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Using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt

Although bacterial communities play important roles in the suppression of pathogenic diseases and crop production, little is known about the bacterial communities associated with bacterial wilt. Based on 16S rRNA gene sequencing, statistical analyses of microbial communities in disease-suppressive a...

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Autores principales: Liu, Xiaojiao, Zhang, Shuting, Jiang, Qipeng, Bai, Yani, Shen, Guihua, Li, Shili, Ding, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5114674/
https://www.ncbi.nlm.nih.gov/pubmed/27857159
http://dx.doi.org/10.1038/srep36773
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author Liu, Xiaojiao
Zhang, Shuting
Jiang, Qipeng
Bai, Yani
Shen, Guihua
Li, Shili
Ding, Wei
author_facet Liu, Xiaojiao
Zhang, Shuting
Jiang, Qipeng
Bai, Yani
Shen, Guihua
Li, Shili
Ding, Wei
author_sort Liu, Xiaojiao
collection PubMed
description Although bacterial communities play important roles in the suppression of pathogenic diseases and crop production, little is known about the bacterial communities associated with bacterial wilt. Based on 16S rRNA gene sequencing, statistical analyses of microbial communities in disease-suppressive and disease-conducive soils from three districts during the vegetation period of tobacco showed that Proteobacteria was the dominant phylum, followed by Acidobacteria. Only samples from September were significantly correlated to disease factors. Fifteen indicators from taxa found in September (1 class, 2 orders, 3 families and 9 genera) were identified in the screen as being associated with disease suppression, and 10 of those were verified for potential disease suppression in March. Kaistobacter appeared to be the genus with the most potential for disease suppression. Elucidating microbially mediated natural disease suppression is fundamental to understanding microecosystem responses to sustainable farming and provides a possible approach for modeling disease-suppressive indicators. Here, using cluster analysis, MRPP testing, LEfSe and specific filters for a Venn diagram, we provide insight into identifying possible indicators of disease suppression of tobacco bacterial wilt.
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spelling pubmed-51146742016-11-25 Using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt Liu, Xiaojiao Zhang, Shuting Jiang, Qipeng Bai, Yani Shen, Guihua Li, Shili Ding, Wei Sci Rep Article Although bacterial communities play important roles in the suppression of pathogenic diseases and crop production, little is known about the bacterial communities associated with bacterial wilt. Based on 16S rRNA gene sequencing, statistical analyses of microbial communities in disease-suppressive and disease-conducive soils from three districts during the vegetation period of tobacco showed that Proteobacteria was the dominant phylum, followed by Acidobacteria. Only samples from September were significantly correlated to disease factors. Fifteen indicators from taxa found in September (1 class, 2 orders, 3 families and 9 genera) were identified in the screen as being associated with disease suppression, and 10 of those were verified for potential disease suppression in March. Kaistobacter appeared to be the genus with the most potential for disease suppression. Elucidating microbially mediated natural disease suppression is fundamental to understanding microecosystem responses to sustainable farming and provides a possible approach for modeling disease-suppressive indicators. Here, using cluster analysis, MRPP testing, LEfSe and specific filters for a Venn diagram, we provide insight into identifying possible indicators of disease suppression of tobacco bacterial wilt. Nature Publishing Group 2016-11-18 /pmc/articles/PMC5114674/ /pubmed/27857159 http://dx.doi.org/10.1038/srep36773 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Liu, Xiaojiao
Zhang, Shuting
Jiang, Qipeng
Bai, Yani
Shen, Guihua
Li, Shili
Ding, Wei
Using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt
title Using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt
title_full Using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt
title_fullStr Using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt
title_full_unstemmed Using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt
title_short Using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt
title_sort using community analysis to explore bacterial indicators for disease suppression of tobacco bacterial wilt
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5114674/
https://www.ncbi.nlm.nih.gov/pubmed/27857159
http://dx.doi.org/10.1038/srep36773
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