Microbiome function predicts amphibian chytridiomycosis disease dynamics.
Microbiome function predicts amphibian chytridiomycosis disease dynamics.
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DOI：
10.1186/s40168-021-01215-6
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发表时间：
2022-03-10
期刊：
影响因子：
15.5
通讯作者：
Fisher MC
中科院分区：
文献类型：
--
作者：
Bates KA;Sommer U;Hopkins KP;Shelton JMG;Wierzbicki C;Sergeant C;Tapley B;Michaels CJ;Schmeller DS;Loyau A;Bosch J;Viant MR;Harrison XA;Garner TWJ;Fisher MC
真菌病原菌枝孢菌（Batrachochytrium dendrobaestrium，Bd）威胁着世界范围内两栖动物的生物多样性和生态系统的稳定。两栖动物皮肤微生物群落结构与Bd感染的临床结果有关，但其整体功能的重要性知之甚少。使用高通量细菌16 S rRNA和真菌ITS 2基因测序、细菌鸟枪宏基因组学和皮肤粘膜代谢组学评估微生物组分类和功能概况。我们采样了56野生助产士蟾蜍（Alytes obstricans）从山区人口表现出Bd流行病或地方病的动态。此外，为了评估疾病特异性微生物组谱是否与微生物介导的保护或Bd诱导的扰动有关，我们进行了实验室Bd攻击实验，其中40只年轻成年A.产科医生暴露于Bd或对照假感染。我们测量了感染高峰期的微生物组的时间变化以及BD暴露和对照动物的功能概况。微生物群落结构和功能不同的野生种群的基础上的感染史和实验对照与BD暴露的动物。实验室中的Bd暴露导致微生物群落结构和功能差异的动态变化，除一只感染动物外，所有感染动物均被清除。鞘氨醇杆菌属，寡养单胞菌属和未分类Commamonadaceae与野生动物流行病的动态，也减少了丰富的实验室BD暴露的动物，清除感染，表明与BD抗性的负相关。这进一步得到了微生物代谢物整合的支持，该整合确定了驱动疾病结果的功能相关分类群，其中鞘氨醇杆菌和Bd在野生动物流行动力学中最具影响力。实验室和田间微生物分类群落组成与皮肤代谢组之间的强相关性与微生物功能冗余不一致，表明微生物分类的差异驱动功能变异。霰弹枪宏基因组分析支持这些发现，在β多样性中具有类似的疾病相关模式。差异丰富的细菌基因和途径的分析表明，细菌的环境传感和Bd资源竞争可能是重要的驱动感染的结果。 感染Bd改变了实验室和野外环境中微生物的分类和功能。我们在实验和现场环境中应用多组学分析，有力地预测了Bd疾病的动态，并确定了新的候选感染生物标志物。 视频摘要在线版本包含补充材料，可通过10. 1186/s40168-021-01215-6获取。
The fungal pathogen Batrachochytrium dendrobatidis (Bd) threatens amphibian biodiversity and ecosystem stability worldwide. Amphibian skin microbial community structure has been linked to the clinical outcome of Bd infections, yet its overall functional importance is poorly understood. Microbiome taxonomic and functional profiles were assessed using high-throughput bacterial 16S rRNA and fungal ITS2 gene sequencing, bacterial shotgun metagenomics and skin mucosal metabolomics. We sampled 56 wild midwife toads (Alytes obstetricans) from montane populations exhibiting Bd epizootic or enzootic disease dynamics. In addition, to assess whether disease-specific microbiome profiles were linked to microbe-mediated protection or Bd-induced perturbation, we performed a laboratory Bd challenge experiment whereby 40 young adult A. obstetricans were exposed to Bd or a control sham infection. We measured temporal changes in the microbiome as well as functional profiles of Bd-exposed and control animals at peak infection. Microbiome community structure and function differed in wild populations based on infection history and in experimental control versus Bd-exposed animals. Bd exposure in the laboratory resulted in dynamic changes in microbiome community structure and functional differences, with infection clearance in all but one infected animal. Sphingobacterium, Stenotrophomonas and an unclassified Commamonadaceae were associated with wild epizootic dynamics and also had reduced abundance in laboratory Bd-exposed animals that cleared infection, indicating a negative association with Bd resistance. This was further supported by microbe-metabolite integration which identified functionally relevant taxa driving disease outcome, of which Sphingobacterium and Bd were most influential in wild epizootic dynamics. The strong correlation between microbial taxonomic community composition and skin metabolome in the laboratory and field is inconsistent with microbial functional redundancy, indicating that differences in microbial taxonomy drive functional variation. Shotgun metagenomic analyses support these findings, with similar disease-associated patterns in beta diversity. Analysis of differentially abundant bacterial genes and pathways indicated that bacterial environmental sensing and Bd resource competition are likely to be important in driving infection outcomes. Bd infection drives altered microbiome taxonomic and functional profiles across laboratory and field environments. Our application of multi-omics analyses in experimental and field settings robustly predicts Bd disease dynamics and identifies novel candidate biomarkers of infection. Video Abstract The online version contains supplementary material available at 10.1186/s40168-021-01215-6.
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影响因子：
48
作者：
Callahan BJ;McMurdie PJ;Rosen MJ;Han AW;Johnson AJ;Holmes SP
通讯作者：
Holmes SP
影响因子：
1.6
作者：
Agematu, Hitosi;Suzuki, Kazuya;Tsuya, Hiroaki
通讯作者：
Tsuya, Hiroaki
影响因子：
16.6
作者：
Bates KA;Clare FC;O'Hanlon S;Bosch J;Brookes L;Hopkins K;McLaughlin EJ;Daniel O;Garner TWJ;Fisher MC;Harrison XA
通讯作者：
Harrison XA
影响因子：
3.6
作者：
Griffitts, Joel S.;Carlyon, Rebecca E.;Long, Sharon R.
通讯作者：
Long, Sharon R.
影响因子：
6.7
作者：
Ford SA;King KC
通讯作者：
King KC