Evidence map›Paper›PMID 27177684›Full record

ArticleBMC infectious diseases2016

Clinical and epidemiological analysis of Campylobacter fetus subsp. fetus infections in humans and comparative genetic analysis with strains isolated from cattle.

Robert Escher, Colette Brunner, Niklaus von Steiger, Isabelle Brodard, Sara Droz, Carlos Abril, Peter Kuhnert

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

10 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Campylobacter in Africa - A specific viewpoint.European journal of microbiology & immunology · 2023
    Review
  4. Antimicrobial resistance inMicrobial genomics · 2023
    Article
  5. Article
  6. Phylogenomic analysis forVeterinary world · 2021
    Article
  7. Article
  8. Isolation ofThe Canadian veterinary journal = La revue veterinaire canadienne · 2020
    Article
  9. Determinants of sporadicClinical epidemiology · 2018
    Article
  10. Review
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 at 2 institutions in 1 country.

Robert EscherDepartment of Medicine, Spital Emmental, Burgdorf, Switzerland. robert.escher@spital-emmental.ch.
Colette BrunnerDepartment of Medicine, Spital Emmental, Burgdorf, Switzerland.
Niklaus von SteigerInstitute for Infectious Diseases, University of Bern, Bern, Switzerland.
Isabelle BrodardInstitute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
Sara DrozInstitute for Infectious Diseases, University of Bern, Bern, Switzerland.
Carlos AbrilInstitute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
Peter KuhnertInstitute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
University of Bern · CHRegionalspital Emmental · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCampylobacter fetus subspecies fetus (CFF) is an important pathogen for both cattle and humans. We performed a systematic epidemiological and clinical study of patients and evaluated the genetic relatedness of 17 human and 17 bovine CFF isolates by using different genotyping methods. In addition, the serotype, the dissemination of the genomic island containing a type IV secretion system (T4SS) and resistance determinants for tetracycline and streptomycin were also evaluated.

methodsThe isolates from patients diagnosed with CFF infection as well as those from faecal samples of healthy calves were genotyped using pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), as well as single locus sequence typing (SLST) targeting cmp1 and cmp2 genes encoding two major outer membrane proteins in CFF. The presence of the genomic island and identification of serotype was determined by PCRs targeting genes of the T4SS and the sap locus, respectively. Tetracycline and streptomycin resistance phenotypes were determined by minimal inhibitory concentration. Clinical data obtained from medical records and laboratory data were supplemented by data obtained via telephone interviews with the patients and treating physicians.

resultsPFGE analysis defined two major clusters; cluster A containing 16 bovine (80 %) isolates and cluster B containing 13 human (92 %) isolates, suggesting a host preference. Further genotypic analysis using MLST, SLST as well as sap and T4SS PCR showed the presence of genotypically identical isolates in cattle and humans. The low diversity observed within the cmp alleles of CFF corroborates the clonal nature of this pathogen. The genomic island containing the tetracycline and streptomycin resistance determinants was found in 55 % of the isolates in cluster A and correlated with phenotypic antibiotic resistance.

conclusionsMost human and bovine isolates were separated on two phylogenetic clusters. However, several human and bovine isolates were identical by diverse genotyping methods, indicating a possible link between strains from these two hosts.

Indexed as

AdultAgedAged, 80 and overAnimalsAnti-Bacterial AgentsCampylobacter fetusCampylobacter InfectionsCattleDrug Resistance, BacterialElectrophoresis, Gel, Pulsed-FieldFemaleGenotypeHumansMaleMicrobial Sensitivity TestsMiddle AgedAnti-Bacterial AgentsStreptomycinTetracyclineCampylobacter fetus subspecies fetusEpidemiologyMajor outer membrane protein (MOMP)Multilocus sequence typing (MLST)Pulsed-field gel electrophoresis (PFGE)Type IV secretion system (T4SS)

Identifiers

PMID27177684
PMCPMC4868008
OpenAlexW2386417829

What OpenQuestion holds

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LicenceCC BY
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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.