Quantitative analysis of early follicular helper T cell development using spatiotemporal modeling and in vivo mouse models

T滤泡辅助（Tfh）细胞是在生发中心反应期间为B细胞提供帮助的CD 4 + T细胞亚群，因此是有吸引力的治疗靶点，例如在抗体介导的自身免疫疾病的情况下。尽管该T细胞亚群的中心生物学作用，但Tfh细胞分化仍不完全清楚。这在很大程度上与以下事实有关，即与其他CD 4 + T细胞亚群如Th 1、Th 2和Th 17相反，Tfh细胞不能在体外产生，这表明该Th亚群的发育需要次级淋巴器官（SLO）的复杂环境。在SLO中，越来越多的证据表明免疫细胞群中存在空间细胞因子梯度，至少在IL-2的充分研究的情况下是如此。我们和其他人先前的数学建模研究预测局部IL-2浓度差异超过1个数量级或更多。最近的体内研究表明，SLO内高和低IL-2的微解剖区域对于Tfh和Th 1发育之间的命运决定至关重要。然而，许多其他细胞因子的梯度和它们的动态相互作用，以及Th细胞分化的生物学后果，在很大程度上仍然是一个未知的领域。在这里，我们将使用一个跨学科的单细胞实验，高分辨率定量组织学和时空建模相结合，以获得一个定量的“制图”的Th细胞信号和分化动力学在非常早期阶段的Tfh细胞分化。具体而言，我们将使用小鼠模型，其允许在免疫后的几个早期时间点直接离体分析抗原特异性T细胞和淋巴组织。数据驱动的建模将允许参数范围的系统表征，并因此得出关于扰动（如细胞因子阻断抗体）影响的预测。反过来，这样的模型预测可以在项目内通过直接评估组织样本来进一步评估，在闭环“系统生物学的迭代循环”中。总之，我们的研究将获得功能，定量的洞察Tfh细胞分化过程中的早期决策过程的组织架构，并进入一般的时空细胞间通讯信号动力学。

T follicular helper (Tfh) cells are the CD4+ T cell subset providing help for B cells during the germinal center reaction, and therefore are an attractive therapeutic target, for instance in the context of antibody-mediated autoimmune diseases. Despite the central biological role of this T cell subset, Tfh cell differentiation is still incompletely understood. This is largely related to the fact, that in contrast to other CD4+ T cell subsets like Th1, Th2 and Th17, Tfh cells cannot be generated in vitro, suggesting that development of this Th subset requires the complex environment of secondary lymphoid organs (SLO). Within SLO, accumulating evidence suggests the occurrence of spatial cytokine gradients among immune cell populations, at least in the well-studied case of IL-2. Previous mathematical modeling studies by us and others predicted local IL-2 concentration differences over 1 order of magnitude and more. Recent in vivo studies demonstrated that microanatomical regions of high and low IL-2 within SLO are crucial for the fate decision between Tfh and Th1 development. Nevertheless, gradients of many other cytokines and their dynamic interplay, as well as biological consequences for Th cell differentiation, remain largely an uncharted area. Here, we will use an interdisciplinary combination of single-cell experiments, high-resolution quantitative histology, and spatio-temporal modeling, to derive a quantitative “cartography” of Th cell signaling and differentiation dynamics in the very early phases of Tfh cell differentiation. Specifically, we will use a mouse model that allows analyzing antigen-specific T cells and lymphoid tissue directly ex vivo at several early time points after immunization. Data-driven modeling will allow systematic characterization of the parameter range and will thus derive predictions regarding the effect of perturbations such as cytokine blocking antibodies. In turn, such model predictions can be further assessed within the project by direct assessment of tissue samples, in a closed-loop “iterative cycle of systems biology”. Taken together, our study will gain functional, quantitative insights into the tissue architecture of early decision-making processes during Tfh cell differentiation, and into spatio-temporal cell-cell communication signaling dynamics in general.