Clinical manifestations, molecular characteristics, antimicrobial susceptibility patterns and contributions of target gene mutation to fluoroquinolone resistance in Elizabethkingia anophelis

Clinical manifestations, molecular characteristics, antimicrobial susceptibility patterns and... Abstract Objectives Elizabethkingia anophelis has recently emerged as a cause of life-threatening infections in humans. We aimed to investigate the clinical and molecular characteristics of E. anophelis. Methods A clinical microbiology laboratory database was searched to identify patients with Elizabethkingia infections between 2005 and 2016. Isolates were re-identified and their species were confirmed using 16S rRNA gene sequencing. Patients with E. anophelis infections were included in this study. Clinical information, antimicrobial susceptibility and mutations in DNA gyrase and topoisomerase IV were analysed. Results A total of 67 patients were identified to have E. anophelis infections, including 47 men and 20 women, with a median age of 61 years. Comorbidity was identified in 85.1% of the patients. Among the 67 E. anophelis isolates, 40 (59.7%) were isolated from blood. The case fatality rate was 28.4%. Inappropriate empirical antimicrobial therapy was an independent risk factor for mortality (adjusted OR = 10.01; 95% CI = 1.20–83.76; P = 0.034). The isolates were ‘not susceptible’ to multiple antibiotics. All the isolates were susceptible to minocycline. Susceptibilities to ciprofloxacin and levofloxacin were 4.5% and 58.2%, respectively. Mutations in DNA gyrase subunit A were identified in 11 isolates that exhibited high-level fluoroquinolone resistance. Conclusions Minocycline has the potential to be the drug of choice in patients with E. anophelis infections. Additional investigations are needed to determine the optimal antimicrobial agents to treat this life-threatening infection. Introduction Elizabethkingia is a genus of aerobic, non-fermenting, non-motile, catalase-positive, oxidase-positive, indole-positive and Gram-negative bacilli that are distributed in the natural environments of soil and water.1–3 Since its first isolation in 1959 by Elizabeth O. King,4,Elizabethkingia has been sporadically reported to cause human infections.1–5 In addition to the previously known Elizabethkingia meningoseptica, Elizabethkingia miricola and Elizabethkingia anophelis,6 three novel species, namely, Elizabethkingia bruuniana, Elizabethkingia ursingii and Elizabethkingia occulta, were proposed to be new members of the Elizabethkingia genus recently.7 Among these species, E. anophelis has emerged recently as a cause of life-threatening infection in humans, particularly in immunocompromised patients.8–14 Several outbreaks of E. anophelis infections have been reported in Africa,8 Singapore,9 Hong Kong10 and the USA.11–14 Elizabethkingia species are often resistant to multiple antibiotics but are variably susceptible to fluoroquinolones.15,16 The major mechanisms for fluoroquinolone resistance include gene alterations in the QRDRs of DNA gyrase (GyrA and GyrB) and topoisomerase IV (ParC and ParE), reduced drug accumulation by decreased entry or increased efflux, and plasmid-mediated quinolone resistance protein Qnr.17 However, information concerning the mechanisms of fluoroquinolone resistance in E. anophelis is limited.12,18–21 Despite being increasingly recognized as an emerging infectious agent, few data describe the clinical