Transcriptomic profiling analysis of the effect of palmitic acid on 3D spheroids of ß-like cells derived from induced pluripotent stem cells.

Type 2 diabetes (T2D) is posing a serious public health concern with a considerable impact on human life and health expenditures worldwide. The disease develops when insulin plasma level is insufficient for coping insulin resistance, caused by the decline of pancreatic ß-cell function and mass. In ß-cells, the lipotoxicity exerted by saturated free fatty acids in particular palmitate (PA), which is chronically elevated in T2D, plays a major role in ß-cell dysfunction and mass. However, there is a lack of human relevant in vitro model to identify the underlying mechanism through which palmitate induces ß-cell failure. In this frame, we have previously developed a cutting-edge 3D spheroid model of ß-like cells derived from human induced pluripotent stem cells. In the present work, we investigated the signaling pathways modified by palmitate in ß-like cells derived spheroids. When compared to the 2D monolayer cultures, the transcriptome analysis (FDR set at  0.1) revealed that the 3D spheroids upregulated the pancreatic markers (such as GCG, IAPP genes), lipids metabolism and transporters (CD36, HMGSC2 genes), glucose transporter (SLC2A6). Then, the 3D spheroids are exposed to PA 0.5 mM for 72 h. The differential analysis demonstrated that 32 transcription factors and 135 target genes were mainly modulated (FDR set at  0.1) including the upregulation of lipid and carbohydrates metabolism (HMGSC2, LDHA, GLUT3), fibrin metabolism (FGG, FGB), apoptosis (CASP7). The pathway analysis using the 135 selected targets extracted the fibrin related biological process and wound healing in 3D PA treated conditions. An overall pathway gene set enrichment analysis, performed on the overall gene set (with pathway significance cutoff at 0.2), highlighted that PA perturbs the citrate cycle, FOXO signaling and Hippo signaling as observed in human islets studies. Additional RT-PCR confirmed induction of inflammatory (IGFBP1, IGFBP3) and cell growth (CCND1, Ki67) pathways by PA. All these changes were associated with unaffected glucose-stimulated insulin secretion (GSIS), suggesting that they precede the defect of insulin secretion and death induced by PA. Overall, we believe that our data demonstrate the potential of our spheroid 3D islet-like cells to investigate the pancreatic-like response to diabetogenic environment.

Correction: Generation of ß-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids.

Correction for 'Generation of ß-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids' by Lisa Morisseau et al., Mol. Omics, 2023, https://doi.org/10.1039/d3mo00050h.

Generation of ß-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids.

Since the identification of four different pancreatic ß-cell subtypes and bi-hormomal cells playing a role in the diabetes pathogenesis, the search for in vitro models that mimics such cells heterogeneity became a key priority in experimental and clinical diabetology. We investigated the potential of human induced pluripotent stem cells to lead to the development of the different ß-cells subtypes in honeycomb microwell-based 3D spheroids. The glucose-stimulated insulin secretion confirmed the spheroids functionality. Then, we performed a single cell RNA sequencing of the spheroids. Using a knowledge-based analysis with a stringency on the pancreatic markers, we extracted the ß-cells INS+/UCN3+ subtype (11%; ß1-like cells), the INS+/ST8SIA1+/CD9- subtype (3%, ß3-like cells) and INS+/CD9+/ST8SIA1-subtype (1%; ß2-like cells) consistently with literature findings. We did not detect the INS+/ST8SIA1+/CD9+ cells (ß4-like cells). Then, we also identified four bi-hormonal cells subpopulations including δ-like cells (INS+/SST+, 6%), γ-like cells (INS+/PPY+, 3%), α-like-cells (INS+/GCG+, 6%) and ε-like-cells (INS+/GHRL+, 2%). Using data-driven clustering, we extracted four progenitors' subpopulations (with the lower level of INS gene) that included one population highly expressing inhibin genes (INHBA+/INHBB+), one population highly expressing KCNJ3+/TPH1+, one population expressing hepatocyte-like lineage markers (HNF1A+/AFP+), and one population expressing stem-like cell pancreatic progenitor markers (SOX2+/NEUROG3+). Furthermore, among the cycling population we found a large number of REST+ cells and CD9+ cells (CD9+/SPARC+/REST+). Our data confirm that our differentiation leads to large ß-cell heterogeneity, which can be used for investigating ß-cells plasticity under physiological and pathophysiological conditions.

Liver organ-on-chip models for toxicity studies and risk assessment.

The liver is a key organ that plays a pivotal role in metabolism and ensures a variety of functions in the body, including homeostasis, synthesis of essential components, nutrient storage, and detoxification. As the centre of metabolism for exogenous molecules, the liver is continuously exposed to a wide range of compounds, such as drugs, pesticides, and environmental pollutants. Most of these compounds can cause hepatotoxicity and lead to severe and irreversible liver damage. To study the effects of chemicals and drugs on the liver, most commonly, animal models or in vitro 2D cell cultures are used. However, data obtained from animal models lose their relevance when extrapolated to the human metabolic situation and pose ethical concerns, while 2D static cultures are poorly predictive of human in vivo metabolism and toxicity. As a result, there is a widespread need to develop relevant in vitro liver models for toxicology studies. In recent years, progress in tissue engineering, biomaterials, microfabrication, and cell biology has created opportunities for more relevant in vitro models for toxicology studies. Of these models, the liver organ-on-chip (OoC) has shown promising results by reproducing the in vivo behaviour of the cell/organ or a group of organs, the controlled physiological micro-environment, and in vivo cellular metabolic responses. In this review, we discuss the development of liver organ-on-chip technology and its use in toxicity studies. First, we introduce the physiology of the liver and summarize the traditional experimental models for toxicity studies. We then present liver OoC technology, including the general concept, materials used, cell sources, and different approaches. We review the prominent liver OoC and multi-OoC integrating the liver for drug and chemical toxicity studies. Finally, we conclude with the future challenges and directions for developing or improving liver OoC models.