Evidence map›Paper›PMID 29789467›Full record

ReviewGenes2018

The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain.

Elena A Oniciuc, Eleni Likotrafiti, Adrián Alvarez-Molina, Miguel Prieto, Jesús A Santos, Avelino Alvarez-Ordóñez

Erratum issuedAbstract readReview
In one paragraph

Review in Genes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 79 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed, 2 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

79 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Predicting Antibiotic Resistance inInternational journal of molecular sciences · 2025
    Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Review
  7. Methicillin-ResistantInternational journal of molecular sciences · 2026
    Review
  8. Review
  9. Article
  10. Review
  11. Exploring the modulatory effects of spotted pumpkin (Translational animal science · 2026
    Article
  12. Journal of biosciences · 2026
    Article
  13. Antibiotic resistance inFrontiers in microbiology · 2026
    Review
  14. Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article

19 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Elena A OniciucFaculty of Food Science and Engineering, Dunarea de Jos University of Galati, Galati 800008, Romania. elena.oniciuc@ugal.ro.
Eleni LikotrafitiLaboratory of Food Microbiology, Department of Food Technology, Alexander Technological Educational Institute of Thessaloniki, Thessaloniki T.K. 57400, Greece. likotraf@food.teithe.gr.
Adrián Alvarez-MolinaDepartment of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, 24071 León, Spain. aalvm@unileon.es.
Miguel PrietoDepartment of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, 24071 León, Spain. miguel.prieto@unileon.es.ORCID 0000-0001-9202-3856
Jesús A SantosDepartment of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, 24071 León, Spain. j.santos@unileon.es.ORCID 0000-0003-4001-3386
Avelino Alvarez-OrdóñezDepartment of Food Hygiene and Technology and Institute of Food Science and Technology, Universidad de León, 24071 León, Spain. aalvo@unileon.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) surveillance is a critical step within risk assessment schemes, as it is the basis for informing global strategies, monitoring the effectiveness of public health interventions, and detecting new trends and emerging threats linked to food. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterization of clinical, environmental and food strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence or spread of AMR genes throughout the food chain. Whole-genome sequencing (WGS) of bacterial pathogens has shown potential for epidemiological surveillance, outbreak detection, and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on AMR genes occurrence. Both technologies can assist the tracking of AMR genes and mobile genetic elements, providing the necessary information for the implementation of quantitative risk assessments and allowing for the identification of hotspots and routes of transmission of AMR across the food chain. This review article summarizes the information currently available on the use of WGS and WMS for surveillance of AMR in foodborne pathogenic bacteria and food-related samples and discusses future needs that will have to be considered for the routine implementation of these next-generation sequencing methodologies with this aim. In particular, methodological constraints that impede the use at a global scale of these high-throughput sequencing (HTS) technologies are identified, and the standardization of methods and protocols is suggested as a measure to upgrade HTS-based AMR surveillance schemes.

Indexed as

antimicrobial resistancefoodborne pathogensmetagenomicssurveillancewhole genome sequencing

Identifiers

PMID29789467
PMCPMC5977208

What OpenQuestion holds

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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.