manifestations, antimicrobial susceptibility and mechanisms of antimicrobial resistance in E. anophelis. In this study, we report the clinical and molecular characteristics of E. anophelis infections in humans. We also examine antimicrobial susceptibility and investigate the contributions of mutations in the QRDRs to fluoroquinolone resistance in clinical isolates of E. anophelis. Materials and methods Ethics This study was conducted in accordance with the Declaration of Helsinki and national and institutional standards. This study was approved by the Institutional Review Board of E-Da Hospital (EMRP-106-105). The need for patient informed consent was waived by the Institutional Review Board because the retrospective analysis of routine blood cultures posed no more than minimal risk of harm to the subjects. Study setting and study design This study was performed at a 1000 bed university-affiliated medical centre in Taiwan. The clinical laboratory database was searched for microbial cultures that contained Elizabethkingia species from January 2005 to December 2016. These isolates were routinely collected from patients according to clinical requirements and then stored as glycerol stocks at −80°C. The Elizabethkingia species were re-identified using 16S rRNA gene sequencing. Clinical conditions (such as shock) were recorded during the episode of E. anophelis infection. Laboratory data were collected within three days surrounding the time of Elizabethkingia isolation. Empirical antimicrobial therapy was considered inappropriate when the isolate was not susceptible to the treatment agents. 16S rRNA gene sequencing Total DNA from each isolate was prepared using a Wizard Genomic DNA Purification Kit (Promega, Madison, WI, USA). PCR was performed using a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA, USA) and the amplicons were sequenced using an Applied Biosystems 3730xl DNA Analyzer. The primers used to amplify internal fragments of the 16S rRNA gene and for sequencing are listed in Table S1 (available as Supplementary data at JAC Online).22,23 The assembled sequences were compared with the 16S rRNA sequences of each type strain: E. meningoseptica KC1913T, E. miricola G4074T, E. anophelis R26T, E. bruuniana G0146T, E. ursingii G4122T and E. occulta G4070T. The species was considered identified if the isolate possessed >99.5% 16S rRNA sequence identity to the type strain.24 Antimicrobial susceptibility testing The MICs of antibiotics were determined using Sensititre 96-well broth microdilution panels (Thermo Fisher Scientific/Trek Diagnostics Systems, Oakwood Village, OH, USA). The susceptibilities were evaluated according to the interpretive standards for ‘other non-Enterobacteriaceae’ from the CLSI guidelines.25 Identification of mutations in the QRDRs The primers and PCR conditions for the amplification of QRDRs in gyrA, gyrB, parC and parE are listed in Table S1. The sequences were aligned with the sequences of E. anophelis strain NUHP1 (GenBank accession number = CP007547).18 PFGE All the isolates were digested by XbaI and subjected to PFGE according to a previously described protocol.10 The digested DNA fragments were separated by a Contour-clamped Homogeneous Electric Field Mapper XA Chiller system (Bio-Rad, Hercules, CA, USA). A dendrogram was constructed using the unweighted pair-group method with the arithmetic mean algorithm by GelCompar II software (version 6; Applied Maths, Sint-Martens-Latem, Belgium). The