The retinal pigment epithelium (RPE) is a specialized cell monolayer that forms the barrier between the subretinal and choroidal spaces. During development, RPE cells polarize perpendicular to the monolayer plane such that organelles attain specific intracellular locations. This allows the RPE to differentially interact with overlying photoreceptors and underlying choriocapillaris. When RPE polarity is disrupted, tissue homeostasis is disturbed, leading to retinal degeneration. The subcellular organizational principles of RPE polarity are unknown. We developed an artificial intelligence (AI), specifically a mask region-based convolutional neural network-assisted high-content image analysis platform combined with mathematical modeling to develop a quantitative three-dimensional digital twin of RPE subcellular structures during the establishment of apical/basal polarity, polarity organization with learning-based analysis for RPE image segmentation (POLARIS). We discovered, during apical/basal polarization, cells constrict along the lateral axis and elongate apically, nuclear volume decreases, nuclear envelope develops invaginations, junctional complexes consolidate to the lateral membrane, the endoplasmic reticulum and mitochondria increase in volume and translocate towards the nucleus, and lysosomes move towards the central-apical side. AI algorithm and mathematical analysis reveal non-stochastic cell state transitions and organelle interactions in 3D during RPE polarization. These integrated AI-based quantitative data provide a reference digital twin to discover intracellular defects in diseased RPE.

Cell-replacement therapies are a new class of treatments, which include induced pluripotent stem cell (iPSC)-derived tissues that aim to replace degenerated cells. iPSCs can potentially be used to generate any cell type of the body, making them a powerful tool for treating degenerative diseases. Cell replacement for retinal degenerative diseases is at the forefront of cell therapies, given the accessibility of the eye for surgical procedures and a huge unmet medical need for retinal degenerative diseases with no current treatment options. Clinical trials are ongoing in different parts of the world using stem cell-derived retinal pigment epithelium (RPE). This review focuses on scientific and regulatory considerations when developing an iPSC-derived RPE cell therapy from the development of a robust and efficient differentiation protocol to critical quality control assays for cell validation, the choice of an appropriate animal model for preclinical testing, and the regulatory aspects that dictate the final approval for proceeding to a first-in-human clinical trial.

Age-related macular degeneration (AMD), the leading cause of geriatric blindness, is a multi-factorial disease with retinal-pigmented epithelial (RPE) cell dysfunction as a central pathogenic driver. With RPE degeneration, lysosomal function is a core process that is disrupted. Transcription factors EB/E3 (TFEB/E3) tightly control lysosomal function; their disruption can cause aging disorders, such as AMD. Here, we show that induced pluripotent stem cells (iPSC)-derived RPE cells with the complement factor H variant [ CFH (Y402H)] have increased AKT2, which impairs TFEB/TFE3 nuclear translocation and lysosomal function. Increased AKT2 can inhibit PGC1α, which downregulates SIRT5, an AKT2 binding partner. SIRT5 and AKT2 co-regulate each other, thereby modulating TFEB-dependent lysosomal function in the RPE. Failure of the AKT2/SIRT5/TFEB pathway in the RPE induced abnormalities in the autophagy-lysosome cellular axis by upregulating secretory autophagy, thereby releasing a plethora of factors that likely contribute to drusen formation, a hallmark of AMD. Finally, overexpressing AKT2 in RPE cells in mice led to an AMD-like phenotype. Thus, targeting the AKT2/SIRT5/TFEB pathway could be a potential therapy for atrophic AMD.

Here, we present a protocol to differentiate induced pluripotent stem cell (iPSC) into adherent hematopoietic progenitors that release floating CD14+ CD45+ monocytes into the culture medium. We describe steps for iPSC expansion, embryoid body (EB) formation, suspension culture, plating EBs, and recurring harvests of monocytes, a.k.a. "monocyte factory." We then describe detailed procedures for freezing/thawing of monocytes and differentiation into polarized M1 and M2 macrophages. This protocol provides foundation to study iPSC monocytes and their progenies such as macrophages, microglial, and dendritic cells. For complete details on the use and execution of this protocol, please refer to Karlson et al.1 and Panicker et al.2.

