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Updated: May 2, 2026

Correlative Light and Electron Microscopy to Study Microglial Interactions with β-Amyloid Plaques
Published on: June 1, 2016
A Step-By-Step Protocol for Correlative Light and Electron Microscopy Imaging of Proteinaceous Deposits in Cultured
Peizhou Jiang1, Dennis W Dickson1
1Neuropathology Laboratory, Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA.
Abstract:
An improved correlative light and electron microscopy (CLEM) method has recently been introduced and successfully employed to identify and analyze protein inclusions in cultured cells as well as pathological proteinaceous deposits in postmortem human brain tissues from individuals with diverse neurodegenerative diseases. This method significantly enhances antigen preservation and target registration by replacing conventional dehydration and embedding reagents. It achieves an optimal balance of sensitivity, accuracy, efficiency, and cost-effectiveness compared to other current CLEM approaches. However, due to space constraints, only a brief overview of this method was provided in the initial publication. To ensure reproducibility and facilitate widespread adoption, the author now presents a detailed, step-by-step protocol of this optimized CLEM technique. By enhancing usability and accessibility, this protocol aims to promote broader application of CLEM in neurodegenerative disease research. Key features • This protocol incorporates optimized sample processing and innovative fiducial marking techniques that enhance antigen preservation and improve target registration, respectively. • By utilizing serial ultrathin sections for CLEM, this protocol significantly increases correlation accuracy. • A novel "sandwich method" is introduced, which enables simultaneous detection of multiple proteinopathies through immunofluorescence staining or precise localization of pathological targets using immunogold labeling. • Overall, this protocol offers an effective balance of sensitivity, accuracy, efficiency, and cost-effectiveness compared to existing CLEM methodologies.
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