isolates were defined as having a clonal relationship when they shared ≥85% similarity between the fragment patterns of their DNA. Data analysis The data were analysed using Statistical Product and Service Solutions (SPSS) version 24.0 (IBM, Armonk, NY, USA). Categorical variables were analysed using the χ2 test or Fisher exact tests, as appropriate. To identify the risk factors for mortality, variables that could contribute to death and were associated with a level of significance <0.20 in univariate analyses were included in a logistic regression model for multivariate analysis using backward stepwise methods by likelihood ratio. The OR, 95% CI and P value were calculated for each factor. A two-tailed P < 0.05 indicated that a difference was statistically significant. Results Characteristics and clinical manifestations Over the 12 year investigation period, 99 non-duplicated isolates of Elizabethkingia species were collected by the clinical microbiology laboratory. Three died after the stored isolates were thawed. The distribution of Elizabethkingia species according to the year and site of isolation is shown in Figure S1. Of the 96 isolates, 67 were identified as E. anophelis, 20 were identified as E. meningoseptica, 6 were identified as E. bruuniana and 3 were unidentified species. Among the 67 E. anophelis isolates, 40 (59.7%) were isolated from blood, 8 (11.9%) were isolated from the respiratory tract and 7 (10.4%) were isolated from the tips of central venous catheters. Regarding the acquisition of infection, 10 (14.9%) were categorized as community-acquired infections and 57 (85.1%) were categorized as healthcare-associated infections (Table 1). Table 1. Demographic characteristics, clinical information and prognosis of 67 patients with E. anophelis infection Age (years)   Range  3–89   median  61   mean ± SD  62.8 ± 19.9  Sex, n (%)   male  47 (70.1)   female  20 (29.9)  Comorbidity, n (%)  57 (85.1)   diabetes mellitus  17 (25.4)   cardiovascular disease  25 (37.3)   end-stage renal disease  4 (6)   malignancy  30 (44.8)   liver cirrhosis  5 (7.5)   alcohol dependence  2 (3)   COPD  8 (11.9)   cerebrovascular disease  10 (14.9)  Site of isolation, n (%)   blood  40 (59.7)   respiratory tract  8 (11.9)   tip of central venous catheters  7 (10.4)   bile  4 (6)   urine  3 (4.5)   wound  2 (3)   ascites  2 (3)   pleural effusion  1 (1.5)  Type of infection acquisition, n (%)   community-acquired infection  10 (14.9)   healthcare-associated infection  57 (85.1)  Laboratory data   white blood cell count (cells/mm3)  13 214 ± 9488   haemoglobin (g/dL)  10.2 ± 2.1   platelet count (×1000 cells/mm3)  226 100 ± 124 277   serum creatinine (mg/dL)  1.92 ± 1.86  Shocka, n (%)  31 (46.3)  Admission to ICU, n (%)  33 (49.3)  Inappropriate empirical antimicrobial therapy, n (%)  50 (74.6)  Outcome, n (%)   survived  48 (71.6)   died  19 (28.4)  Age (years)   Range  3–89   median  61   mean ± SD  62.8 ± 19.9  Sex, n (%)   male  47 (70.1)   female  20 (29.9)  Comorbidity, n (%)  57 (85.1)   diabetes mellitus  17 (25.4)   cardiovascular disease  25 (37.3)   end-stage renal disease  4 (6)   malignancy  30 (44.8)   liver cirrhosis  5 (7.5)   alcohol dependence  2 (3)   COPD  8 (11.9)   cerebrovascular disease  10 (14.9)  Site of isolation, n (%)   blood  40 (59.7)   respiratory tract  8 (11.9)   tip of central venous catheters  7 (10.4)   bile  4 (6)   urine  3 (4.5)   wound  2 (3)   ascites  2 (3)   pleural effusion  1 (1.5)  