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 5,425 Salmonella enterica, 770 Campylobacter spp., and 47 Escherichia coli 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 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.Importance Antimicrobial 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.

Extraintestinal pathogenic Escherichia coli (ExPEC) cause urinary tract and potentially life-threatening invasive infections. Unfortunately, the origins of ExPEC are not always clear. We used genomic data of E. coli isolates from five U.S. government organizations to evaluate potential sources of ExPEC infections. Virulence gene analysis of 38,032 isolates from human, food animal, retail meat, and companion animals classified the subset of 8142 non-diarrheagenic isolates into 40 virulence groups. Groups were identified as low, medium, and high relative risk of containing ExPEC strains, based on the proportion of isolates recovered from humans. Medium and high relative risk groups showed a greater representation of sequence types associated with human disease, including ST-131. Over 90% of food source isolates belonged to low relative risk groups, while >60% of companion animal isolates belonged to medium or high relative risk groups. Additionally, 18 of the 26 most prevalent antimicrobial resistance determinants were more common in high relative risk groups. The associations between antimicrobial resistance and virulence potentially limit treatment options for human ExPEC infections. This study demonstrates the power of large-scale genomics to assess potential sources of ExPEC strains and highlights the importance of a One Health approach to identify and manage these human pathogens.

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.

OBJECTIVE: The 2019 novel coronavirus disease (COVID-19) outbreak progressed rapidly from a public health (PH) emergency of international concern (World Health Organization [WHO], 30 January 2020) to a pandemic (WHO, 11 March 2020). The declaration of a national emergency in the United States (13 March 2020) necessitated the addition and modification of terminology related to COVID-19 and development of the disease's case definition. During this period, the Centers for Disease Control and Prevention (CDC) and standard development organizations released guidance on data standards for reporting COVID-19 clinical encounters, laboratory results, cause-of-death certifications, and other surveillance processes for COVID-19 PH emergency operations. The CDC COVID-19 Information Management Repository was created to address the need for PH and health-care stakeholders at local and national levels to easily obtain access to comprehensive and up-to-date information management resources. MATERIALS AND METHODS: We introduce the clinical and health-care informatics community to the CDC COVID-19 Information Management Repository: a new, national COVID-19 information management tool. We provide a description of COVID-19 informatics resources, including data requirements for COVID-19 data reporting. RESULTS: We demonstrate the CDC COVID-19 Information Management Repository's categorization and management of critical COVID-19 informatics documentation and standards. We also describe COVID-19 data exchange standards, forms, and specifications. CONCLUSIONS: This information will be valuable to clinical and PH informaticians, epidemiologists, data analysts, standards developers and implementers, and information technology managers involved in the development of COVID-19 situational awareness and response reporting and analytics.

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 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 AMRFinder identified. Based on these results, AMRFinder appears to be a highly accurate AMR gene detection system.

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 microg/mL for ceftriaxone, 0.12 microg/mL for cefepime, and 2 microg/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.

We sequenced the genomes of ten Salmonella enterica serovar Infantis containing blaCTX-M-65 isolated from chicken, cattle, and human sources collected between 2012 and 2015 in the United States through routine 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, blaCTX-M-65, fosA3, floR, dfrA14, sul1, tetA, aadA1) located in two distinct sites of a megaplasmid ( approximately 316-323kb) similar to that described in a blaCTX-M-65-positive S. Infantis isolated 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, chicken, and cattle recently evolved from a common ancestor. The U.S. isolates were genetically similar to the blaCTX-M-65-positive S. Infantis isolate from Italy, with a separation of 34 to 47 SNPs. This is the first report of the blaCTX-M-65 gene and the pESI-like megaplasmid from S. Infantis in the United States, and illustrates the importance of applying a global One Health, human and animal perspective to combat antimicrobial resistance.

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 minimum inhibitory concentration (MIC) for each drug was used to categorize isolates as susceptible or resistant based on Clinical and Laboratory Standards Institute clinical breakpoints or 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 ESBLs (blaCTX-M1 and blaSHV2a) in retail meat isolates of Salmonella in the U.S. 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.

OBJECTIVES: The objectives of this study were to identify antimicrobial resistance genotypes for Campylobacter and to evaluate the correlation between resistance phenotypes and genotypes using in vitro antimicrobial susceptibility testing and whole-genome sequencing (WGS). METHODS: One hundred-fourteen Campylobacter sp. (82 C. coli and 32 C. jejuni) isolated from 2000-2013 from ill humans, retails meats and cecal samples from food production animals in the United States as part of the National Antimicrobial Resistance Monitoring System were selected for study. Resistance phenotypes were determined using broth micro-dilution of nine antimicrobials. Genomic DNA was sequenced using the Illumina MiSeq platform, and resistance genotypes were identified using assembled WGS sequences through BLASTx analysis. RESULTS: Eighteen resistance genes, including tetO, blaOXA-61, catA, lnuC, aph(2' ')-Ib, aph(2' ')-Ic, aph(2')-If, aph(2' ')-Ig, aph(2' ')-Ih, aac(6')-Ie/aph(2' ')-Ia, aac(6')-Ie/aph(2' ')-If, aac(6')-Im, aadE, sat4, ant(6'), aad9, aph(3')-Ic, aph(3')-IIIa, and mutations in two house-keeping genes (gyrA and 23S rRNA) were identified. There was a high degree of correlation between phenotypic resistance to a given drug and the presence of one or more corresponding resistance genes. Phenotypic and genotypic correlation was 100% for tetracycline, ciprofloxacin/nalidixic acid, and erythromycin and ranged from 95.4% to 98.7% for gentamicin, azithromycin, clindamycin, and telithromycin. All isolates were susceptible to florfenicol, and no genes associated with florfenicol resistance were detected. CONCLUSIONS: There was a strong correlation (99.2%) between resistance genotypes and phenotypes, suggesting that WGS is a reliable indicator of resistance to the nine antimicrobial agents assayed in this study. WGS has the potential to be a powerful tool for antimicrobial resistance surveillance programs.

