Search

The COVID-19 pandemic presents a continued public health challenge. Veterinary diagnostic laboratories in the United States use RT-rtPCR for animal testing, and many laboratories are certified for testing human samples; hence, ensuring that laboratories have sensitive and specific SARS-CoV2 testing methods is a critical component of the pandemic response. In 2020, the FDA Veterinary Laboratory Investigation and Response Network (Vet-LIRN) led an interlaboratory comparison (ILC1) to help laboratories evaluate their existing RT-rtPCR methods for detecting SARS-CoV2. All participating laboratories were able to detect the viral RNA spiked in buffer and PrimeStore molecular transport medium (MTM). With ILC2, Vet-LIRN extended ILC1 by evaluating analytical sensitivity and specificity of the methods used by participating laboratories to detect 3 SARS-CoV2 variants (B.1; B.1.1.7 [Alpha]; B.1.351 [Beta]) at various copy levels. We analyzed 57 sets of results from 45 laboratories qualitatively and quantitatively according to the principles of ISO 16140-2:2016. More than 95% of analysts detected the SARS-CoV2 RNA in MTM at ≥500 copies for all 3 variants. In addition, for nucleocapsid markers N1 and N2, 81% and 92% of the analysts detected ≤20 copies in the assays, respectively. The analytical specificity of the evaluated methods was >99%. Participating laboratories were able to assess their current method performance, identify possible limitations, and recognize method strengths as part of a continuous learning environment to support the critical need for the reliable diagnosis of COVID-19 in potentially infected animals and humans.

BackgroundSince the beginning of the COVID-19 pandemic veterinary diagnostic laboratories have tested diagnostic samples for SARS-CoV-2 not only in animals, but in over five million human samples. An evaluation of the performance of those laboratories is needed using blinded test samples to ensure that laboratories report reliable data to the public. This interlaboratory comparison exercise (ILC3) builds on two prior exercises to assess whether veterinary diagnostic laboratories can detect Delta and Omicron variants spiked in canine nasal matrix or viral transport medium.MethodsInactivated Delta variant at levels of 25 to 1,000 copies per 50 μL of nasal matrix were prepared for participants by the ILC organizer, an independent laboratory, for blinded analysis. Omicron variant at 1,000 copies per 50 μL of transport medium was also included. Feline infectious peritonitis virus (FIPV) RNA was used as a confounder for specificity assessment. A total of 14 test samples were prepared for each participant. Participants used their routine diagnostic procedures for RNA extraction and real-time RT-PCR. Results were analyzed according to International Organization for Standardization (ISO) 16140 - 2:2016.ResultsThe overall results showed 93% detection for Delta and 97% for Omicron at 1,000 copies per 50 μL (22-200 copies per reaction). The overall specificity was 97% for blank samples and 100% for blank samples with FIPV. No differences in Ct values were significant for samples with the same virus levels between N1 and N2 markers, nor between the two variants.ConclusionsThe results indicated that all ILC3 participants were able to detect both Delta and Omicron variants. The canine nasal matrix did not significantly affect SARS-CoV-2 detection.Impact StatementEnsuring accurate detection methods for SARS-CoV-2 is critical as veterinary diagnostic labs are testing both human and animal samples. This exercise used blinded test samples and provided high confidence in the sensitivity of methods in twenty-nine laboratories for detection of SARS-CoV-2 variants while addressing the impact of sample matrix. Importantly, the results indicated that variants and matrix do not impact detection results. Additionally, this article examined decision-making criteria for Ct cut-off values from different laboratories and encouraged them to review and potentially reassess their criteria to improve future performance. This knowledge will lead to higher confidence in laboratory detection of current and new SARS-CoV-2 variants and aid in establishing reasonable cut-off parameters for these diagnostics tests.

Recently, there have been reports worldwide of a multidrug-resistant, emergent Salmonella Infantis (ESI) clone with a large megaplasmid (pESI), often containing the extended-spectrum beta-lactamase gene blaCTX-M-65. This clone also has a gyrA mutation conferring fluoroquinolone resistance, further limiting treatment options. In the United States, this clone has also been found in poultry sources, indicating a likely source of human illnesses. We conducted short-read sequencing of Salmonella enterica isolated from retail meats as part of routine surveillance by the National Antimicrobial Resistance Monitoring System (NARMS). We analyzed the resulting data temporally and geographically to determine when and where the ESI clone has spread in the United States. We found the ESI clone was first found in retail meats in Tennessee in 2014, but by 2019 was throughout the United States and comprised 29% of all Salmonella isolated from retail chickens, and 7% from retail turkey. Of these isolates, 85.0% were within 20 single nucleotide polymorphisms (SNPs) of those causing human illnesses. Long-read sequencing data indicated substantial recombination in the pESI plasmid resulting in the presence of 0-10 resistance genes, despite all their chromosomes being within 31 SNPs of one another. This work demonstrates the rapid spread of this clone of Salmonella Infantis in poultry in the United States, with the potential for increased burden of human illness attributed to this multidrug-resistant pathogen.

