Literature DB >> 24705449

Evaluation of an automated rapid diagnostic assay for detection of Gram-negative bacteria and their drug-resistance genes in positive blood cultures.

Masayoshi Tojo1, Takahiro Fujita2, Yusuke Ainoda2, Maki Nagamatsu1, Kayoko Hayakawa3, Kazuhisa Mezaki4, Aki Sakurai5, Yoshinori Masui6, Hirohisa Yazaki7, Hiroshi Takahashi8, Tohru Miyoshi-Akiyama9, Kyoichi Totsuka2, Teruo Kirikae9, Norio Ohmagari3.   

Abstract

We evaluated the performance of the Verigene Gram-Negative Blood Culture Nucleic Acid Test (BC-GN; Nanosphere, Northbrook, IL, USA), an automated multiplex assay for rapid identification of positive blood cultures caused by 9 Gram-negative bacteria (GNB) and for detection of 9 genes associated with β-lactam resistance. The BC-GN assay can be performed directly from positive blood cultures with 5 minutes of hands-on and 2 hours of run time per sample. A total of 397 GNB positive blood cultures were analyzed using the BC-GN assay. Of the 397 samples, 295 were simulated samples prepared by inoculating GNB into blood culture bottles, and the remaining were clinical samples from 102 patients with positive blood cultures. Aliquots of the positive blood cultures were tested by the BC-GN assay. The results of bacterial identification between the BC-GN assay and standard laboratory methods were as follows: Acinetobacter spp. (39 isolates for the BC-GN assay/39 for the standard methods), Citrobacter spp. (7/7), Escherichia coli (87/87), Klebsiella oxytoca (13/13), and Proteus spp. (11/11); Enterobacter spp. (29/30); Klebsiella pneumoniae (62/72); Pseudomonas aeruginosa (124/125); and Serratia marcescens (18/21); respectively. From the 102 clinical samples, 104 bacterial species were identified with the BC-GN assay, whereas 110 were identified with the standard methods. The BC-GN assay also detected all β-lactam resistance genes tested (233 genes), including 54 bla(CTX-M), 119 bla(IMP), 8 bla(KPC), 16 bla(NDM), 24 bla(OXA-23), 1 bla(OXA-24/40), 1 bla(OXA-48), 4 bla(OXA-58), and 6 blaVIM. The data shows that the BC-GN assay provides rapid detection of GNB and β-lactam resistance genes in positive blood cultures and has the potential to contributing to optimal patient management by earlier detection of major antimicrobial resistance genes.

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Year:  2014        PMID: 24705449      PMCID: PMC3976387          DOI: 10.1371/journal.pone.0094064

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Sepsis caused by drug-resistant Gram-negative bacteria (GNB) often results in serious clinical outcomes in patients [1]. Inappropriate initial antibiotic treatment occurs in one third of patients with severe sepsis due to GNB, which is associated with increased hospital mortality and length of stay [2]. In contrast, early administration of appropriate antibiotics improves survival of sepsis patients [3]. Effective antibiotic administration within the first hour of documented hypotension was related to increased survival of patients with septic shock; however, 50% of septic shock patients did not receive effective antimicrobial treatment within 6 hours of documented hypotension [4]. To improve diagnosis of causative organisms of sepsis, automated continuous-monitoring blood culture systems were developed and introduced into clinical microbiological laboratories during the 1990s [5]. These early systems and subsequent generations of automated blood culture systems remain key diagnostic tools in the diagnosis of sepsis [5]. However, after a blood culture becomes positive, conventional bacteriological procedures still require 2 to 3 days for isolation, identification, and antimicrobial susceptibility testing. In addition to the time-consuming procedures, the emergence and spread of drug-resistant GNB producing various β-lactamases, including carbapenemase and extended spectrum β-lactamases (ESBLs), has been a serious problem for treatment of sepsis [6]. Thus, there has been an unmet need for rapid and automated technology to identify bacterial species as well as detection of drug resistance genes. Recently, several rapid molecular diagnosis assays for sepsis diagnosis have been introduced and evaluated [7]; including LightCycler SeptiFast Test [8], peptide nucleic acid fluorescence in situ hybridization (PNA-FISH) [9], and matrix-assisted laser desorption-ionization time of flight mass spectrometry (MALDI-TOF MS) [10], and a DNA-based microarray platform [Prove-it sepsis assay [11] and the Verigene Gram-Positive Blood Culture (BC-GP) assay [12]–[19]]. The Verigene Gram-Negative Blood Culture (BC-GN) Nucleic Acid Test (Nanosphere Inc., Northbrook, IL) is a sample-to-result automated microarray-based, multiplexed assay for species identification of GNB and detection of their drug resistance genes in positive blood culture bottles. The Verigene BC-GN assay is designed to directly detect species of GNB from positive blood culture bottles with 5 minutes of hands-on and 2 hours of run time per sample. Recently, the BC-GN assay has been approved by the U.S. Food and Drug Administration (FDA), and the limit of detection, sensitivity, and specificity of the assay is shown on the FDA site (http://www.fda.gov/). In this study, we describe the performance of the BC-GN assay using simulated and clinical samples of positive blood culture bottles.

