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.
Antimicrobial resistance (AMR) is a significant public health threat. With the rise of affordable whole genome sequencing, in silico approaches to assessing AMR gene content can be used to detect known resistance mechanisms and potentially identify novel mechanisms. To enable accurate assessment of AMR gene content, as part of a multi-agency collaboration, NCBI developed a comprehensive AMR gene database, the Bacterial Antimicrobial Resistance Reference Gene Database and the AMR gene detection tool AMRFinder. Here, we describe the expansion of the Reference Gene Database, now called the Reference Gene Catalog, to include putative acid, biocide, metal, stress resistance genes, in addition to virulence genes and species-specific point mutations. Genes and point mutations are classified by broad functions, as well as more detailed functions. As we have expanded both the functional repertoire of identified genes and functionality, NCBI released a new version of AMRFinder, known as AMRFinderPlus. This new tool allows users the option to utilize only the core set of AMR elements, or include stress response and virulence genes, too. AMRFinderPlus can detect acquired genes and point mutations in both protein and nucleotide sequence. In addition, the evidence used to identify the gene has been expanded to include whether nucleotide or protein sequence was used, its location in the contig, and presence of an internal stop codon. These database improvements and functional expansions will enable increased precision in identifying AMR genes, linking AMR genotypes and phenotypes, and determining possible relationships between AMR, virulence, and stress response.
Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Wholegenome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens.
The ability of antimicrobial resistance (AR) to transfer, on mobile genetic elements (MGEs) between bacteria, can cause the rapid establishment of multidrug resistance (MDR) in bacteria from animals, thus creating a foodborne risk to human health. To investigate MDR and its association with plasmids in Salmonella enterica , whole genome sequence (WGS) analysis was performed on 193 S. enterica isolated from sources associated with United States food animals between 1998 and 2011; 119 were resistant to at least one antibiotic tested. Isolates represented 86 serotypes and variants, as well as diverse phenotypic resistance profiles. A total of 923 AR genes and 212 plasmids were identified among the 193 strains. Every isolate contained at least one AR gene. At least one plasmid was detected in 157 isolates. Genes were identified for resistance to aminoglycosides ( n = 472), β-lactams ( n = 84), tetracyclines ( n = 171), sulfonamides ( n = 91), phenicols ( n = 42), trimethoprim ( n = 8), macrolides ( n = 5), fosfomycin ( n = 48), and rifampicin ( n = 2). Plasmid replicon types detected in the isolates were A/C ( n = 32), ColE ( n = 76), F ( n = 43), HI1 ( n = 4), HI2 ( n = 20), I1 ( n = 62), N ( n = 4), Q ( n = 7), and X ( n = 35). Phenotypic resistance correlated with the AR genes identified in 95.4% of cases. Most AR genes were located on plasmids, with many plasmids harboring multiple AR genes. Six antibiotic resistance cassette structures (ARCs) and one pseudo-cassette were identified. ARCs contained between one and five resistance genes (ARC1: sul 2, strAB, tetAR ; ARC2: aac3-iid ; ARC3: aph, sph ; ARC4: cmy-2 ; ARC5: floR ; ARC6: tetB ; pseudo-ARC: aadA, aac3-VIa, sul 1). These ARCs were present in multiple isolates and on plasmids of multiple replicon types. To determine the current distribution and frequency of these ARCs, the public NCBI database was analyzed, including WGS data on isolates collected by the USDA Food Safety and Inspection Service (FSIS) from 2014 to 2018. ARC1, ARC4, and ARC5 were significantly associated with cattle isolates, while ARC6 was significantly associated with chicken isolates. This study revealed that a diverse group of plasmids, carrying AR genes, are responsible for the phenotypic resistance seen in Salmonella isolated from United States food animals. It was also determined that many plasmids carry similar ARCs.
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