PhyloPlus: a Universal Tool for Phylogenetic Interrogation of Metagenomic Communities.
PhyloPlus: a Universal Tool for Phylogenetic Interrogation of Metagenomic Communities.
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作者：
系统发育是一个强有力的工具，可以被纳入到社区多样性的定量描述，但它的使用一直受到限制，主要是由于在构建系统发育，包括广泛的基因组多样性的微生物群落的困难。在这里，我们描述了一个门户网站，PhyloPlus，它使用户能够生成定制的可应用于任何细菌或古菌群落的基因的发展。我们通过比较采用遗传学的指标与应用于两项宏基因组研究（发酵食品，n = 58;人类微生物组，n = 60）的数据集时不采用遗传学的指标来证明遗传学的力量。该实施例显示了包括由分类分类器（Kraken 2和Kaiju）鉴定的所有细菌物种如何使细菌发生与相应的分类输出完全一致。我们基于遗传学的方法还能够构建更多约束的空模型，这些模型（i）揭示了社区结构，（ii）最大限度地减少了I型错误的潜在膨胀。这种零模型的建设允许观察44个（75.86%）的食品样品中的分散不足，与metacompatibility定义为在不同的食品基质中发现的细菌。我们还观察到，如果使用传统的基于物种的指标来测量，不同地点之间丰度高且分布不均匀的密切相关物种可能会夸大遗传相似群落之间的差异（Padj. = 0.003），而这种影响是减轻了纳入hepatogeny（Padj. = 1）。总之，我们的工具可以提供对感兴趣的微生物群落的额外见解，并促进在宏基因组分析中使用基于遗传学的方法。
Phylogeny is a powerful tool that can be incorporated into quantitative descriptions of community diversity, yet its use has been limited largely due to the difficulty in constructing phylogenies which incorporate the wide genomic diversity of microbial communities. Here, we describe the development of a web portal, PhyloPlus, which enables users to generate customized phylogenies that may be applied to any bacterial or archaeal communities. We demonstrate the power of phylogeny by comparing metrics that employ phylogeny with those that do not when applied to data sets from two metagenomic studies (fermented food, n = 58; human microbiome, n = 60). This example shows how inclusion of all bacterial species identified by taxonomic classifiers (Kraken2 and Kaiju) made the phylogeny perfectly congruent to the corresponding classification outputs. Our phylogeny-based approach also enabled the construction of more constrained null models which (i) shed light into community structure and (ii) minimize potential inflation of type I errors. Construction of such null models allowed for the observation of under-dispersion in 44 (75.86%) food samples, with the metacommunity defined as bacteria that were found in different food matrices. We also observed that closely related species with high abundance and uneven distribution across different sites could potentially exaggerate the dissimilarity between phylogenetically similar communities if they were measured using traditional species-based metrics (Padj. = 0.003), whereas this effect was mitigated by incorporating phylogeny (Padj. = 1). In summary, our tool can provide additional insights into microbial communities of interest and facilitate the use of phylogeny-based approaches in metagenomic analyses.
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影响因子：
6.4
作者：
Dmitrijeva M;Kahlert CR;Feigelman R;Kleiner RL;Nolte O;Albrich WC;Baty F;von Mering C
通讯作者：
von Mering C
影响因子：
5.8
作者：
Kembel, Steven W.;Cowan, Peter D.;Webb, Campbell O.
通讯作者：
Webb, Campbell O.
影响因子：
5.9
作者：
FAITH, DP
通讯作者：
FAITH, DP
影响因子：
4.2
作者：
Caputo, Mahrrouz;Zoch-Lesniak, Beate;Mikolajczyk, Rafael T.
通讯作者：
Mikolajczyk, Rafael T.
DOI：
10.1073/pnas.1900506116
发表时间：
2019-07-23
影响因子：
11.1
作者：
Hind, Katharine R.;Starko, Samuel;Martone, Patrick T.
通讯作者：
Martone, Patrick T.