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Comprehensive Meta-analysis of Ontology Annotated 16S rRNA Profiles Identifies Beta Diversity Clusters of Environmental Bacterial Communities

机译:本体注释的16S rRNA配置文件的全面荟萃分析确定了环境细菌群落的Beta多样性簇。

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摘要

Comprehensive mapping of environmental microbiomes in terms of their compositional features remains a great challenge in understanding the microbial biosphere of the Earth. It bears promise to identify the driving forces behind the observed community patterns and whether community assembly happens deterministically. Advances in Next Generation Sequencing allow large community profiling studies, exceeding sequencing data output of conventional methods in scale by orders of magnitude. However, appropriate collection systems are still in a nascent state. We here present a database of 20,427 diverse environmental 16S rRNA profiles from 2,426 independent studies, which forms the foundation of our meta-analysis. We conducted a sample size adaptive all-against-all beta diversity comparison while also respecting phylogenetic relationships of Operational Taxonomic Units(OTUs). After conventional hierarchical clustering we systematically test for enrichment of Environmental Ontology terms and their abstractions in all possible clusters. This post-hoc algorithm provides a novel formalism that quantifies to what extend compositional and semantic similarity of microbial community samples coincide. We automatically visualize significantly enriched subclusters on a comprehensive dendrogram of microbial communities. As a result we obtain the hitherto most differentiated and comprehensive view on global patterns of microbial community diversity. We observe strong clusterability of microbial communities in ecosystems such as human/mammal-associated, geothermal, fresh water, plant-associated, soils and rhizosphere microbiomes, whereas hypersaline and anthropogenic samples are less homogeneous. Moreover, saline samples appear less cohesive in terms of compositional properties than previously reported.
机译:就其组成特征而言,全面绘制环境微生物群图仍然是理解地球微生物生物圈的巨大挑战。它有希望确定观察到的社区模式背后的驱动力以及社区集会是否确定性地发生。下一代测序技术的进步允许进行大型社区分析研究,其规模超出了传统方法测序数据输出的数量级。但是,适当的收集系统仍处于新生状态。我们在这里提供了来自2,426个独立研究的20,427种不同环境16S rRNA谱的数据库,这构成了我们的荟萃分析的基础。我们进行了样本大小自适应所有-所有-β多样性比较,同时还考虑了操作分类单位(OTU)的系统发育关系。在常规的层次聚类之后,我们系统地测试了环境本体术语及其在所有可能的聚类中的抽象的丰富性。此事后算法提供了一种新颖的形式主义,可以量化微生物群落样本的成分和语义相似性相吻合的程度。我们自动在全面的微生物群落树状图上可视化显着丰富的子类。结果,我们获得了迄今为止关于微生物群落多样性全球模式的最有差异和最全面的观点。我们观察到生态系统中微生物群落的强聚集性,例如人类/哺乳动物相关,地热,淡水,植物相关,土壤和根际微生物群落,而高盐和人为样本则较不均匀。而且,就组成特性而言,盐水样品的内聚力似乎比以前报道的要差。

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