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Bioinformatics, Computational and Systems Biology

Bioinformatics, Computational and Systems Biology - Poster Session E

Poster L30 - Meta-analysis of oxytocin receptor trafficking data reveals similar rates across GPCRs.

Saturday, October 26, 2024
10:00 AM – 11:00 AM EST
Location: Exhibit Hall E, F & G

Introduction:  Synthetic oxytocin is used to induce uterine contractions in approximately half of the four million women giving birth in the United States each year. However, the dosage varies up to 20-fold due to differences in patient responses. Our recent findings suggest impaired trafficking of the oxytocin receptor (OXTR) to the cell surface reduces oxytocin signaling ​[1]​, potentially explaining the need for higher doses in some patients.​​ The precise dysfunction of these steps in uterine cells and their impact on OXTR signaling remains unclear. Developing computational models that recapitulate these processes and offer patient-specific personalization will help unravel the complexity of OXTR trafficking, providing mechanistic insights to inform personalized oxytocin treatments. However, the limited availability of OXTR-specific trafficking data poses a significant challenge. To overcome this, we performed a meta-analysis of trafficking data on OXTR-like GPCRs when OXTR-specific data is unavailable. Our meta-analysis will enhance understanding of GPCR trafficking and aid in developing a predictive computational model to improve the efficacy and safety of oxytocin in labor and delivery.

Materials and

Methods:  We performed a literature search through PubMed, Google Scholar, BioModels, B10NUMB3R5, LitSense and the University of Washington Libraries obtaining trafficking rates (Table) from 59 studies, with 132 independent values collected. Inclusion criteria was based on mammalian cell type, class A GPCRs, and experimental assays. We used the Python PyMC3 library to analyze data with two models: 1) Bayesian hierarchical model (BHM) with varying intercepts and 2) a random-effects model (REM) to calculate the weighted average, standard deviation, and evaluate heterogeneity.

Results, Conclusions, and Discussions: Six out of 11 trafficking kinetic parameters (kP, kdp, krecEE, kexpt, krgt, kdeg) exhibited closely similar mean values, all falling within the same order of magnitude across both models. This uniformity suggests a consistent intracellular kinetic profile across OXTR and OXTR-like GPCRs. Similarly remarkable, ten out of the eleven parameters demonstrated minimal variability, with 95% confidence intervals (CIs) falling within two orders of magnitude. This consistency may indicate universal regulatory control mechanisms that ensure efficient receptor trafficking and signaling. Early steps in the trafficking process are expected to have faster rates due to initial high-energy conditions. This trend aligns with the reaction rates observed here and in other studies. [4, 5].
Both models yielded mean values that differ by at most one magnitude, except for kinact. This discrepancy can be attributed to the biological variability of G-protein, GPCRs interactions. [3].The REM model produced a CI with a negative lower bound krgt, [-1.41×10-3, 4.06×10-2], which is biologically implausible, underscoring a model challenge in discerning normally distributed means on the lower bound. Additionally, the REM model faces limitations when applied to studies with small sample sizes (n=3). In such cases, the model may struggle to generate a reliable distribution for the CI. While these limitations do not invalidate the model outright, they emphasize the importance of cautious interpretation, especially when the model's assumptions diverge from real-world data constraints. The similarity between results from the models analysis of kp, kexpt, krgt and kdeg, may be explained by homogeneity of these reactions across GPCRs. The consistent rate kinetic results, especially for intracellular parameters, suggest a robust system. Despite diverse receptors, ligands, and binding partners, the fundamental intracellular processes show similar kinetics in OXTR-like GPCRs. This could hint at a universal regulatory mechanism ensuring efficient receptor trafficking.

Conclusions: We addressed the lack of experimental data for OXTR trafficking by curating and analyzing OXTR-like GPCR data, laying the groundwork for developing trafficking models of OXTR. These models will serve as in-silico testing beds for potential drugs, critical to addressing maladaptive OXTR signaling during labor ​[1]​.

Acknowledgements (Optional):