Evidence map›Paper›PMID 36599823›Full record

ArticleNature communications2023

An ISO-certified genomics workflow for identification and surveillance of antimicrobial resistance.

Norelle L Sherry, Kristy A Horan, Susan A Ballard, Anders Gonҫalves da Silva, Claire L Gorrie, Mark B Schultz, Kerrie Stevens, Mary Valcanis, Michelle L Sait, Timothy P Stinear and 2 more

Open access · goldAbstract read
PubMed Publisher
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
105citing papers in PubMed, 1 pooled it
23.1field-weighted citation impact, top 1% 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

105 citing papers in PubMed, 1 synthesis or guideline pooled it, 153 citations in OpenAlex.

  1. Trends in horizontal gene transfer research inFrontiers in microbiology · 2024
    Pooled it
  2. Genomic investigation and clinical correlates of theAntimicrobial agents and chemotherapy · 2024
    Trial
  3. Article
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  8. JAC-antimicrobial resistance · 2026
    Article
  9. Article
  10. Comprehensive Phenotypic Characterization of ClinicalInternational journal of molecular sciences · 2026
    Article
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  17. Review
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  20. Article

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

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

12 authors at 2 institutions in 1 country.

Norelle L SherryMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.ORCID 0000-0002-7789-8360
Kristy A HoranMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
Susan A BallardMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.ORCID 0000-0002-0096-9474
Anders Gonҫalves da SilvaMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
Claire L GorrieDepartment of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Australia.ORCID 0000-0002-2637-2529
Mark B SchultzMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.ORCID 0000-0002-7689-6531
Kerrie StevensMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
Mary ValcanisMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
Michelle L SaitMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.
Timothy P StinearDepartment of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Australia.ORCID 0000-0003-0150-123X
Benjamin P HowdenMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia. bhowden@unimelb.edu.au.ORCID 0000-0003-0237-1473
Torsten SeemannMicrobiological Diagnostic Unit Public Health Laboratory (MDU-PHL), Department of Microbiology & Immunology, University of Melbourne at the Peter Doherty Institute for Infection & Immunity, Melbourne, Victoria, Australia.ORCID 0000-0001-6046-610X
The University of Melbourne · AUPeter Doherty Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Realising the promise of genomics to revolutionise identification and surveillance of antimicrobial resistance (AMR) has been a long-standing challenge in clinical and public health microbiology. Here, we report the creation and validation of abritAMR, an ISO-certified bioinformatics platform for genomics-based bacterial AMR gene detection. The abritAMR platform utilises NCBI's AMRFinderPlus, as well as additional features that classify AMR determinants into antibiotic classes and provide customised reports. We validate abritAMR by comparing with PCR or reference genomes, representing 1500 different bacteria and 415 resistance alleles. In these analyses, abritAMR displays 99.9% accuracy, 97.9% sensitivity and 100% specificity. We also compared genomic predictions of phenotype for 864 Salmonella spp. against agar dilution results, showing 98.9% accuracy. The implementation of abritAMR in our institution has resulted in streamlined bioinformatics and reporting pathways, and has been readily updated and re-verified. The abritAMR tool and validation datasets are publicly available to assist laboratories everywhere harness the power of AMR genomics in professional practice.

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialComputational BiologyGenomicsMicrobial Sensitivity TestsWorkflowAnti-Bacterial Agents

Identifiers

PMID36599823
OpenAlexW4313544502

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.