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Soil Bacterial Communities Exhibit Strong Biogeographic Patterns at Fine Taxonomic Resolution.
mSystems ( IF 5.0 ) Pub Date : 2020-07-21 , DOI: 10.1128/msystems.00540-20
Sean K Bay 1, 2 , Melodie A McGeoch 3 , Osnat Gillor 4 , Nimrod Wieler 4 , David J Palmer 3 , David J Baker 3 , Steven L Chown 3 , Chris Greening 1, 2
Affiliation  

Bacteria have been inferred to exhibit relatively weak biogeographic patterns. To what extent such findings reflect true biological phenomena or methodological artifacts remains unclear. Here, we addressed this question by analyzing the turnover of soil bacterial communities from three data sets. We applied three methodological innovations: (i) design of a hierarchical sampling scheme to disentangle environmental from spatial factors driving turnover; (ii) resolution of 16S rRNA gene amplicon sequence variants to enable higher-resolution community profiling; and (iii) application of the new metric zeta diversity to analyze multisite turnover and drivers. At fine taxonomic resolution, rapid compositional turnover was observed across multiple spatial scales. Turnover was overwhelmingly driven by deterministic processes and influenced by the rare biosphere. The communities also exhibited strong distance decay patterns and taxon-area relationships, with z values within the interquartile range reported for macroorganisms. These biogeographical patterns were weakened upon applying two standard approaches to process community sequencing data: clustering sequences at 97% identity threshold and/or filtering the rare biosphere (sequences lower than 0.05% relative abundance). Comparable findings were made across local, regional, and global data sets and when using shotgun metagenomic markers. Altogether, these findings suggest that bacteria exhibit strong biogeographic patterns, but these signals can be obscured by methodological limitations. We advocate various innovations, including using zeta diversity, to advance the study of microbial biogeography.

中文翻译:


土壤细菌群落在精细分类分辨率下表现出强烈的生物地理模式。



据推断,细菌表现出相对较弱的生物地理模式。这些发现在多大程度上反映了真实的生物现象或方法学假象仍不清楚。在这里,我们通过分析三个数据集的土壤细菌群落的更替来解决这个问题。我们应用了三项方法创新:(i)设计分层抽样方案,将环境因素与驱动营业额的空间因素分开; (ii) 16S rRNA基因扩增子序列变体的分辨率,以实现更高分辨率的群落分析; (iii) 应用新的 zeta 多样性度量来分析多站点营业额和驱动因素。在精细的分类分辨率下,在多个空间尺度上观察到快速的成分周转。营业额很大程度上是由确定性过程驱动的,并受到稀有生物圈的影响。这些群落还表现出强烈的距离衰减模式和分类单元-面积关系,大型生物体的z值在四分位范围内。在应用两种标准方法处理群落测序数据后,这些生物地理模式被削弱:以 97% 同一性阈值聚类序列和/或过滤稀有生物圈(相对丰度低于 0.05% 的序列)。在使用鸟枪法宏基因组标记时,在本地、区域和全球数据集上得出了可比较的结果。总而言之,这些发现表明细菌表现出强烈的生物地理模式,但这些信号可能因方法学的限制而被掩盖。我们提倡各种创新,包括利用 zeta 多样性来推进微生物生物地理学的研究。
更新日期:2020-08-20
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