A Multicenter Clinical Study To Demonstrate the Diagnostic Accuracy of the GenMark Dx ePlex Blood Culture Identification Gram-Negative Panel.

Bacteremia can progress to septic shock and death without appropriate medical intervention. Increasing evidence supports the role of molecular diagnostic panels in reducing the clinical impact of these infections through rapid identification of the infecting organism and associated antimicrobial resistance genes. We report the results of a multicenter clinical study assessing the performance of the GenMark Dx ePlex investigational-use-only blood culture identification Gram-negative panel (BCID-GN), a rapid diagnostic assay for detection of bloodstream pathogens in positive blood culture (PBC) bottles. Prospective, retrospective, and contrived samples were tested. Results from the BCID-GN were compared to standard-of-care bacterial identification methods. Antimicrobial resistance genes (ARGs) were identified using PCR and sequence analysis. The final BCID-GN analysis included 2,444 PBC samples, of which 926 were clinical samples with negative Gram stain results. Of these, 109 samples had false-negative and/or -positive results, resulting in an overall sample accuracy of 88.2% (817/926). After discordant resolution, overall sample accuracy increased to 92.9% (860/926). Pre- and postdiscordant resolution sample accuracy excludes 37 Gram-negative organisms representing 20 uncommon genera, 10 Gram-positive organisms, and 1 Candida species present in 5% of samples that are not targeted by the BCID-GN. The overall weighted positive percent agreement (PPA), which averages the individual PPAs from the 27 targets (Gram-negative and ARG), was 94.9%. The limit of detection ranged from 104 to 107 CFU/ml, except for one strain of Fusobacterium necrophorum at 108 CFU/ml.

Evaluating the Effect of a Modified Sample Preparation on SARS-CoV-2 Detection in a Cartridge-Based Platform.

INTRODUCTION: The ePlex® SARS-CoV-2 emergency use authorization (EUA) test is a cartridge-based assay for the detection of SARS-CoV-2 in nasopharyngeal specimens. Since performance data has been previously published on this platform, the manufacturer has modified the workflow design in order to improve assay performance. Evaluation of the new workflow, which eliminated the sample delivery device (SDD), led to a dramatic improvement of assay performance while saving time and making cartridge loading more convenient. METHODS: 145 confirmed positive nasopharyngeal swab specimens were used to evaluate the assay analytical sensitivity, accuracy, and overall time-saving for the 2 workflows that is with and without the use of SDD on the ePlex SARS-CoV-2 test. RESULTS: Elimination of the SDD step led to a dramatic increase in accuracy and the overall limit of detection when using 145 previously defined and valid SARS-CoV-2 positive specimens with relatively low, medium, and high cycle thresholds (CT). This simple workflow change led to an overall detection from 94/145 (64.8%) to 131/145 (90.3%), with an additional 37 specimens being detected. CT value ranges revealed that 90% of the specimens in the 33 ≤ CT < 35.3 CT range were detected, whereas with the SDD workflow, only 30% of positive specimens were detected in this same range. Hands-on time for each specimen also improved and showed overall time savings. CONCLUSION: The simple workflow modification eliminating the SDD led to an overall improvement in the detection of positive specimens and also simplified workflow and reduced hands-on time.

Prevalence of blaCTX-M Genes in Gram-Negative Bloodstream Isolates across 66 Hospitals in the United States.

Understanding bacterial species at greatest risk for harboring blaCTX-M genes is necessary to guide antibiotic treatment. We identified the species-specific prevalence of blaCTX-M genes in Gram-negative clinical isolates from the United States. Twenty-four microbiology laboratories representing 66 hospitals using the GenMark Dx ePlex blood culture identification Gram-negative (BCID-GN) panel extracted blood culture results from April 2019 to July 2020. The BCID-GN panel includes 21 Gram-negative targets. Along with identifying blaCTX-M genes, it detects major carbapenemase gene families. A total of 4,209 Gram-negative blood cultures were included. blaCTX-M genes were identified in 462 (11%) specimens. The species-specific prevalence of blaCTX-M genes was as follows: Escherichia coli (16%), Klebsiella pneumoniae (14%), Klebsiella oxytoca (6%), Salmonella spp. (6%), Acinetobacter baumannii (5%), Enterobacter species (3%), Proteus mirabilis (2%), Serratia marcescens (0.6%), and Pseudomonas aeruginosa (0.5%). blaCTX-M prevalence was 26%, 24%, and 22% among participating hospitals in the District of Columbia, New York, and Florida, respectively. Carbapenemase genes were identified in 61 (2%) organisms with the following distribution: blaKPC (59%), blaVIM (16%), blaOXA (10%), blaNDM (8%), and blaIMP (7%). The species-specific prevalence of carbapenemase genes was as follows: A. baumannii (5%), K. pneumoniae (3%), P. mirabilis (3%), Enterobacter species (3%), Citrobacter spp. (3%), P. aeruginosa (2%), E. coli (<1%), K. oxytoca (<1%), and S. marcescens (<1%). Approximately 11% of Gram-negative organisms in our US cohort contain blaCTX-M genes. blaCTX-M genes remain uncommon in organisms beyond E. coli, K. pneumoniae, and K. oxytoca Future molecular diagnostic panels would benefit from the inclusion of plasmid-mediated ampC and SHV and TEM extended-spectrum beta-lactamase (ESBL) targets.