Wildlife play a role in the acquisition, maintenance, and dissemination of antimicrobial resistance (AMR). This is especially true at the human-domestic animal-wildlife interface, like urbanized areas, where interactions occur that can promote the cross-over of AMR bacteria and genes. We conducted a 2-year fecal surveillance (n = 783) of a white-tailed deer (WTD) herd from an urban park system in Ohio to identify and characterize cephalosporin-resistant and carbapenemase-producing bacteria using selective enrichment. Using generalized linear mixed models we found that older (OR = 2.3, P

The coronavirus disease 2019 (COVID-19) pandemic presents a continued public health challenge across the world. Veterinary diagnostic laboratories in the U.S. use real-time reverse transcriptase PCR (RT-PCR) for animal testing, and many are certified for testing human samples, so ensuring laboratories have sensitive and specific SARS-CoV-2 testing methods is a critical component of the pandemic response. In 2020, the FDA Veterinary Laboratory Investigation and Response Network (Vet-LIRN) led the first round of an Inter-Laboratory Comparison (ILC) Exercise to help laboratories evaluate their existing real-time RT-PCR methods for detecting SARS-CoV-2. The ILC1 results indicated that all participating laboratories were able to detect the viral RNA spiked in buffer and PrimeStore molecular transport medium (MTM). The current ILC (ILC2) aimed to extend ILC1 by evaluating analytical sensitivity and specificity of the methods used by participating laboratories to detect three SARS-CoV-2 variants (B.1, B.1.1.7 (Alpha) and B.1.351 (Beta)). ILC2 samples were prepared with RNA at levels between 10 to 10,000 copies per 50 μL MTM. Fifty-seven sets of results from 45 laboratories were qualitatively and quantitatively analyzed according to the principles of ISO 16140-2:2016. The results showed that over 95% of analysts detected the SARS-CoV-2 RNA in MTM at 500 copies or higher for all three variants. In addition, 81% and 92% of the analysts achieved a Level of Detection (LOD95eff. vol.) below 20 copies in the assays with nucleocapsid markers N1 and N2, respectively. The analytical specificity of the evaluated methods was over 99%. The study allowed participating laboratories to assess their current method performance, identify possible limitations, and recognize method strengths as part of a continuous learning environment to support the critical need for reliable diagnosis of COVID-19 in potentially infected animals and humans.

Background The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. Results As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. Conclusions Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI’s BioSample database.

This cross-sectional study determined the serovars, antimicrobial resistance genes, and virulence factors of

There is a growing need for public health and veterinary laboratories to perform whole genome sequencing (WGS) for monitoring antimicrobial resistance (AMR) and protecting the safety of people and animals. With the availability of smaller and more affordable sequencing platforms coupled with well-defined bioinformatic protocols, the technological capability to incorporate this technique for real-time surveillance and genomic epidemiology has greatly expanded. There is a need, however, to ensure that data are of high quality. The goal of this study was to assess the utility of a small benchtop sequencing platform using a multi-laboratory verification approach. Thirteen laboratories were provided the same equipment, reagents, protocols and bacterial reference strains. The Illumina DNA Prep and Nextera XT library preparation kits were compared, and 2×150 bp iSeq i100 chemistry was used for sequencing. Analyses comparing the sequences produced from this study with closed genomes from the provided strains were performed using open-source programs. A detailed, step-by-step protocol is publicly available via protocols.io (https://www.protocols.io/view/iseq-bacterial-wgs-protocol-bij8kcrw). The throughput for this method is approximately 4-6 bacterial isolates per sequencing run (20-26 Mb total load). The Illumina DNA Prep library preparation kit produced high-quality assemblies and nearly complete AMR gene annotations. The Prep method produced more consistent coverage compared to XT, and when coverage benchmarks were met, nearly all AMR, virulence and subtyping gene targets were correctly identified. Because it reduces the technical and financial barriers to generating WGS data, the iSeq platform is a viable option for small laboratories interested in genomic surveillance of microbial pathogens.

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.

We report isolation of a New Delhi metallo-β-lactamase-5–producing carbapenem-resistant Escherichia coli sequence type 167 from companion animals in the United States. Reports of carbapenem-resistant Enterobacteriaceae in companion animals are rare. We describe a unique cluster of blaNDM-5–producing E. coli in a veterinary hospital.

Salmonella enterica serovar Dublin is a host-adapted serotype associated with typhoidal disease in cattle. While rare in humans, it usually causes severe illness, including bacteremia. In the Unite...

