Evidence map›Paper›PMID 41656717›Full record

ArticleThe plant pathology journal2026

Bayesian Pairwise Compositional Lotka-Volterra Modeling Infers Potential Rhizosphere Microbial Suppressors of Ralstonia pseudosolanacearum.

Gyeongjun Cho, Do-Hyun Kim, Jeong-Seon Kim, Jaekyeong Song, Soo-Jin Kim

Abstract read
In one paragraph

Article in The plant pathology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Gyeongjun ChoDivision of Agricultural Microbiology, National Institute of Agriculture Sciences, Rural Development Administration, Wanju 55365, Korea.
Do-Hyun KimDivision of Agricultural Microbiology, National Institute of Agriculture Sciences, Rural Development Administration, Wanju 55365, Korea.
Jeong-Seon KimDivision of Agricultural Microbiology, National Institute of Agriculture Sciences, Rural Development Administration, Wanju 55365, Korea.
Jaekyeong SongDivision of Agricultural Microbiology, National Institute of Agriculture Sciences, Rural Development Administration, Wanju 55365, Korea.
Soo-Jin KimDivision of Agricultural Microbiology, National Institute of Agriculture Sciences, Rural Development Administration, Wanju 55365, Korea.

Funding

Rural Development Administration PJ01727501
6 · The paper itself

Abstract

The Ralstonia solanacearum species complex (RSSC) is a major soil-borne pathogen of solanaceous crops. During a field experiment originally designed to monitor rhizosphere and episphere microbiomes in two pepper cultivars, a naturally emerging and asymptomatic Ralstonia dominance event was detected in the rhizosphere without visible wilt symptoms. This unexpected occurrence provided an opportunity to characterize asymptomatic RSSC dynamics and their microbial interactions under field conditions. Full-length 16S rRNA amplicon sequencing showed that one ASV (Sq_1) was nearly absent from the episphere but increased sharply in the rhizosphere from week 3 onward, dominating 20-80% of samples during weeks 7-10. Phylogenetic comparison with 93 historical Korean RSSC isolates placed Sq_1 within a 16S-defined lineage corresponding to pepper-associated R. pseudosolanacearum biovars 3 and 4. Sq_1 abundance accounted for a large portion of β-diversity turnover in the rhizosphere. After within-plot correlations were meta-analyzed, selected taxa were evaluated using a Bayesian pairwise compositional Lotka-Volterra (pcLV) model, which identified three taxa (Sq_272, TRA3-20; Sq_178, Bradyrhizobium; and Sq_124, Bryobacter) that consistently exerted inhibitory effects on Sq_1 per-interval growth. Supported by the longitudinal design and the high accuracy of PacBio full-length 16S sequencing, these findings highlight potential microbial suppressors of RSSC and demonstrate the utility of pcLV modeling for resolving directional interactions at the ASV level.

Indexed as

Capsicum annuumgeneralized Lotka–Volterrapairwise compositional Lotka–VolterraRalstonia pseudosolanacearumrhizosphere microbiome

Identifiers

PMID41656717
PMCPMC12884050

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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.