Materials and Methods

Bacterial strains

A total of 268 stored clinical isolates at the National Center for Global Health and Medicine (NCGM) were used in the study: 23 Acinetobacter baumannii; 1 Acinetobacter oleivorans; 4 Citrobacter freundii; 14 Enterobacter cloacae; 2 Enterobacter hormaechei; 1 Enterococcus faecalis; 30 Escherichia coli; 6 Klebsiella oxytoca; 43 Klebsiella pneumoniae; 1 methicillin-resistant Staphylococcus aureus (MRSA); 1 methicillin-sensitive Staphylococcus aureus (MSSA); 1 methicillin-resistant Staphylococcus epidermidis (MRSE); 1 Morganella morganii; 4 Proteus mirabilis; 4 Proteus vulgaris; 116 Pseudomonas aeruginosa; 15 Serratia marcescens; and 1 Stenotrophomonas maltophilia. Eighteen bacterial strains were donated by Yoshikazu Ishii (Toho University, Tokyo, Japan), including 2 strains of A. baumannii harboring bla OXA-23; 1 A. baumannii harboring bla OXA-58; 1 Acinetobacter calcoaceticus harboring bla IMP-1; 1 Acinetobacter nosocomialis harboring bla IMP-1; 1 Acinetobacter pittii harboring bla OXA-58; 2 E. cloacae harboring bla CTX-M-2 and bla CTX-M-9, respectively; 6 E. coli harboring bla CTX-M-2, bla CTX-M-3, bla CTX-M-9, bla CTX-M-14, bla CTX-M-15, and bla CTX-M-44, respectively; 2 K. pneumoniae harboring bla CTX-M-2; 1 K. pneumoniae harboring bla CTX-M-9; and 1 P. mirabilis harboring bla CTX-M-2. Bacterial identification of the 18 strains were determined as described previously [20]. Fifteen bacterial strains were obtained from International Health Management Associates, Inc. (Schaumburg, IL), including 3 strains of A. baumannii harboring bla OXA-23; 2 A. baumannii harboring bla OXA-58; 1 A. baumannii harboring bla OXA-24/40; 1 A. baumannii harboring both bla OXA-23 and bla OXA-58; 2 C. freundii harboring bla KPC-2 and bla KPC-3, respectively; 1 K. pneumoniae harboring bla KPC-2; 1 K. pneumoniae harboring bla KPC-4; 2 K. pneumoniae harboring bla KPC-11; 1 K. pneumoniae harboring both bla KPC-3 and bla CTX-M-14; and 1 S. marcescens harboring bla KPC-2.

Preparation of simulated samples

Bacterial isolates were suspended in 10-ml Falcon tubes (Becton Dickinson, Tokyo, Japan) in phosphate-buffered saline, pH 7.4. The suspension was adjusted to McFarland standard 1, followed by a dilution of 106. A 0.1-ml aliquot was inoculated into 5 ml of human whole blood for blood transfusion that was scheduled for disposal (Japanese Red Cross, Kanto-Koshinetsu Block Blood Center, Tokyo, Japan). After mixing of the blood and bacterial inoculum, the sample was injected into a Bactec plus/F aerobic blood culture bottle (Becton Dickinson). A 0.1-ml aliquot from the diluted bacterial suspension was plated, and the colony-forming unit (CFU) was determined. The average CFU of the inoculum was 23.9 ± 22.6 CFUs per bottle (median: 16, range: 1 – 184). The inoculated blood culture bottles were incubated in the BACTEC 9050 automated blood culture system (Becton Dickinson) until positive. If positive blood culture bottles could not be tested by the BC-GN assay within 12 hours of blood culture positivity, positive bottles were refrigerated at 4°C for up to 48 hours. In some experiments, an equal volume from 2–3 positive blood culture bottles was mixed and the mixture was tested by the BC-GN assay.

Clinical samples

Blood culture bottles from suspected sepsis patients were collected from December 2012 to June 2013 at the 801 bed National Center for Global Health and Medicine (NCGM), from February to June 2013 at 572 bed NCGM Kohnodai Hospital, and from March to June 2013 at 1423 bed Tokyo Women's Medical University (TWMU) hospital. Bactec plus/F (Becton Dickinson) and BacT/Alert FA (bioMérieux, Tokyo, Japan) blood culture bottles were used at NCGM and TWMU, respectively. Of 102 clinical samples, 79 and 23 were collected at NCGM and TWMU, respectively. Hospital departments and wards were not specified in the study. The bottles were incubated in the automated blood culture system until positive. Positive blood cultures showing Gram-negative bacteria were tested with the BC-GN assay. To select samples containing organisms listed in the BC-GN panel, positive blood cultures were stored at room temperature and tested within 5 days of positivity. The average of storage periods was 3.1±1.4. Only one positive blood culture per patient was included in the study.

Identification of bacterial species and detection of resistance genes

Bacterial isolates were phenotypically identified using the MicroScan WalkAway™ system (Siemens Healthcare Diagnostics, Tokyo, Japan). Isolates generating identification discrepancies between the MicroScan WalkAway system and the BC-GN assay were analyzed by 16S ribosomal RNA (rRNA) sequencing [21]. DNA sequences were determined using an ABI PRISM3130 sequencer (Applied Biosystems, Foster City, CA). The sequence similarity was determined using the EzTaxon server (http://eztaxon-e.ezbiocloud.net/ezt_identify). The presence of 9 genes listed in the BC-GN panel was examined using PCR in simulated and clinical samples tested, regardless of the results with the BC-GN assay. The primers for PCR were shown in Table 1. The DNA sequences of the drug-resistant genes were determined when isolates generated discrepant results between the BC-GN assay and PCR.
Table 1

Primers used in this study.