Type of infection acquisition, n (%)   community-acquired infection  10 (14.9)   healthcare-associated infection  57 (85.1)  Laboratory data   white blood cell count (cells/mm3)  13 214 ± 9488   haemoglobin (g/dL)  10.2 ± 2.1   platelet count (×1000 cells/mm3)  226 100 ± 124 277   serum creatinine (mg/dL)  1.92 ± 1.86  Shocka, n (%)  31 (46.3)  Admission to ICU, n (%)  33 (49.3)  Inappropriate empirical antimicrobial therapy, n (%)  50 (74.6)  Outcome, n (%)   survived  48 (71.6)   died  19 (28.4)  a Shock was defined as systolic pressure of <90 mm Hg, a reduction of 40 mm Hg in the systolic blood pressure from the baseline or a condition requiring inotropic agents to maintain blood pressure during the episode of E. anophelis infection. Table 1. Demographic characteristics, clinical information and prognosis of 67 patients with E. anophelis infection Age (years)   Range  3–89   median  61   mean ± SD  62.8 ± 19.9  Sex, n (%)   male  47 (70.1)   female  20 (29.9)  Comorbidity, n (%)  57 (85.1)   diabetes mellitus  17 (25.4)   cardiovascular disease  25 (37.3)   end-stage renal disease  4 (6)   malignancy  30 (44.8)   liver cirrhosis  5 (7.5)   alcohol dependence  2 (3)   COPD  8 (11.9)   cerebrovascular disease  10 (14.9)  Site of isolation, n (%)   blood  40 (59.7)   respiratory tract  8 (11.9)   tip of central venous catheters  7 (10.4)   bile  4 (6)   urine  3 (4.5)   wound  2 (3)   ascites  2 (3)   pleural effusion  1 (1.5)  Type of infection acquisition, n (%)   community-acquired infection  10 (14.9)   healthcare-associated infection  57 (85.1)  Laboratory data   white blood cell count (cells/mm3)  13 214 ± 9488   haemoglobin (g/dL)  10.2 ± 2.1   platelet count (×1000 cells/mm3)  226 100 ± 124 277   serum creatinine (mg/dL)  1.92 ± 1.86  Shocka, n (%)  31 (46.3)  Admission to ICU, n (%)  33 (49.3)  Inappropriate empirical antimicrobial therapy, n (%)  50 (74.6)  Outcome, n (%)   survived  48 (71.6)   died  19 (28.4)  Age (years)   Range  3–89   median  61   mean ± SD  62.8 ± 19.9  Sex, n (%)   male  47 (70.1)   female  20 (29.9)  Comorbidity, n (%)  57 (85.1)   diabetes mellitus  17 (25.4)   cardiovascular disease  25 (37.3)   end-stage renal disease  4 (6)   malignancy  30 (44.8)   liver cirrhosis  5 (7.5)   alcohol dependence  2 (3)   COPD  8 (11.9)   cerebrovascular disease  10 (14.9)  Site of isolation, n (%)   blood  40 (59.7)   respiratory tract  8 (11.9)   tip of central venous catheters  7 (10.4)   bile  4 (6)   urine  3 (4.5)   wound  2 (3)   ascites  2 (3)   pleural effusion  1 (1.5)  Type of infection acquisition, n (%)   community-acquired infection  10 (14.9)   healthcare-associated infection  57 (85.1)  Laboratory data   white blood cell count (cells/mm3)  13 214 ± 9488   haemoglobin (g/dL)  10.2 ± 2.1   platelet count (×1000 cells/mm3)  226 100 ± 124 277   serum creatinine (mg/dL)  1.92 ± 1.86  Shocka, n (%)  31 (46.3)  Admission to ICU, n (%)  33 (49.3)  Inappropriate empirical antimicrobial therapy, n (%)  50 (74.6)  Outcome, n (%)   survived  48 (71.6)   died  19 (28.4)  a Shock was defined as systolic pressure of <90 mm Hg, a reduction of 40 mm Hg in the systolic blood pressure from the baseline or a condition requiring inotropic agents to maintain blood pressure during the episode of E. anophelis infection. These non-repeated 67 E. anophelis samples were isolated from 67 consecutive patients (Table 1). Of these patients, 47 (70.1%) were men and 20 (29.9%) were women, with a median age of 61 