Little is known about the prevalence of antimicrobial-resistant (AMR) bacteria in veal meat in the United States. We estimated the prevalence of bacterial contamination and AMR in various veal meats collected during the 2018 U.S. National Antimicrobial Resistance Monitoring System (NARMS) survey of retail outlets in nine states and compared the prevalence with the frequency of AMR bacteria from other cattle sources sampled for NARMS. In addition, we identified genes associated with resistance to medically important antimicrobials and gleaned other genetic details about the resistant organisms. The prevalence of Campylobacter, Salmonella, Escherichia coli, and Enterococcus in veal meats collected from grocery stores in nine states was 0% (0 of 358), 0.6% (2 of 358), 21.1% (49 of 232), and 53.5% (121 of 226), respectively, with ground veal posing the highest risk for contamination. Both Salmonella isolates were resistant to at least one antimicrobial agent as were 65.3% (32 of 49) of E. coli and 73.6% (89 of 121) of Enterococcus isolates. Individual drug and multiple drug resistance levels were significantly higher (P < 0.05) in E. coli and Enterococcus from retail veal than in dairy cattle ceca and retail ground beef samples from 2018 NARMS data. Whole genome sequencing was conducted on select E. coli and Salmonella from veal. Cephalosporin resistance (blaCMY and blaCTX-M), macrolide resistance (mph), and plasmid-mediated quinolone resistance (qnr) genes and gyrA mutations were found. We also identified heavy metal resistance genes ter, ars, mer, fieF, and gol and disinfectant resistance genes qac and emrE. An stx1a-containing E. coli was also found. Sequence types were highly varied among the nine E. coli isolates that were sequenced. Several plasmid types were identified in E. coli and Salmonella, with the majority (9 of 11) of isolates containing IncF. This study illustrates that veal meat is a carrier of AMR bacteria. HIGHLIGHTS

As part of the National Antimicrobial Resistance Monitoring System (NARMS) activities, the United States Department of Agriculture (USDA) Food Safety Inspection Service (FSIS) collected cecal samples from food animal slaughter facilities throughout the country between 2014 and 2018. Of the 26,780 cecal samples from cattle, swine, chicken and turkey , 6,350 (23.71%) tested positive for Salmonella . NARMS tested Salmonella for susceptibility to aminoglycosides, folate pathway inhibitors, macrolides, phenicols, quinolones, beta lactams, and tetracyclines. Using the regional subdivisions defined in the USDA Office of Investigation, we used chi-square test to assess potential association between the region from which the samples were collected and both Salmonella prevalence and susceptibility. The results show a significant association between region and Salmonella prevalence, when accounting for source and establishment size, with the southeast region having the highest probability of finding Salmonella . However, the western region had the highest resistance probability across all antimicrobial classes except for macrolides, which showed no regional association. This association between region and resistance was strongest among isolates from cattle. Analysis of whole-genome sequencing data indicated that a significantly higher prevalence of Salmonella Newport in cattle in the western region (accounting for 9.52% of cattle isolates, compared to 3.44% in other regions) may account for the greater resistance to multiple drug classes. Approximately 90% of Salmonella Newport in the west exhibited the MDR-AmpC phenotype encoded by aph(3'')-Ib/aph(6)-Id , bla CMY-2 , floR , sul2 , and tetA. . Thus, differences in resistance across regions may be due to geographical differences in the prevalence of specific Salmonella serotypes and their accompanying resistance genes.

Recently, there have been reports worldwide of a multidrug-resistant, emergent

The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatic tools and resources, and advocate for greater openness, interoperability, accessibility and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a clear and present need for a fit-for-purpose, open source SARS-CoV-2 contextual data standard. As such, we have developed an extension to the INSDC pathogen package, providing a SARS-CoV-2 contextual data specification based on harmonisable, publicly available, community standards. The specification is implementable via a collection template, as well as an array of protocols and tools to support the harmonisation and submission of sequence data and contextual information to public repositories. Well-structured, rich contextual data adds value, promotes reuse, and enables aggregation and integration of disparate data sets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19.

Salmonella is a leading cause of bacterial infections in animals and humans. We sequenced a collection of 450 Salmonella strains from diseased animals to better understand the genetic makeup of their virulence and resistance features. The presence of Salmonella pathogenicity islands (SPIs) varied by serotype. S. Enteritidis carried the most SPIs (n = 15), while S. Mbandaka, S. Cerro, S. Meleagridis, and S. Havana carried the least (n = 10). S. Typhimurium, S. Choleraesuis, S. I 4,5,12:i:-, and S. Enteritidis each contained the spv operon on IncFII or IncFII-IncFIB hybrid plasmids. Two S. IIIa carried a spv operon with spvD deletion on the chromosome. Twelve plasmid types including 24 hybrid plasmids were identified. IncA/C was frequently associated with S. Newport (83%) and S. Agona (100%) from bovine, whereas IncFII (100%), IncFIB (100%), and IncQ1 (94%) were seen in S. Choleraesuis from swine. IncX (100%) was detected in all S. Kentucky from chicken. A total of 60 antimicrobial resistance genes (ARGs), four disinfectant resistances genes (DRGs) and 33 heavy metal resistance genes (HMRGs) were identified. The Salmonella strains from sick animals contained various SPIs, resistance genes and plasmid types based on the serotype and source of the isolates. Such complicated genomic structures shed light on the strain characteristics contributing to the severity of disease and treatment failures in Salmonella infections, including those causing illnesses in animals.

