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2020
- doi: 10.3389/fnmol.2020.00149
- issn: 1662-5099
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info:eu-repo/semantics/altIdentifier/doi/10.3389/fnmol.2020.00149
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info:eu-repo/semantics/altIdentifier/pmid/33132837
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info:eu-repo/semantics/altIdentifier/pissn/1662-5099
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info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_49FE862930E68
info:eu-repo/semantics/openAccess , CC BY 4.0 , https://creativecommons.org/licenses/by/4.0/
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S. Brioschi et al., « Detection of Synaptic Proteins in Microglia by Flow Cytometry. », Serveur académique Lausannois, ID : 10.3389/fnmol.2020.00149
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A growing body of evidence indicates that microglia actively remove synapses in vivo, thereby playing a key role in synaptic refinement and modulation of brain connectivity. This phenomenon was mainly investigated in immunofluorescence staining and confocal microscopy. However, a quantification of synaptic material in microglia using these techniques is extremely time-consuming and labor-intensive. To address this issue, we aimed to quantify synaptic proteins in microglia using flow cytometry. With this approach, we first showed that microglia from the healthy adult mouse brain contain a detectable level of VGLUT1 protein. Next, we found more than two-fold increased VGLUT1 immunoreactivity in microglia from the developing brain (P15) as compared to adult microglia. These data indicate that microglia-mediated synaptic pruning mostly occurs during the brain developmental period. We then quantified the VGLUT1 staining in microglia in two transgenic models characterized by pathological microglia-mediated synaptic pruning. In the 5xFAD mouse model of Alzheimer's disease (AD) microglia exhibited a significant increase in VGLUT1 immunoreactivity before the onset of amyloid pathology. Moreover, conditional deletion of TDP-43 in microglia, which causes a hyper-phagocytic phenotype associated with synaptic loss, also resulted in increased VGLUT1 immunoreactivity within microglia. This work provides a quantitative assessment of synaptic proteins in microglia, under homeostasis, and in mouse models of disease.