years. Comorbidity was identified in 85.1% of patients. The most prevalent underlying disease was malignancy (44.8%). Antibiotics that were empirically used included β-lactams (41.8%), β-lactam/β-lactamase inhibitors (23.9%), levofloxacin (34.3%), ciprofloxacin (13.4%), carbapenems (16.4%), aminoglycosides (9%), tigecycline (9%), vancomycin (9%) and colistin (3%), either singly or in combination. Inappropriate empirical antimicrobial therapy was identified in 74.6% of patients. The overall mortality rate of patients with E. anophelis infection was 28.4%. Factors associated with mortality Univariate analysis showed that patients who received inappropriate empirical antimicrobial therapy had a significantly higher mortality rate than did those who received appropriate empirical antibiotics (P = 0.027) (Table 2). Anaemia (haemoglobin <10 g/dL) (P = 0.018) and thrombocytopenia (platelet count <100 000 cells/mm3) (P < 0.001) were associated with a higher mortality rate. A multivariate logistic regression model revealed that inappropriate empirical antimicrobial therapy was the only independent risk factor for mortality in patients infected with E. anophelis (adjusted OR = 10.01; 95% CI = 1.20–83.76; P = 0.034). Table 2. Factors associated with mortality in patients with E. anophelis infection Factor  Died (n = 19)  Survived (n = 48)  Univariate analysis, OR (95% CI)  P  Age ≥65 years  9 (47.4)  22 (45.8)  1.06 (0.37–3.08)  0.910  Male  15 (78.9)  32 (66.7)  1.88 (0.53–6.58)  0.322  Underlying disease   diabetes mellitus  6 (31.6)  11 (22.9)  1.55 (0.48–5.05)  0.538   cardiovascular diseasea  4 (21.1)  21 (43.8)  0.34 (0.10–1.19)  0.083   end-stage renal disease  1 (5.3)  3 (6.3)  0.83 (0.08–8.55)  0.999   malignancy  10 (52.6)  20 (41.7)  1.56 (0.54–4.53)  0.416   liver cirrhosisa  3 (15.8)  2 (4.2)  4.31 (0.66–28.19)  0.134   alcohol dependence  1 (5.3)  1 (2.1)  2.61 (0.16–44.01)  0.490   COPD  4 (21.1)  4 (8.3)  2.93 (0.65–13.21)  0.209   cerebrovascular disease  2 (10.5)  8 (16.7)  0.59 (0.11–3.06)  0.712  Inappropriate empirical antimicrobial therapya  18 (94.7)  32 (66.7)  9.00 (1.10–73.58)  0.027  Laboratory test   white blood cell count ≥10 000 cells/mm3  13 (68.4)  26 (54.2)  1.83 (0.60–5.63)  0.286   haemoglobin <10 g/dL  14 (73.7)  20 (41.7)  3.92 (1.22–12.65)  0.018   platelet count <100 000 cells/mm3  8 (42.1)  2 (4.2)  16.73 (3.11–90.05)  <0.001   serum creatinine ≥1.5 mg/dL  9 (47.4)  12 (25.0)  2.70 (0.89–8.21)  0.075  Factor  Died (n = 19)  Survived (n = 48)  Univariate analysis, OR (95% CI)  P  Age ≥65 years  9 (47.4)  22 (45.8)  1.06 (0.37–3.08)  0.910  Male  15 (78.9)  32 (66.7)  1.88 (0.53–6.58)  0.322  Underlying disease   diabetes mellitus  6 (31.6)  11 (22.9)  1.55 (0.48–5.05)  0.538   cardiovascular diseasea  4 (21.1)  21 (43.8)  0.34 (0.10–1.19)  0.083   end-stage renal disease  1 (5.3)  3 (6.3)  0.83 (0.08–8.55)  0.999   malignancy  10 (52.6)  20 (41.7)  1.56 (0.54–4.53)  0.416   liver cirrhosisa  3 (15.8)  2 (4.2)  4.31 (0.66–28.19)  0.134   alcohol dependence  1 (5.3)  1 (2.1)  2.61 (0.16–44.01)  0.490   COPD  4 (21.1)  4 (8.3)  2.93 (0.65–13.21)  0.209   cerebrovascular disease  2 (10.5)  8 (16.7)  0.59 (0.11–3.06)  0.712  Inappropriate empirical antimicrobial therapya  18 (94.7)  32 (66.7)  9.00 (1.10–73.58)  0.027  Laboratory test   white blood cell count ≥10 000 cells/mm3  13 (68.4)  26 (54.2)  1.83 (0.60–5.63)  0.286   haemoglobin <10 g/dL  14 (73.7)  20 (41.7)  3.92 (1.22–12.65)  0.018   