Affinity Proteomics Identifies Interaction Partners and Defines Novel Insights into the Function of the Adhesion GPCR VLGR1/ADGRV1.
Barbara KnappJens RoedigHeiko RoedigJacek KrzyskoNicola HornBaran E GülerDeva Krupakar KusuluriAdem YildirimKarsten BoldtMarius UeffingInes LiebscherUwe WolfrumPublished in: Molecules (Basel, Switzerland) (2022)
The very large G-protein-coupled receptor 1 (VLGR1/ADGRV1) is the largest member of the adhesion G-protein-coupled receptor (ADGR) family. Mutations in VLGR1/ADGRV1 cause human Usher syndrome (USH), a form of hereditary deaf-blindness, and have been additionally linked to epilepsy. In the absence of tangible knowledge of the molecular function and signaling of VLGR1, the pathomechanisms underlying the development of these diseases are still unknown. Our study aimed to identify novel, previously unknown protein networks associated with VLGR1 in order to describe new functional cellular modules of this receptor. Using affinity proteomics, we have identified numerous new potential binding partners and ligands of VLGR1. Tandem affinity purification hits were functionally grouped based on their Gene Ontology terms and associated with functional cellular modules indicative of functions of VLGR1 in transcriptional regulation, splicing, cell cycle regulation, ciliogenesis, cell adhesion, neuronal development, and retinal maintenance. In addition, we validated the identified protein interactions and pathways in vitro and in situ. Our data provided new insights into possible functions of VLGR1, related to the development of USH and epilepsy, and also suggest a possible role in the development of other neuronal diseases such as Alzheimer's disease.
Keyphrases
- cell cycle
- cell adhesion
- mass spectrometry
- healthcare
- binding protein
- endothelial cells
- genome wide
- cognitive decline
- gene expression
- staphylococcus aureus
- machine learning
- protein protein
- electronic health record
- cystic fibrosis
- small molecule
- diabetic retinopathy
- climate change
- dna methylation
- human immunodeficiency virus
- single molecule
- artificial intelligence
- dna binding
- hiv infected
- data analysis
- network analysis
- recombinant human