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Published

Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders

Authors

Yuan Mei, Maya L Gosztyla, Xinzhu Tan, Lara E Dozier, Brent Wilkinson, Justin McKetney, John Lee, Michael Chen, Dorothy Tsai, Hema Kopalle, Marina A Gritsenko, Nicolas Hartel, Nicholas A Graham, Ilse Flores, Stephen K Gilmore-Hall, Shuhao Xu, Charlotte A Marquez, Sophie N Liu, Dylan Fong, Jing Chen, Kate Licon, Derek Hong, Sarah N Wright, Jason F Kreisberg, Alexi Nott, Richard D Smith, Wei-Jun Qian, Danielle L Swaney, Lilia M Iakoucheva, Nevan J Krogan, Gentry N Patrick, Yang Zhou, Guoping Feng, Marcelo P Coba, Gene W Yeo, Trey Ideker

Abstract

Cell Syst. 2025 Mar 3:101204. doi: 10.1016/j.cels.2025.101204. Online ahead of print.

ABSTRACT

The molecular composition of the excitatory synapse is incompletely defined due to its dynamic nature across developmental stages and neuronal populations. To address this gap, we apply proteomic mass spectrometry to characterize the synapse in multiple biological models, including the fetal human brain and human induced pluripotent stem cell (hiPSC)-derived neurons. To prioritize the identified proteins, we develop an orthogonal multi-omic screen of genomic, transcriptomic, interactomic, and structural data. This data-driven framework identifies proteins with key molecular features intrinsic to the synapse, including characteristic patterns of biophysical interactions and cross-tissue expression. The multi-omic analysis captures synaptic proteins across developmental stages and experimental systems, including 493 synaptic candidates supported by proteomics. We further investigate three such proteins that are associated with neurodevelopmental disorders-Cullin 3 (CUL3), DEAD-box helicase 3 X-linked (DDX3X), and Y-box binding protein-1 (YBX1)-by mapping their networks of physically interacting synapse proteins or transcripts. Our study demonstrates the potential of an integrated multi-omic approach to more comprehensively resolve the synaptic architecture.

PMID:40054464 | DOI:10.1016/j.cels.2025.101204

UK DRI Authors

Profile picture of Alexi Nott

Dr Alexi Nott

Group Leader

Investigating how the epigenome regulates cell type specific gene expression in ageing-related brain disorders

Dr Alexi Nott