Detection for antibiotic resistance genes16S rRNA gene sequencing
PrimersSequence(5′-3′)PrimersSequence(5′-3′)
CTX-M-F CGTTGTAAAACGACGGCCAGTGAA 5F TTGGAGAGTTTGATCCTGGCTC
TGTGCAGYACCAGTAARGTKATGGC341F CTACGGGAGGCAGCAGTGGG
CTX-M-RTGGGTRAARTARGTSACCAGAAYCAGCGG810R GCGTGGACTTCCAGGGTATCT
IMP-FGGAATAGAGTGGCTTAAYTCTC1194R ACGTCATCCCCACCTTCCTC
IMP-RGGTTTAAYAAAACAACCACC1485R TACGGTTACCTTGTTACGAC
KPC-F CGTCTAGTTCTGCTGTCTTG
KPC-R CTTGTCATCCTTGTTAGGCG
NDM-F GGTTTGGCGATCTGGTTTTC
NDM-R CGGAATGGCTCATCACGATC
OXA-23like-F GATCGGATTGGAGAACCAGA
OXA-23like-R ATTTCTGACCGCATTTCCAT
OXA-24/40like-F GGTTAGTTGGCCCCCTTAAA
OXA-24/40like-R AGTTGAGCGAAAAGGGGATT
OXA48-F GCGTGGTTAAGGATGAACAC
OXA48-R CATCAAGTTCAACCCAACCG
OXA-58like-F CCCCTCTGCGCTCTACATAC
OXA-58like-R AAGTATTGGGGCTTGTGCTG
VIM-F GATGGTGTTTGGTCGCATA
VIM-R CGAATGCGCAGCACCAG

Minimum inhibitory concentrations of antibiotics

Minimum inhibitory concentrations (MICs) of amikacin (AMK), ampicillin (ABPC), amoxicillin/clavulanate (AMPC/CVA), aztreonam (AZT), cefazolin (CEZ), cefepime (CFPM), cefmetazole (CMZ), cefotaxime (CTX), cefotiam (CTM), ceftazidime (CAZ), ciprofloxacin (CPFX), colistin, gentamicin (GM), imipenem (IPM), levofloxacin (LVFX), minocycline (MINO), meropenem (MEMP), piperacillin (PIPC), piperacillin-tazobactam (PIPC/TAZ), sulfamethoxazole-trimethoprim (ST), and tigecylcine (TGC) were determined by the Microscan Walkaway and/or the broth microdilution method, according to the guidelines of the Clinical and Laboratory Standards Institute (CLSI) [22]. Values of MICs at which 50% and 90% of E. coli isolates from clinical samples were inhibited (MIC50 and MIC90, respectively) were determined in β-lactams.

Verigene System

The Verigene BC-GN assay detects 9 bacterial species and 9 drug resistance genes (Table 2). The Verigene System consists of the Verigene Reader and the Processor SP. Following loading of the extraction tray, utility tray and test cartridge into the Verigene Processor SP, 700 μl of positive blood culture was added to the extraction tray sample well. The Verigene Processor SP extracted nucleic acids from positive blood culture media. The extracted nucleic acids were automatically transferred to the test cartridge and hybridized to synthetic specific oligonucleotides attached to the microarray slide. The nucleic acids bound on the microarray slide were further hybridized to the second specific oligonucleotides with gold nanoparticles. After 2 hours, the microarray slide was manually removed and inserted into the Verigene Reader for analysis. The Verigene system contains internal controls, including negative controls, hybridization controls, and extraction controls. When any internal control do not generate correct results, or target signals were not adequately higher than the negative control signals, the Verigene Reader reported “No Call” meaning a technical error. When the Verigene Reader reported “No Call”, the BC-GN assay was repeated until results other than “No Call” were generated. Once the result was obtained, the BC-GN assay was not repeated.
Table 2

Bacterial species and Antimicrobial resistance genes identified by the BC-GN assay.

Gram-negative species
Acinetobacter spp.
Citrobacter spp.
Enterobacter spp.
E. coli
K. oxytoca
K. pneumoniae
Proteus spp.
P. aeruginosa
S. marcescens

Statistical analysis

The concordance rate between the BC-GN assay and standard laboratory methods was examined, and the 95% confidence interval of the rate was calculated with the R Software (http://www.r-project.org/).

Ethical considerations

The study protocol was carefully reviewed and approved by the ethics committee of the National Center for Global Health and Medicine (No. 1268) and Tokyo Women's Medical University hospital (No. 2740-R), respectively. Individual informed consent was waived by the ethics committee listed above because this study used currently existing sample collected during the course of routine medical care and did not pose any additional risks to the patients.

Results

Bacterial identification of simulated samples

Of the 397 positive blood culture samples in the study, 295 were simulated samples prepared by inoculating an isolate of one of the Gram-negative bacterial species listed in Table 2. All the samples became culture-positive. Of the 295 samples, 289 generated a result of the BC-GN assay on the first attempt (98.1%) (data not shown). The remaining 6 generated “No Call ” results meaning technical errors. When retested, all the 6 samples generated results (data not shown). The concordance rate of the 295 simulated samples between the BC-GN assay and the MicroScan WalkAway system for bacterial identification were as follows: Acinetobacter spp., Citrobacter spp., Enterobacter spp., E. coli, K. oxytoca, Proteus spp., and P. aeruginosa: 100%; K. pneumoniae: 88.2%; and S. marcescens: 81.3% (left columns in Table 3).
Table 3

Identification of bacterial isolates in blood culture samples with the BC-GN assay.

