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The complex functions of neuronal synapses depend on their tightly interconnected protein network, and their dysregulation is implicated in the pathogenesis of autism spectrum disorders and schizophrenia. However, it remains unclear how synaptic molecular networks are altered biochemically in these disorders. Here, we apply multiplexed imaging to probe the effects of RNAi knockdown of 16 autism- and schizophrenia-associated genes on the simultaneous joint distribution of 10 synaptic proteins, observing several protein composition phenotypes associated with these risk genes. We apply Bayesian network analysis to infer hierarchical dependencies among eight excitatory synaptic proteins, yielding predictive relationships that can only be accessed with single-synapse, multiprotein measurements performed simultaneously in situ. Finally, we find that central features of the network are affected similarly across several distinct gene knockdowns. These results offer insight into the convergent molecular etiology of these widespread disorders and provide a general framework to probe subcellular molecular networks.
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Synaptic composition, activity, mRNA translation and dynamics in combined single-synapse profiling using multimodal imaging
Abstract The function of neuronal circuits, and its perturbation by psychoactive molecules or disease-associated genetic variants, is governed by the interplay between synapse activity and synaptic protein localization and synthesis across a heterogeneous synapse population. Here, we combine in situ measurement of synaptic multiprotein compositions and activation states, synapse activity in calcium traces or glutamate spiking, and local translation of specific genes, across the same individual synapses. We demonstrate how this high-dimensional data enables identification of interdependencies in the multiprotein-activity network, and causal dissection of complex synaptic phenotypes in disease-relevant chemical and genetic NMDAR loss of function that translatein vivo. We show how this method generalizes to other subcellular systems by deriving mitochondrial protein networks, and, using support vector machines, its value in overcoming animal variability in phenotyping. Integrating multiple synapse information modalities enables deep structure-function characterization of synapse populations and their responses to genetic and chemical perturbations.
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- Award ID(s):
- 1707999
- PAR ID:
- 10561119
- Publisher / Repository:
- bioRxiv
- Date Published:
- Format(s):
- Medium: X
- Institution:
- bioRxiv
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Posted Content:
- https://doi.org/10.1101/2024.10.28.620504
