Brain‐Wide Cellular Resolution Regional Quantification of Microglia and Amyloid in 5xFAD mice. (20th December 2022)

• Record Type: Journal Article
• Authors: Guanzon, Nathaniel; Murry, Alexandria; May, Emily; Wells, Alicia; Gallegos, Yessenia; Redd, Chase; Azevedo, Ricardo; Shamloo, Mehrdad; Gandho, Sunil; Wheeler, Damian G.
• Is Part Of: Alzheimer's & dementia. Volume 18(2022)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-20
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.066431
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Recent advances in optical clearing and light sheet imaging have opened an exciting new avenue for brain‐wide, cellular resolution immunostaining at the forefront of a dimensional shift from 2D to 3D histology. Traditional histological methods have been a mainstay of neuroscience research dating back more than 100 years. Yet, despite great advances in tissue labeling and imaging technology, until very recently imaging more than a few hundred microns into a tissue has required slicing and mounting on slides. When looking for read‐outs of genetic or pharmacological manipulations that affect the entire brain, this traditional focused approach is lacking, forcing researchers to look at specific brain regions of interest. Method: To help solve this issue, we have developed an optimized iDISCO‐based tissue clearing method and with our Mesoscale Imaging System for ZEISS Lightsheet microscopes, we can image cellular‐resolution immunoreactivity across entire intact mouse brains in ∼25 min. Further, our machine learning‐enabled 3TK software identifies individual immunostained cells and objects throughout the brain and aligns them to the Allen Reference Atlas to produce an unbiased, regionalized read‐out of cellular patterns across 100's brain areas. We have applied this technology to quantify microglia and β‐amyloid plaques in the 5xFAD mouse model of Alzheimer's Disease. Result: Using antibodies targeting the microglial protein Iba1, we can identify microglia throughout the entire brain. We have developed two machine learning‐enabled workflows; one counts the microglia and the other measures microglial shape. We have also validated methods for labeling β‐amyloid throughout the brain and have used machine learning to differentially quantify immunoreactivity in plaques vs neuronal cell bodies in the same fluorescence channel. In 5xFAD Tg mice, rather than displaying the ramified morphology seen in WT mice, microglia become condensed and colocalize with β‐amyloid plaques. Our automated methods can identify and count plaques and plaque‐associated microglia (PAM) throughout the brain. Conclusion: These new methods for whole‐brain, next generation 3D immunohistochemistry are ideally suited to pre‐clinical studies for unbiased, complete and anatomically precise mapping of the efficacy of CNS therapeutics affecting amyloid deposition and neuroinflammation. We thank NIMH for Grant R43MH122070.