ResFinder 4.0 for predictions of phenotypes from genotypes

Valeria Bortolaia(Technical University of Denmark), Rolf Sommer Kaas(Technical University of Denmark), Étienne Ruppé(Inserm), Marilyn C. Roberts(University of Washington), Štefan Schwarz(Freie Universität Berlin), Vincent Cattoir(Inserm), A. Philippon(Délégation Paris 5), Rosa Lundbye Allesøe(University of Copenhagen), Ana Rita Rebelo(Technical University of Denmark), Alfred Ferrer Florensa(Technical University of Denmark), Linda Fagelhauer(Justus-Liebig-Universität Gießen), Trinad Chakraborty(Justus-Liebig-Universität Gießen), Bernd Neumann(Robert Koch Institute), Guido Werner(Robert Koch Institute), Jennifer K. Bender(Robert Koch Institute), Kerstin Stingl(Federal Institute for Risk Assessment), Minh Ngoc Nguyen(University of Antwerp), Jasmine Coppens(University of Antwerp), Basil Britto Xavier(University of Antwerp), Surbhi Malhotra‐Kumar(University of Antwerp), Henrik Westh(University of Copenhagen), Mette Pinholt(Hvidovre Hospital), Muna F. Anjum(Animal and Plant Health Agency), Nicholas Duggett(Animal and Plant Health Agency), Isabelle Kempf(Agence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du Travail), Suvi Nykäsenoja(Finnish Food Authority), Satu Olkkola(Finnish Food Authority), Kinga Wieczorek(National Veterinary Research Institute), Ana Amaro(Instituto Nacional de Investigação Agrária e Veterinária), Lurdes Clemente(Instituto Nacional de Investigação Agrária e Veterinária), Joël Mossong(Laboratoire National de Santé), Serge Losch(Laboratoire National de Santé), Catherine Ragimbeau(Laboratoire National de Santé), Ole Lund(Technical University of Denmark), Frank M. Aarestrup(Technical University of Denmark)
Journal of Antimicrobial Chemotherapy
July 16, 2020
Cited by 3,215Open Access
Full Text

Abstract

OBJECTIVES: WGS-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. METHODS: The 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. RESULTS: Genotype-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. CONCLUSIONS: WGS-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.


Related Papers

No related papers found

Powered by citation graph analysis