Joint Institute for Food Safety and Applied Nutrition, Center for Food Safety Security Systems, University of Maryland, College Park, Maryland, USA.
Department of Nutrition and Food Science, University of Maryland, College Park, Maryland, USA.
mBio. 2023 Feb 28;14(1):e0345522. doi: 10.1128/mbio.03455-22. Epub 2023 Jan 16.
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, = 58; human microbiome, = 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 ( = 0.003), whereas this effect was mitigated by incorporating phylogeny ( = 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. There has been an explosion of interest in how microbial diversity affects human health, food safety, and environmental functions among many other processes. Accurately measuring the diversity and structure of those communities is central to understanding their effects. Here, we describe the development of a freely available online tool, PhyloPlus, which allows users to generate custom phylogenies that may be applied to any data set, thereby removing a major obstacle to the application of phylogeny to metagenomic data analysis. We demonstrate that the genetic relatedness of the organisms within those communities is a critical feature of their overall diversity, and that using a phylogeny which captures and quantifies this diversity allows for much more accurate descriptions while preventing misleading conclusions based on estimates that ignore evolutionary relationships.
系统发生是一种强大的工具，可以将其纳入社区多样性的定量描述中，但由于难以构建包含微生物群落广泛基因组多样性的系统发生，因此其应用受到很大限制。在这里，我们描述了一个网络门户 PhyloPlus 的开发，该门户使用户能够生成可应用于任何细菌或古菌群落的自定义系统发生。我们通过将使用系统发生和不使用系统发生的度量标准应用于来自两项宏基因组研究的数据集中（发酵食品， = 58；人类微生物组， = 60），证明了系统发生的强大功能。这个例子表明，通过分类器（Kraken2 和 Kaiju）识别的所有细菌物种的纳入使系统发生与相应的分类学输出完全一致。我们基于系统发生的方法还能够构建更受限制的零模型，这些模型（i）阐明群落结构，（ii）最小化潜在的 I 型错误膨胀。构建这样的零模型允许观察到 44 个（75.86%）食品样本中存在过度分散的现象，而宏群落被定义为在不同的食物基质中发现的细菌。我们还观察到，如果使用传统的基于物种的度量标准（ = 0.003）来测量高度丰富且在不同地点分布不均匀的密切相关的物种，则它们可能会夸大在系统发生上相似的群落之间的差异，而通过纳入系统发生（ = 1）则可以减轻这种影响。总之，我们的工具可以为感兴趣的微生物群落提供更多的见解，并促进在宏基因组分析中使用基于系统发生的方法。微生物多样性如何影响人类健康、食品安全和许多其他过程中的环境功能，引起了人们的极大兴趣。准确测量这些群落的多样性和结构是理解其影响的核心。在这里，我们描述了一种免费在线工具 PhyloPlus 的开发，该工具允许用户生成可应用于任何数据集的自定义系统发生，从而消除了将系统发生应用于宏基因组数据分析的主要障碍。我们证明，这些群落中生物体的遗传关系是其整体多样性的关键特征，并且使用捕获和量化这种多样性的系统发生可以允许更准确的描述，同时防止基于忽略进化关系的估计而得出误导性结论。
