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.

The widespread use of antibiotics in association with high-density clinical care has driven the emergence of drugresistant bacteria that are adapted to thrive in hospitalized patients. Of particular concern are globally disseminated methicillin-resistant Staphylococcus aureus (MRSA) clones that cause outbreaks and epidemics associated with health care. The most rapidly spreading and tenacious health-care-associated clone in Europe currently is EMRSA-15, which was first detected in the UK in the early 1990s and subsequently spread throughout Europe and beyond. Using phylogenomic methods to analyze the genome sequences for 193 S. aureus isolates, we were able to show that the current pandemic population of EMRSA-15 descends from a health-care-associated MRSA epidemic that spread throughout England in the 1980s, which had itself previously emerged from a primarily community-associated methicillin-sensitive population. The emergence of fluoroquinolone resistance in this EMRSA-15 subclone in the English Midlands during the mid-1980s appears to have played a key role in triggering pandemic spread, and occurred shortly after the first clinical trials of this drug. Genome-based coalescence analysis estimated that the population of this subclone over the last 20 yr has grown four times faster than its progenitor. Using comparative genomic analysis we identified the molecular genetic basis of 99.8% of the antimicrobial resistance phenotypes of the isolates, highlighting the potential of pathogen genome sequencing as a diagnostic tool. We document the genetic changes associated with adaptation to the hospital environment and with increasing drug resistance over time, and how MRSA evolution likely has been influenced by country-specific drug use regimens.

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