Multicenter Evaluation of a PCR-Based Digital Microfluidics and Electrochemical Detection System for the Rapid Identification of 15 Fungal Pathogens Directly from Positive Blood Cultures.

Routine identification of fungal pathogens from positive blood cultures by culture-based methods can be time-consuming, delaying treatment with appropriate antifungal agents. The GenMark Dx ePlex investigational use only blood culture identification fungal pathogen panel (BCID-FP) rapidly detects 15 fungal targets simultaneously in blood culture samples positive for fungi by Gram staining. We aimed to determine the performance of the BCID-FP in a multicenter clinical study. Blood culture samples collected at 10 United States sites and tested with BCID-FP at 4 sites were compared to the standard-of-care microbiological and biochemical techniques, fluorescence in situ hybridization using peptide nucleic acid probes (PNA-FISH) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Discrepant results were analyzed by bi-directional PCR/sequencing of residual blood culture samples. A total of 866 clinical samples, 120 retrospectively and 21 prospectively collected, along with 725 contrived samples were evaluated. Sensitivity and specificity of detection of Candida species (C. albicans, C. auris, C. dubliniensis, C. famata, C. glabrata, C. guilliermondii, C. kefyr, C. krusei, C. lusitaniae, C. parapsilosis, and C. tropicalis) ranged from 97.1 to 100% and 99.8 to 100%, respectively. For the other organism targets, sensitivity and specificity were as follows: 100% each for Cryptococcus neoformans and C. gattii, 98.6% and 100% for Fusarium spp., and 96.2% and 99.9% for Rhodotorula spp., respectively. In 4 of the 141 clinical samples, the BCID-FP panel correctly identified an additional Candida species, undetected by standard-of-care methods. The BCID-FP panel offers a faster turnaround time for identification of fungal pathogens in positive blood cultures that may allow for earlier antifungal interventions and includes C. auris, a highly multidrug-resistant fungus.

Clinical Performance of the Novel GenMark Dx ePlex Blood Culture ID Gram-Positive Panel.

Rapid identification from positive blood cultures is standard of care (SOC) in many clinical microbiology laboratories. The GenMark Dx ePlex Blood Culture Identification Gram-Positive (BCID-GP) Panel is a multiplex nucleic acid amplification assay based on competitive DNA hybridization and electrochemical detection using eSensor technology. This multicenter study compared the investigational-use-only (IUO) BCID-GP Panel to other methods of identification of 20 Gram-positive bacteria, four antimicrobial resistance genes, and both Pan Candida and Pan Gram-Negative targets that are unique to the BCID-GP Panel. Ten microbiology laboratories throughout the United States collected residual, deidentified positive blood culture samples for analysis. Five laboratories tested both clinical and contrived samples with the BCID-GP Panel. Comparator identification methods included each laboratory's SOC, which included matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and automated identification systems as well as targeted PCR/analytically validated real-time PCR (qPCR) with bidirectional sequencing. A total of 2,342 evaluable samples (1,777 clinical and 565 contrived) were tested with the BCID-GP Panel. The overall sample accuracy for on-panel organisms was 89% before resolution of discordant results. For pathogenic Gram-positive targets (Bacillus cereus group, Enterococcus spp., Enterococcus faecalis, Enterococcus faecium, Staphylococcus spp., Staphylococcus aureus, Staphylococcus epidermidis, Staphylococcus lugdunensis, Listeria spp., Listeria monocytogenes, Streptococcus spp., Streptococcus agalactiae, Streptococcus anginosus group, Streptococcus pneumoniae, and Streptococcus pyogenes), positive percent agreement (PPA) and negative percent agreement (NPA) ranged from 93.1% to 100% and 98.8% to 100%, respectively. For contamination rule-out targets (Bacillus subtilis group, Corynebacterium, Cutibacterium acnes, Lactobacillus, and Micrococcus), PPA and NPA ranged from 84.5% to 100% and 99.9% to 100%, respectively. Positive percent agreement and NPA for the Pan Candida and Pan Gram-Negative targets were 92.4% and 95.7% for the former and 99.9% and 99.6% for the latter. The PPAs for resistance markers were as follows: mecA, 97.2%; mecC, 100%; vanA, 96.8%; and vanB, 100%. Negative percent agreement ranged from 96.6% to 100%. In conclusion, the ePlex BCID-GP Panel compares favorably to SOC and targeted molecular methods for the identification of 20 Gram-positive pathogens and four antimicrobial resistance genes in positive blood culture bottles. This panel detects a broad range of pathogens and mixed infections with yeast and Gram-negative organisms from the same positive blood culture bottle.

