Ralstonia solanacearum pathogen disrupts bacterial rhizosphere microbiome during an invasion

根际 青枯菌 生物 微生物群 病菌 丰度(生态学) 相对物种丰度 生态学 寄主(生物学) 青枯病 微生物学 细菌 遗传学
作者
Zhong Wei,Jie Hu,Yian Gu,Shixue Yin,Yangchun Xu,Alexandre Jousset,Qirong Shen,Ville‐Petri Friman
出处
期刊:Soil Biology & Biochemistry [Elsevier BV]
卷期号:118: 8-17 被引量:160
标识
DOI:10.1016/j.soilbio.2017.11.012
摘要

Plant pathogen invasions are often associated with changes in physical environmental conditions and the composition of host-associated rhizosphere microbiome. It is however unclear how these factors interact and correlate with each other in determining plant disease dynamics in natural field conditions. To study this, we temporally sampled the rhizosphere of tomato plants that were exposed to moderate to aggressive Ralstonia solanacearum pathogen invasions over one crop season. We found that physiochemical soil properties correlated weakly with the severity of pathogen invasion apart from the water-soluble nitrogen concentration, which increased more clearly during the aggressive invasion. Instead, a much stronger link was found between pathogen invasion and reduced abundance and diversity of various rhizosphere bacterial taxa, simplification of bacterial interaction networks and loss of several predicted functional genes. We further verified our results in a separate greenhouse experiment to show that pathogen invasion causally drives similar changes in rhizosphere microbiome diversity and composition under controlled environmental conditions. Our results suggest that R. solanacearum invasion disrupts rhizosphere bacterial communities leading to clear reduction in the diversity and abundance of non-pathogenic bacteria. These changes could potentially affect the likelihood of secondary pathogen invasions during following crop seasons as less diverse microbial communities are also often less resistant to invasions. Strong negative correlation between pathogen and non-pathogenic bacterial densities further suggest that relative pathogen abundance could better predict the severity of bacterial wilt disease outbreaks compared to absolute pathogen abundance. Monitoring the dynamics of whole microbiomes could thus open new avenues for more accurate disease diagnostics in the future.
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