platelet count <100 000 cells/mm3  8 (42.1)  2 (4.2)  16.73 (3.11–90.05)  <0.001   serum creatinine ≥1.5 mg/dL  9 (47.4)  12 (25.0)  2.70 (0.89–8.21)  0.075  a Multivariate logistic regression for mortality: liver cirrhosis, adjusted OR = 4.95 (95% CI = 0.61–40.36; P = 0.136); cardiovascular disease, adjusted OR = 0.30 (95% CI = 0.08–1.10; P = 0.069); and inappropriate empirical antimicrobial therapy, adjusted OR = 10.01 (95% CI = 1.20–83.76; P = 0.034). Table 2. Factors associated with mortality in patients with E. anophelis infection Factor  Died (n = 19)  Survived (n = 48)  Univariate analysis, OR (95% CI)  P  Age ≥65 years  9 (47.4)  22 (45.8)  1.06 (0.37–3.08)  0.910  Male  15 (78.9)  32 (66.7)  1.88 (0.53–6.58)  0.322  Underlying disease   diabetes mellitus  6 (31.6)  11 (22.9)  1.55 (0.48–5.05)  0.538   cardiovascular diseasea  4 (21.1)  21 (43.8)  0.34 (0.10–1.19)  0.083   end-stage renal disease  1 (5.3)  3 (6.3)  0.83 (0.08–8.55)  0.999   malignancy  10 (52.6)  20 (41.7)  1.56 (0.54–4.53)  0.416   liver cirrhosisa  3 (15.8)  2 (4.2)  4.31 (0.66–28.19)  0.134   alcohol dependence  1 (5.3)  1 (2.1)  2.61 (0.16–44.01)  0.490   COPD  4 (21.1)  4 (8.3)  2.93 (0.65–13.21)  0.209   cerebrovascular disease  2 (10.5)  8 (16.7)  0.59 (0.11–3.06)  0.712  Inappropriate empirical antimicrobial therapya  18 (94.7)  32 (66.7)  9.00 (1.10–73.58)  0.027  Laboratory test   white blood cell count ≥10 000 cells/mm3  13 (68.4)  26 (54.2)  1.83 (0.60–5.63)  0.286   haemoglobin <10 g/dL  14 (73.7)  20 (41.7)  3.92 (1.22–12.65)  0.018   platelet count <100 000 cells/mm3  8 (42.1)  2 (4.2)  16.73 (3.11–90.05)  <0.001   serum creatinine ≥1.5 mg/dL  9 (47.4)  12 (25.0)  2.70 (0.89–8.21)  0.075  Factor  Died (n = 19)  Survived (n = 48)  Univariate analysis, OR (95% CI)  P  Age ≥65 years  9 (47.4)  22 (45.8)  1.06 (0.37–3.08)  0.910  Male  15 (78.9)  32 (66.7)  1.88 (0.53–6.58)  0.322  Underlying disease   diabetes mellitus  6 (31.6)  11 (22.9)  1.55 (0.48–5.05)  0.538   cardiovascular diseasea  4 (21.1)  21 (43.8)  0.34 (0.10–1.19)  0.083   end-stage renal disease  1 (5.3)  3 (6.3)  0.83 (0.08–8.55)  0.999   malignancy  10 (52.6)  20 (41.7)  1.56 (0.54–4.53)  0.416   liver cirrhosisa  3 (15.8)  2 (4.2)  4.31 (0.66–28.19)  0.134   alcohol dependence  1 (5.3)  1 (2.1)  2.61 (0.16–44.01)  0.490   COPD  4 (21.1)  4 (8.3)  2.93 (0.65–13.21)  0.209   cerebrovascular disease  2 (10.5)  8 (16.7)  0.59 (0.11–3.06)  0.712  Inappropriate empirical antimicrobial therapya  18 (94.7)  32 (66.7)  9.00 (1.10–73.58)  0.027  Laboratory test   white blood cell count ≥10 000 cells/mm3  13 (68.4)  26 (54.2)  1.83 (0.60–5.63)  0.286   haemoglobin <10 g/dL  14 (73.7)  20 (41.7)  3.92 (1.22–12.65)  0.018   platelet count <100 000 cells/mm3  8 (42.1)  2 (4.2)  16.73 (3.11–90.05)  <0.001   serum creatinine ≥1.5 mg/dL  9 (47.4)  12 (25.0)  2.70 (0.89–8.21)  0.075  a Multivariate logistic regression for mortality: liver cirrhosis, adjusted OR = 4.95 (95% CI = 0.61–40.36; P = 0.136); cardiovascular disease, adjusted OR = 0.30 (95% CI = 0.08–1.10; P = 0.069); and inappropriate empirical antimicrobial therapy, adjusted OR = 10.01 (95% CI = 1.20–83.76; P = 0.034). Antimicrobial susceptibility The MICs for and susceptibilities of E. anophelis isolates are shown in Table 3. Most isolates (98.5%) were ‘not susceptible’ to carbapenems, aminoglycosides, β-lactams or β-lactam/β-lactamase inhibitors (except piperacillin and piperacillin/tazobactam). The rates of susceptibility