DataSheet_2_Systems and computational analysis of gene expression datasets reveals GRB-2 suppression as an acute immunomodulatory response against enteric infections in endemic settings.csv

IntroductionEnteric infections are a major cause of under-5 (age) mortality in low/middle-income countries. Although vaccines against these infections have already been licensed, unwavering efforts are required to boost suboptimalefficacy and effectiveness in regions that are highly endemic to enteric pathogens. The role of baseline immunological profiles in influencing vaccine-induced immune responses is increasingly becoming clearer for several vaccines. Hence, for the development of advanced and region-specific enteric vaccines, insights into differences in immune responses to perturbations in endemic and non-endemic settings become crucial.
Materials and methodsFor this reason, we employed a two-tiered system and computational pipeline (i) to study the variations in differentially expressed genes (DEGs) associated with immune responses to enteric infections in endemic and non-endemic study groups, and (ii) to derive features (genes) of importance that keenly distinguish between these two groups using unsupervised machine learning algorithms on an aggregated gene expression dataset. The derived genes were further curated using topological analysis of the constructed STRING networks. The findings from these two tiers are validated using multilayer perceptron classifier and were further explored using correlation and regression analysis for the retrieval of associated gene regulatory modules.
ResultsOur analysis reveals aggressive suppression of GRB-2, an adaptor molecule integral for TCR signaling, as a primary immunomodulatory response against S. typhi infection in endemic settings. Moreover, using retrieved correlation modules and multivariant regression models, we found a positive association between regulators of activated T cells and mediators of Hedgehog signaling in the endemic population, which indicates the initiation of an effector (involving differentiation and homing) rather than an inductive response upon infection. On further exploration, we found STAT3 to be instrumental in designating T-cell functions upon early responses to enteric infections in endemic settings.
ConclusionOverall, through a systems and computational biology approach, we characterized distinct molecular players involved in immune responses to enteric infections in endemic settings in the process, contributing to the mounting evidence of endemicity being a major determiner of pathogen/vaccine-induced immune responses. The gained insights will have important implications in the design and development of region/endemicity-specific vaccines.

引言
肠道感染是低、中等收入国家5岁以下儿童死亡的主要诱因。尽管针对此类感染的疫苗已获批上市，但仍需持之以恒地开展优化工作，以提升肠道病原体高流行地区疫苗的亚最佳效力与保护效果。多项疫苗的研究已愈发明确，基线免疫谱会对疫苗诱导的免疫应答产生影响。因此，为开发更先进的、针对特定区域的肠道感染疫苗，明晰流行区与非流行区环境下病原体侵染引发的免疫应答差异，便显得尤为关键。

材料与方法
基于上述背景，本研究采用双层研究系统与计算分析流程开展两项工作：(i) 分析流行区与非流行区研究群体中，与肠道感染免疫应答相关的差异表达基因（differentially expressed genes, DEGs）的表达差异；(ii) 基于聚合基因表达数据集，通过无监督机器学习算法提取可精准区分这两类群体的关键特征基因。随后，通过对构建完成的STRING网络（STRING networks）进行拓扑分析，对提取得到的特征基因进行进一步筛选与整理。采用多层感知器分类器（multilayer perceptron classifier）对上述两个层级的分析结果进行验证，并通过相关性与回归分析进一步探索，以获取相关的基因调控模块。

结果
本研究分析发现，在流行区环境下，针对伤寒沙门氏菌（S. typhi）感染的主要免疫调节应答，表现为对T细胞受体（TCR）信号通路关键接头分子生长因子受体结合蛋白2（GRB-2）的强效抑制。此外，通过提取的相关性模块与多元回归模型，本研究在流行区群体中发现，活化T细胞调控因子与Hedgehog信号通路（Hedgehog signaling）介质之间存在正相关关系，这表明感染后引发的是效应应答（涵盖细胞分化与归巢过程）而非诱导应答。进一步探索还发现，在流行区环境下，信号转导与转录激活因子3（STAT3）在肠道感染早期应答中对T细胞功能的调控发挥着关键作用。

结论
综上，本研究通过系统与计算生物学方法，对流行区环境下肠道感染免疫应答涉及的独特分子效应因子进行了表征，进一步佐证了流行状态是决定病原体/疫苗诱导免疫应答的关键因素这一结论。本研究所得的见解，将为设计与开发针对特定区域或特定流行状态的疫苗提供重要参考。