Beyond Taxonomic Identification: Integration of Ecological Responses to a Soil Bacterial 16S rRNA Gene Database.
Beyond Taxonomic Identification: Integration of Ecological Responses to a Soil Bacterial 16S rRNA Gene Database.
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DOI：
10.3389/fmicb.2021.682886
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发表时间：
2021
影响因子：
5.2
通讯作者：
Griffiths RI
中科院分区：
文献类型：
--
作者：
Jones B;Goodall T;George PBL;Gweon HS;Puissant J;Read DS;Emmett BA;Robinson DA;Jones DL;Griffiths RI
高通量16S rRNA基因测序研究使人们对土壤细菌多样性有了新的认识，并进一步了解了不同景观中细菌丰度的生态驱动因素。然而，目前的分析方法在将已发现的分类群的生态属性综合形式化方面的作用有限，因为衍生的分类单位通常是个别研究所独有的，而序列鉴定数据库仅表征分类。为了解决这一问题，我们利用从全国大型土壤调查（GB rural survey，简称CS）中获得的序列，建立了一个综合的土壤特异性16S参考数据库，并结合了从调查元数据中获得的生态信息。具体而言，我们利用层次逻辑回归（HOF）模型在OTU水平上模拟了分类单元对土壤pH的响应，以提供景观尺度pH丰度响应的形状和pH最优值（OTU丰度最大的pH值）的信息。我们发现，大多数土壤otu与土壤pH呈非平坦关系。此外，pH的最优值不能通过广泛的分类来概括，这突出表明需要在更精细的分类分辨率下综合生态性状的工具和数据库。通过对地理上分散的查询16S数据集进行测试，我们进一步展示了该数据库的实用性；通过量化匹配来评估有效性，以及预测来自单独的大型土壤调查的查询序列的pH响应的准确性。我们发现CS数据库提供了很好的优势分类群覆盖率；查询数据集中指示土壤pH的分类群与CS数据库中top匹配的pH分类相对应。此外，利用基于土壤pH值的优势类群丰度预测和匹配CS数据库分类群的HOF模型，可以预测查询数据集的群落结构。具有相关HOF模型输出的数据库作为在线门户发布，用于查询感兴趣的单个序列（https://shiny-apps.ceh.ac）。uk/ID-TaxER/)，并提供平面文件供生物信息学管道使用。结合模拟生态属性和新的功能基因组信息的先进信息学基础设施的进一步发展，可能有助于在当前和未来环境变化情景下大规模探索和预测土壤微生物功能生物多样性。
High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalizing syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterize taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth CS) to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from survey metadata. Specifically, we modeled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on both the shape of landscape scale pH-abundance responses, and pH optima (pH at which OTU abundance is maximal). We identify that most of the soil OTUs examined exhibited a non-flat relationship with soil pH. Further, the pH optima could not be generalized by broad taxonomy, highlighting the need for tools and databases synthesizing ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER/), and flat files are made available for use in bioinformatic pipelines. The further development of advanced informatics infrastructures incorporating modeled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.
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DOI：
10.1073/pnas.1000080107
发表时间：
2011-03-15
影响因子：
11.1
作者：
Caporaso, J. Gregory;Lauber, Christian L.;Knight, Rob
通讯作者：
Knight, Rob
影响因子：
2.8
作者：
Jansen, Florian;Oksanen, Jari
通讯作者：
Oksanen, Jari
影响因子：
4.4
作者：
Kozich, James J.;Westcott, Sarah L.;Schloss, Patrick D.
通讯作者：
Schloss, Patrick D.
影响因子：
11
作者：
Martiny, Adam C.;Treseder, Kathleen;Pusch, Gordon
通讯作者：
Pusch, Gordon
影响因子：
28.3
作者：
Brewer, Tess E.;Handley, Kim M.;Fierer, Noah
通讯作者：
Fierer, Noah