Sex- and experience-dependent regulation of synaptic protein turnover

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Authors: Seok Heo, Shiyu Zhang, Dong‐Gi Mun, Akhilesh Pandey, Alexei M. Bygrave, Richard L. Huganir
Cited by: 2
References: 30

Abstract

Synaptic transmission can be tuned through plasticity mechanisms that regulate synaptic strength, structure, and number. In vivo measurements demonstrate remarkable spine dynamics, with subsets of synapses persisting for months. This correlates with the longevity of certain memories, which can persist for an organism's lifetime. The molecular basis supporting the long-term stability of specific synapses and the long-term durability of memories remains unknown. At the protein level, most proteins persist for a relatively short amount of time before they are degraded and replaced with new molecules. However, recent work has identified a population of proteins, including those present at the synapse, that are exceptionally long-lived. It has been speculated that long-lived proteins (LLPs) could contribute to long-term synapse stability, function, and memory. Here, we used stable isotope labeling in mammals to first identify LLPs in the post synaptic density (PSD) of the hippocampus and subsequently determine if protein turnover rates varied by sex or following learning. We identified synaptic LLPs and found that both sex and experience can regulate synaptic protein turnover rates. We identified sex-dependent changes in protein turnover rates in autism spectrum disorder risk genes, including increased stability of Gabrg2, a GABA-A receptor subunit, in male mice. Furthermore, we observed stabilization of a subset of PSD proteins, such as Shank3, following contextual fear conditioning. We propose that sex- and experience-dependent changes in protein turnover rates could help explain sex-differences in psychiatric risk and aid our understanding of the molecular mechanisms that support learning and memory.

Fields of Study & Subjects

Neuroscience and Neuropharmacology Research Stress Responses and Cortisol Memory and Neural Mechanisms

Publication details

Journal / source
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Volume
123
Issue
28
Pages
e2602111123–e2602111123
Publication date
7 July 2026
Language
EN