Unsafe practices are an underestimated contributor to the disease burden of bloodborne viruses. Outbreaks associated with failures in basic infection prevention have been identified in nonhospital settings with increased frequency in the United States during the past 15 years, representing an alarming trend and indicating that the challenge of providing consistently safe care is not always met. As has been the case with most medical specialties, there have been public health investigations by state and local health departments, and the Centers for Disease Control and Prevention have identified some instances of unsafe practices that have placed podiatric medical patients at risk for viral, bacterial, and fungal infections. All health-care providers, including podiatric physicians, must make infection prevention a priority in any setting in which care is delivered.

Fungal endophthalmitis is a rare but serious infection. In March 2012, several cases of probable and laboratory-confirmed fungal endophthalmitis occurring after invasive ocular procedures were reported nationwide. We identified 47 cases in 9 states: 21 patients had been exposed to the intraocular dye Brilliant Blue G (BBG) during retinal surgery, and the other 26 had received an intravitreal injection containing triamcinolone acetonide. Both drugs were produced by Franck's Compounding Lab (Ocala, FL, USA). Fusarium incarnatum-equiseti species complex mold was identified in specimens from BBG-exposed case-patients and an unopened BBG vial. Bipolaris hawaiiensis mold was identified in specimens from triamcinolone-exposed case-patients. Exposure to either product was the only factor associated with case status. Of 40 case-patients for whom data were available, 39 (98%) lost vision. These concurrent outbreaks, associated with 1 compounding pharmacy, resulted in a product recall. Ensuring safety and integrity of compounded medications is critical for preventing further outbreaks associated with compounded products.

Permanent ductal closure involves anatomic remodeling, in which transforming growth factor (TGF)-beta appears to play a role. Our objective was to evaluate the relationship, if any, between blood spot TGF-beta on day 3 and day 7 of life and patent ductus arteriosus (PDA) in extremely low birth weight (ELBW) infants. Prospective observational study involving ELBW infants (n = 968) in the National Institute of Child Health and Human Development Neonatal Research Network who had TGF-beta measured on filter paper spot blood samples using a Luminex assay. Infants with a PDA (n = 493) were significantly more immature, had lower birth weights, and had higher rates of respiratory distress syndrome than those without PDA (n = 475). TGF-beta on days 3 and 7 of life, respectively, were significantly lower among neonates with PDA (median 1,177 pg/ml [range 642-1,896]; median 1,386 pg/ml [range 868-1,913]) compared with others without PDA (median 1,334 pg/ml [range 760-2,064]; median 1,712 pg/ml [range 1,014-2,518 pg/ml]). The significant difference persisted when death or PDA was considered a composite outcome. TGF-beta levels were not significantly different among subgroups of infants with PDA who were not treated (n = 51) versus those who were treated medically (n = 283) or by surgical ligation (n = 159). TGF-beta was not a significant predictor of death or PDA (day 3 odds ratio [OR] 0.99, 95 % confidence interval [CI] 0.83-1.17; day 7 OR 0.88, 95 % CI 0.74-1.04) on adjusted analyses. Our results suggest that blood spot TGF-beta alone is unlikely to be a reliable biomarker of a clinically significant PDA or its responsiveness to treatment.

OBJECTIVE: To determine if selected pro-inflammatory and anti-inflammatory cytokines and/or mediators of inflammation reported to be related to the development of cerebral palsy (CP) predict neurodevelopmental outcome in extremely low birth weight infants. STUDY DESIGN: Infants with birth weights ≤1000 g (n = 1067) had blood samples collected at birth and on days 3 +/- 1, 7 +/- 1, 14 +/- 3, and 21 +/- 3 to examine the association between cytokines and neurodevelopmental outcomes. The analyses were focused on 5 cytokines (interleukin [IL] 1beta; IL-8; tumor necrosis factor-alpha; regulated upon activation, normal T-cell expressed, and secreted (RANTES); and IL-2) reported to be most predictive of CP in term and late preterm infants. RESULTS: IL-8 was higher on days 0-4 and subsequently in infants who developed CP compared with infants who did not develop CP in both unadjusted and adjusted analyses. Other cytokines (IL-12, IL-17, tumor necrosis factor-beta, soluble IL R alpha, macrophage inflammatory protein 1beta) were found to be altered on days 0-4 in infants who developed CP. CONCLUSIONS: CP in former preterm infants may, in part, have a late perinatal and/or early neonatal inflammatory origin.