Mass histology to quantify neurodegeneration in drosophila

Elizabeth R. Sunderhaus, Doris Kretzschmar

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

Progressive neurodegenerative diseases like Alzheimer's disease (AD) or Parkinson's disease (PD) are an increasing threat to human health worldwide. Although mammalian models have provided important insights into the underlying mechanisms of pathogenicity, the complexity of mammalian systems together with their high costs are limiting their use. Therefore, the simple but well-established Drosophila model-system provides an alternative for investigating the molecular pathways that are affected in these diseases. Besides behavioral deficits, neurodegenerative diseases are characterized by histological phenotypes such as neuronal death and axonopathy. To quantify neuronal degeneration and to determine how it is affected by genetic and environmental factors, we use a histological approach that is based on measuring the vacuoles in adult fly brains. To minimize the effects of systematic error and to directly compare sections from control and experimental flies in one preparation, we use the 'collar' method for paraffin sections. Neurodegeneration is then assessed by measuring the size and/or number of vacuoles that have developed in the fly brain. This can either be done by focusing on a specific region of interest or by analyzing the entire brain by obtaining serial sections that span the complete head. Therefore, this method allows one to measure not only severe degeneration but also relatively mild phenotypes that are only detectable in a few sections, as occurs during normal aging.

Original languageEnglish (US)
Article numbere54809
JournalJournal of Visualized Experiments
Volume2016
Issue number118
DOIs
StatePublished - Dec 15 2016

Keywords

  • Adult nervous system
  • Degenerative diseases
  • Drosophila
  • Histology
  • Issue 118
  • Neurobiology
  • Neuroscience
  • Paraffin sections
  • Vacuoles

ASJC Scopus subject areas

  • Neuroscience(all)
  • Chemical Engineering(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

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