Here we present a step-by-step protocol to generate mature human retinal organoids and utilize them in a photoreceptor toxicity assay to identify pharmaceutical candidates for the age-related retinal degenerative disease macular telangiectasia type 2 (MacTel).
Organoids provide a promising platform to study disease mechanism and treatments, directly in the context of human tissue with the versatility and throughput of cell culture. Mature human retinal organoids are utilized to screen potential pharmaceutical treatments for the age-related retinal degenerative disease macular telangiectasia type 2 (MacTel).
We have recently shown that MacTel can be caused by elevated levels of an atypical lipid species, deoxysphingolipids (deoxySLs). These lipids are toxic to the retina and may drive the photoreceptor loss that occurs in MacTel patients. To screen drugs for their ability to prevent deoxySL photoreceptor toxicity, we generated human retinal organoids from a non-MacTel induced pluripotent stem cell (iPSC) line and matured them to a post-mitotic age where they develop all of the neuronal lineage-derived cells of the retina, including functionally mature photoreceptors. The retinal organoids were treated with a deoxySL metabolite and apoptosis was measured within the photoreceptor layer using immunohistochemistry. Using this toxicity model, pharmacological compounds that prevent deoxySL-induced photoreceptor death were screened. Using a targeted candidate approach, we determined that fenofibrate, a drug commonly prescribed for the treatment of high cholesterol and triglycerides, can also prevent deoxySL toxicity in the cells of the retina.
The toxicity screen successfully identified an FDA-approved drug that can prevent photoreceptor death. This is a directly actionable finding owing to the highly disease-relevant model tested. This platform can be easily modified to test any number of metabolic stressors and potential pharmacological interventions for future treatment discovery in retinal diseases.
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.
1. Thawing, passaging, and expanding iPSCs/ESCs
NOTE: For all cell culturing steps, use best practices to maintain a sterile cell culture.
2. Making embryoid bodies (EBs)
NOTE: EB formation and differentiation media recipes are derived from protocols in Cowan et al.5, Ohlemacher et al.18, and Zhong et al.19.
3. Plating EBs and initiating neural retinal differentiation
4. Making free-floating organoids and maintaining free-floating organoid cultures
5. Maintaining mature organoids and differentiating them to a post-mitotic retinal tissue
6. Deoxysphinganine (deoxySA) and drug treatment
NOTE: Presented here is a single treatment of fenofibrate to rescue deoxySA toxicity over the period of 4 days (Figure 2). Concentration of deoxySA added to organoids, duration of deoxySA treatment on organoids and the type of drug used to rescue toxicity14 can, however, be modified as per the experimental needs to assay toxicity and toxicity rescue.
7. Embedding and cryosectioning of organoids
8. TUNEL staining for apoptotic cells
9. Imaging organoid slices and quantifying death.
NOTE: Imaging requires a confocal microscope with capabilities to distinguish between three fluorophore channels. This experiment uses green (Alexa Fluor 488), orange (Alexa Fluor 555), and UV (DAPI) channels. Any combination of fluorophores can be used ensuring that emissions do not bleed into the other channels.
10. Quantifying dying cells
Retinal organoids were generated from a non-MacTel control iPSC line. After organoids reached 26 weeks in culture they were selected and split into experimental groups. Organoids were treated with varying concentrations of deoxySA to determine if deoxySA is toxic to photoreceptors. Four concentrations of deoxySA were tested, from 0 to 1 µM (Figure 2) and organoids were treated for 8 days, with media changes every other day. Cell death in response to deoxySA is concentration-dependent and detectible in as little as 50 nM deoxySA (Figure 2D). The highest concentration tested, 1 µM deoxySA, gave a robust effect while maintaining the integrity of the retinal organoid (Figure 2B,D). A higher concentration of 5 µM deoxySA caused disintegration of organoids within a few days (data not shown). The results of the deoxySA dose response determined the optimal concentration of deoxySA for future toxicity experiments. The 1 µM deoxySA dose resulted in a substantial cell death without oversaturating toxicity, as was observed at 5 µM.
To test the ability of fenofibrate to rescue deoxySA-induced cell death, retinal organoids were treated with either 1 µM deoxySA, 1 µM deoxySA plus 20 µM fenofibrate, or a no treatment vehicle control (Figure 2A-C,E). The 20 µM fenofibrate treatment prevented deoxySA-induced toxicity in the photoreceptors of retinal organoids, significantly reducing cell death by approximately 80% after 4 days of treatment (Figure 2A-C,E)16. Additional lipid-altering drugs were tested using the same protocol, including fumonosin-B1, which showed a complete rescue of deoxySA toxicity. Related lipid species were also tested to identify the specific downstream sphingolipid metabolite that leads to photoreceptor cell death14.