Simulated samplesb (n = 295)Clinical samplesc (n = 102)Total (n = 397)
Bacterial speciesa Inocultaed isolatesCorrectly identified isolatesd (%)Not detected isolatese (%)Incorrectly identified isolatesf (%)Identified speciesg Correctly identified isolatesd (%)Not detected isolatese (%)Concordance rateh (95% CIi)
Acinetobacter spp.3737 (100%)0022 (100%)0100% (91.0–100)
Citrobacter spp.66 (100%)0011 (100%)0100% (59.0–100)
Enterobacter spp.1818 (100%)001211 (91.7%)1 (8.3%)96.7% (82.8–99.9)
E. coli 3636 (100%)005151 (100%)0100% (95.8–100)
K. oxytoca 66 (100%)0077 (100%)0100% (75.3–100)
K. pneumoniae 5145 (88.2%)5 (9.8%)1j (2.0%)2117 (81.0%)4 (19%)86.1% (75.9–93.1)
Proteus spp.99 (100%)0022 (100%)0100% (91.0–100)
P. aeruginosa 116116 (100%)0098 (88.9%)1 (11.1%)99.2% (95.6–99.9)
S. marcescens 1613 (81.3%)3 (18.7%)055 (100%)085.7% (63.7–97.0)
Total295286 (96.9%)8 (2.7%)1 (0.3%)110104 (94.5%)6 (5.5%)96.3% (94.0–97.9)

a Bacterial species inoculated into blood culture bottles or bacterial species identified in clinical samples of blood culture bottles.

b Blood culture samples into which bacterial isolates were inoculated.

c Clinical blood culture samples obatined from sepsis patients.

d Numbers of isolates which were correctly identified with the BC-GN assay.

e Numbers of isolates which were not detected with the BC-GN assay.

f Numbers of isolates which were incorrectly identified with theBC-GN assay.

g Numbers of bacterial species which were identified in clinical samples with the conventional methods. Some of the samples contained 2 or 3 bacterial species.

h Concordance rate between the BC-GN assay and the conventional methods for bacterial identification.

i CI indicates confidence interval

j A sample inoculated with K. pneumoniae was identified as Enterobacter spp. with the assay.

a Bacterial species inoculated into blood culture bottles or bacterial species identified in clinical samples of blood culture bottles. b Blood culture samples into which bacterial isolates were inoculated. c Clinical blood culture samples obatined from sepsis patients. d Numbers of isolates which were correctly identified with the BC-GN assay. e Numbers of isolates which were not detected with the BC-GN assay. f Numbers of isolates which were incorrectly identified with theBC-GN assay. g Numbers of bacterial species which were identified in clinical samples with the conventional methods. Some of the samples contained 2 or 3 bacterial species. h Concordance rate between the BC-GN assay and the conventional methods for bacterial identification. i CI indicates confidence interval j A sample inoculated with K. pneumoniae was identified as Enterobacter spp. with the assay. Of 51 samples inoculated with stored K. pneumoniae isolates (left columns in Table 3), 45 were detected with the BC-GN assay, but the remaining 6 were not correctly detected. Of these 6 samples, 5 were reported as “Not detected”, and 1 was reported as Enterobacter spp. The MicroScan WalkAway system reported these 6 samples as K. pneumoniae. The 16S rRNA sequences of these samples showed more than 99.3% similarity to both K. pneumoniae and K. variicola. Of 16 samples inoculated with stored S. marcescens (left columns in Table 3), 3 were not detected with the BC-GN assay. The MicroScan WalkAway system reported these 3 samples as S. marcescens. The 16S rRNA sequences of these samples showed more than 99.5% similarity to both S. marcescens and Serratia nematodiphila. Their biochemical profile based on carbohydrates utilization corresponded to those of S. marcescens [23]. The BC-GN assay was tested on blood culture bottles inoculated simultaneously with 2 or 3 clinical isolates. The following combinations of bacteria species were tested: A. baumannii (harboring bla OXA-23) and K. pneumoniae (bla CTX-M and bla NDM); A. baumannii (bla OXA-23) and MRSA; C. freundii, K. pneumoniae (bla KPC) and P. mirabilis; C. freundii (bla KPC), E. faecalis and MSSA; E. cloacae (bla IMP) and S. marcescens; E. faecalis and E. coli (bla CTX-M); E. coli (bla CTX-M) and P. aeruginosa (bla VIM); P. aeruginosa (bla VIM) and MRSE. All Gram-negative bacterial isolates were correctly detected by the BC-GN assay regardless of the presence of other bacterial species, including Gram-positive strains. The BC-GN assay also detected all drug resistance genes under these conditions (data not shown). The BC-GN assay was also tested on 2 blood culture bottles inoculated with M. morganii and S. maltophilia, respectively, which are Gram-negative pathogens but are not among the targets of the BC-GN assay. As expected, the BC-GN assay did not detect these species (data not shown).