Reports of transmissible colistin resistance show the importance of comprehensive colistin resistance surveillance. Recently, a new allele of the mobile colistin resistance (mcr) gene family designated mcr-9, which shows variation in genetic context and colistin susceptibility, was reported. We tested over 100 Salmonella enterica and Escherichia coli isolates with mcr-9 from the National Antimicrobial Resistance Monitoring System (NARMS) in the United States for their susceptibility to colistin and found that every isolate was susceptible, with an MIC of ≤1 μg/ml. Long-read sequencing of 12 isolates revealed mcr-9 on IncHI plasmids that were either independent or integrated into the chromosome. Overall, these results demonstrate that caution is necessary when determining the clinical relevance of new resistance genes.

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

We tested a diverse set of 500 isolates of nontyphoidal Salmonella enterica subsp. enterica from various animal, food, and human clinical sources for susceptibility to antimicrobials currently lacking epidemiological cutoff values (ECOFFs) set by the European Committee on Antimicrobial Susceptibility Testing. A consortium of five different laboratories each tested 100 isolates, using broth microdilution panels containing twofold dilutions of ceftriaxone, cefepime, and colistin to determine the minimum inhibitory concentrations of each drug when tested against the Salmonella isolates. Based on the resulting data, new ECOFFs of 0.25 μg/mL for ceftriaxone, 0.12 μg/mL for cefepime, and 2 μg/mL for colistin have been proposed. These thresholds will aid in the identification of Salmonella that have phenotypically detectable resistance mechanisms to these important antimicrobials.

Fluoroquinolones are used to treat serious bacterial infections, including those caused by Escherichia coli and Salmonella enterica. The emergence of plasmid-mediated quinolone resistance (PMQR) represent a new challenge to the successful treatment of Gram-negative infections. As part of a long-term strategy to generate a reference database of closed plasmids from antimicrobial resistant foodborne bacteria, we performed long-read sequencing of eleven E. coli isolates from retail meats that were non-susceptible to ciprofloxacin. Each of the isolates had PMQR genes, including qnrA1, qnrS1, and qnrB19. The four qnrB19 genes were carried on two distinct ColE-type plasmids among isolates from pork chop and ground turkey and were identical to plasmids previously identified in Salmonella. Seven other plasmids differed from any other sequences in GenBank and comprised IncF and IncR plasmids that ranged in size from 48-180 kb. These plasmids also contained different combinations of resistance genes, including those conferring resistance to beta-lactams, macrolides, sulfonamides, tetracycline, and heavy metals. Although relatively few isolates have PMQR genes, the identification of diverse plasmids in multiple retail meat sources suggests the potential for further spread of fluoroquinolone resistance, including through co-selection. These results highlight the value of long-read sequencing in characterizing antimicrobial resistance genes of public health concern.

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.

The recent advancements in rapid and affordable DNA sequencing technologies have revolutionized diagnostic microbiology and microbial surveillance. The availability of bioinformatics tools and online accessible databases has been a prerequisite for this. We conducted a scientific literature review and here we present a description of examples of available tools and databases for antimicrobial resistance (AMR) detection and provide future perspectives and recommendations. At least 47 freely accessible bioinformatics resources for detection of AMR determinants in DNA or amino acid sequence data have been developed to date. These include, among others but not limited to, ARG-ANNOT, CARD, SRST2, MEGARes, Genefinder, ARIBA, KmerResistance, AMRFinder, and ResFinder. Bioinformatics resources differ for several parameters including type of accepted input data, presence/absence of software for search within a database of AMR determinants that can be specific to a tool or cloned from other resources, and for the search approach employed, which can be based on mapping or on alignment. As a consequence, each tool has strengths and limitations in sensitivity and specificity of detection of AMR determinants and in application, which for some of the tools have been highlighted in benchmarking exercises and scientific articles. The identified tools are either available at public genome data centers, from GitHub or can be run locally. NCBI and European Nucleotide Archive (ENA) provide possibilities for online submission of both sequencing and accompanying phenotypic antimicrobial susceptibility data, allowing for other researchers to further analyze data, and develop and test new tools. The advancement in whole genome sequencing and the application of online tools for real-time detection of AMR determinants are essential to identify control and prevention strategies to combat the increasing threat of AMR. Accessible tools and DNA sequence data are expanding, which will allow establishing global pathogen surveillance and AMR tracking based on genomics. There is however, a need for standardization of pipelines and databases as well as phenotypic predictions based on the data.

The carbapenem resistance gene blaNDM-5 was identified in an Escherichia coli strain isolated from a dog. We report here the complete genome sequence of this E. coli strain; the blaNDM-5 gene was present on a large IncFII multidrug-resistant plasmid. This is the first blaNDM-5-carrying E. coli strain from an animal in the United States.

