ABSTRACT
Kidney organoids derived from human pluripotent stem cells (hPSCs) contain multilineage nephrogenic progenitor cells and can recapitulate the development of the kidney. Kidney organoids derived from hPSCs have the potential to be applied in regenerative medicine as well as renal disease modeling, drug screening, and nephrotoxicity testing. Despite biotechnological advances, individual differences in morphological and growth characteristics among kidney organoids need to be addressed before clinical and commercial application. In this study, we hypothesized that an automated noninvasive method based on deep learning of bright-field images of kidney organoids can predict their differentiation status. Methods: Bright-field images of kidney organoids were collected on day 18 after differentiation. To train convolutional neural networks (CNNs), we utilized a transfer learning approach. CNNs were trained to predict the differentiation of kidney organoids on bright-field images based on the messenger RNA expression of renal tubular epithelial cells as well as podocytes. Results: The best prediction model was DenseNet121 with a total Pearson correlation coefficient score of 0.783 on a test dataset. W classified the kidney organoids into two categories: organoids with above-average gene expression (Positive) and those with below-average gene expression (Negative). Comparing the best-performing CNN with human-based classifiers, the CNN algorithm had a receiver operating characteristic-area under the curve (AUC) score of 0.85, while the experts had an AUC score of 0.48. Conclusion: These results confirmed our original hypothesis and demonstrated that our artificial intelligence algorithm can successfully recognize the differentiation status of kidney organoids.
ABSTRACT
Background/Aims@#Tacrolimus has been used as an immunosuppressive agent in organ transplantation. Despite the therapeutic benefits, tacrolimus’s use is limited due to its nephrotoxicity. To reduce tacrolimus nephrotoxicity, effective humanized experimental models may be helpful. Here, we modeled tacrolimus nephrotoxicity using kidney organoids derived from human inducible pluripotent stem cells (iPSCs) in vitro. @*Methods@#Kidney organoids were differentiated from the CMC11 iPSC cell line, re-seeded in 96-well plates, and treated with tacrolimus at doses of 0, 30, or 60 μM for 24 hours. This in vitro model was compared to a mouse model of tacrolimus nephrotoxicity and the associated mechanisms were investigated. @*Results@#The size of the kidney organoids and cell viability decreased in dose-dependent manners after treatment with tacrolimus. The number of tubular cells decreased with a loss of polarity, similar to the effects seen in mouse tacrolimus nephrotoxicity. Ultrastructural analysis showed numerous vacuoles in the proximal tubular cells of the kidney organoids treated with tacrolimus. Tacrolimus treatment induced oxidative stress and mitochondrial dysfunction, and autophagic activity was enhanced in the kidney organoids. Rapamycin, an autophagy inducer, accelerated cell death in the kidney organoid model of tacrolimus nephrotoxicity, which was attenuated by treatment with 3-methyladenine, an autophagy inhibitor. These findings indicate that the augmentation of autophagy by rapamycin treatment accelerated tacrolimus nephrotoxicity. @*Conclusions@#Our data suggest that human kidney organoids are an effective in vitro model of tacrolimus nephrotoxicity and that autophagy plays a critical role in tacrolimus nephrotoxicity.
ABSTRACT
The establishment of protocols to differentiate kidney organoids from human pluripotent stem cells provides potential applications of kidney organoids in regenerative medicine. Modeling of renal diseases, drug screening, nephrotoxicity testing of compounds, and regenerative therapy are attractive applications. Although much progress still remains to be made in the development of kidney organoids, recent advances in clustered regularly interspaced short palindromic repeat (CRISPR)-CRISPR-associated system 9 (Cas9) genome editing and three-dimensional bioprinting technologies have contributed to the application of kidney organoids in clinical fields. In this section, we review recent advances in the applications of kidney organoids to kidney disease modelling, drug screening, nephrotoxicity testing, and regenerative therapy.
Subject(s)
Humans , Bioprinting , Clustered Regularly Interspaced Short Palindromic Repeats , Drug Evaluation, Preclinical , Genome , Kidney Diseases , Kidney , Organoids , Pluripotent Stem Cells , Regenerative Medicine , TransplantationABSTRACT
BACKGROUND/AIMS: Mind bomb-1 (Mib1) encodes an E3 ubiquitin ligase, which is required for the initiation of Notch signaling. Recently, it was demonstrated that the renal collecting duct plays an important role in renal fibrosis. Here, we investigated the role of Notch signaling in renal fibrosis using conditional knockout mice with the specific ablation of Mib1 in renal collecting duct principal cells. METHODS: Mib1-floxed mice (Mib1f/f ) were crossed with aquaporin 2 (AQP2)-Cre mice in order to generate principal cell-specific Mib1 knockout mice (Mib1f/f :AQP2-Cre+). Unilateral ureteral obstruction (UUO) was performed, and mice were sacrificed 7 days after UUO. RESULTS: After performing the UUO, renal tubulointerstitial fibrosis and the expression of transforming growth factor β were markedly enhanced in the obstructed kidneys of Mib1f/f mice compared with the sham-operated kidney of Mib1f/f mice. These changes were shown to be even more pronounced in the obstructed kidneys of Mib1f/f :AQP2-Cre+ mice than in those of the Mib1f/f mice . Furthermore, the number of TUNNEL-positive cells in renal collecting duct was higher in the obstructed kidneys of Mib1f/f :AQP2-Cre+ mice than in the kidneys of Mib1f/f mice. CONCLUSIONS: Notch signaling in the renal collecting duct plays an important role in the regulation of renal tubulointerstitial fibrosis and apoptosis after UUO.