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

越来越多的证据表明，肠-骨轴是绝经后妇女有希望的治疗靶点。 骨质疏松卵巢激素缺乏诱导效应T细胞的肠道微生物群依赖性转变 群体（例如，辅助性T细胞17 [Th 17]和调节性T细胞[Treg]，它们在肠道和骨髓中破坏 骨稳态并导致骨丢失。虽然肠道微生物群被认为在 对于这种骨免疫反应，人们对肠道树突状细胞的信号传导知之甚少， 将这些局部效应转化为系统性T细胞应答。益生元，如低聚糖， 肠道内微生物的底物。肠道微生物群发酵低聚糖 产生代谢物，其有利地影响肠上皮细胞内衬粘膜和免疫细胞内， 肠淋巴组织益生菌诱导免疫和骨反应机制的研究 已经遇到了实验挑战，即那些在研究相互作用时遇到的挑战。 在多个生理系统之间。在这个R21项目中，我们建议研究树突状细胞介导的 骨和T细胞对雌激素缺乏和B-低聚半乳糖（B-GOS）益生元饮食的反应 本发明使用计算机模拟的组合在外周（骨和血液）和局部在肠道中进行 数学模型和体内动物模型。我们将开发的数学模型将侧重于 B-GOS和雌激素通过T细胞和树突状细胞调节的相互作用系统。该模型将 使用微分方程来跟踪肠道中的免疫细胞、细胞因子、激素和代谢物， 外周血和骨隔室。该模型将建立在我们的文献知情的初步 模型的相互作用，在肠道-骨骼轴，以响应饮食干预，并将完善 与研究中收集的实验数据相比，特别是增加了树突细胞的作用， 雌激素和不同的T细胞群。除了细胞因子和代谢物的蛋白质分析外， 从体内研究中获得，我们将使用计算去卷积方法来推断细胞类型特异性 来自异质样品的转录谱。转录组学数据旨在提供更多 比单独的流式细胞术更全面的免疫应答信息， 从初步计算模型中排除的相互作用，例如，树突状细胞该项目乃设计 提供关于饮食B-GOS刺激的树突状细胞和T细胞免疫应答的关键数据 在完整和卵巢激素缺乏动物模型中补充。成功完成本 该项目将产生一个预测性的数学模型，可用作解释可能机制的工具 了解局部肠道刺激和免疫反应如何相互作用，产生外周表型变化， 设计未来的实验，并确定关键控制点内的肠骨轴的设计和 优化治疗策略。

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.