Dataset Information

PH dependence of a GPR4 selective antagonist hampers its therapeutic potential

ABSTRACT: Inflammatory bowel disease (IBD) is characterized by chronic mucosal inflammation of the gastrointestinal tract and is associated with extracellular acidification of mucosal tissue. Several extracellular pH-sensing receptors, including G protein-coupled receptor 4 (GPR4), play an important role in the regulation of inflammatory and immune responses and GPR4 deficiency has been shown to be protective in IBD animal models. To confirm the therapeutic potential of GPR4 antagonism in IBD, we tested Compound 13, a selective GPR4 antagonist, in the IL10-/- mouse model of colitis. Despite reasonable bioavailability, Compound 13 treatment did not improve colitis in this model and there were no signs of target engagement. Interestingly, Compound 13 behaved as an “orthosteric” antagonist, i.e., its potency was pH-dependent and mostly inactive at pH levels lower than 6.8 with preferential binding to the inactive conformation of GPR4. Mutagenesis studies confirmed Compound 13 likely binds to the conserved orthosteric binding site in G protein-coupled receptors, where a histidine sits in GPR4 likely preventing Compound 13 binding when protonated in acidic conditions. While the exact mucosal pH in the human disease and relevant IBD mice models is unknown, it is well established that the degree of acidosis is positively correlated with the degree of inflammation, suggesting Compound 13 is not an ideal tool to study the role of GPR4 in moderate-to-severe inflammatory conditions.

ORGANISM(S): Mus musculus

PROVIDER: GSE225694 | GEO | 2024/01/03

REPOSITORIES: GEO

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Project description:Kilian2024 - Immune cell dynamics in Cue-Induced Extended Human Colitis Model Single-cell technologies such as scRNA-seq and flow cytometry provide critical insights into immune cell behavior in inflammatory bowel disease (IBD). However, integrating these datasets into computational models for dynamic analysis remains challenging. Here, Kilian et al., (2024) developed a deterministic ODE-based model that incorporates these technologies to study immune cell population changes in murine colitis. The model parameters were optimized to fit experimental data, ensuring an accurate representation of immune cell behavior over time. It was then validated by comparing simulations with experimental data using Pearson’s correlation and further tested on independent datasets to confirm its robustness. Additionally, the model was applied to clinical bulk RNA-seq data from human IBD patients, providing valuable insights into immune system dynamics and potential therapeutic strategies. Figure 4c, obtained from the simulation of human colitis model is highlighted here. This model is described in the article: Kilian, C., Ulrich, H., Zouboulis, V.A. et al. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. npj Syst Biol Appl 10, 69 (2024). https://doi.org/10.1038/s41540-024-00395-9 Abstract: Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease. This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.