Evidence map›Paper›PMID 40390122›Full record

ArticleMicrobiome2025

Interactions with native microbial keystone taxa enhance the biocontrol efficiency of Streptomyces.

Tianyu Sun, Hongwei Liu, Ningqi Wang, Mingcong Huang, Samiran Banerjee, Alexandre Jousset, Yangchun Xu, Qirong Shen, Shimei Wang, Xiaofang Wang and 1 more

Erratum issuedAbstract read
In one paragraph

Article in Microbiome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Plant signaling & behavior · 2026
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  5. Biofilm synergy byBiofilm · 2026
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  6. Review
  7. High bacterial diversity drives the suppression of a soilborne plant disease.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
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  15. Article
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  18. Review
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  20. From Biocontrol to Synthesis: Innovative Progress ofInternational journal of molecular sciences · 2025
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Tianyu Sun *Jiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China.
Hongwei Liu *College of Agro-Grassland Science, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, People's Republic of China.
Ningqi WangJiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China.
Mingcong HuangJiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China.
Samiran BanerjeeDepartment of Microbiological Sciences, North Dakota State University, Fargo, ND, USA.
Alexandre JoussetJiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China.
Yangchun XuJiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China.
Qirong ShenJiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China.
Shimei WangJiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China. smwang@njau.edu.cn.
Xiaofang WangJiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China. wangxf@niau.edu.cn.
Zhong WeiJiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-Based Fertilizers of China, Jiangsu Collaborative Innovation Center for Solid Organic Wastes, Educational Ministry Engineering Center of Resource-saving fertilizers, Nanjing Agricultural University, Nanjing, 210095, China. weizhong@njau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStreptomyces spp. are known for producing bioactive compounds that suppress phytopathogens. However, previous studies have largely focused on their direct interactions with pathogens and plants, often neglecting their interactions with the broader soil microbiome. In this study, we hypothesized that these interactions are critical for effective pathogen control. We investigated a diverse collection of Streptomyces strains to select those with strong protective capabilities against tomato wilt disease caused by Ralstonia solanacearum. Leveraging a synthetic community (SynCom) established in our lab, alongside multiple in planta and in vitro co-cultivation experiments, as well as transcriptomic and metabolomic analyses, we explored the synergistic inhibitory mechanisms underlying bacterial wilt resistance facilitated by both Streptomyces and the soil microbiome.

resultsOur findings indicate that direct antagonism by Streptomyces is not sufficient for their biocontrol efficacy. Instead, the efficacy was associated with shifts in the rhizosphere microbiome, particularly the promotion of two native keystone taxa, CSC98 (Stenotrophomonas maltophilia) and CSC13 (Paenibacillus cellulositrophicus). In vitro co-cultivation experiments revealed that CSC98 and CSC13 did not directly inhibit the pathogen. Instead, the metabolite of CSC13 significantly enhanced the inhibition efficiency of Streptomyces R02, a highly effective biocontrol strain in natural soil. Transcriptomic and metabolomic analyses revealed that CSC13's metabolites induced the production of Erythromycin E in Streptomyces R02, a key compound that directly suppressed R. solanacearum, as demonstrated by our antagonism tests.

conclusionsCollectively, our study reveals how beneficial microbes engage with the native soil microbiome to combat pathogens, suggesting the potential of leveraging microbial interactions to enhance biocontrol efficiency. These findings highlight the significance of intricate microbial interactions within the microbiome in regulating plant diseases and provide a theoretical foundation for devising efficacious biocontrol strategies in sustainable agriculture. Video Abstract.

Indexed as

Microbial InteractionsMicrobiotaPlant DiseasesStreptomycesAntibiosisRalstonia solanacearumRhizosphereSoil MicrobiologySolanum lycopersicumMicrobial interactionMulti-omics analysisPaenibacillusStenotrophomonasStreptomycesSynthetic communityTomato bacterial wilt

Identifiers

PMID40390122
PMCPMC12087250

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.