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      Exploring Biocontrol Agents From Microbial Keystone Taxa Associated to Suppressive Soil: A New Attempt for a Biocontrol Strategy

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          Abstract

          Recent studies have observed differing microbiomes between disease-suppressive and disease-conducive soils. However, it remains unclear whether the microbial keystone taxa in suppressive soil are critical for the suppression of diseases. Bacterial wilt is a common soil-borne disease caused by Ralstonia solanacearum that affects tobacco plants. In this study, two contrasting tobacco fields with bacterial wilt disease incidences of 0% (disease suppressive) and 100% (disease conducive) were observed. Through amplicon sequencing, as expected, a high abundance of Ralstonia was found in the disease-conducive soil, while large amounts of potential beneficial bacteria were found in the disease-suppressive soil. In the fungal community, an abundance of the Fusarium genus, which contains species that cause Fusarium wilt, showed a positive correlation ( p < 0.001) with the abundance of Ralstonia. Network analysis revealed that the healthy plants had more complex bacterial networks than the diseased plants. A total of 9 and 13 bacterial keystone taxa were identified from the disease-suppressive soil and healthy root, respectively. Accumulated abundance of these bacterial keystones showed a negative correlation ( p < 0.001) with the abundance of Ralstonia. To complement network analysis, culturable strains were isolated, and three species belonging to Pseudomonas showed high 16S rRNA gene similarity (98.4–100%) with keystone taxa. These strains displayed strong inhibition on pathogens and reduced the incidence of bacterial wilt disease in greenhouse condition. This study highlighted the importance of keystone species in the protection of crops against pathogen infection and proposed an approach to obtain beneficial bacteria through identifying keystone species, avoiding large-scale bacterial isolation and cultivation.

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          Cutadapt removes adapter sequences from high-throughput sequencing reads

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            MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

            We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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              QIIME allows analysis of high-throughput community sequencing data.

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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                19 March 2021
                2021
                : 12
                : 655673
                Affiliations
                [1] 1Pest Integrated Management Key Laboratory of China Tobacco, Tobacco Research Institute of Chinese Academy of Agricultural Sciences , Qingdao, China
                [2] 2Biological Organic Fertilizer Engineering Technology Center of China Tobacco, Zunyi Branch of Guizhou Tobacco Company , Zunyi, China
                Author notes

                Edited by: Roberta Marra, University of Naples Federico II, Italy

                Reviewed by: Bruno Brito Lisboa, State Secretariat of Agriculture, Livestock and Irrigation, Brazil; Luciano Kayser Vargas, State Secretariat of Agriculture, Livestock and Irrigation, Brazil

                *Correspondence: Cheng-Sheng Zhang, zhangchengsheng@ 123456caas.cn

                These authors have contributed equally to this work

                This article was submitted to Plant Pathogen Interactions, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2021.655673
                8095248
                33959142
                143e2075-a14e-4fc1-ba8d-87dc31e725fd
                Copyright © 2021 Zheng, Han, Zhao, Wei, Yuan, Li, Liu and Zhang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 19 January 2021
                : 22 February 2021
                Page count
                Figures: 7, Tables: 0, Equations: 0, References: 59, Pages: 13, Words: 8357
                Funding
                Funded by: China Association for Science and Technology Youth Talent Promotion Project
                Award ID: 110201902003
                Funded by: Science and Technology Project of Guizhou Tobacco Corporation
                Award ID: 201809
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                bacterial wilt disease,microbiome,biocontrol agents,network,biocontrol,suppressive soil

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