Clinical Utility of Advanced Microbiology Testing Tools.

Advanced microbiology technologies are rapidly changing our ability to diagnose infections, improve patient care, and enhance clinical workflow. These tools are increasing the breadth, depth, and speed of diagnostic data generated per patient, and testing is being moved closer to the patient through rapid diagnostic technologies, including point-of-care (POC) technologies. While select stakeholders have an appreciation of the value/importance of improvements in the microbial diagnostic field, there remains a disconnect between clinicians and some payers and hospital administrators in terms of understanding the potential clinical utility of these novel technologies. Therefore, a key challenge for the clinical microbiology community is to clearly articulate the value proposition of these technologies to encourage payers to cover and hospitals to adopt advanced microbiology tests. Specific guidance on how to define and demonstrate clinical utility would be valuable. Addressing this challenge will require alignment on this topic, not just by microbiologists but also by primary care and emergency room (ER) physicians, infectious disease specialists, pharmacists, hospital administrators, and government entities with an interest in public health. In this article, we discuss how to best conduct clinical studies to demonstrate and communicate clinical utility to payers and to set reasonable expectations for what diagnostic manufacturers should be required to demonstrate to support reimbursement from commercial payers and utilization by hospital systems.

Predicting Antibiotic Resistance in Gram-Negative Bacilli from Resistance Genes.

We developed a rapid high-throughput PCR test and evaluated highly antibiotic-resistant clinical isolates of Escherichia coli (n = 2,919), Klebsiella pneumoniae (n = 1,974), Proteus mirabilis (n = 1,150), and Pseudomonas aeruginosa (n = 1,484) for several antibiotic resistance genes for comparison with phenotypic resistance across penicillins, cephalosporins, carbapenems, aminoglycosides, trimethoprim-sulfamethoxazole, fluoroquinolones, and macrolides. The isolates originated from hospitals in North America (34%), Europe (23%), Asia (13%), South America (12%), Africa (7%), or Oceania (1%) or were of unknown origin (9%). We developed statistical methods to predict phenotypic resistance from resistance genes for 49 antibiotic-organism combinations, including gentamicin, tobramycin, ciprofloxacin, levofloxacin, trimethoprim-sulfamethoxazole, ertapenem, imipenem, cefazolin, cefepime, cefotaxime, ceftazidime, ceftriaxone, ampicillin, and aztreonam. Average positive predictive values for genotypic prediction of phenotypic resistance were 91% for E. coli, 93% for K. pneumoniae, 87% for P. mirabilis, and 92% for P. aeruginosa across the various antibiotics for this highly resistant cohort of bacterial isolates.

Surveillance for severe acute respiratory infections in Southern Arizona, 2010-2014.

