A guide to enterotypes across the human body: meta-analysis of microbial community structures in human microbiome datasets.
A guide to enterotypes across the human body: meta-analysis of microbial community structures in human microbiome datasets.
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DOI：
10.1371/journal.pcbi.1002863
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发表时间：
2013
影响因子：
4.3
通讯作者：
Ley RE
中科院分区：
文献类型：
--
作者：
Koren O;Knights D;Gonzalez A;Waldron L;Segata N;Knight R;Huttenhower C;Ley RE
最近对人类相关细菌多样性的分析根据肠道微生物群中关键细菌属的丰度将个体分为“肠型”或簇。然而，对于肠型的分析基础和这些结果的解释缺乏共识。我们测试了以下因素如何影响肠型检测：聚类方法、距离度量、OTU 挑选方法、测序深度、数据类型（全基因组鸟枪法 (WGS) 与 16S rRNA 基因序列数据）和 16S rRNA 区域。我们纳入了来自人类微生物组计划 (HMP) 和 16 项其他研究的 16S rRNA 基因序列以及来自 HMP 和 MetaHIT 的 WGS 序列。在大多数身体部位，我们观察到关键属的平滑丰度梯度，而没有离散的样本聚类。一些身体栖息地显示样本丰度的双峰（例如肠道）或多峰（例如阴道）分布，但并非所有聚类方法和工作流程都能准确突出此类聚类。由于识别数据集中的肠型不仅取决于数据的结构，而且还对用于识别聚类强度的方法敏感，因此我们建议在测试肠型时使用多种方法并进行比较。最近的研究表明，可以根据肠道微生物群落中关键细菌类群的丰度将个体分为“肠型”。然而，不同人群肠型的普遍性以及其他身体部位是否存在类似的簇类型仍有待评估。我们将人类微生物组计划 16S rRNA 基因序列数据和宏基因组与类似的已发表数据相结合，以评估跨身体部位肠型的存在。我们发现，大多数样本不是形成肠型（请注意，我们使用这个术语来表示所有身体部位的簇），而是根据拟杆菌等细菌的分类丰度落入梯度，尽管在某些身体部位，样本在梯度上存在双/多模态分布。此外，分析中使用的许多方法（例如距离度量和聚类方法）影响了在特定身体栖息地识别肠型的可能性。我们建议在测试肠型时使用并比较多种方法。
Recent analyses of human-associated bacterial diversity have categorized individuals into ‘enterotypes’ or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes. Recent work has suggested that individuals can be classified into ‘enterotypes’ based on the abundance of key bacterial taxa in gut microbial communities. However, the generality of enterotypes across populations, and the existence of similar cluster types for other body sites, remains to be evaluated. We combined the Human Microbiome Project 16S rRNA gene sequence data and metagenomes with similar published data to assess the existence of enterotypes across body sites. We found that rather than forming enterotypes (note we use this term for clusters in all body sites), most samples fell into gradients based on taxonomic abundances of bacteria such as Bacteroides, although in some body sites there is a bi/multi modal distribution of samples across gradients. Furthermore, many of the methods used in the analysis (e.g., distance metrics and clustering approaches) affected the likelihood of identifying enterotypes in particular body habitats. We recommend that multiple approaches be used and compared when testing for enterotypes.
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影响因子：
3.7
作者：
Kumar PS;Brooker MR;Dowd SE;Camerlengo T
通讯作者：
Camerlengo T
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
64.8
作者：
Arumugam, Manimozhiyan;Raes, Jeroen;Pelletier, Eric;Le Paslier, Denis;Yamada, Takuji;Mende, Daniel R.;Fernandes, Gabriel R.;Tap, Julien;Bruls, Thomas;Batto, Jean-Michel;Bertalan, Marcelo;Borruel, Natalia;Casellas, Francesc;Fernandez, Leyden;Gautier, Laurent;Hansen, Torben;Hattori, Masahira;Hayashi, Tetsuya;Kleerebezem, Michiel;Kurokawa, Ken;Leclerc, Marion;Levenez, Florence;Manichanh, Chaysavanh;Nielsen, H. Bjorn;Nielsen, Trine;Pons, Nicolas;Poulain, Julie;Qin, Junjie;Sicheritz-Ponten, Thomas;Tims, Sebastian;Torrents, David;Ugarte, Edgardo;Zoetendal, Erwin G.;Wang, Jun;Guarner, Francisco;Pedersen, Oluf;de Vos, Willem M.;Brunak, Soren;Dore, Joel;Weissenbach, Jean;Ehrlich, S. Dusko;Bork, Peer
通讯作者：
Bork, Peer
影响因子：
3
作者：
MILLIGAN, GW;COOPER, MC
通讯作者：
COOPER, MC
DOI：
10.1073/pnas.1002601107
发表时间：
2010-06-29
影响因子：
11.1
作者：
Dominguez-Bello, Maria G.;Costello, Elizabeth K.;Knight, Rob
通讯作者：
Knight, Rob