Antimicrobial resistance (AMR) is a major public health problem that requires publicly available tools for rapid analysis. To identify acquired AMR genes in whole genome sequences, the National Center for Biotechnology Information (NCBI) has produced a high-quality, curated, AMR gene reference database consisting of up-to-date protein and gene nomenclature, a set of hidden Markov models (HMMs), and a curated protein family hierarchy. Currently, the Bacterial Antimicrobial Resistance Reference Gene Database contains 4,579 antimicrobial resistance gene proteins and more than 560 HMMs.Here, we describe AMRFinder, a tool that uses this reference dataset to identify AMR genes. To assess the predictive ability of AMRFinder, we measured the consistency between predicted AMR genotypes from AMRFinder against resistance phenotypes of 6,242 isolates from the National Antimicrobial Resistance Monitoring System (NARMS). This included 5,425Salmonella enterica, 770Campylobacterspp., and 47Escherichia coliphenotypically 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 database. Most gene calls were identical, but there were 1,229 gene symbol differences between them, with differences due to both algorithmic differences and database composition. AMRFinder missed 16 loci that Resfinder found, while Resfinder missed 1,147 loci AMRFinder identified. Two missing drug classes from the 2017 version of ResFinder contributed 81% of missed loci. Based on these results, AMRFinder appears to be a highly accurate AMR gene detection system.ImportanceAntimicrobial resistance is a major public health problem. Traditionally, antimicrobial resistance has been identified using phenotypic assays. With the advent of genome sequencing, we now can identify resistance genes and deduce if an isolate could be resistant to antibiotics. We describe a database of 4,579 acquired antimicrobial resistance genes, the largest publicly available, and a software tool to identify genes in bacterial genomes, AMRFinder. Unlike other tools, AMRFinder uses a gene hierarchy to prevent overpredicting what the correct gene call should be, enabling more accurate assessment. To assess these resources, we determined the resistance gene content of over 6,200 bacterial isolates from the National Antimicrobial Resistance Monitoring System that have been assayed using traditional methods and that also have had their genomes sequenced. We also compared our gene assessments to those of a popularly used tool. We found that AMRFinder has a high overall consistency between genotypes and phenotypes.

Nontyphoidal Salmonella species are the leading bacterial cause of foodborne disease in the United States. Whole-genome sequences and paired antimicrobial susceptibility data are available for Salmonella strains because of surveillance efforts from public health agencies. In this study, a collection of 5,278 nontyphoidal Salmonella genomes, collected over 15 years in the United States, was used to generate extreme gradient boosting (XGBoost)-based machine learning models for predicting MICs for 15 antibiotics. The MIC prediction models had an overall average accuracy of 95% within ±1 2-fold dilution step (confidence interval, 95% to 95%), an average very major error rate of 2.7% (confidence interval, 2.4% to 3.0%), and an average major error rate of 0.1% (confidence interval, 0.1% to 0.2%). The model predicted MICs with no a priori information about the underlying gene content or resistance phenotypes of the strains. By selecting diverse genomes for the training sets, we show that highly accurate MIC prediction models can be generated with less than 500 genomes. We also show that our approach for predicting MICs is stable over time, despite annual fluctuations in antimicrobial resistance gene content in the sampled genomes. Finally, using feature selection, we explore the important genomic regions identified by the models for predicting MICs. To date, this is one of the largest MIC modeling studies to be published. Our strategy for developing whole-genome sequence-based models for surveillance and clinical diagnostics can be readily applied to other important human pathogens.

Background Antimicrobial resistance (AMR) of bacterial pathogens is an emerging public health threat. This threat extends to pets as it also compromises our ability to treat their infections. Surveillance programs in the United States have traditionally focused on collecting data from food animals, foods, and people. The Veterinary Laboratory Investigation and Response Network (Vet-LIRN), a national network of 45 veterinary diagnostic laboratories, tested the antimicrobial susceptibility of clinically relevant bacterial isolates from animals, with companion animal species represented for the first time in a monitoring program. During 2017, we systematically collected and tested 1968 isolates. To identify genetic determinants associated with AMR and the potential genetic relatedness of animal and human strains, whole genome sequencing (WGS) was performed on 192 isolates: 69 Salmonella enterica (all animal sources), 63 Escherichia coli (dogs), and 60 Staphylococcus pseudintermedius (dogs). Results We found that most Salmonella isolates (46/69, 67%) had no known resistance genes. Several isolates from both food and companion animals, however, showed genetic relatedness to isolates from humans. For pathogenic E. coli, no resistance genes were identified in 60% (38/63) of the isolates. Diverse resistance patterns were observed, and one of the isolates had predicted resistance to fluoroquinolones and cephalosporins, important antibiotics in human and veterinary medicine. For S. pseudintermedius, we observed a bimodal distribution of resistance genes, with some isolates having a diverse array of resistance mechanisms, including the mecA gene (19/60, 32%). Conclusion The findings from this study highlight the critical importance of veterinary diagnostic laboratory data as part of any national antimicrobial resistance surveillance program. The finding of some highly resistant bacteria from companion animals, and the observation of isolates related to those isolated from humans demonstrates the public health significance of incorporating companion animal data into surveillance systems. Vet-LIRN will continue to build the infrastructure to collect the data necessary to perform surveillance of resistant bacteria as part of fulfilling its mission to advance human and animal health. A One Health approach to AMR surveillance programs is crucial and must include data from humans, animals, and environmental sources to be effective. Electronic supplementary material The online version of this article (10.1186/s12917-019-1864-2) contains supplementary material, which is available to authorized users.

