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Journal of Zhejiang University SCIENCE B 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/jzus.B2300914


Implications of bacteria-bacteria interactions within plant microbiota for plant health and productivity


Author(s):  Giovanni Davide BARONE, Yaqi ZHOU, Hongkai WANG, Sunde XU, Zhonghua MA, Tomislav CERNAVA, Yun CHEN

Affiliation(s):  State Key Laboratory of Rice Biology and Breeding; more

Corresponding email(s):   chenyun0927@zju.edu.cn, tomislav.cernava@tugraz.at

Key Words:  Plant microbiome, Bacteria-bacteria interactions, Plant pathogens, Crop production, Molecular interactions


Giovanni Davide BARONE, Yaqi ZHOU, Hongkai WANG, Sunde XU, Zhonghua MA, Tomislav CERNAVA, Yun CHEN. Implications of bacteria-bacteria interactions within plant microbiota for plant health and productivity[J]. Journal of Zhejiang University Science B, 1998, -1(-1): .

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%T Implications of bacteria-bacteria interactions within plant microbiota for plant health and productivity
%A Giovanni Davide BARONE
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%A Hongkai WANG
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%A Zhonghua MA
%A Tomislav CERNAVA
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%J Journal of Zhejiang University SCIENCE B
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A1 - Tomislav CERNAVA
A1 - Yun CHEN
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Abstract: 
crop production currently relies on the widespread use of agrochemicals to ensure food security. This practice is considered unsustainable, yet has no viable alternative at present. Plant microbiota can fulfil various functions in their host, some of which could be the basis for developing sustainable protection and fertilization strategies for plants without relying on chemicals. To harness such functions, a detailed understanding of plant-microbe and microbe-microbe interactions is necessary. Among interactions within the plant microbiota, those between bacteria are the most common ones; they are not only of ecological importance but also essential for maintaining the health and productivity of the host plants. This review focuses on recent literature in this field and highlights various consequences of bacteria-bacteria interactions under different agricultural settings. In addition, the molecular and genetic backgrounds of bacteria that facilitate such interactions are emphasized. Representative examples of commonly found bacterial metabolites with bioactive properties, as well as their modes of action, are given. Integrating our understanding of various binary interactions into complex models that encompass the entire microbiota will benefit future developments in agriculture and beyond, which could be further facilitated by artificial intelligence-based technologies.

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