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An Image Processing Application for Quantification of Protein Aggregates in Caenorhabditis Elegans

  • Andreia Teixeira-Castro
  • Nuno Dias
  • Pedro Rodrigues
  • João Filipe Oliveira
  • Nuno F. Rodrigues
  • Patrícia Maciel
  • João L. Vilaça
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 93)

Abstract

Protein aggregation became a widely accepted marker of many polyQ disorders, including Machado-Joseph disease (MJD), and is often used as readout for disease progression and development of therapeutic strategies. The lack of good platforms to rapidly quantify protein aggregates in a wide range of disease animal models prompted us to generate a novel image processing application that automatically identifies and quantifies the aggregates in a standardized and operator-independent manner. We propose here a novel image processing tool to quantify the protein aggregates in a Caenorhabditis elegans (C. elegans) model of MJD. Confocal microscopy images were obtained from animals of different genetic conditions. The image processing application was developed using MeVisLab as a platform to process, analyse and visualize the images obtained from those animals. All segmentation algorithms were based on intensity pixel levels.The quantification of area or numbers of aggregates per total body area, as well as the number of aggregates per animal were shown to be reliable and reproducible measures of protein aggregation in C. elegans. The results obtained were consistent with the levels of aggregation observed in the images. In conclusion, this novel imaging processing application allows the non-biased, reliable and high throughput quantification of protein aggregates in a C. elegans model of MJD, which may contribute to a significant improvement on the prognosis of treatment effectiveness for this group of disorders.

Keywords

C. elegans image processing quantification of aggregates 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Andreia Teixeira-Castro
    • 1
  • Nuno Dias
    • 1
    • 2
  • Pedro Rodrigues
    • 1
  • João Filipe Oliveira
    • 1
  • Nuno F. Rodrigues
    • 2
    • 3
  • Patrícia Maciel
    • 1
  • João L. Vilaça
    • 1
    • 2
  1. 1.Life and Health Sciences Research InstituteUniversity of MinhoBragaPortugal
  2. 2.DIGARCPolytechnic Institute of Cávado and AveBarcelosPortugal
  3. 3.DI-CCTCUniversity of MinhoBragaPortugal

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