Bacterial identification of clinical samples

A total of 102 blood culture-positive samples obtained from sepsis patients, and 101 of them generated a result of the BC-GN assay on the first attempt (99.0%) (data not shown). From the 102 blood culture-positive samples, a total of 110 Gram-negative bacterial species were isolated (middle columns in Table 3). The concordance rate of 110 bacterial species between the BC-GN assay and the MicroScan WalkAway system for bacterial identification were 94.5% (NCGM: 82/86; TWMU: 22/24), and the rate of each bacterial species were as follows: Acinetobacter spp., Citrobacter spp., E. coli, K. oxytoca, Proteus spp., and S. marcescens: 100%; Enterobacter spp.: 91.7%; K. pneumoniae: 81.0%; and P. aeruginosa: 88.9% (middle columns in Table 3). Of all the clinical samples, 8 were obtained from anaerobic bottles, and all the 8 results of the BC-GN assay agreed with those of the MicroScan WalkAway system (data not shown). Of the 110 bacterial isolates, 6 isolates (5.5%) were not detected with the BC-GN assay (middle columns in Table 3). Of these 6 isolates, the MicroScan WalkAway system reported 1 isolate as Enterobacter spp., 4 isolates as K. pneumoniae and 1 isolate as P. aeruginosa (middle columns in Table 3). The sample reported as Enterobacter spp. by the MicroScan WalkAway system was reported as “No Call” with the BC-GN assay on two tries. The 16S rRNA sequence of the isolate reported as Enterobacter spp. by the MicroScan WalkAway system showed more than 99.9% similarity to Enterobacter agglomerance. Of the 4 samples reported as K. pneumoniae by the MicroScan WalkAway system and not detected by the BC-GN assay, 2 were from polymicrobial bacteremia cases: E. coli and K. pneumoniae was isolated from one positive bottle, and K. pneumoniae and P. aeruginosa was isolated from another. The 16S rRNA sequences of the 4 isolates reported as K. pneumoniae by the MicroScan WalkAway system showed more than 99.2% similarity to both K. pneumoniae and K. variicola. One P. aeruginosa sample not detected with the BC-GN was from a polymicrobial bacteremia case of K. pneumoniae and P. aeruginosa. The 16S rRNA sequence of the isolate reported as P. aeruginosa by the MicroScan WalkAway system showed more than 99.9% similarity to P. aeruginosa. Seven of the 102 clinical samples were polymicrobial. In 4 of the 7 samples, the BC-GN assay detected all of the multiple bacterial species, even in a sample containing 3 different Gram-negative species. In a sample containing Enterococcus casseliflavus and E. coli, the BC-GN assay detected only E. coli but not E. casseliflavus, since it detects only Gram-negative bacteria but not Gram-positive ones. In the remaining 3 polymicrobial positive blood culture samples, the BC-GN assay did not detect one of the multiple pathogens (K. pneumoniae in 2 samples and P. aeruginosa in 1 samples). The bacterial identification of the samples not detected by the BC-GN assay was described above.

Identification of drug resistance genes

With respect to drug resistant genes, the BC-GN assay reported that, of the 295 simulated samples tested, 184 were positive for one of the resistance gene targets detected by the BC-GN assay and 18 were positive for two of the targets. These results agreed with those of PCR and/or DNA sequencing. As shown on left columns in Table 4, 42 bla CTX-M (2 E. cloacae, 19 E. coli, 2 E. hormaechei, 18 K. pneumoniae, and 1 P. mirabilis isolates), 119 bla IMP (1 A. calcoaceticus, 1 A. nosocomialis, 1 A. pittii, 9 E. cloacae, 4 K. pneumoniae, and 103 P. aeruginosa), 8 bla KPC (2 C. freundii, 5 K. pneumoniae, and 1 S. marcescens), 16 bla NDM (2 A. baumannii, 1 E. hormaechei, 1 E. coli, 11 K. pneumoniae, and 1 P. aeruginosa), 24 bla OXA-23 (24 A. baumannii), 1 bla OXA-24/40 (1 A. baumannii), 1 bla OXA-48 (1 K. pneumoniae), 3 bla OXA-58 (2 A. baumannii and 1 A. pittii), and 6 bla VIM (6 P. aeruginosa) were detected by the BC-GN assay.
Table 4

Identification of resistance genes in blood culture samples with the BC-GN assay.

Resistance genesa Simulated samplesb (n = 295)Clinical samplesc (n = 102)Total (n = 397)
Positive genes for PCR/DNAsequencesCorrectly identified genesd (%)Not detected genese Positive genes for PCR/DNAsequencesCorrectly identified genesd (%)Not detected genese Concordance ratef (95% CIg)
bla CTX-M 4242 (100%)01212 (100%)0100% (93.3–100)
bla IMP 119119 (100%)0000100% (96.9–100)
bla KPC 88 (100%)0000100% (63.1–100)
bla NDM 1616 (100%)0000100% (79.4–100)
bla OXA-23 2424 (100%)0000100% (85.8–100)
bla OXA-24/40 11 (100%)0000100% (2.5–100)
bla OXA-48 11 (100%)0000100% (2.5–100)
bla OXA-58 33 (100%)011 (100%)0100% (39.8–100)
bla VIM 66 (100%)0000100% (54.1–100)
Total220220 (100%)01313 (100%)0100% (98.4–100)

a Resistance genes which were harbored by bacterial species inoculated into blood culture bottles or isolated from sepsis patients.

b, c See footnotes b and c in Table 3.

d Numbers of genes which were correctly identified with the BC-GN assay.

e Numbers of genes which were not detected with the BC-GN assay.

f Concordance rate between the BC-GN assay and the conventional methods for resistance-genes identification.