Laboratory-based in vitro antimicrobial susceptibility testing is the foundation for guiding anti-infective therapy and monitoring antimicrobial resistance trends. We used whole-genome sequencing (WGS) technology to identify known antimicrobial resistance determinants among strains of nontyphoidal Salmonella and correlated these with susceptibility phenotypes to evaluate the utility of WGS for antimicrobial resistance surveillance. Six hundred forty Salmonella of 43 different serotypes were selected from among retail meat and human clinical isolates that were tested for susceptibility to 14 antimicrobials using broth microdilution. The MIC for each drug was used to categorize isolates as susceptible or resistant based on Clinical and Laboratory Standards Institute clinical breakpoints or National Antimicrobial Resistance Monitoring System (NARMS) consensus interpretive criteria. Each isolate was subjected to whole-genome shotgun sequencing, and resistance genes were identified from assembled sequences. A total of 65 unique resistance genes, plus mutations in two structural resistance loci, were identified. There were more unique resistance genes ( n = 59) in the 104 human isolates than in the 536 retail meat isolates ( n = 36). Overall, resistance genotypes and phenotypes correlated in 99.0% of cases. Correlations approached 100% for most classes of antibiotics but were lower for aminoglycosides and beta-lactams. We report the first finding of extended-spectrum β-lactamases (ESBLs) ( bla CTX-M1 and bla SHV2a ) in retail meat isolates of Salmonella in the United States. Whole-genome sequencing is an effective tool for predicting antibiotic resistance in nontyphoidal Salmonella , although the use of more appropriate surveillance breakpoints and increased knowledge of new resistance alleles will further improve correlations.

National one health monitoring programs for antimicrobial-resistant enteric pathogens often include Escherichia coli as a sentinel for resistance to antimicrobials with Gram-negative activity. The purpose of this study was to investigate if antimicrobial resistance for E. coli can predict resistance in Salmonella when they occur together in the same surveillance sample of raw retail meat or food animal cecal contents collected by the National Antimicrobial Resistance Monitoring System (NARMS). One colony of each bacterium was isolated from each culture-positive sample and assayed for antimicrobial susceptibility by broth microdilution using the standard NARMS panel of 14 antimicrobial agents. A total of 1305 raw retail meats and 348 slaughter animal cecal samples contained both bacteria. Likelihood ratios were used to assess the extent to which antimicrobial resistance in E. coli coincides with resistance in Salmonella from the same sample. Results showed that for 8 out of 10, and 5 out of 10 antimicrobials tested in retail meat and cecal respectively, there was a statistically significant increase in the probability of finding Salmonella resistant to a particular antimicrobial when E. coli from the same sample was resistant to the same drug. Among those 8 and 5, likelihood ratios show that E. coli resistant predicted Salmonella resistance to ceftriaxone, ceftiofur, cefoxitin, and amoxicillin-clavulanic acid in retail meat, and to gentamicin, ceftriaxone and amoxicillin-clavulanic acid in cecal samples. Although E. coli is used as a sentinel for integrated antimicrobial resistance surveillance, these results suggest that E. coli may have limited value as the sole predictor of antimicrobial resistance in Salmonella except for beta lactams antimicrobials.

Objectives To sequence the genomes and determine the genetic mechanisms for linezolid resistance identified in three strains of Enterococcus isolated from cattle and swine caecal contents as part of the US National Antimicrobial Resistance Monitoring System (NARMS) surveillance programme. Methods Broth microdilution was used for in vitro antimicrobial susceptibility testing to assess linezolid resistance. Resistance mechanisms and plasmid types were identified from data generated by WGS on Illumina® and PacBio® platforms. Conjugation experiments were performed to determine whether identified mechanisms were transmissible. Results Linezolid resistance plasmids containing optrA were identified in two Enterococcus faecalis isolates and one Enterococcus faecium. The E. faecium isolate also carried the linezolid resistance gene cfr on the same plasmid as optrA. The linezolid resistance plasmids had various combinations of additional resistance genes conferring resistance to phenicols (fexA), aminoglycosides [spc and aph(3')-III] and macrolides [erm(A) and erm(B)]. One of the plasmids was confirmed to be transmissible by conjugation, resulting in linezolid resistance in the transconjugant. Conclusions To the best of our knowledge, this is the first identification of linezolid resistance in the USA in bacteria isolated from food animals. The oxazolidinone class of antibiotics is not used in food animals in the USA, but the genes responsible for resistance were identified on plasmids with other resistance markers, indicating that there may be co-selection for these plasmids due to the use of different antimicrobials. The transmissibility of one of the plasmids demonstrated the potential for linezolid resistance to spread horizontally. Additional surveillance is necessary to determine whether similar plasmids are present in human strains of Enterococcus.

