Quantitative cell biology of neurodegeneration in drosophila through unbiased analysis of fluorescently tagged proteins using imageJ

Jennifer M. Brazill, Yi Zhu, Chong Li, Rong G Zhai

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

With the rising prevalence of neurodegenerative diseases, it is increasingly important to understand the underlying pathophysiology that leads to neuronal dysfunction and loss. Fluorescence-based imaging tools and technologies enable unprecedented analysis of subcellular neurobiological processes, yet there is still a need for unbiased, reproducible, and accessible approaches for extracting quantifiable data from imaging studies. We have developed a simple and adaptable workflow to extract quantitative data from fluorescence-based imaging studies using Drosophila models of neurodegeneration. Specifically, we describe an easy-to-follow, semi-automated approach using Fiji/ImageJ to analyze two cellular processes: first, we quantify protein aggregate content and profile in the Drosophila optic lobe using fluorescent-tagged mutant huntingtin proteins; and second, we assess autophagy-lysosome flux in the Drosophila visual system with ratiometric-based quantification of a tandem fluorescent reporter of autophagy. Importantly, the protocol outlined here includes a semi-automated segmentation step to ensure all fluorescent structures are analyzed to minimize selection bias and to increase resolution of subtle comparisons. This approach can be extended for the analysis of other cell biological structures and processes implicated in neurodegeneration, such as proteinaceous puncta (stress granules and synaptic complexes), as well as membrane-bound compartments (mitochondria and membrane trafficking vesicles). This method provides a standardized, yet adaptable reference point for image analysis and quantification, and could facilitate reliability and reproducibility across the field, and ultimately enhance mechanistic understanding of neurodegeneration.

Original languageEnglish (US)
Article numbere58041
JournalJournal of Visualized Experiments
Volume2018
Issue number138
DOIs
StatePublished - Aug 3 2018

Fingerprint

Cytology
Drosophila
Cell Biology
Optical Imaging
Autophagy
Proteins
Imaging techniques
Fluorescence
Fiji
Neurodegenerative diseases
Membranes
Biological Phenomena
Mitochondria
Workflow
Selection Bias
Mutant Proteins
Lysosomes
Neurodegenerative Diseases
Image analysis
Optics

Keywords

  • Aggregate
  • Autophagy
  • Brain
  • Drosophila
  • ImageJ
  • Issue 138
  • Neurodegeneration
  • Neuroscience
  • Ratiometric
  • Segmentation

ASJC Scopus subject areas

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

Cite this

Quantitative cell biology of neurodegeneration in drosophila through unbiased analysis of fluorescently tagged proteins using imageJ. / Brazill, Jennifer M.; Zhu, Yi; Li, Chong; Zhai, Rong G.

In: Journal of Visualized Experiments, Vol. 2018, No. 138, e58041, 03.08.2018.

Research output: Contribution to journalArticle

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