Germaine Aalderink

The intestinal epithelium forms a selective barrier between the intestinal lumen and the subepithelial layer. Intestinal epithelium plays a critical role in initiating inflammatory tissue responses in vivo, which remains challenging to emulate in vitro. Caco-2 cells are commonly used models of the intestinal epithelium, but lack crucial receptors and pathways associated with pro-inflammatory reactions. Human-induced pluripotent stem cell (iPSC)-based in vitro models are assumed to provide a system that better emulates in vivo responses. This study evaluated the inflammatory response of iPSC-derived intestinal epithelial cells (IEC) and Caco-2-derived intestinal epithelial cells to the microbial toxins lipopolysaccharide (LPS) and nigericin. Here, iPSCs were differentiated towards enterocyte, goblet- and Paneth-like cells without using three-dimensional culture techniques. The formed monolayer barriers were exposed to a combination of 0–100 µM nigericin and 100 ng/mL LPS on either the apical or basolateral side. The treatment-induced expression of cytokine genes and cytokine secretion were compared between the iPSC-derived cell model and differentiated Caco-2 cell layers. Nigericin exposure in combination with LPS significantly reduced transepithelial electrical resistance in the iPSC-derived model, and resulted in a tenfold increased secretion of the pro-inflammatory cytokines interleukin (IL)-6, IL-8, and tumor necrosis factor-alpha compared to the negative control. A similar increase was observed for the mRNA expression of these cytokines. No significant effect on TEER, cytokine secretion, or mRNA expression was observed in the Caco-2 model. Overall, this study shows that iPSC-IECs are a more sensitive model compared to Caco-2 to emulate inflammatory perturbations of the human intestinal epithelium.

Recent years have seen a dramatic increase in the application of organoids to developmental biology, biomedical and translational studies. Organoids are large structures with high phenotypic complexity and are imaged on a wide range of platforms, from simple benchtop stereoscopes to high-content confocal-based imaging systems. The large volumes of images, resulting from hundreds of organoids cultured at once, are becoming increasingly difficult to inspect and interpret. Hence, there is a pressing demand for a coding-free, intuitive and scalable solution that analyses such image data in an automated yet rapid manner. Here, we present MOrgAna, a Python-based software that implements machine learning to segment images, quantify and visualize morphological and fluorescence information of organoids across hundreds of images, each with one object, within minutes. Although the MOrgAna interface is developed for users with little to no programming experience, its modular structure makes it a customizable package for advanced users. We showcase the versatility of MOrgAna on several in vitro systems, each imaged with a different microscope, thus demonstrating the wide applicability of the software to diverse organoid types and biomedical studies.

Intestinal organoids have emerged as the new paradigm for modelling the healthy and diseased intestine with patient-relevant properties. In this study, we show directed differentiation of induced pluripotent stem cells towards intestinal-like phenotype within a microfluidic device. iPSCs are cultured against a gel in microfluidic chips of the OrganoPlate, in which they undergo stepwise differentiation. Cells form a tubular structure, lose their stem cell markers and start expressing mature intestinal markers, including markers for Paneth cells, enterocytes and neuroendocrine cells. Tubes develop barrier properties as confirmed by transepithelial electrical resistance (TEER). Lastly, we show that tubules respond to pro-inflammatory cytokine triggers. The whole procedure for differentiation lasts 14 days, making it an efficient process to make patient-specific organoid tubules. We anticipate the usage of the platform for disease modelling and drug candidate screening.