NontyphoidalSalmonellaspecies are the leading bacterial cause of food-borne disease in the United States. Whole genome sequences and paired antimicrobial susceptibility data are available forSalmonellastrains because of surveillance efforts from public health agencies. In this study, a collection of 5,278 nontyphoidalSalmonellagenomes, collected over 15 years in the United States, were used to generate XGBoost-based machine learning models for predicting minimum inhibitory concentrations (MICs) for 15 antibiotics. The MIC prediction models have average accuracies between 95-96% within ± 1 two-fold dilution factor and can predict MICs with noa prioriinformation about the underlying gene content or resistance phenotypes of the strains. By selecting diverse genomes for training sets, we show that highly accurate MIC prediction models can be generated with fewer than 500 genomes. We also show that our approach for predicting MICs is stable over time despite annual fluctuations in antimicrobial resistance gene content in the sampled genomes. Finally, using feature selection, we explore the important genomic regions identified by the models for predicting MICs. To date, this is one of the largest MIC modeling studies to be published. Our strategy for developing whole genome sequence-based models for surveillance and clinical diagnostics can be readily applied to other important human pathogens.

Bacteria of the genus Enterococcus are important human pathogens that are frequently resistant to a number of clinically important antibiotics. They are also used as markers of animal fecal contamination of human foods and are employed as sentinel organisms for tracking trends in resistance to antimicrobials with Gram-positive activity. As part of the National Antimicrobial Resistance Monitoring System (NARMS), we evaluated several retail meat commodities for the presence of enterococci from 2002 to 2014, and we found 92.0% to be contaminated. The majority of isolates were either Enterococcus faecalis (64.0%) or Enterococcus faecium (28.6%), and the antimicrobial resistance of each isolate was assessed by broth microdilution. The resistance prevalences for several drugs, including erythromycin and gentamicin, were significantly higher among poultry isolates, compared to retail beef or pork isolates. None of the isolates was resistant to the clinically important human drug vancomycin, only 1 isolate was resistant to linezolid, and resistance to tigecycline was below 1%. In contrast, a majority of both E. faecalis (67.5%) and E. faecium (53.7%) isolates were resistant to tetracycline. Overall, the robust NARMS testing system employed consistent sampling practices and methods throughout the testing period, with the only significant trend in resistance prevalence being decreased E. faecium resistance to penicillin. These data provide excellent baseline levels of resistance that can be used to measure future changes in resistance prevalence that may result from alterations in the use of antimicrobials in food animal production. IMPORTANCE Enterococci, including E. faecalis and E. faecium , are present in the guts of food-producing animals and are used as a measure of fecal contamination of meat. We used the large consistent sampling methods of NARMS to assess the prevalence of Enterococcus strains isolated from retail meats, and we found over 90% of meats to be contaminated with enterococci. We also assessed the resistance of the Enterococcus strains, commonly used as a measure of resistance to agents with Gram-positive activity, in foods. Resistance prevalence was over 25% for some antimicrobials and sample sources but was less than 1% for several of the most important therapeutic agents used in human medicine.

Whole-genome sequencing (WGS) has transformed our understanding of antimicrobial resistance, yielding new insights into the genetics underlying resistance. To date, most studies using WGS to study antimicrobial resistance have focused on gram-negative bacteria in the family Enterobacteriaceae, such as Salmonella spp. and Escherichia coli, which have well-defined resistance mechanisms. In contrast, relatively few studies have been performed on gram-positive organisms. We sequenced 197 strains of Enterococcus from various animal and food sources, including 100 Enterococcus faecium and 97 E. faecalis. From analyzing acquired resistance genes and known resistance-associated mutations, we found that resistance genotypes correlated with resistance phenotypes in 96.5% of cases for the 11 drugs investigated. Some resistances, such as those to tigecycline and daptomycin, could not be investigated due to a lack of knowledge of mechanisms underlying these phenotypes. This study showed the utility of WGS for predicting antimicrobial resistance based on genotype alone.

