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.
