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      Cross-kingdom synthetic microbiota supports tomato suppression of Fusarium wilt disease

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          Abstract

          The role of rhizosphere microbiota in the resistance of tomato plant against soil-borne Fusarium wilt disease (FWD) remains unclear. Here, we showed that the FWD incidence was significantly negatively correlated with the diversity of both rhizosphere bacterial and fungal communities. Using the microbiological culturomic approach, we selected 205 unique strains to construct different synthetic communities (SynComs), which were inoculated into germ-free tomato seedlings, and their roles in suppressing FWD were monitored using omics approach. Cross-kingdom (fungi and bacteria) SynComs were most effective in suppressing FWD than those of Fungal or Bacterial SynComs alone. This effect was underpinned by a combination of molecular mechanisms related to plant immunity and microbial interactions contributed by the bacterial and fungal communities. This study provides new insight into the dynamics of microbiota in pathogen suppression and host immunity interactions. Also, the formulation and manipulation of SynComs for functional complementation constitute a beneficial strategy in controlling soil-borne disease.

          Abstract

          Rhizosphere microbiota can influence plant pathogen interactions. Here the authors use field- and lab-based approaches to show that rhizosphere bacteria and fungi of healthy tomatoes can enhance tomato resistance against Fusarium wilt disease and formulate synthetic microbial communities that could help to control soil-borne disease.

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          Most cited references66

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          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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            Plant–microbiome interactions: from community assembly to plant health

            Healthy plants host diverse but taxonomically structured communities of microorganisms, the plant microbiota, that colonize every accessible plant tissue. Plant-associated microbiomes confer fitness advantages to the plant host, including growth promotion, nutrient uptake, stress tolerance and resistance to pathogens. In this Review, we explore how plant microbiome research has unravelled the complex network of genetic, biochemical, physical and metabolic interactions among the plant, the associated microbial communities and the environment. We also discuss how those interactions shape the assembly of plant-associated microbiomes and modulate their beneficial traits, such as nutrient acquisition and plant health, in addition to highlighting knowledge gaps and future directions.
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              Keystone taxa as drivers of microbiome structure and functioning

              Microorganisms have a pivotal role in the functioning of ecosystems. Recent studies have shown that microbial communities harbour keystone taxa, which drive community composition and function irrespective of their abundance. In this Opinion article, we propose a definition of keystone taxa in microbial ecology and summarize over 200 microbial keystone taxa that have been identified in soil, plant and marine ecosystems, as well as in the human microbiome. We explore the importance of keystone taxa and keystone guilds for microbiome structure and functioning and discuss the factors that determine their distribution and activities.
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                Author and article information

                Contributors
                cail@im.ac.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                22 December 2022
                22 December 2022
                2022
                : 13
                : 7890
                Affiliations
                [1 ]GRID grid.9227.e, ISNI 0000000119573309, State Key Laboratory of Mycology, Institute of Microbiology, , Chinese Academy of Sciences, ; Beijing, P. R. China
                [2 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, University of Chinese Academy of Sciences, ; 100101 Beijing, P. R. China
                [3 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, Faculty of Medicine, , University of British Columbia, ; Vancouver, Canada
                [4 ]GRID grid.240988.f, ISNI 0000 0001 0298 8161, National Centre for Infectious Diseases, , Tan Tock Seng Hospital, ; Singapore, Singapore
                [5 ]GRID grid.59025.3b, ISNI 0000 0001 2224 0361, Lee Kong Chian School of Medicine, , Nanyang Technological University, ; Singapore, Singapore
                [6 ]GRID grid.467063.0, ISNI 0000 0004 0397 4222, Department of Pathology, , Sidra Medicine, ; Doha, Qatar
                Author information
                http://orcid.org/0000-0003-3143-2079
                http://orcid.org/0000-0002-8131-7274
                Article
                35452
                10.1038/s41467-022-35452-6
                9780251
                36550095
                8f6a1c6f-b581-4a3a-b17f-7bfb1be6f4cf
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 December 2021
                : 2 December 2022
                Funding
                Funded by: Excellent Young Scholars of State Key Laboratory of Mycology, SKLMQN202101
                Funded by: National Science Fund for Distinguished Young Scholars,NSFC31725001 Biological Resources Programme, Chinese Academy of Sciences,KFJ-BRP-009
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                microbiome,microbial ecology,biotic,metagenomics
                Uncategorized
                microbiome, microbial ecology, biotic, metagenomics

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