Evidence map›Paper›PMID 36221919›Full record

ArticleThe plant pathology journal2022

Optimization of the Bacteriophage Cocktail for the Prevention of Brown Blotch Disease Caused by Pseudomonas tolaasii.

Yeong-Bae Yun, Yurry Um, Young-Kee Kim

Open access · goldAbstract read
In one paragraph

Article in The plant pathology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 36% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. 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

3 authors at 2 institutions in 1 country.

Yeong-Bae YunDepartment of Environmental and Biological Chemistry, Chungbuk National University, Cheongju 28644, Korea.
Yurry UmForest Medicinal Resources Research Center, National Institute of Forest Science, Yeongju 36040, Korea.
Young-Kee KimDepartment of Environmental and Biological Chemistry, Chungbuk National University, Cheongju 28644, Korea.
Chungbuk National University · KRKorea Forest Service · KR

Funding

Ministry of EducationNational Research Foundation of Korea 2017R1D1A3B03032718
6 · The paper itself

Abstract

Brown blotch disease, caused by Pseudomonas tolaasii, is one of the most serious diseases in mushroom cultivation, and its control remains an important issue. This study isolated and evaluated pathogen-specific bacteriophages for the biological control of the disease. In previous studies, 23 varieties of P. tolaasii were isolated from infected mushrooms with disease symptoms and classified into three subtypes, Ptα, Ptβ, and Ptγ, based on their 16S rRNA gene sequences analysis and pathogenic characters. In this study, 42 virulent bacteriophages were isolated against these pathogens and tested for their host range. Some phages could lyse more than two pathogens only within the corresponding subtype, and no phage exhibited a wide host range across different pathogen subtypes. To eliminate all pathogens of the Ptα, Ptβ, and Ptγ subtype, corresponding phages of one, six, and one strains were required, respectively. These phages were able to suppress the disease completely, as confirmed by the field-scale on-farm cultivation experiments. These results suggested that a cocktail of these eight phages is sufficient to control the disease induced by all 23 P. tolaasii pathogens. Additionally, the antibacterial effect of this phage cocktail persisted in the second cycle of mushroom growth on the cultivation bed.

Indexed as

bacteriophagemushroom blotch diseasephage therapyPseudomonas tolaasiitolaasin

Identifiers

PMID36221919
PMCPMC9561164
OpenAlexW4297969076

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.