GliaMorph: a modular image analysis toolkit to quantify Müller glial cell morphology.

Area of Science:

• Neuroscience
• Cell Biology
• Image Analysis

Background:

• Glial cell morphology is vital for neuronal support and function.
• Accurate quantification of complex glial cell shapes is currently lacking.
• Müller glia (MG) exhibit stereotypic shapes related to their maturation and physiological state.

Purpose of the Study:

• To develop and validate an image analysis pipeline, GliaMorph, for quantifying glial cell morphology.
• To characterize Müller glia morphology in developing and diseased retinas.
• To enable in-depth understanding of glial cell shape in various physiological and pathological contexts.

Main Methods:

• GliaMorph pipeline includes image pre-processing, semi-automatic ROI selection, apicobasal texture analysis, glia segmentation, and cell feature quantification.
• Characterization of Müller glia at global image-level, apicobasal texture, and regional alignment.
• Application of GliaMorph to analyze Müller glia development in zebrafish and protein localization changes in a mouse glaucoma model.

Main Results:

• GliaMorph successfully quantified Müller glia development in the zebrafish retina, revealing increased feature elaboration and subcellular rearrangement.
• Analysis in a mouse glaucoma model identified subcellular protein localization changes in Müller glia.
• The toolkit provides a robust method for detailed morphological analysis of glial cells.

Conclusions:

• GliaMorph is a powerful, modular toolkit for accurate and reproducible quantification of glial cell morphology.
• The developed methods allow for detailed insights into Müller glia morphology during development and in disease states.
• GliaMorph facilitates a deeper understanding of glial cell function and its alterations in neurological conditions.