The retinal pigment epithelium (RPE) is a specialized cell monolayer that forms the barrier between the subretinal and the choroidal spaces. During development RPE cells polarize perpendicular to the monolayer plane such that organelles attain specific intracellular locations. This allows the RPE to differentially interact with overlying photoreceptors and underlying choriocapillaris. When RPE polarity is disrupted, tissue homeostasis is disturbed leading to retinal degeneration. The subcellular organizational principles of RPE polarity are unknown. We used high-content imaging, machine-learning-based image-segmentation, phenotypic quantification, and mathematical modeling to develop quantitative 3-dimensional maps of subcellular structures during the establishment of RPE apical/basal polarity. Leveraging the statistical power of large imaging datasets, we discovered holistic RPE cell phenotypic states at four polarization timepoints. We discovered, during apical/basal polarization, cells constrict along the lateral axis and elongate apically, nuclear volume decreases while nuclear envelope develops invaginations, junctional complexes consolidate to the lateral membrane, the endoplasmic reticulum and mitochondria increase in volume and translocate towards the nucleus, and lysosomes move towards the central-apical side. Mathematical analysis using generalized linear models suggests non-stochastic cell state transitions and spatial organelle interactions during RPE polarization. These integrated quantitative morphometric data provide reference maps to discover intracellular defects in diseased RPE.

Stargardt maculopathy, caused predominantly by mutations in the ABCA4 gene, is characterized by an accumulation of non-degradable visual pigment derivative, lipofuscin, in the retinal pigment epithelium (RPE) - resulting in RPE atrophy. RPE is a monolayer tissue located adjacent to retinal photoreceptors and regulates their health and functioning; RPE atrophy triggers photoreceptor cell death and vision loss in Stargardt patients. Previously, ABCA4 mutations in photoreceptors were thought to be the major contributor to lipid homeostasis defects in the eye. Recently, we demonstrated that ABCA4 loss of function in the RPE leads to cell-autonomous lipid homeostasis defects. Our work underscores that an incomplete understanding of lipid metabolism and lipid-mediated signaling in the retina and RPE are potential causes for lacking treatments for this disease. Here we report altered lipidomic in mouse and human Stargardt models. This work provides the basis for therapeutics that aim to restore lipid homeostasis in the retina and the RPE.

The retinal pigment epithelium (RPE) is a monolayer of hexagonal cells located at the back of the eye. It provides nourishment and support to photoreceptors and choroidal capillaries, performs phagocytosis of photoreceptor outer segments (POS), and secretes cytokines in a polarized manner for maintaining the homeostasis of the outer retina. Dysfunctional RPE, caused by mutations, aging, and environmental factors, results in the degeneration of other retinal layers and causes vision loss. A hallmark phenotypic feature of degenerating RPE is intra and sub-cellular lipid-rich deposits. These deposits are a common phenotype across different retinal degenerative diseases. To reproduce the lipid deposit phenotype of monogenic retinal degenerations in vitro, induced pluripotent stem cell-derived RPE (iRPE) was generated from patients' fibroblasts. Cell lines generated from patients with Stargardt and Late-onset retinal degeneration (L-ORD) disease were fed with POS for 7 days to replicate RPE physiological function, which caused POS phagocytosis-induced pathology in these diseases. To generate a model for age-related macular degeneration (AMD), a polygenic disease associated with alternate complement activation, iRPE was challenged with alternate complement anaphylatoxins. The intra and sub-cellular lipid deposits were characterized using Nile Red, boron-dipyrromethene (BODIPY), and apolipoprotein E (APOE). To quantify the density of lipid deposits, a machine learning-based software, LipidUNet, was developed. The software was trained on maximum-intensity projection images of iRPE on culture surfaces. In the future, it will be trained to analyze three-dimensional (3D) images and quantify the volume of lipid droplets. The LipidUNet software will be a valuable resource for discovering drugs that decrease lipid accumulation in disease models.

