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Modeling human disease in cell culture and animal models has provided invaluable tools for the discovery, modification, and validation of pharmacologic therapeutics, allowing them to advance from candidate drug to approved therapy. Although a combination of in vitro and non-human in vivo models has long been a critical component of the drug development pipeline they frequently fail to predict the clinical performance of novel drug candidates1. There is a clear need for the development of technologies that bridge the gap between simplistic human cellular monocultures and clinical trials. Recent technological advances in self-organized three-dimensional tissue cultures, organoids, have improved their fidelity to the tissues they model making them promising tools in the preclinical drug development pipeline2.
A major advantage of human cell culture over non-human in vivo models is the ability to replicate the specific intricacies of human metabolism which can vary considerably even between higher order vertebrates such as humans and mice3. However, this specificity can be overshadowed by a loss in tissue complexity; such is the case for retinal tissue where multiple cell types are intricately interwoven and have a unique symbiotic metabolic interplay between cellular subtypes that cannot be replicated in a monoculture4. Human organoids, which provide a facsimile of complex human tissues with the accessibility and scalability of cell culture, have the potential to overcome the deficiencies of these disease modeling platforms.
Retinal organoids derived from stem cells have proven to be particularly faithful in modeling the complex tissue of the human neural retina5. This has made the retinal organoid model a promising technology for the study and treatment of retinal disease6,7. To date much of the disease modeling in retinal organoids has focused on monogenic retinal diseases where retinal organoids are derived from iPSC lines with disease-causing genetic variants7. These are generally highly penetrant mutations that manifest as developmental phenotypes. Less work has been effectively done on aging diseases where genetic mutations and environmental stressors impact tissue that has developed normally. Neurodegenerative diseases of aging can have complex genetic inheritance and contributions from environmental stressors that are inherently difficult to model using short-term cell cultures. However, in many cases these complex diseases can coalesce on common cellular or metabolic stressors that, when tested on a fully developed human tissue, can provide powerful insights into neurodegenerative diseases of aging8.
The late-onset macular degenerative disease, macular telangiectasia type II (MacTel), is a great example of a genetically complex neurodegenerative disease that coalesces on a common metabolic defect. MacTel is an uncommon retinal degenerative disease of aging that results in photoreceptor and Müller glia loss in the macula, leading to a progressive loss in central vision9,10,11,12,13. In MacTel, an undetermined, possibly multifactorial, genetic inheritance drives a common reduction in circulating serine in patients, resulting in an increase in a neurotoxic lipid species called deoxysphingolipids (deoxySL)14,15. To prove that accumulation of deoxySL is toxic to the retina and to validate potential pharmaceutical therapeutics, we developed this protocol to assay photoreceptor toxicity in human retinal organoids14.
Here we outline a specific protocol for differentiating human retinal organoids, establishing a toxicity and rescue assay using organoids, and quantifying outcomes. We provide a successful example where we determine the tissue-specific toxicity of a suspected disease-causing agent, deoxySL, and validate the use of a safe generic drug, fenofibrate, for the potential treatment of deoxySL-induced retinal toxicity. Previous work has shown that fenofibrate can increase the degradation of deoxySL and lower circulating deoxySL in patients, however, its efficacy in reducing deoxySL-induced retinal toxicity has not been tested16,17. Although we present a specific example, this protocol can be utilized to evaluate the effect of any number of metabolic/environmental stressors and potential therapeutic drugs on retinal tissue.