Prediction of signalling pathway of synaptic cell adhesion molecules mediating early synapse formation based on bioinformatics
10.3969/j.issn.1674-8115.2019.12.005
- Author:
Guo-Hao MENG
1
Author Information
1. Department of Pathophysiology, Shanghai Jiao Tong University College of Basic Medical Sciences
- Publication Type:Journal Article
- Keywords:
Bioinformatics;
Neurodevelopment;
Protein-protein interaction;
RNA-sequencing;
Synapse formation;
Synaptic cell adhesion molecule (sCAM)
- From:
Journal of Shanghai Jiaotong University(Medical Science)
2019;39(12):1366-1374
- CountryChina
- Language:Chinese
-
Abstract:
Objective • To investigate the signalling pathways mediated by synaptic cell adhesion molecules (sCAMs) in the process of human prenatal synapse formation. Methods • The single-cell RNA-sequencing dataset of prenatal human prefrontal cortex was downloaded from GEO (Gene Expression Omnibus) database. The gene expression dynamics was modelled with pseudotime ordering approach and the protein-protein interaction (PPI) network was constructed by utilizing gene co-expression analysis and PPI database. The interacting molecules and associated pathways of sCAMs were explored. Results • The gene expression dynamics of early synapse formation in excitatory neurons can be modelled with linear trajectory. PPI network analysis identified the interacting molecules of neurexins, neuroligins, and LAR-type receptor-type protein tyrosine phosphatases (LAR-type RPTPs). Guanine nucleotide exchange factor 9 (ARHGEF9) interacted with neurexins and neuroligins, while cell division cycle 42 (CDC42) was the hub of the network. Amyloid precursor protein (APP) interacted with neuroligins and leucine-rich repeat transmembrane neuronal protein 3 (LRRTM3), which is a ligand of neurexins. Finally, mitogen-activated protein kinase 8 (MAPK8), dual specificity phosphatase 4 (DUSP4), and CDC42, which participate MAPK signalling pathways, were involved in the PPI network of protein tyrosine phosphatase receptor type D (PTPRD, a member of LAR-type RPTPs) and its ligands leucine rich repeat and fibronectin type III domain containing 1 (LRFN1), LRFN2, and LRFN5. Conclusion • Interacting proteins and associated pathways of neurexins, neuroligins, and LAR-type RPTPs can be predicted with bioinformatics methods, which may provide insights in experimental studies.
