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NuMorph: Tools for cortical cellular phenotyping in tissue-cleared whole-brain images
Oleh Krupa1, Giulia Fragola2, Ellie Hadden-Ford3
1Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC 27514, USA; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
NuMorph is a new computational tool for quantifying all nuclei in cleared mouse brain images. It reveals how gene deletion impacts cell counts and brain structure in neurodegenerative and overgrowth models.
Area of Science:
- Neuroscience
- Computational Biology
- Genetics
Background:
- Tissue-clearing techniques enable whole-brain imaging, but current computational tools struggle with dense cell populations.
- Accurate cell quantification is crucial for understanding brain structure and disease.
Purpose of the Study:
- To introduce NuMorph, a novel computational analysis toolset for quantifying all nuclei and nuclear markers in cleared mouse cortex images.
- To apply NuMorph to mouse models with distinct neurological phenotypes.
Main Methods:
- Development and application of the NuMorph analysis tool.
- Light-sheet microscopy for imaging cleared mouse brain tissue.
- Analysis of Topoisomerase 1 (Top1) and Neurofibromin 1 (Nf1) mouse models.
Main Results:
- NuMorph successfully quantifies all nuclei and nuclear markers in cleared mouse cortex.
- Differential effects of gene deletion on cell-type counts and distribution were identified in Top1 and Nf1 models.
- Observed changes in cell populations correlated with alterations in gross brain morphology.
Conclusions:
- NuMorph provides a valuable tool for high-resolution cellular phenotyping of the mouse brain.
- Whole-brain imaging combined with NuMorph analysis can reveal subtle and severe brain structure phenotypes.
- The tools are broadly applicable for diverse research in neuroscience and neurobiology.