Figure 1: Representative bright field images of organoids under an inverted light microscope. (A) 4-week-old organoids at 2 days following detachment show appropriate retinal layering (white *) or non-retinal organoid development. (B) Developing organoids at week 13. (C) Retinal organoids at week 28 with clear retinal layering and well-formed outer segments projecting from the outer photoreceptor layer (white bar). Please click here to view a larger version of this figure.
Figure 2: Representative confocal images of cell death. Representative confocal images of cell death (TUNEL, green) within the photoreceptor layer (Recoverin, red) of the retinal organoid following 4 days of treatment with either control media (A), 1 µM deoxySA (B), or 1 µM deoxySA with 20 µM fenofibrate (C). (D) Quantification of cell death in human photoreceptors following treatment of retinal organoid tissue with varying concentrations of deoxySA. (E) Quantification of cell death in human photoreceptors following treatment of retinal organoid tissue with control media (n=6), 1 µM deoxySA (n=22), 1 µM deoxySA + 20 µM fenofibrate (n=21). *p<0.05, ***p<0.001 with one way ANOVA and post hoc Tukey test. Data derived from New England Journal of Medicine, Gantner, M., Eade, K., and Wallace. M., et al. Serine and lipid metabolism in macular disease and peripheral neuropathy, 381(15), 1422-1433, Copyright © (2019) Massachusetts Medical Society. Reprinted with permission.14 Please click here to view a larger version of this figure.
Figure 3: Screen shots showing a confocal image of a sectioned and stained organoid treated with 1 µM deoxySA viewed using FIJI software. Fluorescent channels have been split in to α-Recoverin (A, red), TUNEL (B, green), and DAPI (C, blue). (A) The photoreceptor area has been outlined using the polygon tool selected in the toolbar (top left). (B,C) Cell counts using the multi-point tool, selected in the tool bar, of TUNEL positive (B, green) and DAPI positive (C, blue) cells within the photoreceptor layer. Please click here to view a larger version of this figure.
Differentiation protocol variations
Since the invention of self-forming optic cups by Yoshiki Sasai's group20, many labs have developed protocols to generate retinal organoids that can vary at almost every step5,18,19,21. An exhaustive list of protocols can be found in Capowski et al.22. The differentiation protocol we provide here is a simple, low-intervention protocol that provides a good starting point for any lab attempting to differentiate mature retinal organoids. Users are encouraged to explore and adopt variations on this protocol. Common steps for protocol variation are the production and early differentiation of EBs, and the use of differentiation factors such as BMP4, DKK-1, or retinoic acid to improve efficiency5,19,23.
Culturing organoids on a shaker for much of the late-stage development has been an effective step to increase differentiation efficiency and reduce the time spent handling organoids. Bioreactors achieve the same ends24, however, using a shaker with disposable Erlenmyer flasks is more cost-effective and can be done with common lab equipment. The main advantage of keeping the organoids in mobilized suspension is that it removes the need to separate organoids that stick together on the plate while they are growing. The suspended cultures also facilitate greater nutrient exchange, so organoids have a tendency to grow larger than those on a standard still plate. For this reason, it is good to start out by fragmenting plated EBs as small as possible in step 4.1.
Since obtaining mature retinal organoids requires differentiating a single culture for nearly 6 months, performing toxicity assays on retinal organoids can seem time-consuming compared to using a 2-D monoculture. However, toxicity assays are performed on a single control line, and differentiations can be set up routinely. Following an initial 6-month investment, a regular supply of organoids to perform additional experiments and protocol modifications will be at hand without delay. Initiating 2-3 rounds of retinal organoid differentiation every 1-2 months provides ample tissue for complex and thorough sets of experiments.
Organoids provide a versatile model for targeted drug testing.
This protocol describes a photoreceptor toxicity assay to test the efficacy of lipid-altering drugs to rescue deoxySL-induced cell death. Although this is a specific application showing a pharmacological rescue for a disease-causing agent in MacTel, this protocol can be utilized to test any number of insults (e.g., nutrient deficiency, hypoxic conditions, light toxicity) and pharmacological rescues. Therefore, it can be adapted to model other retinal diseases. In our own work we have shown that by using this same protocol and substituting various related sphingolipid species and drugs that directly block sphingolipid metabolism we were also able to provide insights to the MacTel disease mechanism by determining the specific toxic downstream sphingolipid metabolite that leads to photoreceptor cell death14. Unlike modeling diseases at the level of genetic mutations, which require establishing variant iPSC lines, using organoids to model toxic metabolic conditions and environmental stressors allows for the use of a common control iPSC line as a dynamic model with abundant and readily available tissue source.