to the antibiotics were: piperacillin, 17.9%; piperacillin/tazobactam, 26.9%; minocycline, 100%; ciprofloxacin, 4.5%; and levofloxacin, 58.2%. Both MIC50 and MIC90 values of minocycline were low (<1 mg/L). Eleven isolates exhibited MICs of both levofloxacin and ciprofloxacin >32 mg/L. The MIC of tigecycline ranged from <1 to >8 mg/L, with MIC50 and MIC90 values of 4 and 8 mg/L, respectively. Table 3. Antimicrobial MICs for and susceptibilities of 67 E. anophelis isolates Antimicrobial agent  MICa (mg/L)   Interpretation of susceptibilityb, n (%)   lowest  highest  MIC50c  MIC90d  susceptible  intermediate  resistant  Piperacillin  <16  >64  64  >64  12 (17.9)  34 (50.7)  21 (31.3)  Piperacillin/tazobactam  <8/4  >128/4  64/4  >128/4  18 (26.9)  16 (23.9)  33 (49.3)  Ticarcillin/clavulanic acid  64/2  >64/2  >64/2  >64/2  0  3 (4.5)  64 (95.5)  Ceftazidime  >16  >16  >16  >16  0  0  67 (100)  Cefepime  8  >32  >32  >32  1 (1.5)  3 (4.5)  63 (94)  Ceftriaxone  32  >32  >32  >32  0  9 (13.4)  58 (86.6)  Aztreonam  >16  >16  >16  >16  0  0  67 (100)  Ertapenem  8  >8  >8  >8  —  —  —  Imipenem  >8  >8  >8  >8  0  0  67 (100)  Meropenem  >8  >8  >8  >8  0  0  67 (100)  Doripenem  >4  >4  >4  >4  —  —  —  Gentamicin  8  >8  >8  >8  0  2 (3)  65 (97)  Tobramycin  >8  >8  >8  >8  0  0  67 (100)  Amikacin  16  >32  >32  >32  1 (1.5)  12 (17.9)  54 (80.6)  Tetracycline  >8  >8  >8  >8  0  0  67 (100)  Minocycline  <1  4  <1  <1  67 (100)  0  0  Tigecyclinee  <1  >8  4  8  —  —  —  Ciprofloxacin  <1  >32  2  >32  3 (4.5)  34 (50.7)  30 (44.8)  Levofloxacin  <1  >32  2  >32  39 (58.2)  12 (17.9)  16 (23.9)  Trimethoprim/sulfamethoxazole  <2/38  >4/76  >4/76  >4/76  9 (13.4)  —  58 (86.6)  Vancomycin  8  64  16  32  —  —  —  Antimicrobial agent  MICa (mg/L)   Interpretation of susceptibilityb, n (%)   lowest  highest  MIC50c  MIC90d  susceptible  intermediate  resistant  Piperacillin  <16  >64  64  >64  12 (17.9)  34 (50.7)  21 (31.3)  Piperacillin/tazobactam  <8/4  >128/4  64/4  >128/4  18 (26.9)  16 (23.9)  33 (49.3)  Ticarcillin/clavulanic acid  64/2  >64/2  >64/2  >64/2  0  3 (4.5)  64 (95.5)  Ceftazidime  >16  >16  >16  >16  0  0  67 (100)  Cefepime  8  >32  >32  >32  1 (1.5)  3 (4.5)  63 (94)  Ceftriaxone  32  >32  >32  >32  0  9 (13.4)  58 (86.6)  Aztreonam  >16  >16  >16  >16  0  0  67 (100)  Ertapenem  8  >8  >8  >8  —  —  —  Imipenem  >8  >8  >8  >8  0  0  67 (100)  Meropenem  >8  >8  >8  >8  0  0  67 (100)  Doripenem  >4  >4  >4  >4  —  —  —  Gentamicin  8  >8  >8  >8  0  2 (3)  65 (97)  Tobramycin  >8  >8  >8  >8  0  0  67 (100)  Amikacin  16  >32  >32  >32  1 (1.5)  12 (17.9)  54 (80.6)  Tetracycline  >8  >8  >8  >8  0  0  67 (100)  Minocycline  <1  4  <1  <1  67 (100)  0  0  Tigecyclinee  <1  >8  4  8  —  —  —  Ciprofloxacin  <1  >32  2  >32  3 (4.5)  34 (50.7)  30 (44.8)  Levofloxacin  <1  >32  2  >32  39 (58.2)  12 (17.9)  16 (23.9)  Trimethoprim/sulfamethoxazole  <2/38  >4/76  >4/76  >4/76  9 (13.4)  —  58 (86.6)  Vancomycin  8  64  16  32  —  —  —  a The MICs were determined using 96-well broth microdilution panels. b Interpretations according to the interpretive standards for ‘other non-Enterobacteriaceae’ from the CLSI guidelines. c MIC at which 50% of the isolates tested are inhibited. d MIC at which 90% of the isolates tested are inhibited. e The MICs of tigecycline: <1, n = 3 (4.5%); 2, n = 12 (17.9%); 4, n = 27 (40.3%); 8, n = 18 (26.9%); and >8, n = 7 (10.4%). Table 3. Antimicrobial MICs for and