ResFinder 4.0 for predictions of phenotypes from genotypes

Author:

Bortolaia Valeria1,Kaas Rolf S1ORCID,Ruppe Etienne2,Roberts Marilyn C3,Schwarz Stefan4ORCID,Cattoir Vincent567ORCID,Philippon Alain8,Allesoe Rosa L19,Rebelo Ana Rita1,Florensa Alfred Ferrer1,Fagelhauer Linda101112,Chakraborty Trinad1011,Neumann Bernd13,Werner Guido13,Bender Jennifer K13,Stingl Kerstin14,Nguyen Minh15ORCID,Coppens Jasmine15,Xavier Basil Britto15,Malhotra-Kumar Surbhi15,Westh Henrik1617,Pinholt Mette16,Anjum Muna F18,Duggett Nicholas A18,Kempf Isabelle19,Nykäsenoja Suvi20,Olkkola Satu20,Wieczorek Kinga21,Amaro Ana22,Clemente Lurdes22,Mossong Joël23,Losch Serge24,Ragimbeau Catherine23,Lund Ole1,Aarestrup Frank M1ORCID

Affiliation:

1. Technical 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

2. Université de Paris, IAME, INSERM, Paris, France

3. Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA

4. Institute of Microbiology and Epizootics, Centre for Infection Medicine, Department of Veterinary Medicine, Freie Universität Berlin, Berlin, Germany

5. Rennes University Hospital, Department of Clinical Microbiology, Rennes, France

6. National Reference Center for Antimicrobial Resistance (lab Enterococci), Rennes, France

7. University of Rennes 1, INSERM U1230, Rennes, France

8. Faculty of Medicine Paris Descartes, Bacteriology, Paris, France

9. Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark

10. Institute of Medical Microbiolgy, Justus Liebig University Giessen, Giessen, Germany

11. German Center for Infection Research, site Giessen-Marburg-Langen, Justus Liebig University Giessen, Giessen, Germany

12. Institute of Hygiene and Environmental Medicine, Justus Liebig University Giessen, Giessen, Germany

13. Robert Koch Institute, Wernigerode Branch, Department of Infectious Diseases, Division of Nosocomial Pathogens and Antibiotic Resistances, Wernigerode, Germany

14. German Federal Institute for Risk Assessment, Department of Biological Safety, National Reference Laboratory for Campylobacter, Berlin, Germany

15. Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Belgium

16. Department of Clinical Microbiology, Hvidovre University Hospital, Hvidovre, Denmark

17. Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark

18. Animal and Plant Health Agency, Addlestone, Surrey, UK

19. ANSES, Ploufragan-Plouzané-Niort Laboratory, Ploufragan, France

20. Finnish Food Authority, Helsinki, Finland

21. National Veterinary Research Institute, Pulawy, Poland

22. National Institute of Agrarian and Veterinary Research (INIAV), National Reference Laboratory for Animal Health, Oeiras, Portugal

23. Laboratoire National de Santé, Epidemiology and Microbial Genomics, Dudelange, Luxembourg

24. Laboratoire de Médecine Vétérinaire de l'Etat, Veterinary Services Administration, Dudelange, Luxembourg

Abstract

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.

Funder

European Union Horizon 2020

Novo Nordisk Foundation

Global Surveillance of Antimicrobial Resistance

German Center of Infection Research

Zoonoses Network ‘ESBL

German Federal Ministry of Education and Research

BMBF

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Pharmacology (medical),Pharmacology,Microbiology (medical)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3