Skovorodkin, I. | bioRxiv Science

bioRxiv2026

Evidence for early kidney vasculature development by vasculogenesis and angiogenesis based on advanced in vivo chimeric model and depletion of CD31+/CD146+ intrinsic endothelial progenitors

Kidney diseases are a significant health concern worldwide, with a growing demand for fundamental treatments, such as generation of transplantable organs from programmed cells. The generation of kidney organoids has led to significant advances in disease modeling. However, failure to establish a robust endothelial vasculature network in kidney organoids remains a barrier to oxygen support and gas exchange in renal tissue engineering. We targeted the development of early kidney vasculature system by advancing the classic mouse embryonic kidney organ culture and organoid model system by introducing a novel mini reservoir setup. The method improved integration with the highly vascularized chicken Chorion Allantois Membrane (CAM), enabling host blood flow to developing kidney organoids. We examined the origin and role of the CD31+ endothelial cells (ECs) and their CD146+ progenitors by applying a dissociated embryonic kidney approach. This enabled selected depletion of specific cell populations, followed by regeneration of the kidney organ primordia by reaggregation and placement on the CAM to assess organogenesis. The cell lineage and fate tracing with constitutively labelled cells revealed that the intrinsic endothelial CD146+ progenitor and those of CD31+ ECs in the kidney initiating organogenesis established the kidney vasculature. If the intrinsic EC progenitors were depleted, the mouse glomerular vascularization was rescued by the CAM derived ECs.

developmental biology↗

bioRxiv2020

Computational Modelling of Cell Movements and Aggregations during Kidney Organogenesis

During early kidney organogenesis, nephron progenitor (NP) cells move from the tip to the corner region of the ureteric bud (UB) branches in order to form the pretubular aggregate, the early structure giving rise to nephron formation. Chemotaxis and cell-cell adhesion differences are believed to drive cell patterning during this critical period of organogenesis, but the spatiotemporal organization of this process is incompletely understood. We applied a Cellular Potts model to explore to how these processes contribute to directed cell movement and aggregation. Model parameters were estimated based on fitting to experimental data obtained in ex vivo kidney explant and dissociation-reaggregation organoid culture studies. Our simulations indicated that optimal enrichment and aggregation of NP cells in the UB corner niche requires chemoattractant secretion from both the UB epithelial cells and the NP cells themselves, as well as differences in cell-cell adhesion energies. Furthermore, NP cells were observed, both experimentally and by modelling, to move at higher speed in the UB corner as compared to the tip region where they originated. The existence of different cell speed domains along the UB was confirmed using self-organizing map analysis. In summary, we demonstrated the suitability of a Cellular Potts Model approach to simulate cell movement and patterning during early nephrogenesis. Further refinement of the model should allow us to recapitulate the effects of developmental changes of cell phenotypes and molecular crosstalk during organ development. Author SummaryThe emergence of tissue patterns during vertebrate development is a major interest of both experimental research and biocomputational modelling. In this study, we established a Cellular Potts Model to explore cellular processes during early kidney development. The goal was to elucidate movements and aggregations of nephron progenitor cells. These precursor cells derive from mesenchymal cells around the ureteric buds and eventually form the epithelial structure of the nephron. Moreover, we wanted to explore computationally the mechanisms how these cells segregate from metanephric mesenchyme and move towards the location where the nephron will be formed. Utilizing the Compucell3D simulation software, we developed a model which assumes that nephron progenitor movement and aggregation is governed by only two mechanisms, i.e. cell-cell adhesion differences between cell types and nephron progenitor cell chemotaxis in response to chemoattractant secretion from two sources. These sources were either the epithelial cells of a static ureteric bud and/or the nephron progenitor cells themselves. The simulations indicated faster average cell speeds near the ureteric bud corner, the target region of cell movement and aggregation, and slower speeds near the place of origin, the tip of ureteric bud. The results were validated by comparison of the model predictions with experimental data from two ex vivo embryonic kidney models and a computational optimization protocol.

systems biology↗

bioRxiv2019

Ureteric Bud Cells Programmed from Embryonic Stem Cells Obtain Competence for Secondary Induction in the Kidney

Generation of kidney organoids from pluripotent stem cells (PSCs) is regarded as a potentially powerful way to study kidney development, disease, and regeneration. Direct differentiation of PSCs towards renal lineages is well studied, however, most of the studies relates to generation of nephron progenitor population from PSCs. Until now, differentiation of PSCs into ureteric bud (UB) progenitor cells demonstrates limited success. Here, we describe a simple, efficient and reproductive protocol to direct differentiation of mouse embryonic stem cells (mESCs) into UB progenitor cells. The mESC-derived UB cells were able to induce nephrogenesis when placed in the interaction with the primary metanephric mesenchyme (pMM). In generated kidney organoids, the embryonic pMM developed nephron structures and the mESC-derived UB cells formed network of collecting ducts, connected with the nephron tubules. Altogether, our studies established an uncomplicated and reproducible platform for kidney disease modelling, drug testing and regenerative medicine applications.

developmental biology↗