A systems biology approach to understand retinal ciliopathies

• Published in: Acta ophthalmologica (Oxford, England) Vol. 102; no. S279
• Main Authors: Liu, Xiaonan, Pacwa, Anna, Bugara, Klaudia, Machna, Bartosz, Rodak, Piotr, Machowicz, Joanna, Lewin‐Kowalik, Joanna, Smedowski, Adrian
• Format: Journal Article
• Language: English
• Published: Malden Wiley Subscription Services, Inc 01.01.2024
• Subjects: Genotypes; Localization; Mass spectroscopy; Phenotypes; Photoreceptors; Protein interaction; Proteins; Proteomes; Retina
• ISSN: 1755-375X; 1755-3768
• DOI: 10.1111/aos.16126

Aims/Purpose: Many of the described ciliopathies display multi‐organ developmental phenotypes, including retina. A variety of proteins encoded by genes associated with retinal ciliopathies are present in the connecting cilium of the retina, which is essential for photoreceptor function. Owing to the complicated genetic networks of ciliopathies, it is more difficult to characterize ciliopathies than other rare diseases, and only a handful of exact genotype–phenotype correlations have been established. The scientific aim of this study was to unravel the protein‐level mechanisms of retinal ciliopathies using system and molecular biology techniques. Methods: Due to the network of protein interactions, the effect of a ciliopathy mutation is not limited to a single gene product. Instead, it impacts the interacting partners and, as a result, can have an effect on the activity of a whole subnetwork. To analyse this, we selected 46 genes that have been previously associated with non‐syndromic and multi‐syndromic retinal ciliopathies and applied proximity labeling‐based method (UltraID) coupled with mass spectrometry (MS) approach for systematic analysis of retinal ciliopathy proteomes. Results: Bioinformatic analysis of the comprehensive dataset reveals 3772 high confidence interactions and among them 179 interactions (4.7%) were previously reported for the retinal ciliopathy protein. We further conducted a subcellular localization analysis on the interacting proteins. There are 232 unique prey proteins (13.6%) with annotated subcellular localization or tissue distribution in photoreceptor, cilium, retina, or eye, indicating our PPI data are retinal ciliopathy context specific. Conclusions: Protein–protein interaction (PPI)‐based analyses, rather than focusing on specific genes or loci implicated in retinal ciliopathies, highlight connections that are most affected by the disease state, thereby facilitating the discovery of higher‐order relationships within the genetic architecture of ciliopathies.