Semi-Quantitative Determination of Dopaminergic Neuron Density in the Substantia Nigra of Rodent Models using Automated Image Analysis

Darren M. O'Hara; Minesh Kapadia; Susan Ping; Suneil K. Kalia; Lorraine V. Kalia

doi:10.3791/62062

Détermination semi-quantitative de la densité des neurones dopaminergiques dans la Substantia Nig...

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JoVE Journal Neuroscience

Semi-Quantitative Determination of Dopaminergic Neuron Density in the Substantia Nigra of Rodent Models using Automated Image Analysis

Détermination semi-quantitative de la densité des neurones dopaminergiques dans la Substantia Nigra des modèles de rongeurs à l’aide de l’analyse automatisée d’images

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06:09 min

February 2, 2021

DOI: 10.3791/62062-v

Darren M. O'Hara^1,2, Minesh Kapadia^1,2, Susan Ping^1,2, Suneil K. Kalia^1,2,3, Lorraine V. Kalia^1,2,4,5,6

¹Krembil Research Institute, Toronto Western Hospital,University Health Network, ²Department of Laboratory Medicine and Pathobiology,University of Toronto, ³Department of Surgery, Division of Neurosurgery,University of Toronto, ⁴Department of Medicine, Division of Neurology,University of Toronto, ⁵Department of Medicine, Division of Neurology, Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital,University Health Network, ⁶Tanz Centre for Research in Neurodegenerative Diseases,University of Toronto

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Overview

This study presents an automated method for semi-quantitative determination of dopaminergic neuron numbers in the rat substantia nigra pars compacta. The protocol significantly reduces the workload and enhances accuracy when estimating neuron counts, which is crucial in Parkinson's disease research.

Key Study Components

Area of Science

Neuroscience
Psychiatry
Cell Biology

Background

Estimation of dopaminergic neuron numbers is vital for Parkinson's disease research.
Traditional methods can be time-consuming and less accurate.
Automated methods can provide time efficiency and cost advantages.
Quantitative changes in neuron numbers can assess therapeutic effects.

Purpose of Study

To present a method for efficient and accurate detection of dopaminergic neuron numbers.
To enable researchers to analyze changes in neuron counts due to various interventions.
To simplify the imaging and data analysis process for dopaminergic neurons.

Methods Used

Automated imaging method using confocal microscopy.
Focus on the substantia nigra pars compacta in a rat model.
Protocol involves capturing IHC images at 10X magnification with specific imaging settings.
Real-time tuning and analysis of neuronal images via automated software.
Included data analysis for changes in neuron density post-intervention.

Main Results

This method showed significant reductions in TH positive neuron density following AAV injections expressing mutant A53T alpha-synuclein.
Results indicated a decrease in dopaminergic neuron counts compared to control groups.
Utilized unbiased stereology to validate findings.
Enables detection of morphological changes in response to therapeutic interventions.

Conclusions

The study validates an efficient method for quantifying dopaminergic neurons.
This technique enhances understanding of neuronal loss in Parkinson's disease models.
Methods presented can facilitate exploration of therapeutic impacts on neuron density.

Frequently Asked Questions

What are the advantages of this imaging method?

This method allows for significant reductions in workload and enhances the accuracy of dopaminergic neuron counting in research.

How is the biological model implemented?

The biological model involves rat subjects with induced dopaminergic neuron loss, specifically focusing on the substantia nigra pars compacta.

What types of data are obtained with this method?

The method provides quantitative data on neuron density and allows for analysis of neuronal response to therapeutic interventions.

How can this method be adapted for other brain regions?

The automated imaging method can be modified to accurately count neurons in various brain regions while maintaining efficiency.

What are key considerations when using this technique?

Attention must be paid to software training and parameter adjustments to ensure accurate cell identification during analysis.

What is the significance of the AAV-induced changes?

AAV injections expressing mutant alpha-synuclein resulted in measurable and significant reductions in dopaminergic neuron density, highlighting the model's relevance for studying neurodegeneration.

Ici nous présentons une méthode automatisée pour la détermination semi-quantitative du nombre dopaminergique de neurone dans le substantia nigra compacta de substantia de rat.

L’estimation du nombre de neurones dopaminergiques dans le nigra de substantia est une mesure de résultats clé dans la recherche sur la maladie de Parkinson. Ce protocole raccourcit considérablement la charge de travail requise pour estimer le nombre de neurones. Cette méthode fournit un processus efficace dans le temps et précis pour détecter les changements dans le nombre de neurones dopaminergiques et convient pour déterminer l’effet des interventions sur la survie cellulaire.

Cette méthode pourrait être facilement adaptée pour fournir des comptages précis de neurones dans différentes régions du cerveau tout en maintenant les avantages de coût et de temps par rapport aux méthodes thétéologiques traditionnelles. Pour capturer des images IHC, utilisez le logiciel couplé à un microscope confocal à un grossissement 10X. Ouvrez le trou de la goupille à 1,5 unité de surface pour capturer un plan large totalisant 1,5 micromètre et mettre l’accent sur le côté injecté du cerveau.

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