Methods to differentiate human pluripotent stem cells into kidney organoids were first introduced about 5 years ago, and since that time, the field has grown substantially. Protocols are producing increasingly complex three-dimensional structures, have been used to model human kidney disease, and have been adapted for high-throughput screening. Over this same time frame, technologies for massively parallel, single-cell RNA sequencing (scRNA-seq) have matured. Now, both of these powerful approaches are being combined to better understand how kidney organoids can be applied to the understanding of kidney development and disease. There are several reasons why this is a synergistic combination. Kidney organoids are complicated and contain many different cell types of variable maturity. scRNA-seq is an unbiased technology that can comprehensively categorize cell types, making it ideally suited to catalog all cell types present in organoids. These same characteristics also make scRNA-seq a powerful approach for quantitative comparisons between protocols, batches, and pluripotent cell lines as it becomes clear that reproducibility and quality can vary across all three variables. Lineage trajectories can be reconstructed using scRNA-seq data, enabling the rational adjustment of differentiation strategies to promote maturation of desired kidney cell types or inhibit differentiation of undesired off-target cell types.
Here, researchers from Washington University in St. Louis School of Medicine discuss the ways that scRNA-seq has been successfully applied in the organoid field and predict future applications for this powerful technique. They also discuss other developing single-cell technologies and discuss how they may be combined, using “multiomic” approaches, to improve our understanding of kidney organoid differentiation and usefulness in modeling development, disease, and toxicity testing.
Therapeutic potential of kidney organoids
Scheme illustrating the ways that kidney organoids can be used for patient-specific disease modeling and drug screening.