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Identification of keystone taxa in rhizosphere microbial communities using different methods and their effects on compounds of the host Cinnamomum migao.
Sun, Qing-Wen; Chen, Jing-Zhong; Liao, Xiao-Feng; Huang, Xiao-Long; Liu, Ji-Ming.
Affiliation
  • Sun QW; School of Pharmacy, Guizhou University of Traditional Chinese Medicine, Guiyang 550025, China; Guizhou Province Key Laboratory of Chinese Pharmacology and Pharmacognosy, 550025, China.
  • Chen JZ; School of Pharmacy, Guizhou University of Traditional Chinese Medicine, Guiyang 550025, China; Guizhou Province Key Laboratory of Chinese Pharmacology and Pharmacognosy, 550025, China. Electronic address: chenjingzhong022@gzy.edu.cn.
  • Liao XF; Guizhou Academy of Sciences, Guiyang 550025, China.
  • Huang XL; Guizhou Academy of Forestry, Guiyang 550025, China. Electronic address: 1028842676@qq.com.
  • Liu JM; College of Forestry, Guizhou University, Guiyang 550025, China.
Sci Total Environ ; 926: 171952, 2024 May 20.
Article de En | MEDLINE | ID: mdl-38537823
ABSTRACT
Exploring keystone taxa affecting microbial community stability and host function is crucial for understanding ecosystem functions. However, identifying keystone taxa from humongous microbial communities remains challenging. We collected 344 rhizosphere and bulk soil samples from the endangered plant C. migao for 2 years consecutively. Used high-throughput sequencing 16S rDNA and ITS to obtain the composition of bacterial and fungal communities. We explored keystone taxa and the applicability and limitations of five methods (SPEC-OCCU, Zi-Pi, Subnetwork, Betweenness, and Module), as well as the impact of microbial community domain, time series, and rhizosphere boundary on the identification of keystone taxa in the communities. Our results showed that the five methods, identified abundant keystone taxa in rhizosphere and bulk soil microbial communities. However, the keystone taxa shared by the rhizosphere and bulk soil microbial communities over time decreased rapidly decrease in the five methods. Among five methods on the identification of keystone taxa in the rhizosphere community, Module identified 113 taxa, SPEC-OCCU identified 17 taxa, Betweenness identified 3 taxa, Subnetwork identified 3 taxa, and Zi-Pi identified 4 taxa. The keystone taxa are mainly conditionally rare taxa, and their ecological functions include chemoheterotrophy, aerobic chemoheterotrophy, nitrate reduction, and anaerobic photoautotrophy. The results of the random forest model and structural equation model predict that keystone taxa Mortierella and Ellin6513 may have an effects on the accumulation of 1, 4, 7, - Cycloundecatriene, 1, 5, 9, 9-tetramethyl-, Z, Z, Z-, beta-copaene, bicyclogermacrene, 1,8-Cineole in C. migao fruits, but their effects still need further evidence. Our study evidence an unstable microbial community in the bulk soil, and the definition of microbial boundary and ecologically functional affected the identification of keystone taxa in the community. Subnetwork and Module are more in line with the definition of keystone taxa in microbial ecosystems in terms of maintaining community stability and hosting function.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Rhizosphère / Microbiote Langue: En Journal: Sci Total Environ Année: 2024 Type de document: Article Pays d'affiliation: Chine

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Rhizosphère / Microbiote Langue: En Journal: Sci Total Environ Année: 2024 Type de document: Article Pays d'affiliation: Chine