Deciphering the rhizosphere bacteriome associated with biological control of tobacco black shank disease.

amplicon sequencing biocontrol agent co-occurrence network microbiome tobacco black shank

Journal

Frontiers in plant science
ISSN: 1664-462X
Titre abrégé: Front Plant Sci
Pays: Switzerland
ID NLM: 101568200

Informations de publication

Date de publication:
2023
Historique:
received: 28 01 2023
accepted: 22 03 2023
medline: 20 4 2023
pubmed: 20 4 2023
entrez: 20 04 2023
Statut: epublish

Résumé

The black shank disease seriously affects the health of tobacco plants. Conventional control methods have limitations in terms of effectiveness or economic aspects and cause public health concerns. Thus, biological control methods have come into the field, and microorganisms play a key role in suppressing tobacco black shank disease. In this study, we examined the impact of soil microbial community on black shank disease basing on the structural difference of bacterial communities in rhizosphere soils. We used Illumina sequencing to compare the bacterial community diversity and structure in different rhizosphere soil samples in terms of healthy tobacco, tobacco showing typical black shank symptoms, and tobacco treated with the biocontrol agent, Bacillus velezensis S719. We found that Alphaproteobacteria in the biocontrol group, accounted for 27.2% of the ASVs, was the most abundant bacterial class among three groups. Heatmap and LEfSe analyses were done to determine the distinct bacterial genera in the three sample groups. For the healthy group, Pseudomonas was the most significant genus; for the diseased group, Stenotrophomonas exhibited the strongest enrichment trend, and Sphingomonas showed the highest linear discriminant analysis score, and was even more abundant than Bacillus; for the biocontrol group, Bacillus, and Gemmatimonas were the largely distributed genus. In addition, co-occurrence network analysis confirmed the abundance of taxa, and detected a recovery trend in the network topological parameters of the biocontrol group. Further functional prediction also provided a possible explanation for the bacterial community changes with related KEGG annotation terms. These findings will improve our knowledge of plant-microbe interactions and the application of biocontrol agents to improve plant fitness, and may contribute to the selection of biocontrol strains.

Identifiants

pubmed: 37077642
doi: 10.3389/fpls.2023.1152639
pmc: PMC10108594
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1152639

Informations de copyright

Copyright © 2023 Ma, Gu, Liu, Zhang, Wang, Xia and Wei.

Déclaration de conflit d'intérêts

Author JL is employed by Zunyi Tobacco Company of Guizhou Provincial Tobacco Corporation, and author YZ is employed by China National Tobacco Corporation Shandong Branch. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Yi-Nan Ma (YN)

Key Laboratory of Microbial Resources Collection and Preservation, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China.

Yi-Lin Gu (YL)

Key Laboratory of Microbial Resources Collection and Preservation, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China.

Jing Liu (J)

Zunyi Tobacco Company of Guizhou Provincial Tobacco Corporation, Zunyi, China.

Yuqin Zhang (Y)

China National Tobacco Corporation Shandong Branch, Jinan, China.

Xinwei Wang (X)

Key Laboratory of Tobacco Pest Monitoring & Integrated Management in Tobacco, Tobacco Research Institute of Chinese Academy of Agricultural Sciences, Qingdao, China.

Zhenyuan Xia (Z)

Yunnan Academy of Tobacco Agricultural Science, Kunming, China.

Hai-Lei Wei (HL)

Key Laboratory of Microbial Resources Collection and Preservation, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China.

Classifications MeSH