Evidence map›Paper›PMID 29140998›Full record

ArticlePloS one2017

Using whole genome sequencing to study American foulbrood epidemiology in honeybees.

Joakim Ågren, Marc Oliver Schäfer, Eva Forsgren

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Genomic diversity and tracing ofMicrobial genomics · 2025
    Article
  3. Genomic analysis of the population structure ofFrontiers in microbiology · 2023
    Article
  4. Review
  5. Article
  6. Article
  7. ERIC and WGS Typing ofInsects · 2021
    Article
  8. Analysis of the Global Population Structure ofFrontiers in veterinary science · 2021
    Article
  9. 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.

Joakim ÅgrenDepartment of Microbiology, National Veterinary Institute, Uppsala, Sweden.
Marc Oliver SchäferFederal Research Institute for Animal Health, Friedrich-Loeffler-Institut, Greifswald, Insel Riems, Germany.
Eva ForsgrenDepartment of Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden.ORCID http://orcid.org/0000-0002-8244-7265

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

American foulbrood (AFB), caused by Paenibacillus larvae, is a devastating disease in honeybees. In most countries, the disease is controlled through compulsory burning of symptomatic colonies causing major economic losses in apiculture. The pathogen is endemic to honeybees world-wide and is readily transmitted via the movement of hive equipment or bees. Molecular epidemiology of AFB currently largely relies on placing isolates in one of four ERIC-genotypes. However, a more powerful alternative is multi-locus sequence typing (MLST) using whole-genome sequencing (WGS), which allows for high-resolution studies of disease outbreaks. To evaluate WGS as a tool for AFB-epidemiology, we applied core genome MLST (cgMLST) on isolates from a recent outbreak of AFB in Sweden. The high resolution of the cgMLST allowed different bacterial clones involved in the disease outbreak to be identified and to trace the source of infection. The source was found to be a beekeeper who had sold bees to two other beekeepers, proving the epidemiological link between them. No such conclusion could have been made using conventional MLST or ERIC-typing. This is the first time that WGS has been used to study the epidemiology of AFB. The results show that the technique is very powerful for high-resolution tracing of AFB-outbreaks.

Indexed as

Genome, BacterialAnimalsBeesDisease OutbreaksMolecular EpidemiologyMultilocus Sequence TypingPaenibacillus larvaeSweden

Identifiers

PMID29140998
PMCPMC5687730

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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.