Evidence map›Paper›PMID 32780112›Full record

ArticleThe Journal of antimicrobial chemotherapy2020

ResFinder 4.0 for predictions of phenotypes from genotypes.

Valeria Bortolaia, Rolf S Kaas, Etienne Ruppe, Marilyn C Roberts, Stefan Schwarz, Vincent Cattoir, Alain Philippon, Rosa L Allesoe, Ana Rita Rebelo, Alfred Ferrer Florensa and 25 more

Abstract read
In one paragraph

Article in The Journal of antimicrobial chemotherapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2,163 papers.

0numbers the graph read from it
0cells of the map it votes in
2,163citing 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

2,163 citing papers in PubMed.

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2,103 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

35 authors.

Valeria BortolaiaTechnical University of Denmark, National Food Institute, European Union Reference Laboratory for Antimicrobial Resistance, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, FAO Reference Laboratory for Antimicrobial Resistance, Kgs. Lyngby, Denmark.
Rolf S KaasTechnical University of Denmark, National Food Institute, European Union Reference Laboratory for Antimicrobial Resistance, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, FAO Reference Laboratory for Antimicrobial Resistance, Kgs. Lyngby, Denmark.
Etienne RuppeUniversité de Paris, IAME, INSERM, Paris, France.
Marilyn C RobertsDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA.
Stefan SchwarzInstitute of Microbiology and Epizootics, Centre for Infection Medicine, Department of Veterinary Medicine, Freie Universität Berlin, Berlin, Germany.
Vincent CattoirRennes University Hospital, Department of Clinical Microbiology, Rennes, France.
Alain PhilipponFaculty of Medicine Paris Descartes, Bacteriology, Paris, France.
Rosa L AllesoeTechnical University of Denmark, National Food Institute, European Union Reference Laboratory for Antimicrobial Resistance, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, FAO Reference Laboratory for Antimicrobial Resistance, Kgs. Lyngby, Denmark.
Ana Rita RebeloTechnical University of Denmark, National Food Institute, European Union Reference Laboratory for Antimicrobial Resistance, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, FAO Reference Laboratory for Antimicrobial Resistance, Kgs. Lyngby, Denmark.
Alfred Ferrer FlorensaTechnical University of Denmark, National Food Institute, European Union Reference Laboratory for Antimicrobial Resistance, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, FAO Reference Laboratory for Antimicrobial Resistance, Kgs. Lyngby, Denmark.
Linda FagelhauerInstitute of Medical Microbiolgy, Justus Liebig University Giessen, Giessen, Germany.
Trinad ChakrabortyInstitute of Medical Microbiolgy, Justus Liebig University Giessen, Giessen, Germany.
Bernd NeumannRobert Koch Institute, Wernigerode Branch, Department of Infectious Diseases, Division of Nosocomial Pathogens and Antibiotic Resistances, Wernigerode, Germany.
Guido WernerRobert Koch Institute, Wernigerode Branch, Department of Infectious Diseases, Division of Nosocomial Pathogens and Antibiotic Resistances, Wernigerode, Germany.
Jennifer K BenderRobert Koch Institute, Wernigerode Branch, Department of Infectious Diseases, Division of Nosocomial Pathogens and Antibiotic Resistances, Wernigerode, Germany.
Kerstin StinglGerman Federal Institute for Risk Assessment, Department of Biological Safety, National Reference Laboratory for Campylobacter, Berlin, Germany.
Minh NguyenLaboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Belgium.
Jasmine CoppensLaboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Belgium.
Basil Britto XavierLaboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Belgium.
Surbhi Malhotra-KumarLaboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Belgium.
Henrik WesthDepartment of Clinical Microbiology, Hvidovre University Hospital, Hvidovre, Denmark.
Mette PinholtDepartment of Clinical Microbiology, Hvidovre University Hospital, Hvidovre, Denmark.
Muna F AnjumAnimal and Plant Health Agency, Addlestone, Surrey, UK.
Nicholas A DuggettAnimal and Plant Health Agency, Addlestone, Surrey, UK.
Isabelle KempfANSES, Ploufragan-Plouzané-Niort Laboratory, Ploufragan, France.
Suvi NykäsenojaFinnish Food Authority, Helsinki, Finland.
Satu OlkkolaFinnish Food Authority, Helsinki, Finland.
Kinga WieczorekNational Veterinary Research Institute, Pulawy, Poland.
Ana AmaroNational Institute of Agrarian and Veterinary Research (INIAV), National Reference Laboratory for Animal Health, Oeiras, Portugal.
Lurdes ClementeNational Institute of Agrarian and Veterinary Research (INIAV), National Reference Laboratory for Animal Health, Oeiras, Portugal.
Joël MossongLaboratoire National de Santé, Epidemiology and Microbial Genomics, Dudelange, Luxembourg.
Serge LoschLaboratoire de Médecine Vétérinaire de l'Etat, Veterinary Services Administration, Dudelange, Luxembourg.
Catherine RagimbeauLaboratoire National de Santé, Epidemiology and Microbial Genomics, Dudelange, Luxembourg.
Ole LundTechnical University of Denmark, National Food Institute, European Union Reference Laboratory for Antimicrobial Resistance, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, FAO Reference Laboratory for Antimicrobial Resistance, Kgs. Lyngby, Denmark.
Frank M AarestrupTechnical University of Denmark, National Food Institute, European Union Reference Laboratory for Antimicrobial Resistance, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and Genomics, FAO Reference Laboratory for Antimicrobial Resistance, Kgs. Lyngby, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesWGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output.

methodsThe ResFinder code was re-written to process raw reads and use Kmer-based alignment. The existing ResFinder and PointFinder databases were revised and expanded. Additional databases were developed including a genotype-to-phenotype key associating each AMR determinant with a phenotype at the antimicrobial compound level, and species-specific panels for in silico antibiograms. ResFinder 4.0 was validated using Escherichia coli (n = 584), Salmonella spp. (n = 1081), Campylobacter jejuni (n = 239), Enterococcus faecium (n = 106), Enterococcus faecalis (n = 50) and Staphylococcus aureus (n = 163) exhibiting different AST profiles, and from different human and animal sources and geographical origins.

resultsGenotype-phenotype concordance was ≥95% for 46/51 and 25/32 of the antimicrobial/species combinations evaluated for Gram-negative and Gram-positive bacteria, respectively. When genotype-phenotype concordance was <95%, discrepancies were mainly linked to criteria for interpretation of phenotypic tests and suboptimal sequence quality, and not to ResFinder 4.0 performance.

conclusionsWGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialAnimalsGenotypeHumansMicrobial Sensitivity TestsPhenotypeAnti-Bacterial Agents

Identifiers

PMID32780112
PMCPMC7662176

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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.