Background: Significant progress has been made in cell replacement therapy for neural retinal diseases using retinal cells differentiated from human pluripotent stem cells. Low tumorigenicity and the ability to mature to form synaptic junctions make precursor cells a promising donor source. Here, we attempted to improve the yield of photoreceptor precursor cells in three-dimensional retinal organoids from human embryonic stem cells (hESCs). Methods: A CRX-tdTomato-tagged hESC line was generated to track retinal precursors in 3D retinal organoids. COCO, a multifunctional antagonist of the Wnt, TGF-β, and BMP pathways, was employed to 3D organoid differentiation schemes for enhanced photoreceptor precursor cells. Organoid fluorescence intensity measurement was used to monitor retinalization tendency with the number of precursors further checked by flow cytometry. Signature gene expression during organoid differentiation were assessed by qPCR and immunocytochemistry after COCO supplementation. Results: CRX-positive cells can be spatiotemporally tracked by tdTomato without affecting retinalization during retinal organoid differentiation. Fluorescence intensity of organoids, which turned out highly consistent with flow cytometry measurement, allowed us to determine the differentiation efficiency of precursors during organoid culturing directly. Using COCO as an auxiliary supplement, rather than alone, can yield an increased number of photoreceptor precursors in the early stage of organoid differentiation. Over a longer time-frame, photoreceptor precursors enhanced their fate of cones and decreased fate of rods after treatment with COCO. Conclusions: Tracing with the CRX-reporter system showed that in retinal organoids derived from human pluripotent stem cells, COCO increased the differentiation efficiency of photoreceptor precursors and cones.

Although an increasing number of disease genes have been identified, the exact cellular mechanisms of retinitis pigmentosa (RP) remain largely unclear. Retinal organoids (ROs) derived from the induced pluripotent stem cells (iPSCs) of patients provide a potential but unvalidated platform for deciphering disease mechanisms and an advantageous tool for preclinical testing of new treatments. Notably, early-onset RP has been extensively recapitulated by patient-iPSC-derived ROs. However, it remains a challenge to model late-onset disease in a dish due to its chronicity, complexity, and instability. Here, we generated ROs from late-onset RP proband-derived iPSCs harboring a PDE6B mutation. Transcriptome analysis revealed a remarkably distinct gene expression profile in the patient ROs at differentiation day (D) 230. Changes in the expression genes regulating cGMP hydrolysis prompted the elevation of cGMP levels, which was verified by a cGMP enzyme-linked immunosorbent assay (ELISA) in patient ROs. Furthermore, significantly higher cGMP levels in patient ROs than in control ROs at D193 and D230 might lead to impaired formation of synaptic connections and the connecting cilium in photoreceptor cells. In this study, we established the first late-onset RP model with a consistent phenotype using an in vitro cell culture system and provided new insights into the PDE6B-related mechanism of RP.

T-cell receptors (TCRs) and B-cell receptors (BCRs) are critical in recognizing antigens and activating the adaptive immune response. Stochastic V(D)J recombination generates massive TCR/BCR repertoire diversity. Single-cell immune profiling with transcriptome analysis allows the high-throughput study of individual TCR/BCR clonotypes and functions under both normal and pathological settings. However, a comprehensive database linking these data is not yet readily available. Here, we present the human Antigen Receptor database (huARdb), a large-scale human single-cell immune profiling database that contains 444 794 high confidence T or B cells (hcT/B cells) with full-length TCR/BCR sequence and transcriptomes from 215 datasets. All datasets were processed in a uniform workflow, including sequence alignment, cell subtype prediction, unsupervised cell clustering, and clonotype definition. We also developed a multi-functional and user-friendly web interface that provides interactive visualization modules for biologists to analyze the transcriptome and TCR/BCR features at the single-cell level. HuARdb is freely available at https://huarc.net/database with functions for data querying, browsing, downloading, and depositing. In conclusion, huARdb is a comprehensive and multi-perspective atlas for human antigen receptors.