Protein trafficking and synaptic demand configure complex and dynamic synaptome architectures of individual neurons

Excitatory synapses are the most abundant synapse type in the brain. Being essential for behaviour and implicated in hundreds of brain disorders, these synapses exhibit striking structural and functional diversity. Synaptome mapping at single-synapse resolution reveals that synaptic protein diversity is spatially organised along the dendritic tree of individual neurons and varies with age and cell type. However, the cell biological mechanisms underlying the generation of these complex spatial synaptic patterns remain poorly understood. Potential mechanisms include somatic and dendritic protein synthesis, protein trafficking, and local regulatory mechanisms such as activity-dependent degradation. Here we developed computational models to test how combinations of these processes account for empirical synaptome data. We found that a combination of molecular transport mechanisms and local synaptic demand for proteins was sufficient to explain very complex profiles of synaptic protein distributions observed in young, mature and old mice and in different cell types. Our findings suggest the highly complex and dynamic synaptome architecture of the brain is an emergent property of a minimal set of cell biological processes. Our model sets the stage for simulations of brain tissue incorporating molecularly diverse neuronal and synaptic types in a synaptome and connectome architecture.

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Journal
Scientific Reports
Published
2026-03-02
DOI
https://doi.org/10.1038/s41598-026-40513-7
Primary Topic
Neuroscience and Neuropharmacology Research
Type
article
Field-Weighted Citation Impact
0.00

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Protein trafficking and synaptic demand configure complex and dynamic synaptome architectures of individual neurons

Anatoly Sorokin, Edita Bulovaite, Seth G. N. Grant, Oksana Sorokina et al.
Scientific Reports
Neuroscience and Neuropharmacology Research
article

Protein trafficking and synaptic demand configure complex and dynamic synaptome architectures of individual neurons

Anatoly Sorokin, Edita Bulovaite, Seth G. N. Grant, Oksana Sorokina, J. Douglas Armstrong
article en

Abstract

Excitatory synapses are the most abundant synapse type in the brain. Being essential for behaviour and implicated in hundreds of brain disorders, these synapses exhibit striking structural and functional diversity. Synaptome mapping at single-synapse resolution reveals that synaptic protein diversity is spatially organised along the dendritic tree of individual neurons and varies with age and cell type. However, the cell biological mechanisms underlying the generation of these complex spatial synaptic patterns remain poorly understood. Potential mechanisms include somatic and dendritic protein synthesis, protein trafficking, and local regulatory mechanisms such as activity-dependent degradation. Here we developed computational models to test how combinations of these processes account for empirical synaptome data. We found that a combination of molecular transport mechanisms and local synaptic demand for proteins was sufficient to explain very complex profiles of synaptic protein distributions observed in young, mature and old mice and in different cell types. Our findings suggest the highly complex and dynamic synaptome architecture of the brain is an emergent property of a minimal set of cell biological processes. Our model sets the stage for simulations of brain tissue incorporating molecularly diverse neuronal and synaptic types in a synaptome and connectome architecture.

Scientific Reports
Mott MacDonald (United Kingdom) (GB), Okinawa Institute of Science and Technology Graduate University (JP), Forschungszentrum Jülich (DE), University of Edinburgh (GB)
European Commission, Biotechnology and Biological Sciences Research Council
Openalex Percentile: Top 38%
Neuroscience and Neuropharmacology Research
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Protein trafficking and synaptic demand configure complex and dynamic synaptome architectures of individual neurons — Anatoly Sorokin, Edita Bulovaite, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS