Phagocytosis in the retina promotes local insulin production in the eye.
J Iker EtchegarayShannon KelleyKristen Kelley PenberthyLaura KarvelyteYosuke NagasakaSofia GasperinoSoumen PaulVikram SeshadriMichael RaymondAna Royo MarcoJonathan PinneyMarta E StremskaBrady J BarronChristopher D LucasNishikant WaseYong FanEmil R UnanueBijoy KunduTal Burstyn-CohenJustin S A PerryJayakrishna AmbatiKodi S RavichandranPublished in: Nature metabolism (2023)
The retina is highly metabolically active, relying on glucose uptake and aerobic glycolysis. Situated in close contact to photoreceptors, a key function of cells in the retinal pigment epithelium (RPE) is phagocytosis of damaged photoreceptor outer segments (POS). Here we identify RPE as a local source of insulin in the eye that is stimulated by POS phagocytosis. We show that Ins2 messenger RNA and insulin protein are produced by RPE cells and that this production correlates with RPE phagocytosis of POS. Genetic deletion of phagocytic receptors ('loss of function') reduces Ins2, whereas increasing the levels of the phagocytic receptor MerTK ('gain of function') increases Ins2 production in male mice. Contrary to pancreas-derived systemic insulin, RPE-derived local insulin is stimulated during starvation, which also increases RPE phagocytosis. Global or RPE-specific Ins2 gene deletion decreases retinal glucose uptake in starved male mice, dysregulates retinal physiology, causes defects in phototransduction and exacerbates photoreceptor loss in a mouse model of retinitis pigmentosa. Collectively, these data identify RPE cells as a phagocytosis-induced local source of insulin in the retina, with the potential to influence retinal physiology and disease.
Keyphrases
- type diabetes
- diabetic retinopathy
- induced apoptosis
- glycemic control
- optic nerve
- cell cycle arrest
- optical coherence tomography
- mouse model
- cell death
- machine learning
- genome wide
- blood pressure
- oxidative stress
- gene expression
- endothelial cells
- diabetic rats
- adipose tissue
- weight loss
- artificial intelligence
- binding protein
- genome wide identification