Evidence map›Paper›PMID 39513723›Full record

ArticleApplied and environmental microbiology2024

Soil fungal networks exhibit sparser interactions than bacterial networks in diseased banana plantations.

Peng Chen, Jinku Li, Dandan Wei, Yanlin Chen, Chen He, Huanyu Bao, Zhongjun Jia, Yunze Ruan, Pingshan Fan

Abstract read
In one paragraph

Article in Applied and environmental microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Peng ChenSanya Institute of Breeding and Multiplication, Hainan University, Sanya, China.
Jinku LiSanya Institute of Breeding and Multiplication, Hainan University, Sanya, China.
Dandan WeiSanya Institute of Breeding and Multiplication, Hainan University, Sanya, China.
Yanlin ChenSanya Institute of Breeding and Multiplication, Hainan University, Sanya, China.
Chen HeSanya Institute of Breeding and Multiplication, Hainan University, Sanya, China.
Huanyu BaoSanya Institute of Breeding and Multiplication, Hainan University, Sanya, China.
Zhongjun JiaSchool of Tropical Agriculture and Forestry, Hainan University, Haikou, China.ORCID 0000-0003-2915-8648
Yunze RuanSanya Institute of Breeding and Multiplication, Hainan University, Sanya, China.ORCID 0000-0002-0539-776X
Pingshan FanSanya Institute of Breeding and Multiplication, Hainan University, Sanya, China.ORCID 0009-0005-7975-0633

Funding

MOST | National Natural Science Foundation of China (NSFC) 32160750Natural Science Foundation of Hainan Province (Hainan Natural Science Foundation) 324QN203the project of Sanya Yazhou Bay Science and Technology City SCKJ-JYRC-2022-94
6 · The paper itself

Abstract

Soil microorganisms play a crucial role in suppressing soil-borne diseases. Although the composition of microbial communities in healthy versus diseased soils is somewhat understood, the interplay between microbial interactions and disease incidence remains unclear. This study used 16S rRNA and fungal internal transcribed spacer (ITS) sequencing to investigate the bacterial and fungal community composition in three soil types: forest soil (Z), soil from healthy banana plantations (H), and soil from diseased banana plantations (D). Principal coordinate analysis revealed significant differences among the bacterial and fungal community structures of the three soil types. Compared with those in forest soil, bacterial and fungal diversities significantly decreased in diseased banana soil. Key microorganisms, including the bacteria Chloroflexi and Pseudonocardia and the fungi Mortierellomycota and Moesziomyces, were significantly increased in soil from diseased banana plantations. Redundancy analysis revealed that total nitrogen and available phosphorus were the primary drivers of the soil microbial community structure. The neutral community model posited that the bacterial community assembly in banana plantations is predominantly governed by stochastic processes, whereas the fungal community assembly in banana plantations is primarily driven by deterministic processes. Furthermore, co-occurrence network analysis revealed that the proportion of positive edges in the fungal network of soil from diseased banana plantations was 5.92 times lower than that in soil from healthy banana plantations, and its fungal network structure was sparse and simple. In conclusion, reduced interactions within the fungal network were significantly linked to the epidemiology of Fusarium wilt. These findings underscore the critical role of soil fungal communities in modulating pathogens. IMPORTANCE: Soil microorganisms are pivotal in mitigating soil-borne diseases. The intricate mechanisms underlying the interactions among microbes and their impact on disease occurrence remain enigmatic. This study underscores that a reduction in fungal network interactions correlates with the incidence of soil-borne Fusarium wilt.

Indexed as

BacteriaFungiMusaPlant DiseasesSoil MicrobiologyFusariumMicrobial InteractionsMicrobiotaRNA, Ribosomal, 16SSoilRNA, Ribosomal, 16SSoilbanana wilt diseasefungal communitymicrobial network stabilityneutral model

Identifiers

PMID39513723
PMCPMC11653737

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Registered trials

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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.