Evidence map›Paper›PMID 19863821›Full record

ArticleBMC microbiology2009

Application and evaluation of the MLVA typing assay for the Brucella abortus strains isolated in Korea.

Moon Her, Sung-Il Kang, Dong-Hee Cho, Yun-Sang Cho, In-Yeong Hwang, Young-Ran Heo, Suk-Chan Jung, Han-Sang Yoo

Abstract readEvaluation Study
In one paragraph

Article in BMC microbiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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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

16 citing papers in PubMed.

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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

8 authors.

Moon HerOIE Reference Laboratory for Brucellosis & Zoonosis Laboratory, Bacteriology and Parasitology Division, Veterinary Research Department, National Veterinary Research and Quarantine Service, Anyang, Gyeonggi, Republic of Korea. herm@nvrqs.go.kr
Sung-Il Kang
Dong-Hee Cho
Yun-Sang Cho
In-Yeong Hwang
Young-Ran Heo
Suk-Chan Jung
Han-Sang Yoo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA Brucella eradication program has been executed in Korea. To effectively prevent and control brucellosis, a molecular method for genetic identification and epidemiological trace-back must be established. As part of that, the MLVA typing assay was evaluated and applied to B. abortus isolates for analyzing the characteristics of the regional distribution and relationships of foreign isolates.

resultsA total of 177 isolates originating from 105 cattle farms for the period 1996 to 2008 were selected as representatives for the nine provinces of South Korea. A dendrogram of strain relatedness was constructed in accordance with the number of tandem repeat units for 17 loci so that it was possible to trace back in the restricted areas. Even in a farm contaminated by one source, however, the Brucella isolates showed an increase or decrease in one TRs copy number at some loci with high DI values. Moreover, those 17 loci was confirmed in stability via in-vitro and in-vivo passage, and found to be sufficiently stable markers that can readily identify the inoculated strain even if minor changes were detected. In the parsimony analysis with foreign Brucella isolates, domestic isolates were clustered distinctively, and located near the Central and Southern American isolates.

conclusionThe MLVA assay has enough discrimination power in the Brucella species level and can be utilized as a tool for the epidemiological trace-back of the B. abortus isolates. But it is important to consider that Brucella isolates may be capable of undergoing minor changes at some loci in the course of infection or in accordance with the changes of the host.

Indexed as

AnimalsBacterial Typing TechniquesBrucella abortusCattleCluster AnalysisDNA, BacterialGenetic VariationGenotypeRepublic of KoreaTandem Repeat SequencesDNA, Bacterial

Identifiers

PMID19863821
PMCPMC2774859

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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.