Arendt 2023 BDNF

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Abstract/Contents

Abstract
Homeostatic synaptic plasticity is a non-Hebbian synaptic mechanism that adjusts synaptic strength to maintain network stability while achieving optimal information processing. Among the molecular mediators shown to regulate this form of plasticity, synaptic signaling through retinoic acid (RA) and its receptor, RARα, has been shown to be critically involved in the homeostatic adjustment of synaptic transmission in both hippocampus and sensory cortices. In this study, we explore the molecular mechanism through which postsynaptic RA and RARα regulates presynaptic neurotransmitter release during prolonged synaptic inactivity at mouse glutamatertic synapses. We show that RARα binds to a subset of dendritically sorted brain-derived neurotrophic factor (Bdnf) mRNA splice isoforms and represses their translation. The RA-mediated translational de-repression of postsynaptic BDNF results in the retrograde activation of presynaptic Tropomyosin receptor kinase B (TrkB) receptors, facilitating presynaptic homeostatic compensation through enhanced presynaptic release. Together, our study illustrates a RA-mediated retrograde synaptic signaling pathway through which postsynaptic protein synthesis during synaptic inactivity drives compensatory changes at the presynaptic site.

Description

Type of resource Dataset
Date created September 1, 2017 - September 1, 2022
Date modified October 20, 2023
Publication date October 19, 2023; December 28, 2022

Creators/Contributors

Author Chen, Lu
Author Arendt, Kristin

Subjects

Subject homeostatic synaptic plasticity
Genre Data
Genre Unedited recording
Genre Data sets
Genre Dataset

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User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
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This work is licensed under a Creative Commons Attribution Non Commercial No Derivatives 4.0 International license (CC BY-NC-ND).

Preferred citation

Preferred citation
Chen, L. and Arendt, K. (2023). Arendt 2023 BDNF. Stanford Digital Repository. Available at https://purl.stanford.edu/zk891by2827. https://doi.org/10.25740/zk891by2827.

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Research from the Lu Chen Lab at Stanford

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