g CI indicates confidence interval

a Resistance genes which were harbored by bacterial species inoculated into blood culture bottles or isolated from sepsis patients. b, c See footnotes b and c in Table 3. d Numbers of genes which were correctly identified with the BC-GN assay. e Numbers of genes which were not detected with the BC-GN assay. f Concordance rate between the BC-GN assay and the conventional methods for resistance-genes identification. g CI indicates confidence interval Of the 102 clinical samples tested, 13 were positive for one of the 9 drug resistance genes. As shown on middle columns in Table 4, 12 bla CTX-M (2 E. cloacae, 8 E. coli, and 2 K. pneumoniae), and 1 bla OXA-58 (1 A. baumannii) were detected by the BC-GN assay. These results were completely agreed with those of our laboratory methods. MICs of E. coli isolates from patients harboring or not harboring bla CTX-M were determined (Table 5). The E. coli isolates harboring bla CTX-M showed higher MIC50 and MIC90 of β-lactams tested than the isolates not harboring bla CTX-M. MICs of IMP were ≤1 μg/ml in E. coli isolates harboring or not harboring bla CTX-M. An isolate of Acinetobacter spp. harboring bla OXA-58 was susceptible to all β-lactams tested (Table S1). MICs of all clinical isolates were shown in Table S1, 2.
Table 5

Drug susceptibility of β-lactams of E. coli harboring or not harboring.

β-lactams
Number of isolatesPIPCCAZCTXIMP
MIC50 MIC90 MIC50 MIC90 MIC50 MIC90 MIC50 MIC90
(μg/ml)(μg/ml)(μg/ml)(μg/ml)(μg/ml)(μg/ml)(μg/ml)(μg/ml)
E. coli (bla CTX-M -positive)8>512>5128>16>32>32≤1≤1
E. coli (bla CTX-M -negative)43≤8>64≤1≤1≤8≤8≤1≤1

Discussion

We determined the overall concordance rate, 96.3%, between the BC-GN assay and standard laboratory methods (Table 3). All bacterial species tested except for K. pneumoniae and S. marcescens showed the concordance rate of over 95%. In addition to the good performance, the BC-GN assay can be completed within 2 h with less than 5 min of hands-on time, enabling same day analysis and starting on appropriate treatment. The concordance rate of the BC-GN assay was comparable to that of the BC-GP assay. However, the BC-GN assay will need to be evaluated using various blood culture systems, since the BC-GP assay have already evaluated as well [12]–[19]. The BC-GN assay did not accurately identify a total of 15 isolates from 9 simulated samples and 6 clinical samples (Table 3). Of the 15 isolates, 10, 3, 1 and 1 were reported as K. pneumoniae, S. marcescens, Enterobacter spp., P. aeruginosa by the MicroScan WalkAway system, respectively. Relatively higher rates of misidentification in K. pneumoniae and S. marcescens isolates were likely to be due to the probes used in the BC-GN assay. These probes will be improved in the further study. The concordance rates of Gram-positive bacteria were comparable in the BC-GP assay [12]–[19]. The lower accuracy results of K. pneumoniae were shown in both the spiked and clinical observations. The 16S rRNA sequence revealed that the 10 misidentified isolates shared over 99% similarity to both K. pneumoniae and K. variicola. Previous studies have reported that routine methods may identify K. variicola as K. pneumoniae [24]. Further studies are required to clarify the clinical significance of K. variicola in sepsis patients. As described above, three samples containing S. marcescens were not detected with the BC-GN assay, which were observed only in the simulated samples. It is unclear whether clinical samples containing S. marcescens were not detected accurately with the BC-GN assay, since the number of samples tested was low. As for the detection of polymicrobial samples, the BC-GN assay performed well in the simulated samples, but not in the clinical samples. All isolates were not detected completely in 3 of 7 clinical samples containing polymicrobial organisms. Although fungal species like Candida albicans were not tested, these results can have significant clinical implications. Rapid molecular-based assays including the BC-GP assay and the FilmArray blood culture identification assay showed relatively low sensitivity in polymicrobial infections [14], [25]. We evaluated the performance of the BC-GN assay in detecting various drug resistance genes using simulated samples. The BC-GN assay correctly detected all the drug resistance genes tested, even when multiple drug resistance genes were present in a sample. In addition, MICs of E. coli isolates from clinical samples indicated that the presence of bla CTX-M was related to drug susceptibility profiles with high MICs of PIPC, CAZ, and CTX, not IPM. These results suggest that the BC-GN assay is useful for earlier administration of appropriate antibiotics and de-escalation. Whereas, no genotypic-phenotypic correlation was found in the Acinetobacter spp. isolate harboring bla OXA-58. In that case, the BC-GN assay may lead to inappropriate use of antibiotic, and de-escalation is needed after conventional drug susceptibility testing. Although bla CTX-M is the most prevalent among genes of extended-spectrum β-lactamases (ESBLs)[26], [27], the BC-GN assay cannot detect other ESBLs genes like bla TEM and bla SHV, and there remains concern of bacteria harboring drug resistance genes which were not detected by the assay. More than 200 bla TEM and more than 100 bla SHV genes are currently known in the Lahey clinic database [28]. Thus, it remains unfeasible to detect these variants in a rapid and simple manner. The emergence of various β-lactam resistance genes, including carbapenemases and ESBLs, have been extensively reported [6]. The timely direct detection of resistance genes from positive blood cultures will be very useful in clinical situations, since multidrug-resistant bacteria and polymicrobial infections are important causes of failure in the treatment of sepsis. Because drug resistance genes will continue to evolve and spread, it is necessary to carefully monitor the spread of drug resistance genes. Of the 10 most frequently isolated microorganisms in ICU-acquired bloodstream infection in Europe, 7 were Gram-negative pathogens targeted by the BC-GN assay [29]. Similar results were obtained from monomicrobial nosocomial bloodstream infections both in ICU and non-ICU wards in the USA [30]. The National Healthcare Safety Network at CDC reported that a significant proportion of central line-associated bloodstream infections are caused by drug-resistant Gram-negative pathogens in the USA [31]. Of the 6 major pathogens other than coagulase-negative staphylococci associated with nosocomial blood stream infections in Japan, 3 were Gram-negative pathogens, 2 were Gram-positive ones, and 1 was Candida spp. [32]. The BC-GN assay, which targets 9 Gram-negative bacterial species, will contribute to the diagnosis and management of patients with Gram-negative sepsis. A number of new diagnostic methods have been developed for rapid detection of pathogens in positive blood cultures. A real-time PCR-based assay (LightCycler SeptiFast Test) can detect a number of Gram-negative and Gram-positive bacteria and fungi in a single assay, although it cannot detect drug resistance genes [8]. PNA-FISH can detect 3 Gram-negative pathogens, including E. coli, K. pneumoniae, and P. aeruginosa, but cannot detect drug resistance genes [9]. MALDI-TOF MS can detect bacterial isolates in blood culture, but cannot detect 2 or more bacterial species in polymicrobial samples or drug resistance gene products [33]. A DNA-based microarray platform, Probe-it sepsis assay, can detect various Gram-negative and Gram-positive pathogens in blood cultures. Nevertheless, it cannot detect drug resistance genes other than mecA [11]. To integrate the Verigene system into a laboratory workflow, Gram stain was needed after blood culture was positive to determine whether the BC-GN or BC-GP assay was used. The Verigene system cannot measure MICs of antibiotics, and thus should be used in combination with biochemical characteristics of bacteria obtained from conventional drug susceptibility testing. This study has some limitations. Firstly, we could not fully evaluate the ability of the BC-GN assay to detect some drug resistance genes, such as bla OXA-24/40 and bla OXA-48. Secondly, to select samples containing organisms listed in the BC-GN panel, positive blood culture was stored for 3.1±1.4 days (maximum 5 days) before the BC-GN assay was done. The BC-GN assay should be done immediately after the culture becomes positive, although the storage of the culture in the study was unlikely to affect the assay results. A large-scale prospective clinical evaluation of the BC-GN assay is planned to determine the clinical impact of the assay including selection of antibiotics, length of stay, morbidity, and cost-effectiveness. In conclusion, the Verigene system BC-GN assay accurately detects common Gram-negative bacterial isolates and their drug resistance genes from positive blood cultures in a rapid manner. The BC-GN assay demonstrated high sensitivity and specificity in the study, and it will generate significantly faster results compared to conventional methods in the medical settings. This new anitibioticroarray platform can be easily introduced into microbiological laboratories in various clinical settings. It will contribute to improved sepsis management as a result of earlier reporting of critical information leading to earlier administration of appropriate antibiotics and de-escalation. MICs of antibiotics in clinical isolates harboring drug resistance genes. It was measured using the broth microdilution method, according to the guidelines of the Clinical and Laboratory Standards Institute (CLSI). (XLSX) Click here for additional data file. MICs of antibiotics in all clinical isolates determined by Microscan Walkaway. (XLSX) Click here for additional data file.
  30 in total

