Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.
Linking Spatial Structure and Community-Level Biotic Interactions through Cooccurrence and Time Series Modeling of the Human Intestinal Microbiota.
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DOI：
10.1128/msystems.00086-17
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发表时间：
2017-09
期刊：
影响因子：
6.4
通讯作者：
Trosvik P
中科院分区：
文献类型：
--
作者：
de Muinck EJ;Lundin KEA;Trosvik P
人体肠道微生物群因其对健康和疾病的重要性而受到广泛研究。这些研究大多是基于对粪便的分析。然而，粪便样品中的微生物组成与胃肠道微生物类群的空间分布之间的关系尚不清楚。通过描述肠道组织样本和日常粪便样本中的微生物含量，我们为空间结构如何与群落水平上的生物相互作用相关提供了一个概念框架。我们进一步描述了空间分布格局的一般类别，并确定了符合这些类别的分类群。据我们所知，这是第一个将人类肠道微生物组的时空分析结合起来的研究。这种类型的分析可用于确定候选益生菌和设计临床干预策略。胃肠道（GI）微生物组是一个人口密集的生态系统，其动态是由微生物群落成员之间的相互作用以及宿主因素决定的。这个系统的空间组织被认为对人类健康很重要，然而我们的常驻微生物组的这方面仍然知之甚少。在这项研究中，我们报告了胃肠道微生物群的显著空间结构，并确定了健康人类胃肠道微生物类群分布的一般空间格局。我们通过对大量连续收集的粪便样本的微生物群落数据进行时间序列和共发生建模，进一步估计了胃肠道微生物群中的生物相互作用结构。两种方法的比较表明，具有显著负相互作用的物种对具有较强的正同期相关性，反之亦然，而对于没有显著相互作用的物种对，同期相关性分布在零附近。当将这些模型与附着微生物群中确定的分类群之间的空间相关性进行比较时，我们观察到类似的模式。这表明微生物分类群对的共定位，以及胃肠道微生物群的空间组织，至少在一定程度上是由直接或间接的生物相互作用驱动的。因此，我们的研究可以为人类肠道生物地理学的生态学解释提供基础。人体肠道微生物群因其对健康和疾病的重要性而成为人们深入研究的主题。这些研究大多是基于对粪便的分析。然而，粪便样品中的微生物组成与胃肠道微生物类群的空间分布之间的关系尚不清楚。通过描述肠道组织样本和日常粪便样本中的微生物含量，我们为空间结构如何与群落水平上的生物相互作用相关提供了一个概念框架。我们进一步描述了空间分布格局的一般类别，并确定了符合这些类别的分类群。据我们所知，这是第一个将人类肠道微生物组的时空分析结合起来的研究。这种类型的分析可用于确定候选益生菌和设计临床干预策略。作者视频：本文的作者视频摘要是可用的。
The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention. The gastrointestinal (GI) microbiome is a densely populated ecosystem where dynamics are determined by interactions between microbial community members, as well as host factors. The spatial organization of this system is thought to be important in human health, yet this aspect of our resident microbiome is still poorly understood. In this study, we report significant spatial structure of the GI microbiota, and we identify general categories of spatial patterning in the distribution of microbial taxa along a healthy human GI tract. We further estimate the biotic interaction structure in the GI microbiota, both through time series and cooccurrence modeling of microbial community data derived from a large number of sequentially collected fecal samples. Comparison of these two approaches showed that species pairs involved in significant negative interactions had strong positive contemporaneous correlations and vice versa, while for species pairs without significant interactions, contemporaneous correlations were distributed around zero. We observed similar patterns when comparing these models to the spatial correlations between taxa identified in the adherent microbiota. This suggests that colocalization of microbial taxon pairs, and thus the spatial organization of the GI microbiota, is driven, at least in part, by direct or indirect biotic interactions. Thus, our study can provide a basis for an ecological interpretation of the biogeography of the human gut. IMPORTANCE The human gut microbiome is the subject of intense study due to its importance in health and disease. The majority of these studies have been based on the analysis of feces. However, little is known about how the microbial composition in fecal samples relates to the spatial distribution of microbial taxa along the gastrointestinal tract. By characterizing the microbial content both in intestinal tissue samples and in fecal samples obtained daily, we provide a conceptual framework for how the spatial structure relates to biotic interactions on the community level. We further describe general categories of spatial distribution patterns and identify taxa conforming to these categories. To our knowledge, this is the first study combining spatial and temporal analyses of the human gut microbiome. This type of analysis can be used for identifying candidate probiotics and designing strategies for clinical intervention. Author Video: An author video summary of this article is available.