Bacterial toxins require localization to specific intracellular compartments following injection into host cells. In this study, we examined the membrane targeting of a broad family of bacterial proteins, the patatin-like phospholipases. The best characterized member of this family is ExoU, an effector of the Pseudomonas aeruginosa type III secretion system. Upon injection into host cells, ExoU localizes to the plasma membrane, where it uses its phospholipase A2 activity to lyse infected cells. The targeting mechanism of ExoU is poorly characterized, but it was recently found to bind to the phospholipid phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2), a marker for the plasma membrane of eukaryotic cells. We confirmed that the membrane localization domain (MLD) of ExoU had a direct affinity for PI(4,5)P2, and we determined that this binding was required for ExoU localization. Previously uncharacterized ExoU homologs from Pseudomonas fluorescens and Photorhabdus asymbiotica also localized to the plasma membrane and required PI(4,5)P2 for this localization. A conserved arginine within the MLD was critical for interaction of each protein with PI(4,5)P2 and for localization. Furthermore, we determined the crystal structure of the full-length P. fluorescens ExoU and found that it was similar to that of P. aeruginosa ExoU. Each MLD contains a four-helical bundle, with the conserved arginine exposed at its cap to allow for interaction with the negatively charged PI(4,5)P2. Overall, these findings provide a structural explanation for the targeting of patatin-like phospholipases to the plasma membrane and define the MLD of ExoU as a member of a new class of PI(4,5)P2 binding domains.

Fluoroquinolones are important antimicrobial drugs used to treat human Salmonella infections, and resistance is rare in the United States for isolates from human and animal sources. Recently, a number of Salmonella isolates from swine cecal contents and retail pork products from National Antimicrobial Resistance Monitoring System (NARMS) surveillance exhibited decreased susceptibility to ciprofloxacin. We identified two qnrB19 quinolone resistance plasmids that are predominantly responsible for this phenomenon and found them distributed among several Salmonella serotypes isolated throughout the United States.

We sequenced the genomes of 10 Salmonella enterica serovar Infantis isolates containing bla CTX-M-65 obtained from chicken, cattle, and human sources collected between 2012 and 2015 in the United States through routine National Antimicrobial Resistance Monitoring System (NARMS) surveillance and product sampling programs. We also completely assembled the plasmids from four of the isolates. All isolates had a D87Y mutation in the gyrA gene and harbored between 7 and 10 resistance genes [ aph(4)-Ia , aac(3)-IVa , aph(3 ′ )-Ic , bla CTX-M-65 , fosA3 , floR , dfrA14 , sul1 , tetA , aadA1 ] located in two distinct sites of a megaplasmid (∼316 to 323 kb) similar to that described in a bla CTX-M-65 -positive S . Infantis isolate from a patient in Italy. High-quality single nucleotide polymorphism (hqSNP) analysis revealed that all U.S. isolates were closely related, separated by only 1 to 38 pairwise high-quality SNPs, indicating a high likelihood that strains from humans, chickens, and cattle recently evolved from a common ancestor. The U.S. isolates were genetically similar to the bla CTX-M-65 -positive S . Infantis isolate from Italy, with a separation of 34 to 47 SNPs. This is the first report of the bla CTX-M-65 gene and the pESI (plasmid for emerging S . Infantis)-like megaplasmid from S . Infantis in the United States, and it illustrates the importance of applying a global One Health human and animal perspective to combat antimicrobial resistance.

Whole-genome sequencing (WGS) has transformed our understanding of antimicrobial resistance, helping us to better identify and track the genetic mechanisms underlying phenotypic resistance. Previous studies have demonstrated high correlations between phenotypic resistance and the presence of known resistance determinants. However, there has never been a large-scale assessment of how well resistance genotypes correspond to specific MICs. We performed antimicrobial susceptibility testing and WGS of 1,738 nontyphoidal Salmonella strains to correlate over 20,000 MICs with resistance determinants. Using these data, we established what we term genotypic cutoff values (GCVs) for 13 antimicrobials against Salmonella . For the drugs we tested, we define a GCV as the highest MIC of isolates in a population devoid of known acquired resistance mechanisms. This definition of GCV is distinct from epidemiological cutoff values (ECVs or ECOFFs), which currently differentiate wild-type from non-wild-type strains based on MIC distributions alone without regard to genetic information. Due to the large number of isolates involved, we observed distinct MIC distributions for isolates with different resistance gene alleles, including for ciprofloxacin and tetracycline, suggesting the potential to predict MICs based on WGS data alone.

Campylobacter spp. commonly cause gastrointestinal illness in humans. Poultry meats have long been considered the predominant source of these infections, but few in-depth Campylobacter source attribution studies have been completed. We analyzed more than 1,300 Campylobacter isolates recovered from a number of animal and food sources, including dairy and beef cattle, pigs, poultry, and retail poultry meat, and compared them with Campylobacter isolates recovered from human clinical samples. Each isolate was subtyped using pulsed-field gel electrophoresis (PFGE) with SmaI and queried against the Centers for Disease Control and Prevention PulseNet database to identify human isolates with indistinguishable patterns. Half (49.5%) of the PFGE patterns from poultry animal and retail meat isolates were indistinguishable from patterns of at least one human isolate. Among the isolates from beef and dairy cows, 56.6 and 65.0%, respectively, of their PFGE patterns were indistinguishable from those of human isolates. Only a small portion of the PFGE patterns of Campylobacter isolated from pigs (9.5%) were found to have PFGE patterns in common with human isolates. These data imply that cattle may be larger contributors to Campylobacter infections than previously recognized and help further our understanding of potential sources of human campylobacteriosis.