Antimicrobial resistance (AMR) is a major public health problem that requires publicly available tools for rapid analysis. To identify AMR genes in whole-genome sequences, the National Center for Biotechnology Information (NCBI) has produced AMRFinder, a tool that identifies AMR genes using a high-quality curated AMR gene reference database. The Bacterial Antimicrobial Resistance Reference Gene Database consists of up-to-date gene nomenclature, a set of hidden Markov models (HMMs), and a curated protein family hierarchy. Currently, it contains 4,579 antimicrobial resistance proteins and more than 560 HMMs. Here, we describe AMRFinder and its associated database. To assess the predictive ability of AMRFinder, we measured the consistency between predicted AMR genotypes from AMRFinder and resistance phenotypes of 6,242 isolates from the National Antimicrobial Resistance Monitoring System (NARMS). This included 5,425 Salmonella enterica, 770 Campylobacter spp., and 47 Escherichia coli isolates phenotypically tested against various antimicrobial agents. Of 87,679 susceptibility tests performed, 98.4% were consistent with predictions. To assess the accuracy of AMRFinder, we compared its gene symbol output with that of a 2017 version of ResFinder, another publicly available resistance gene detection system. Most gene calls were identical, but there were 1,229 gene symbol differences (8.8%) between them, with differences due to both algorithmic differences and database composition. AMRFinder missed 16 loci that ResFinder found, while ResFinder missed 216 loci that AMRFinder identified. Based on these results, AMRFinder appears to be a highly accurate AMR gene detection system.

Determining drug resistance trends will optimize treatment and public health responses.

WGS can provide comprehensive resistance genotypes and is capable of accurately predicting resistance phenotypes, making it a valuable tool for surveillance. Moreover, the data presented here showing the ability to accurately predict resistance suggest that WGS may be used as a screening tool in selecting anti-infective therapy, especially as costs drop and methods improve.

BackgroundOver the last decade, nosocomial infections due to Acinetobacter baumannii have been described with an increasing trend towards multidrug resistance, mostly in intensive care units. The aim of the present study was to determine the clonal relatedness of clinical isolates and to elucidate the genetic basis of imipenem resistance.MethodsA. baumannii isolates (n = 83) originated from two hospital settings in central Ohio were used in this study. Pulsed-field gel electrophoresis genotyping and antimicrobial susceptibility testing for clinically relevant antimicrobials were performed. Resistance determinants were characterized by using different phenotypic (accumulation assay for efflux) and genotypic (PCR, DNA sequencing, plasmid analysis and electroporation) approaches.ResultsThe isolates were predominantly multidrug resistant (>79.5%) and comprised of thirteen unique pulsotypes, with genotype VII circulating in both hospitals. The presence of blaOXA-23 in 13% (11/83) and ISAba1 linked blaOXA-66 in 79.5% (66/83) of clinical isolates was associated with high level imipenem resistance. In this set of OXA producing isolates, multidrug resistance was bestowed by blaADC-25, class 1 integron-borne aminoglycoside modifying enzymes, presence of sense mutations in gyrA/parC and involvement of active efflux (with evidence for the presence of adeB efflux gene).ConclusionThis study underscores the major role of carbapenem-hydrolyzing class D β-lactamases, and in particular the acquired OXA-23, in the dissemination of imipenem-resistant A. baumannii. The co-occurrence of additional resistance determinant could also be a significant threat.