An Automated Analysis Pipeline for Microglia Morphology in Nikon NIS-Elements.

Area of Science:

• Neuroscience
• Cell Biology
• Computational Biology

Background:

• Microglial cell morphology is crucial for determining activation states and indicating pathologies.
• Automated quantification of microglia in mouse brains (300,000-500,000 cells) offers efficiency over manual methods.
• Existing automated tools lack the modularity and comprehensive analysis required for microglial morphology.

Purpose of the Study:

• To develop and present a customizable, automated analysis pipeline for quantifying microglial cell morphology.
• To enable efficient and less biased assessment of microglial activation states in brain sections.
• To provide a modular pipeline adaptable for other ramified cell types, such as neurons.

Main Methods:

• An annotated analysis pipeline was developed using Nikon NIS-Elements software.
• The pipeline incorporates pre-processing, thresholding, skeletonization, puncta detection, Sholl analysis, and branch classification.
• Batch analysis of image files, including entire microscope slides, is enabled after threshold validation.

Main Results:

• The pipeline automates the quantification of microglia morphology in stained brain sections.
• It generates detailed measurement tables, significantly increasing data output per animal.
• Analysis is rapid and hands-off post-segmentation, minimizing human bias.

Conclusions:

• The developed pipeline offers a fast, modular, and customizable solution for automated microglial morphology analysis.
• It provides a valuable tool for researchers studying neuroinflammation and related pathologies.
• This approach maximizes data generation and reduces experimental time, allowing more focus on research.