Towards a mechanistic understanding of the role of gut microbiota in postnatal growth impairment

项目总结 肠道微生物区系的精密工程需要对微生物如何与 寄主生理途径，以产生预期的健康结果。发育迟缓儿童的共生肠道 微生物与异常宿主炎症和生长障碍相关，但机制 人们对这些联系背后的理解很少。老鼠模型已经提出了因果关系，但他们未能做到 重述人类粘膜免疫系统的动态和人类肠道的复杂性 微生物区系。该项目将在活体中询问1500名农村儿童的这些问题 孟加拉国面临发育迟缓的风险，生物标本是从0-3岁的纵向收集的 年龄。3700份儿童粪便标本16S rRNA基因序列初步分析 已经发现了一种双歧杆菌序列变体，它与肠道炎症和 随后的增长步履蹒跚。在目标1中，我将识别可能调节这些的特定菌株的微生物基因。 观察到的关联。在目标2中，我将通过评估微生物微小的- 粪便和血液中的分子代谢物与高水平的双歧杆菌和同时存在的肠道和/或 14个月大的儿童全身炎症。在目标3中，我将使用高级潜在变量统计建模 确定相关微生物组(分类学、后基因组学和代谢学)和 宿主(肠道和全身炎症)特征对未来的增长步履蹒跚。我也会估计最大 从理论上100%有效的微生物区系操作可实现儿童成长的改善 干预，提供预期效果大小，以便与其他干预替代方案进行比较。这项工作将 增加我们对早期生命肠道微生物区系和异常之间联系的机械性理解 肠道/全身炎症以及未来的增长步履蹒跚，为可预见的 操纵肠道微生物区系以减轻不利的健康后果。拟议的项目将提供一个 在肠道微生物区系、微生物代谢物、多元统计和 在一群科学专家的指导下，儿科胃肠病学，并将装备我的技能 成为一名独立研究人员所必需的。

PROJECT SUMMARY Precision engineering of the gut microbiota requires a mechanistic understanding of how microbes interact with host physiological pathways in order to produce desired health outcomes. In stunted children, commensal gut microbes have been correlated with aberrant host inflammation and growth impairment, but mechanisms underlying these associations are poorly understood. Mouse models have suggested causality, but they fail to recapitulate the dynamics of the mucosal immune system in humans and the complexity of the human gut microbiota. This project will interrogate these questions in vivo in a cohort of >1500 children from rural Bangladesh at risk for stunting, for which biological specimens were collected longitudinally from 0-3 years of age. Preliminary analysis of 16S rRNA gene sequences from >3700 fecal samples collected from these children has identified a Bifidobacterium sequence variant that is highly correlated with intestinal inflammation and subsequent growth faltering. In Aim 1, I will identify strain-specific microbial genes that might mediate these observed associations. In Aim 2, I will interrogate the mechanistic underpinnings by evaluating microbial small- molecule metabolites in feces and blood associated with high levels of Bifidobacterium and concurrent gut and/or systemic inflammation in children 14 months old. In Aim 3, I will use advanced latent variable statistical modeling to determine the importance of associated groups of microbial (taxonomic, metagenomic, and metabolic) and host (gut and systemic inflammation) features on future growth faltering. I will also estimate the maximum achievable improvement in child growth from a theoretical, 100% efficacious microbiota-manipulation intervention, providing an expected effect size for comparison with other intervention alternatives. This work will increase our mechanistic understanding of the associations between early life gut microbiota and aberrant intestinal/systemic inflammation as well as future growth faltering, producing new options for predictably manipulating the gut microbiota to mitigate adverse health outcomes. The proposed project will provide a rigorous training experience in the fields of gut microbiota, microbial metabolites, multivariate statistics, and pediatric gastroenterology under the mentorship of a group of scientific experts, and will equip me with the skills necessary to become an independent researcher.