Mathematical Modeling of the Impacts of Prebiotic Dietary Intervention on Immunomodulation During Estrogen Deficiency

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A growing body of evidence points to the gut-bone axis as a promising therapeutic target for postmenopausal osteoporosis. Ovarian hormone deficiency induces a gut microbiota-dependent shift in effector T cell populations (e.g., T helper 17 [Th17] and T regulatory [TREG] cells) within the gut and bone marrow that disrupt bone homeostasis and lead to bone loss. Although the gut microbiota is recognized for playing a critical role in this osteoimmunological response, little is known about the signaling of gut resident dendritic cells that translates these local effects into systemic T cell responses. Prebiotics such as oligosaccharides serve as substrates for microorganisms residing within the gut. Fermentation of oligosaccharides by gut microbiota yields metabolites that favorably affect intestinal epithelial cells lining the mucosa and immune cells within the gut lymphoid tissues. The investigation of the mechanisms of prebiotic-induced immune and bone responses has been met with experimental challenges, namely those encountered when studying the interactions between multiple physiological systems. In this R21 project, we propose to study the dendritic cell-mediated bone and T cell responses to estrogen deficiency and to B-galactooligosaccharides (B-GOS) prebiotic dietary invention in the periphery (bone and blood) and locally in the gut using a combination of in silico mathematical models and in vivo animal models. The mathematical model we will develop will focus on the interacting systems modulated by B-GOS and by estrogen through T cells and dendritic cells. The model will use differential equations to track immune cells, cytokines, hormones, and metabolites in the gut and peripheral blood and bone compartments. The model will build from our literature-informed preliminary model of the interactions in the gut-bone axis in response to dietary intervention and will be refined by comparison to the experimental data collected in the study, specifically adding the roles of dendritic cells, estrogen, and different T cell populations. In addition to protein analysis of the cytokines and metabolites obtained from in vivo studies, we will use computational deconvolution methods to infer cell type-specific transcriptional profiles from heterogeneous samples. The transcriptomics data is intended to provide more comprehensive immune response information than flow cytometry alone and to be exploratory of cellular interactions excluded from the preliminary computational model, e.g., dendritic cells. This project is designed to provide key data about the dendritic cell and T cell immune responses stimulated by dietary B-GOS supplementation in both intact and ovarian hormone deficient animal models. Successful completion of this project will yield a predictive mathematical model that can be used as a tool to explain possible mechanisms for how local gut stimuli and immune responses interact to yield peripheral phenotype changes, to inform the design of future experiments, and to identify critical control points within the gut-bone axis for designing and optimizing treatment strategies.