An amplification-selection model for quantified rhizosphere microbiota assembly
An amplification-selection model for quantified rhizosphere microbiota assembly
复制标题
量化根际微生物群组装的扩增选择模型
DOI：
10.1016/j.scib.2020.03.005
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发表时间：
2020
期刊：
影响因子：
18.9
通讯作者：
Ertao Wang
中科院分区：
文献类型：
--
作者：
Xiaolin Wang;Mingxing Wang;Xingguang Xie;Siyi Guo;Yun Zhou;Xuebin Zhang;Nan Yu;Ertao Wang
植物与许多微生物共生并相互作用。根际补充的流行模型认为，根产生的因素吸引特定的细菌类群在根际和更专门的细菌类群进一步丰富根内。在这里，我们量化了苜蓿和水稻根际微生物的绝对丰度，这表明大多数优势细菌门在根际不同程度地显著升高，随后特定类群被招募到根中，这表明根微生物组组装的扩增选择模型。微生物在根际（根周围的区域）的定殖对植物生产力和土壤地球化学循环至关重要，植物为根际微生物群提供光合作用，并在交换中接收营养和水[1，2]。下一代测序的出现使得微生物组的培养独立分析成为可能，并为与不同宿主相关的细菌群落的多样性和组成提供了深刻的见解，包括宿主植物的地上和地下隔室[3]。主要从细菌16 S rRNA基因序列推断的土壤样品中细菌分类群的相对丰度表明，细菌根微生物组通过两步或多步选择过程形成，其中细菌群落在土壤中密集且多样，然后逐渐分化并富集从根际到根的特定门[1，3-5]。变形菌门、拟杆菌门和放线菌门的细菌门似乎在根际和根内生隔室（根内）中富集，而酸性细菌似乎在根际中耗尽[5-9]。虽然微生物16 S rRNA基因序列的相对丰度为了解细菌群落的多样性和组成提供了重要的见解，但它并不能反映微生物的绝对丰度。例如，种群中的特定群体可以经历绝对丰度的增加沿着相对丰度的减少。这样，相对丰度可以掩盖潜在的植物病理学和微生物生态功能[10]。此外，细菌通常具有用于推断相对丰度的16 S rRNA基因的不同拷贝数[11]，这在许多微生物群研究中被忽视，并且可能混淆相对丰度分析。为了克服这些障碍，我们使用了一种方法[10]，通过用合成的嵌合细菌16 S DNA加标样品来绝对定量散装土壤和根区室中的细菌16 S rRNA基因（图S1在线）。对于每个操作分类单位（OTU），我们使用rrnDB数据库[12]估计了16 S rRNA基因拷贝数，遵循用于定量肠道微生物组分析的方法[13]。我们随后计算并评估（通过与单拷贝ropB基因比较）细菌分类群的绝对丰度加权平均rRNA操纵子拷贝数（定量细菌丰度）（图1A和1B）。S1和S2在线）。我们使用这种方法来量化在不同土壤类型中生长的两种不同植物的土壤、根际土壤和根中的微生物群落，所述两种不同植物即，蒺藜苜蓿（'Jemalong A170）（其代表在旱地土壤中生长的植物）和水稻（Oryza sativa ssp. japonica 'Nipponbare'），其表示https：//doi。org/10.1016/j. scib. 2020.03. 005 2095-9273/© 2020中国科学出版社.由Elsevier BV和Science China Press出版。All rights reserved.
Plants live in association and interact with a multitude of microorganisms. The prevalent model for rhizosphere recruitment argues that factors produced by root attract the specific bacterial taxa in the rhizosphere and the more specialized bacterial taxa are further enriched within root. Here, we quantified the absolute abundance of root microbiota in Medicago and rice, which revealed that most of the dominant bacterial phyla are significantly elevated in the rhizosphere to different degrees, followed by the recruitment of specific taxa into the root, suggesting an amplificationselection model for root microbiome assembly. Colonization of the rhizosphere (the zone immediately surrounding the root) by microbes is crucial to plant productivity and soil biogeochemical cycles, with plants giving photosynthate to the rhizosphere microbiota and receiving nutrients and water in exchange [1, 2]. The emergence of next-generation sequencing has enabled cultivation-independent analyses of microbiomes and has provided deep insights into the diversity and composition of the bacterial communities associated with diverse hosts, including aboveground and underground compartments of host plants [3]. The relative abundance of bacterial taxa in soil samples, inferred mainly from bacterial 16S rRNA gene sequences, has suggested that the bacterial root microbiome forms via a two-step or multiple-step selection process whereby the bacterial community is dense and diverse in bulk soil, and then gradually becomes differentiated and enriched for specific phyla from rhizosphere to root [1, 3–5]. Bacterial phyla of Proteobacteria, Bacteroidetes and Actinobacteria appear to be enriched in the rhizosphere and root endophytic compartment (within the root), whereas Acidobacteria appear to be depleted from the rhizosphere [5–9]. Although the relative abundance of microbial 16S rRNA gene sequences provides important insights into the diversity and composition of bacterial communities, it does not reflect the absolute abundance of microbes. For instance, a specific group within a population can undergo an increase in absolute abundance along with a decrease in the relative abundance. In this way, the relative abundance can mask underlying plant pathology and microbial ecological function [10]. In addition, bacteria often possess different copy numbers of the 16S rRNA gene used to infer relative abundance [11], which has been overlooked in many microbiota studies and could confound relative abundance analyses. To overcome these obstacles, we used a method [10] to absolutely quantify bacterial 16S rRNA gene in bulk soil and rhizocompartments by spiking samples with synthetic chimeric bacterial 16S DNA (Fig. S1 online). For each Operational Taxonomic Unit (OTU), we estimated the 16S rRNA gene copy number using the rrnDB database [12], followed the method used for quantitative gut microbiome profiling [13]. We subsequently calculated and evaluated (through comparison with the single copy ropB gene) the absolute abundance-weighted average rRNA operon copy number of bacterial taxa (quantified bacteria abundance)(Figs. S1 and S2 online). We used this approach to quantify the microbial communities in bulk soil, rhizosphere soil and roots of two different plants growing in different soil types, namely, Medicago truncatula (‘Jemalong A170), which represent a plant growing in dry land soil, and rice (Oryza sativa ssp. japonica ‘Nipponbare’), which represent https://doi. org/10.1016/j. scib. 2020.03. 005 2095-9273/© 2020 Science China Press. Published by Elsevier BV and Science China Press. All rights reserved.