The human organoid models are particularly advantageous when studying metabolic diseases in the retina, where different cell types have a unique symbiotic metabolic interplay that cannot be replicated in a monoculture of photoreceptor-like cells4. This complex metabolic model has allowed us to discover the effectiveness of the drug fenofibrate in preventing the toxic effects of deoxySLs directly in humans. In mouse models of elevated deoxySLs14 (unpublished data) and mouse embryonic fibroblast cell culture models of deoxySL metabolism fenofibrate proved to be ineffective16. Testing drugs in the context of complex human tissue models will allow us to identify effective treatments and discount ineffective treatments that would have otherwise been missed had we only relied on mice or simplistic monocultures.
Future development for drug screening
In this protocol we quantify apoptosis in photoreceptors, the most abundant cell type. However, by utilizing any of the proven antibodies that specifically label the other retinal cell types this protocol is modifiable to assay cell death in any retinal cell type, or cell subtype (e.g., cone vs rod). The disadvantage of quantifying apoptosis using TUNEL staining in tissue slices is that it is a low throughput technique to quantify cell death, limiting the application of this assay to screening small lists of candidate drugs. A larger screen of untargeted drug libraries would not be feasible using an IHC approach. Future developments in this protocol to facilitate larger drug screens would require the integration of a more readily quantifiable cell death marker. While these are available, the irregularity of retinal organoids in size, presence or absence of non-retinal tissue appendages, and variability in photoreceptor layer quality makes it difficult to normalize results across organoids. We expect that future developments to increase the throughput of human organoid disease models to screen large drug libraries will vastly improve our ability to discover, modify, and validate drugs that will advance from preclinical trials to approved therapeutics.
The authors have nothing to disclose.
Supported by the Lowy Medical Research Institute. We would like to thank the Lowy family for their support of the MacTel project. We would like to thank Mari Gantner, Mike Dorrell, and Lea Scheppke for their intellectual input and assistance preparing the manuscript.
0.5M EDTA | Invitrogen | 15575020 | |
125mL Erlenmeyer Flasks | VWR | 89095-258 | |
1-deoxysphinganine | Avanti | 860493 | |
B27 Supplement, minus vitamin A | Gibco | 12587010 | |
Beaver 6900 Mini-Blade | Beaver-Visitec | BEAVER6900 | |
D-(+)-Sucrose | VWR | 97061-432 | |
DAPI | Thermo-fisher | D1306 | |
Dispase II, powder | Gibco | 17105041 | |
DMEM, high glucose, pyruvate | Gibco | 11995073 | |
DMEM/F12 | Gibco | 11330 | |
Donkey anti-rabbit Ig-G, Alexa Fluor plus 555 | Thermo-fisher | A32794 | |
donkey serum | Sigma | D9663-10ML | |
FBS, Heat Inactivated | Corning | 45001-108 | |
Fenofibrate | Sigma | F6020 | |
Glutamax | Gibco | 35050061 | |
Heparin | Stemcell Technologies | 7980 | |
In Situ Cell Death Detection Kit, Fluorescin | Sigma | 11684795910 | |
Matrigel, growth factor reduced | Corning | 356230 | |
MEM Non-Essential Amino Acids Solution | Gibco | 11140050 | |
mTeSR 1 | Stemcell Technologies | 85850 | |
N2 Supplement | Gibco | 17502048 | |
Penicillin-Streptomycin | Gibco | 15140122 | |
Pierce 16% Formaldehyde | Thermo-fisher | 28906 | |
Rabbit anti-Recoverin antibody | Millipore | AB5585 | |
Sodium Citrate | Sigma | W302600 | |
Steriflip Sterile Disposable Vacuum Filter Units | MilliporeSigma | SE1M179M6 | |
Taurine | Sigma | T0625 | |
Tissue Plus- O.C.T. compound | Fisher Scientific | 23-730-571 | |
Tissue-Tek Cryomold | EMS | 62534-10 | |
Triton X-100 | Sigma | X100 | |
Tween-20 | Sigma | P1379 | |
Ultra-Low Attachment 6 well Plates | Corning | 29443-030 | |
Ultra-Low Attachment 75cm2 U-Flask | Corning | 3814 | |
Vacuum Filtration System | VWR | 10040-436 | |
Vectashield-mounting medium | vector Labs | H-1000 | |
wax pen-ImmEdge | vector Labs | H-4000 | |
Y-27632 Dihydrochloride (Rock inhibitor) | Sigma | Y0503 |