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Mapping Alzheimer's Molecular Pathologies in Large-Scale Connectomics Data: A Publicly Accessible Correlative
Biorxiv : the Preprint Server for Biology
|November 14, 2023
Summary
This study introduces a volumetric-correlated-light-and-electron microscopy (vCLEM) method to map Alzheimer's disease (AD) pathology in neuronal networks. The research reveals new insights into amyloid-β and hyperphosphorylated-Tau localization and their impact on synapses.
Area of Science:
- Neuroscience
- Cell Biology
- Biochemistry
Background:
- Alzheimer's disease (AD) is characterized by amyloid-β (Aβ) and hyperphosphorylated-Tau (pTau) pathologies.
- Connectomics, using volume-electron-microscopy, maps neuronal networks to understand circuit function and dysfunction.
- Understanding the interplay between AD pathologies and neural circuits is crucial for developing effective treatments.
Purpose of the Study:
- To develop and present a volumetric-correlated-light-and-electron microscopy (vCLEM) protocol for localizing Aβ and pTau within large-scale connectomics datasets.
- To create a publicly accessible vCLEM dataset from the hippocampus of a 3xTg AD mouse model.
- To investigate the ultrastructural context of Aβ and pTau in relation to neurons, glia, and synapses.
Main Methods:
- Utilized fluorescent nanobodies for Aβ and pTau localization.
- Applied vCLEM to a large-scale connectomics dataset from the 3xTg AD mouse model hippocampus.
- Segmented neurons, glia, and synapses within the ultrastructural context.
Main Results:
- Generated a publicly accessible vCLEM dataset with localized Aβ and pTau at the ultrastructural level.
- Identified novel localizations of pTau, including spine-like protrusions at the axon initial segment.
- Observed alterations in synapse number and size in proximity to Aβ plaques.
Conclusions:
- The vCLEM approach effectively integrates molecular pathology with large-scale connectomics.
- This method facilitates the discovery of molecular and structural changes in neurodegenerative diseases like AD.
- The generated dataset serves as a valuable resource for advancing connectomics research in neurodegenerative diseases.
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