge. After the preliminary sample preparation, concentration and pooling steps, samples were labelled with CyDyes (Cydye 2, 3 and 5), after which isoelectric focusing and gel electrophoresis were carried out respectively. DiGE gels were subsequently scanned and ImageQuant, ImageJ and DeCyder™ 2D (version 7.0) softwares were used to crop, obtain jpeg images and carry out 2-D differential analysis and processing of the images, respectively. Biological variation analysis (BVA) software (GE Healthcare Life Sciences, Buckinghamshire, UK) was also used to analyse the gels and create gel to gel matching of spots (qualitatively and quantitatively) within the three gels produced. Overall, a total of 521 protein spots were identified as significantly differentially expressed (qualitatively or quantitatively) in mastitis milk during the course of the intramammary infection. This demonstrates the large repertoire of protein biomarker candidates available, revealed through this technique. Further studies are required to elucidate the merits and demerits of these changing proteins in order to identify the one most suitable for clinical application in mastitis diagnosis.

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