The retinal pigment epithelium (RPE) is a monolayer of hexagonal cells located at the back of the eye. It provides nourishment and support to photoreceptors and choroidal capillaries, performs phagocytosis of photoreceptor outer segments (POS), and secretes cytokines in a polarized manner for maintaining the homeostasis of the outer retina. Dysfunctional RPE, caused by mutations, aging, and environmental factors, results in the degeneration of other retinal layers and causes vision loss. A hallmark phenotypic feature of degenerating RPE is intra and sub-cellular lipid-rich deposits. These deposits are a common phenotype across different retinal degenerative diseases. To reproduce the lipid deposit phenotype of monogenic retinal degenerations in vitro, induced pluripotent stem cell-derived RPE (iRPE) was generated from patients' fibroblasts. Cell lines generated from patients with Stargardt and Late-onset retinal degeneration (L-ORD) disease were fed with POS for 7 days to replicate RPE physiological function, which caused POS phagocytosis-induced pathology in these diseases. To generate a model for age-related macular degeneration (AMD), a polygenic disease associated with alternate complement activation, iRPE was challenged with alternate complement anaphylatoxins. The intra and sub-cellular lipid deposits were characterized using Nile Red, boron-dipyrromethene (BODIPY), and apolipoprotein E (APOE). To quantify the density of lipid deposits, a machine learning-based software, LipidUNet, was developed. The software was trained on maximum-intensity projection images of iRPE on culture surfaces. In the future, it will be trained to analyze three-dimensional (3D) images and quantify the volume of lipid droplets. The LipidUNet software will be a valuable resource for discovering drugs that decrease lipid accumulation in disease models.

The retinal pigment epithelium (RPE) is a monolayer of hexagonal cells located at the back of the eye. It provides nourishment and support to photoreceptors and choroidal capillaries, performs phagocytosis of photoreceptor outer segments (POS), and secretes cytokines in a polarized manner for maintaining the homeostasis of the outer retina. Dysfunctional RPE, caused by mutations, aging, and environmental factors, results in the degeneration of other retinal layers and causes vision loss. A hallmark phenotypic feature of degenerating RPE is intra and sub-cellular lipid-rich deposits. These deposits are a common phenotype across different retinal degenerative diseases. To reproduce the lipid deposit phenotype of monogenic retinal degenerations in vitro, induced pluripotent stem cell-derived RPE (iRPE) was generated from patients' fibroblasts. Cell lines generated from patients with Stargardt and Late-onset retinal degeneration (L-ORD) disease were fed with POS for 7 days to replicate RPE physiological function, which caused POS phagocytosis-induced pathology in these diseases. To generate a model for age-related macular degeneration (AMD), a polygenic disease associated with alternate complement activation, iRPE was challenged with alternate complement anaphylatoxins. The intra and sub-cellular lipid deposits were characterized using Nile Red, boron-dipyrromethene (BODIPY), and apolipoprotein E (APOE). To quantify the density of lipid deposits, a machine learning-based software, LipidUNet, was developed. The software was trained on maximum-intensity projection images of iRPE on culture surfaces. In the future, it will be trained to analyze three-dimensional (3D) images and quantify the volume of lipid droplets. The LipidUNet software will be a valuable resource for discovering drugs that decrease lipid accumulation in disease models.

The retinal pigment epithelium (RPE) is a monolayer of hexagonal cells located at the back of the eye. It provides nourishment and support to photoreceptors and choroidal capillaries, performs phagocytosis of photoreceptor outer segments (POS), and secretes cytokines in a polarized manner for maintaining the homeostasis of the outer retina. Dysfunctional RPE, caused by mutations, aging, and environmental factors, results in the degeneration of other retinal layers and causes vision loss. A hallmark phenotypic feature of degenerating RPE is intra and sub-cellular lipid-rich deposits. These deposits are a common phenotype across different retinal degenerative diseases. To reproduce the lipid deposit phenotype of monogenic retinal degenerations in vitro, induced pluripotent stem cell-derived RPE (iRPE) was generated from patients' fibroblasts. Cell lines generated from patients with Stargardt and Late-onset retinal degeneration (L-ORD) disease were fed with POS for 7 days to replicate RPE physiological function, which caused POS phagocytosis-induced pathology in these diseases. To generate a model for age-related macular degeneration (AMD), a polygenic disease associated with alternate complement activation, iRPE was challenged with alternate complement anaphylatoxins. The intra and sub-cellular lipid deposits were characterized using Nile Red, boron-dipyrromethene (BODIPY), and apolipoprotein E (APOE). To quantify the density of lipid deposits, a machine learning-based software, LipidUNet, was developed. The software was trained on maximum-intensity projection images of iRPE on culture surfaces. In the future, it will be trained to analyze three-dimensional (3D) images and quantify the volume of lipid droplets. The LipidUNet software will be a valuable resource for discovering drugs that decrease lipid accumulation in disease models.