Review 1.  Molecular diagnosis of bloodstream infections: planning to (physically) reach the bedside.

Authors:  N Leggieri; A Rida; P François; Jacques Schrenzel
Journal:  Curr Opin Infect Dis       Date:  2010-08       Impact factor: 4.915

2.  Inappropriate antibiotic therapy in Gram-negative sepsis increases hospital length of stay.

Authors:  Andrew F Shorr; Scott T Micek; Emily C Welch; Joshua A Doherty; Richard M Reichley; Marin H Kollef
Journal:  Crit Care Med       Date:  2011-01       Impact factor: 7.598

Review 3.  The CTX-M beta-lactamase pandemic.

Authors:  Rafael Cantón; Teresa M Coque
Journal:  Curr Opin Microbiol       Date:  2006-08-30       Impact factor: 7.934

4.  Molecular diagnosis of sepsis in neutropenic patients with haematological malignancies.

Authors:  Nicasio Mancini; Daniela Clerici; Roberta Diotti; Mario Perotti; Nadia Ghidoli; Donata De Marco; Beatrice Pizzorno; Thomas Emrich; Roberto Burioni; Fabio Ciceri; Massimo Clementi
Journal:  J Med Microbiol       Date:  2008-05       Impact factor: 2.472

Review 5.  Updated functional classification of beta-lactamases.

Authors:  Karen Bush; George A Jacoby
Journal:  Antimicrob Agents Chemother       Date:  2009-12-07       Impact factor: 5.191

6.  Multicenter evaluation of a new shortened peptide nucleic acid fluorescence in situ hybridization procedure for species identification of select Gram-negative bacilli from blood cultures.

Authors:  Margie Morgan; Elizabeth Marlowe; Phyllis Della-Latta; Hossein Salimnia; Susan Novak-Weekley; Fann Wu; Benjamin S Crystal
Journal:  J Clin Microbiol       Date:  2010-03-31       Impact factor: 5.948

Review 7.  Hospital-acquired infections due to gram-negative bacteria.

