增加干旱对干旱土壤微生物组的显著影响
Significant Impacts of Increasing Aridity on the Arid Soil Microbiome
mSystems, [6.519]
2017-05-30 Articles
DOI: https://doi.org/10.1128/mSystems.00195-16
第一作者:Julia W. Neilsona, Katy Califfb
通讯作者:Raina M. Maiera
其它作者:
Cesar Cardona, Audrey Copeland, Will van Treuren, Karen L. Josephson, Rob Knight, Jack A. Gilbert, Jay Quade, J. Gregory Caporaso
作者主要单位:
a亚利桑那大学土壤水与环境科学系,美国亚利桑那州图森市(Department of Soil Water and Environmental Science, University of Arizona, Tucson, Arizona, USA)
b病原体和微生物组研究所,北亚利桑那大学,弗拉格斯塔夫,亚利桑那州,美国(Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, USA)
全球沙漠占地球表面的三分之一,对有机碳储存作出了重大贡献,这是一个极易受气候驱动的生态系统退化影响的旱地生态系统风险过程。控制沙漠生态系统退化率的力量知之甚少,特别是在干旱土壤微生物组的相关性方面。在这里,我们记录了干旱和土壤细菌和古菌微生物组成以及穿越智利阿塔卡马沙漠的干旱横断面之间的相关性。荟萃分析显示,阿塔卡马土壤微生物组在组成上呈现梯度,不同于非断层土壤的广泛横截面,但与来自不同大陆的三个沙漠类似。群落丰富度和多样性与土壤相对湿度(SoilRH)显著正相关。系统发育组成与SoilRH,温度和电导率密切相关。SoilRH和门相对丰度之间的最强和最显着的相关性观察到酸杆菌,变形菌门,浮霉菌Planctomycetes,疣微菌门Verrucomicrobia和广古菌门Euryarchaeota(Spearman等级相关[rs] => 0.81;错误发现率[q] = ≤0.005),特征为每个分类群的相对丰度减少10至300倍。此外,网络分析显示,沿着干旱和超干旱梯度的类群之间的显著关联降低,这种模式可能会损害超干旱群落的恢复能力,因为它们缺乏与更加整合的群落相关的特性。总之,结果表明干旱土壤微生物组稳定性对干旱敏感,这表现为与干旱类向超级类转变相关的群落连通性降低以及SoilRH与多样性和关键微生物相对丰度之间观察到的显着相关性的门通常在全球土壤中占主导地位。
我们确定了影响干旱土壤微生物组的关键环境和地球化学因素,这些因素沿着智利阿塔卡马沙漠300多公里的干旱和植被梯度。降低平均土壤相对湿度和升高温度可以解释这些沙漠土壤微生物群落的多样性和连通性的显著降低,并导致通常与肥沃土壤相关的关键类群的丰度显著降低。这一发现很重要,因为它表明预测的气候变化驱动的干旱增加可能会损害干旱土壤微生物组的能力,以维持必要的养分循环和碳固存功能以及沙漠生态系统中的植被覆盖,其占三分之一地球上的陆地生物群落。
Baquedano(红色)和Yungay(黄色)横断面的地点位置图。
Map of site locations for Baquedano (red) and Yungay (yellow) transects.
平均土壤相对湿度与微生物丰富度(PD)(上图)和多样性(Shannon指数)之间的相关性(下图); rs =斯皮尔曼等级相关,P <0.0001。
湿度与多样性指数显著正相关
Correlation between average soil relative humidity and microbial richness (PD) (top panel) and diversity (Shannon index) (bottom panel); rs = Spearman’s rank correlation, P < 0.0001.
(A)来自现在的阿塔卡马沙漠研究和Fierer等人的综合数据。按地理来源着色样品。
(B到E)仅阿塔卡马数据。由土壤特性着色的样品,其中浅色表示指定范围的低端,深色表示指定范围的高端。这些数据说明了表S3中的统计结果,具体而言,平均土壤相对湿度是阿塔卡马沙漠中样本组成比高土壤温度,电导率或pH更好的预测因子。
Unweighted UniFrac PCoA plots. (A) Combined data from the present Atacama Desert study and from Fierer et al. (19). (B to E) Atacama-only data. (A) Samples colored by their geographic origins. (B to F) Samples colored by soil properties, where light colors indicate the low end of the specified range and dark colors indicate the high end of the specified range. These data illustrate statistical results presented in Table S3, specifically, that average soil relative humidity is a better predictor of sample composition in the Atacama Desert than high soil temperature, electrical conductivity, or pH.
最佳分析识别样本变量的组合,最好地解释土壤微生物组系统发育组成的方差
BEST analysis identifying combinations of sample variables best explaining variance in soil microbiome phylogenetic compositiona
(A)完整的阿塔卡马沙漠网络。(B)干旱子网。(C)边缘子网。(D)超干旱子网。节点颜色表示OTU所在站点的土壤相对湿度的平均水平,相对节点大小表示节点OTU的度数。子网是单独创建的。
Network topology plots of Atacama microbial communities. (A) Full Atacama desert network. (B) Arid subnetwork. (C) Margin subnetwork. (D) Hyperarid subnetwork. Node colors represent average levels of soil relative humidity of the site or sites where the OTU is located, and the relative node sizes indicate the degrees of the node OTU. Subnetworks were created individually.
个体门的相对丰度(RA)与土壤平均相对湿度(AvgSoilRH)密切相关(| rs | => 0.6; q = < 0.02)。通过降低阳性相关强度(rs = 0.93至-0.95;表S4)列出门,其中RA根据样带位点的AvgSoilRH列出。放线菌门数据与AvgSoilRH呈负相关(rs = -0.95; q = 2.3×10-15)。热图在每个门内标准化为该门的最大RA(深红色)。分析仅限于具有位点RA => 0.1%的门。干旱等级标签:H,hyperrarid; M,margin; A,arid(如文中所定义)。
Relative abundance (RA) of individual phyla that are strongly correlated (|rs| = >0.6; q = <0.02) with average soil relative humidity (AvgSoilRH). Phyla are listed by decreasing strength of positive correlation (rs = 0.93 to −0.95; Table S4) with RA listed according to the AvgSoilRH of the transect site. Actinobacteria data are negatively correlated (rs = −0.95; q = 2.3 × 10−15) with AvgSoilRH. The heat map is normalized within each phylum to the maximum RA (dark red) for that phylum. Analysis is limited to phyla with site RA = >0.1%. Aridity class labels: H, hyperarid; M, margin; A, arid (as defined in the text).
Neilson, J. W. et al. Significant Impacts of Increasing Aridity on the Arid Soil Microbiome. mSystems 2, e00195-00116, doi:10.1128/mSystems.00195-16 (2017).
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