Azarbad Hamed, Tremblay Julien, Bainard Luke D, Yergeau Etienne
Evolutionary Ecology of Plants, Faculty of Biology, Philipps-University Marburg, Marburg, Germany.
Energy, Mining and Environment, National Research Council Canada, Montréal, QC, Canada.
Front Microbiol. 2022 Jan 24;12:798023. doi: 10.3389/fmicb.2021.798023. eCollection 2021.
Next-generation sequencing is one of the most popular and cost-effective ways of characterizing microbiome in multiple samples. However, most of the currently available amplicon sequencing approaches are limited, as they result in relative abundance profiles of microbial taxa, which does not represent actual abundance in the environment. Here, we combined amplicon sequencing (16S rRNA gene for bacteria and ITS region for fungi) with real-time quantitative PCR (qPCR) to characterize the rhizosphere microbiome of wheat. We show that changes in the relative abundance of major microbial phyla do not necessarily follow the same pattern as the estimated quantitative abundance. Most of the bacterial phyla linked with the rhizosphere of plants grown in soil with no history of water stress showed enrichment patterns in their estimated absolute abundance, which was in contradiction with the trends observed in the relative abundance data. However, in the case of the fungal groups (except for ), such an enrichment pattern was not observed and the abundance of fungi remained relatively unchanged under different soil water stress history when estimated absolute abundance was considered. Comparing relative and estimated absolute abundances of dominant bacterial and fungal phyla, as well as their correlation with the functional processes in the rhizosphere, our results suggest that the estimated absolute abundance approach gives a different and more realistic perspective than the relative abundance approach. Such a quantification approach provides complementary information that helps to better understand the rhizosphere microbiomes and their associated ecological functional processes.
下一代测序是对多个样本中的微生物群落进行特征分析最常用且性价比最高的方法之一。然而,目前大多数可用的扩增子测序方法都存在局限性,因为它们只能得出微生物分类群的相对丰度概况,无法代表环境中的实际丰度。在此,我们将扩增子测序(细菌的16S rRNA基因和真菌的ITS区域)与实时定量PCR(qPCR)相结合,以表征小麦的根际微生物群落。我们发现,主要微生物门类相对丰度的变化不一定与估计的定量丰度遵循相同模式。大多数与在无水分胁迫历史土壤中生长的植物根际相关的细菌门类,其估计的绝对丰度呈现富集模式,这与相对丰度数据中观察到的趋势相矛盾。然而,对于真菌类群(除了 ),未观察到这种富集模式,并且在考虑估计的绝对丰度时,不同土壤水分胁迫历史下真菌的丰度相对保持不变。通过比较优势细菌和真菌门类的相对丰度与估计的绝对丰度,以及它们与根际功能过程的相关性,我们的结果表明,估计的绝对丰度方法比相对丰度方法提供了不同且更现实的视角。这种定量方法提供了补充信息,有助于更好地理解根际微生物群落及其相关的生态功能过程。