Specific metabolites drive the deterministic assembly of diseased rhizosphere microbiome through weakening microbial degradation of autotoxin

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Abstract

Background

Process and function that underlie the assembly of a rhizosphere microbial community may be strongly linked to the maintenance of plant health. However, their assembly processes and functional changes in the deterioration of soilborne disease remain unclear. Here, we investigated features of rhizosphere microbiomes related to Fusarium wilt disease and assessed their assembly by comparison pair of diseased/healthy sequencing data. The untargeted metabolomics was employed to explore potential community assembly drivers, and shotgun metagenome sequencing was used to reveal the mechanisms of metabolite-mediated process after soil conditioning.

Results

Results showed the deterministic assembly process associated with diseased rhizosphere microbiomes, and this process was significantly correlated to five metabolites (tocopherol acetate, citrulline, galactitol, octadecylglycerol, and behenic acid). Application of the metabolites resulted in a deterministic assembly of microbiome with the high morbidity of watermelon. Furthermore, metabolite conditioning was found to weaken the function of autotoxin degradation undertaken by specific bacterial group ( Bradyrhizobium, Streptomyces, Variovorax, Pseudomonas, and Sphingomonas) while promoting the metabolism of small-molecule sugars and acids initiated from another bacterial group ( Anaeromyxobacter, Bdellovibrio, Conexibacter, Flavobacterium, and Gemmatimonas).

Conclusion

These findings strongly suggest that shifts in a metabolite-mediated microbial community assembly process underpin the deterministic establishment of soilborne Fusarium wilt disease and reveal avenues for future research focusing on ameliorating crop loss due to this pathogen.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40168-022-01375-z.

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Most cited references 54

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Search and clustering orders of magnitude faster than BLAST.

Robert Edgar (2010)

Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.

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Is Open Access

CD-HIT: accelerated for clustering the next-generation sequencing data

Limin Fu, Beifang Niu, Zhengwei Zhu … (2012)

Summary: CD-HIT is a widely used program for clustering biological sequences to reduce sequence redundancy and improve the performance of other sequence analyses. In response to the rapid increase in the amount of sequencing data produced by the next-generation sequencing technologies, we have developed a new CD-HIT program accelerated with a novel parallelization strategy and some other techniques to allow efficient clustering of such datasets. Our tests demonstrated very good speedup derived from the parallelization for up to ∼24 cores and a quasi-linear speedup for up to ∼8 cores. The enhanced CD-HIT is capable of handling very large datasets in much shorter time than previous versions. Availability: http://cd-hit.org. Contact: liwz@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

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MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph.

Dinghua Li, Chi-Man Liu, Ruibang Luo … (2015)

MEGAHIT is a NGS de novo assembler for assembling large and complex metagenomics data in a time- and cost-efficient manner. It finished assembling a soil metagenomics dataset with 252 Gbps in 44.1 and 99.6 h on a single computing node with and without a graphics processing unit, respectively. MEGAHIT assembles the data as a whole, i.e. no pre-processing like partitioning and normalization was needed. When compared with previous methods on assembling the soil data, MEGAHIT generated a three-time larger assembly, with longer contig N50 and average contig length; furthermore, 55.8% of the reads were aligned to the assembly, giving a fourfold improvement. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Author and article information

Contributors

Jun Yuan: junyuan@njau.edu.cn

Journal

Journal ID (nlm-ta): Microbiome

Journal ID (iso-abbrev): Microbiome

Title: Microbiome

Publisher: BioMed Central (London )

ISSN (Electronic): 2049-2618

Publication date (Electronic): 21 October 2022

Publication date PMC-release: 21 October 2022

Publication date Collection: 2022

Volume: 10

Electronic Location Identifier: 177

Affiliations

[1 ]GRID grid.27871.3b, ISNI 0000 0000 9750 7019, The Key Laboratory of Plant ImmunityJiangsu Provincial Key Lab for Organic Solid Waste UtilizationJiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, , National Engineering Research Center for Organic-based Fertilizers, Nanjing Agricultural University, ; Nanjing, 210095 China

[2 ]GRID grid.215654.1, ISNI 0000 0001 2151 2636, Center for Fundamental and Applied Microbiomics, , Biodesign Institute, Arizona State University, ; Tempe, AZ 85287 USA

[3 ]GRID grid.215654.1, ISNI 0000 0001 2151 2636, Faculty of Science and Mathematics, College of Integrative Sciences and Arts, , Arizona State University, ; Mesa, AZ USA

[4 ]GRID grid.512850.b, Agricultural Research Service, , USDA, San Joaquin Valley Agricultural Sciences Center, ; Parlier, CA 93648 USA

[5 ]GRID grid.508980.c, Agricultural Research Service, US Department of Agriculture, , Wheat Health, Genetics and Quality Research Unit, ; Pullman, WA 99164 USA

Article

Publisher ID: 1375

DOI: 10.1186/s40168-022-01375-z

PMC ID: 9587672

PubMed ID: 36271396

SO-VID: b48719c4-a4a4-4a1b-b233-6e8d009002dd

License:

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 4 April 2022

Date accepted : 19 September 2022

Custom metadata

Keywords: microbial community assembly,phylogenetic pattern,rhizosphere metabolomics,fusarium wilt disease,integration analysis metadata

Data availability:

Keywords: microbial community assembly, phylogenetic pattern, rhizosphere metabolomics, fusarium wilt disease, integration analysis metadata

Specific metabolites drive the deterministic assembly of diseased rhizosphere microbiome through weakening microbial degradation of autotoxin

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Abstract

Background

Results

Conclusion

Supplementary Information

Related collections

Tick microbiome

Most cited references 54

Search and clustering orders of magnitude faster than BLAST.

CD-HIT: accelerated for clustering the next-generation sequencing data

MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph.

Author and article information

Contributors

Journal

Affiliations

Article

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