Evidence map›Paper›PMID 39215347›Full record

ArticleMicrobiome2024

Deciphering the role of rhizosphere microbiota in modulating disease resistance in cabbage varieties.

Xingxing Ping, Raja Asad Ali Khan, Shumin Chen, Yang Jiao, Xia Zhuang, Lijun Jiang, Liqun Song, Yuhong Yang, Jianlong Zhao, Yan Li and 3 more

Abstract read
In one paragraph

Article in Microbiome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Plant signaling & behavior · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Xingxing PingState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Raja Asad Ali KhanSchool of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, YaZhou, 572024, China.
Shumin ChenState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Yang JiaoState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Xia ZhuangSchool of Life Sciences, National Navel Orange Engineering Research Center, Gannan Normal University, Ganzhou, China.
Lijun JiangState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Liqun SongMicrobial Research Institute of Liaoning Province, Liaoning Academy of Agricultural Sciences, Chaoyang, China.
Yuhong YangState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Jianlong ZhaoState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Yan LiState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
Zhenchuan MaoState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China. maozhenchuan@caas.cn.
Bingyan XieState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China. xiebingyan@caas.cn.
Jian LingState Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China. lingjian@caas.cn.

Funding

National Key Research and Development Program of China 2022YFD1401200National Natural Science Foundation of China NSFC 31571962
6 · The paper itself

Abstract

backgroundCabbage Fusarium wilt (CFW) is a devastating disease caused by the soil-borne fungus Fusarium oxysporum f. sp. conglutinans (Foc). One of the optimal measures for managing CFW is the employment of tolerant/resistant cabbage varieties. However, the interplay between plant genotypes and the pathogen Foc in shaping the rhizosphere microbial community, and the consequent influence of these microbial assemblages on biological resistance, remains inadequately understood.

resultsBased on amplicon metabarcoding data, we observed distinct differences in the fungal alpha diversity index (Shannon index) and beta diversity index (unweighted Bray-Curtis dissimilarity) within the rhizosphere of the YR (resistant to Foc) and ZG (susceptible to Foc) cabbage varieties, irrespective of Foc inoculation. Notably, the Shannon diversity shifts in the resistant YR variety were more pronounced following Foc inoculation. Disease-resistant plant variety demonstrate a higher propensity for harboring beneficial microorganisms, such as Pseudomonas, and exhibit superior capabilities in evading harmful microorganisms, in contrast to their disease-susceptible counterparts. Furthermore, the network analysis was performed on rhizosphere-associated microorganisms, including both bacteria and fungi. The networks of association recovered from YR exhibited greater complexity, robustness, and density, regardless of Foc inoculation. Following Foc infection in the YR rhizosphere, there was a notable increase in the dominant bacterium NA13, which is also a hub taxon in the microbial network. Reintroducing NA13 into the soil significantly improved disease resistance in the susceptible ZG variety, by directly inhibiting Foc and triggering defense mechanisms in the roots.

conclusionsThe rhizosphere microbial communities of these two cabbage varieties are markedly distinct, with the introduction of the pathogen eliciting significant alterations in their microbial networks which is correlated with susceptibility or resistance to soil-borne pathogens. Furthermore, we identified a rhizobacteria species that significantly boosts disease resistance in susceptible cabbages. Our results indicated that the induction of resistance genes leading to varied responses in microbial communities to pathogens may partly explain the differing susceptibilities of the cabbage varieties tested to CFW. Video Abstract.

Indexed as

BrassicaDisease ResistanceFusariumMicrobiotaPlant DiseasesRhizosphereSoil MicrobiologyBacteriaFungiPlant RootsCabbageCo-occurrence networksDisease resistanceFusarium oxysporum f. sp. ConglutinansFusarium wiltPlant defenceRhizosphere microbes

Identifiers

PMID39215347
PMCPMC11363401

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.