BACKGROUND: The Binational Border Infectious Disease Surveillance program began surveillance for severe acute respiratory infections (SARI) on the US-Mexico border in 2009. Here, we describe patients in Southern Arizona. METHODS: Patients admitted to five acute care hospitals that met the SARI case definition (temperature ≥37·8°C or reported fever or chills with history of cough, sore throat, or shortness of breath in a hospitalized person) were enrolled. Staff completed a standard form and collected a nasopharyngeal swab which was tested for selected respiratory viruses by reverse transcription polymerase chain reaction. RESULTS: From October 2010-September 2014, we enrolled 332 SARI patients. Fifty-two percent were male and 48% were white non-Hispanic. The median age was 63 years (47% ≥65 years and 5·2% <5 years). During hospitalization, 51 of 230 (22%) patients required intubation, 120 of 297 (40%) were admitted to intensive care unit, and 28 of 278 (10%) died. Influenza vaccination was 56%. Of 309 cases tested, 49 (16%) were positive for influenza viruses, 25 (8·1%) for human metapneumovirus, 20 (6·5%) for parainfluenza viruses, 16 (5·2%) for coronavirus, 11 (3·6%) for respiratory syncytial virus, 10 (3·2%) for rhinovirus, 4 (1·3%) for rhinovirus/enterovirus, 3 (1·0%) for enteroviruses, and 3 (1·0%) for adenovirus. Among the 49 influenza-positive specimens, 76% were influenza A (19 H3N2, 17 H1N1pdm09, and 1 not subtyped), and 24% were influenza B. CONCLUSION: Influenza viruses were a frequent cause of SARI in hospitalized patients in Southern Arizona. Monitoring respiratory illness in border populations will help better understand the etiologies. Improving influenza vaccination coverage may help prevent some SARI cases.

Mouse macrophages are permissive to motile Legionella species that fail to trigger pyroptosis.

Legionella pneumophila, a motile opportunistic pathogen of humans, is restricted from replicating in the lungs of C57BL/6 mice. Resistance of mouse macrophages to L. pneumophila depends on recognition of cytosolic flagellin. Once detected by the NOD-like receptors Naip5 and Ipaf (Nlrc4), flagellin triggers pyroptosis, a proinflammatory cell death. In contrast, motile strains of L. parisiensis and L. tucsonensis replicate profusely within C57BL/6 macrophages, similar to flagellin-deficient L. pneumophila. To gain insight into how motile species escape innate defense mechanisms of mice, we compared their impacts on macrophages. L. parisiensis and L. tucsonensis do not induce proinflammatory cell death, as measured by lactate dehydrogenase (LDH) release and interleukin-1beta (IL-1beta) secretion. However, flagellin isolated from L. parisiensis and L. tucsonensis triggers cell death and IL-1beta secretion when transfected into the cytosol of macrophages. Neither strain displays three characteristics of the canonical L. pneumophila Dot/Icm type IV secretion system: sodium sensitivity, LAMP-1 evasion, and pore formation. Therefore, we postulate that when L. parisiensis and L. tucsonensis invade a mouse macrophage, flagellin is confined to the phagosome, protecting the bacteria from recognition by the cytosolic surveillance system and allowing Legionella to replicate. Despite their superior capacity to multiply in mouse macrophages, L. parisiensis and L. tucsonensis have been associated with only two cases of disease, both in renal transplant patients. These results point to the complexity of disease, a product of the pathogenic potential of the microbe, as defined in the laboratory, and the capacity of the host to mount a measured defense.

Cytosolic recognition of flagellin by mouse macrophages restricts Legionella pneumophila infection.

To restrict infection by Legionella pneumophila, mouse macrophages require Naip5, a member of the nucleotide-binding oligomerization domain leucine-rich repeat family of pattern recognition receptors, which detect cytoplasmic microbial products. We report that mouse macrophages restricted L. pneumophila replication and initiated a proinflammatory program of cell death when flagellin contaminated their cytosol. Nuclear condensation, membrane permeability, and interleukin-1beta secretion were triggered by type IV secretion-competent bacteria that encode flagellin. The macrophage response to L. pneumophila was independent of Toll-like receptor signaling but correlated with Naip5 function and required caspase 1 activity. The L. pneumophila type IV secretion system provided only pore-forming activity because listeriolysin O of Listeria monocytogenes could substitute for its contribution. Flagellin monomers appeared to trigger the macrophage response from perforated phagosomes: once heated to disassemble filaments, flagellin triggered cell death but native flagellar preparations did not. Flagellin made L. pneumophila vulnerable to innate immune mechanisms because Naip5+ macrophages restricted the growth of virulent microbes, but flagellin mutants replicated freely. Likewise, after intratracheal inoculation of Naip5+ mice, the yield of L. pneumophila in the lungs declined, whereas the burden of flagellin mutants increased. Accordingly, macrophages respond to cytosolic flagellin by a mechanism that requires Naip5 and caspase 1 to restrict bacterial replication and release proinflammatory cytokines that control L. pneumophila infection.