Evidence map›Paper›PMID 25781022›Full record

ArticlePloS one2015

Unraveling antimicrobial resistance genes and phenotype patterns among Enterococcus faecalis isolated from retail chicken products in Japan.

Arata Hidano, Takehisa Yamamoto, Yoko Hayama, Norihiko Muroga, Sota Kobayashi, Takeshi Nishida, Toshiyuki Tsutsui

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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

7 authors.

Arata HidanoViral Disease and Epidemiology Research Division, National Institute of Animal Health, National Agriculture, and Food Research Organization, Tsukuba, Ibaraki, Japan; EpiCentre, Institute of Veterinary, Animal and Biomedical Sciences, Massey University, Palmerston North, New Zealand.
Takehisa YamamotoViral Disease and Epidemiology Research Division, National Institute of Animal Health, National Agriculture, and Food Research Organization, Tsukuba, Ibaraki, Japan.
Yoko HayamaViral Disease and Epidemiology Research Division, National Institute of Animal Health, National Agriculture, and Food Research Organization, Tsukuba, Ibaraki, Japan.
Norihiko MurogaViral Disease and Epidemiology Research Division, National Institute of Animal Health, National Agriculture, and Food Research Organization, Tsukuba, Ibaraki, Japan.
Sota KobayashiViral Disease and Epidemiology Research Division, National Institute of Animal Health, National Agriculture, and Food Research Organization, Tsukuba, Ibaraki, Japan.
Takeshi NishidaAnimal Products Safety Division, Food Safety and Consumer Affairs Bureau, Ministry of Agriculture, Forestry and Fisheries, Chiyoda-ku, Tokyo, Japan.
Toshiyuki TsutsuiViral Disease and Epidemiology Research Division, National Institute of Animal Health, National Agriculture, and Food Research Organization, Tsukuba, Ibaraki, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multidrug-resistant enterococci are considered crucial drivers for the dissemination of antimicrobial resistance determinants within and beyond a genus. These organisms may pass numerous resistance determinants to other harmful pathogens, whose multiple resistances would cause adverse consequences. Therefore, an understanding of the coexistence epidemiology of resistance genes is critical, but such information remains limited. In this study, our first objective was to determine the prevalence of principal resistance phenotypes and genes among Enterococcus faecalis isolated from retail chicken domestic products collected throughout Japan. Subsequent analysis of these data by using an additive Bayesian network (ABN) model revealed the co-appearance patterns of resistance genes and identified the associations between resistance genes and phenotypes. The common phenotypes observed among E. faecalis isolated from the domestic products were the resistances to oxytetracycline (58.4%), dihydrostreptomycin (50.4%), and erythromycin (37.2%), and the gene tet(L) was detected in 46.0% of the isolates. The ABN model identified statistically significant associations between tet(L) and erm(B), tet(L) and ant(6)-Ia, ant(6)-Ia and aph(3')-IIIa, and aph(3')-IIIa and erm(B), which indicated that a multiple-resistance profile of tetracycline, erythromycin, streptomycin, and kanamycin is systematic rather than random. Conversely, the presence of tet(O) was only negatively associated with that of erm(B) and tet(M), which suggested that in the presence of tet(O), the aforementioned multiple resistance is unlikely to be observed. Such heterogeneity in linkages among genes that confer the same phenotypic resistance highlights the importance of incorporating genetic information when investigating the risk factors for the spread of resistance. The epidemiological factors that underlie the persistence of systematic multiple-resistance patterns warrant further investigations with appropriate adjustments for ecological and bacteriological factors.

Indexed as

Food MicrobiologyGenes, BacterialAnimalsAnti-Bacterial AgentsChickensDrug Resistance, Multiple, BacterialEnterococcus faecalisJapanModels, BiologicalPoultry ProductsTetracycline ResistanceAnti-Bacterial Agents

Identifiers

PMID25781022
PMCPMC4363150

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.