Authors:  Anton Y Peleg; David C Hooper
Journal:  N Engl J Med       Date:  2010-05-13       Impact factor: 91.245

8.  Fatal sepsis caused by an unusual Klebsiella species that was misidentified by an automated identification system.

Authors:  Masafumi Seki; Kazuyoshi Gotoh; Shota Nakamura; Yukihiro Akeda; Tadashi Yoshii; Shinichi Miyaguchi; Hidenori Inohara; Toshihiro Horii; Kazunori Oishi; Tetsuya Iida; Kazunori Tomono
Journal:  J Med Microbiol       Date:  2013-02-28       Impact factor: 2.472

9.  Serratia nematodiphila sp. nov., associated symbiotically with the entomopathogenic nematode Heterorhabditidoides chongmingensis (Rhabditida: Rhabditidae).

Authors:  Chong-Xing Zhang; Shou-Yun Yang; Ming-Xu Xu; Jie Sun; Huan Liu; Jing-Rui Liu; Hui Liu; Fei Kan; Jing Sun; Ren Lai; Ke-Yun Zhang
Journal:  Int J Syst Evol Microbiol       Date:  2009-07       Impact factor: 2.747

10.  Impact of time to antibiotics on survival in patients with severe sepsis or septic shock in whom early goal-directed therapy was initiated in the emergency department.

Authors:  David F Gaieski; Mark E Mikkelsen; Roger A Band; Jesse M Pines; Richard Massone; Frances F Furia; Frances S Shofer; Munish Goyal
Journal:  Crit Care Med       Date:  2010-04       Impact factor: 7.598

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  22 in total

1.  A Stewardship Approach To Optimize Antimicrobial Therapy through Use of a Rapid Microarray Assay on Blood Cultures Positive for Gram-Negative Bacteria.

Authors:  Conner Sothoron; Jason Ferreira; Nilmarie Guzman; Petra Aldridge; Yvette S McCarter; Christopher A Jankowski
Journal:  J Clin Microbiol       Date:  2015-08-19       Impact factor: 5.948

2.  Rapid testing using the Verigene Gram-negative blood culture nucleic acid test in combination with antimicrobial stewardship intervention against Gram-negative bacteremia.

Authors:  Jacqueline T Bork; Surbhi Leekha; Emily L Heil; LiCheng Zhao; Rilwan Badamas; J Kristie Johnson
Journal:  Antimicrob Agents Chemother       Date:  2014-12-29       Impact factor: 5.191

3.  Evaluation of the Accelerate Pheno System for Fast Identification and Antimicrobial Susceptibility Testing from Positive Blood Cultures in Bloodstream Infections Caused by Gram-Negative Pathogens.

Authors:  Matthias Marschal; Johanna Bachmaier; Ingo Autenrieth; Philipp Oberhettinger; Matthias Willmann; Silke Peter
Journal:  J Clin Microbiol       Date:  2017-04-26       Impact factor: 5.948

4.  Parallel Evaluation of the MALDI Sepsityper and Verigene BC-GN Assays for Rapid Identification of Gram-Negative Bacilli from Positive Blood Cultures.

Authors:  Miguel A Arroyo; Gerald A Denys
Journal:  J Clin Microbiol       Date:  2017-06-21       Impact factor: 5.948

5.  Identification of Gram-Negative Bacteria and Genetic Resistance Determinants from Positive Blood Culture Broths by Use of the Verigene Gram-Negative Blood Culture Multiplex Microarray-Based Molecular Assay.

Authors:  Nathan A Ledeboer; Bert K Lopansri; Neelam Dhiman; Robert Cavagnolo; Karen C Carroll; Paul Granato; Richard Thomson; Susan M Butler-Wu; Heather Berger; Linoj Samuel; Preeti Pancholi; Lettie Swyers; Glen T Hansen; Nam K Tran; Christopher R Polage; Kenneth S Thomson; Nancy D Hanson; Richard Winegar; Blake W Buchan
Journal:  J Clin Microbiol       Date:  2015-05-20       Impact factor: 5.948

6.  Evaluation of FilmArray and Verigene systems for rapid identification of positive blood cultures.

Authors:  M M Bhatti; S Boonlayangoor; K G Beavis; V Tesic
Journal:  J Clin Microbiol       Date:  2014-07-16       Impact factor: 5.948

7.  Evaluation of the nanosphere Verigene BC-GN assay for direct identification of gram-negative bacilli and antibiotic resistance markers from positive blood cultures and potential impact for more-rapid antibiotic interventions.

Authors:  Joseph T Hill; Kim-Dung T Tran; Karen L Barton; Matthew J Labreche; Susan E Sharp
Journal:  J Clin Microbiol       Date:  2014-08-13       Impact factor: 5.948

Review 8.  Emerging technologies for the clinical microbiology laboratory.

Authors:  Blake W Buchan; Nathan A Ledeboer
Journal:  Clin Microbiol Rev       Date:  2014-10       Impact factor: 26.132

9.  Performance of the Verigene Gram-negative blood culture assay for rapid detection of bacteria and resistance determinants.

Authors:  Magali Dodémont; Ricardo De Mendonça; Claire Nonhoff; Sandrine Roisin; Olivier Denis
Journal:  J Clin Microbiol       Date:  2014-06-04       Impact factor: 5.948

10.  Point-Counterpoint: Large Multiplex PCR Panels Should Be First-Line Tests for Detection of Respiratory and Intestinal Pathogens.

Authors:  Paul C Schreckenberger; Alexander J McAdam
Journal:  J Clin Microbiol       Date:  2015-03-11       Impact factor: 5.948

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