目的:独家肠内营养[EEN]是一种饮食干预措施,可在患有活动性克罗恩病[CD]的儿童中引起临床缓解。虽然肠道微生物群落的变化与实现这种缓解有关,缺乏对微生物生态学在恢复肠道稳态中的作用的精确理解。
方法:在这里,我们从12名儿科受试者的肠道宏基因组中重建了基因组,在EEN期间和之后。然后,我们根据每个个体在整个治疗过程中相对丰度的变化,将每个微生物群体分为不同的“表型”或反应模式。
结果:我们的数据表明,在治疗期间获得临床缓解的儿童富含微生物种群,这些微生物种群要么被抑制,要么被证明是EEN的功能。相比之下,在EEN失败的情况下,未观察到这种生态系统水平的响应。进一步的分析显示,与治疗期间短暂开花的人群相比,在EEN期间受到抑制的人群在全球健康儿童和成人中更为普遍。
结论:这些观察结果共同表明,EEN的成功结果是健康个体中罕见的微生物种群的暂时出现。并伴随着通常与肠道稳态相关的微生物的减少。我们的工作是第一次尝试突出个人的特点,影响EEN中微生物反应的复杂环境因素。这个模型提供了一个小说,用于表征与健康和疾病状态关联的传统分类策略的替代观点。
OBJECTIVE: Exclusive enteral nutrition [EEN] is a dietary intervention to induce clinical remission in children with active luminal Crohn\'s disease [CD]. While changes in the gut microbial communities have been implicated in achieving this remission, a precise understanding of the role of microbial ecology in the restoration of gut homeostasis is lacking.
METHODS: Here we reconstructed genomes from the gut metagenomes of 12 paediatric subjects who were sampled before, during and after EEN. We then classified each microbial population into distinct \'phenotypes\' or patterns of response based on changes in their relative abundances throughout the therapy on a per-individual basis.
RESULTS: Our data show that children achieving clinical remission during therapy were enriched with microbial populations that were either suppressed or that demonstrated a transient bloom as a function of EEN. In contrast, this ecosystem-level response was not observed in cases of EEN failure. Further analysis revealed that populations that were suppressed during EEN were significantly more prevalent in healthy children and adults across the globe compared with those that bloomed ephemerally during the therapy.
CONCLUSIONS: These observations taken together suggest that successful outcomes of EEN are marked by a temporary emergence of microbial populations that are rare in healthy individuals, and a concomitant reduction in microbes that are commonly associated with gut homeostasis. Our work is a first attempt to highlight individual-specific, complex environmental factors that influence microbial response in EEN. This model offers a novel, alternative viewpoint to traditional taxonomic strategies used to characterize associations with health and disease states.