susceptibilities of 67 E. anophelis isolates Antimicrobial agent  MICa (mg/L)   Interpretation of susceptibilityb, n (%)   lowest  highest  MIC50c  MIC90d  susceptible  intermediate  resistant  Piperacillin  <16  >64  64  >64  12 (17.9)  34 (50.7)  21 (31.3)  Piperacillin/tazobactam  <8/4  >128/4  64/4  >128/4  18 (26.9)  16 (23.9)  33 (49.3)  Ticarcillin/clavulanic acid  64/2  >64/2  >64/2  >64/2  0  3 (4.5)  64 (95.5)  Ceftazidime  >16  >16  >16  >16  0  0  67 (100)  Cefepime  8  >32  >32  >32  1 (1.5)  3 (4.5)  63 (94)  Ceftriaxone  32  >32  >32  >32  0  9 (13.4)  58 (86.6)  Aztreonam  >16  >16  >16  >16  0  0  67 (100)  Ertapenem  8  >8  >8  >8  —  —  —  Imipenem  >8  >8  >8  >8  0  0  67 (100)  Meropenem  >8  >8  >8  >8  0  0  67 (100)  Doripenem  >4  >4  >4  >4  —  —  —  Gentamicin  8  >8  >8  >8  0  2 (3)  65 (97)  Tobramycin  >8  >8  >8  >8  0  0  67 (100)  Amikacin  16  >32  >32  >32  1 (1.5)  12 (17.9)  54 (80.6)  Tetracycline  >8  >8  >8  >8  0  0  67 (100)  Minocycline  <1  4  <1  <1  67 (100)  0  0  Tigecyclinee  <1  >8  4  8  —  —  —  Ciprofloxacin  <1  >32  2  >32  3 (4.5)  34 (50.7)  30 (44.8)  Levofloxacin  <1  >32  2  >32  39 (58.2)  12 (17.9)  16 (23.9)  Trimethoprim/sulfamethoxazole  <2/38  >4/76  >4/76  >4/76  9 (13.4)  —  58 (86.6)  Vancomycin  8  64  16  32  —  —  —  Antimicrobial agent  MICa (mg/L)   Interpretation of susceptibilityb, n (%)   lowest  highest  MIC50c  MIC90d  susceptible  intermediate  resistant  Piperacillin  <16  >64  64  >64  12 (17.9)  34 (50.7)  21 (31.3)  Piperacillin/tazobactam  <8/4  >128/4  64/4  >128/4  18 (26.9)  16 (23.9)  33 (49.3)  Ticarcillin/clavulanic acid  64/2  >64/2  >64/2  >64/2  0  3 (4.5)  64 (95.5)  Ceftazidime  >16  >16  >16  >16  0  0  67 (100)  Cefepime  8  >32  >32  >32  1 (1.5)  3 (4.5)  63 (94)  Ceftriaxone  32  >32  >32  >32  0  9 (13.4)  58 (86.6)  Aztreonam  >16  >16  >16  >16  0  0  67 (100)  Ertapenem  8  >8  >8  >8  —  —  —  Imipenem  >8  >8  >8  >8  0  0  67 (100)  Meropenem  >8  >8  >8  >8  0  0  67 (100)  Doripenem  >4  >4  >4  >4  —  —  —  Gentamicin  8  >8  >8  >8  0  2 (3)  65 (97)  Tobramycin  >8  >8  >8  >8  0  0  67 (100)  Amikacin  16  >32  >32  >32  1 (1.5)  12 (17.9)  54 (80.6)  Tetracycline  >8  >8  >8  >8  0  0  67 (100)  Minocycline  <1  4  <1  <1  67 (100)  0  0  Tigecyclinee  <1  >8  4  8  —  —  —  Ciprofloxacin  <1  >32  2  >32  3 (4.5)  34 (50.7)  30 (44.8)  Levofloxacin  <1  >32  2  >32  39 (58.2)  12 (17.9)  16 (23.9)  Trimethoprim/sulfamethoxazole  <2/38  >4/76  >4/76  >4/76  9 (13.4)  —  58 (86.6)  Vancomycin  8  64  16  32  —  —  —  a The MICs were determined using 96-well broth microdilution panels. b Interpretations according to the interpretive standards for ‘other non-Enterobacteriaceae’ from the CLSI guidelines. c MIC at which 50% of the isolates tested are inhibited. d MIC at which 90% of the isolates tested are inhibited. e The MICs of tigecycline: <1, n = 3 (4.5%); 2, n = 12 (17.9%); 4, n = 27 (40.3%); 8, n = 18 (26.9%); and >8, n = 7 (10.4%). Mutations in the QRDRs Replacements of serine by isoleucine (Ser83Ile; AGC→ATC) and arginine (Ser83Arg; AGC→AGA) at position 83 in the QRDR of GyrA were identified in eight and three isolates, respectively. All of these 11 isolates exhibited levofloxacin and ciprofloxacin resistance (both MICs >32 mg/L). No non-synonymous substitutions were observed in the QRDRs of GyrB, ParC or ParE in any isolate. PFGE The PFGE dendrogram is shown in Figure S2. One isolate was resistant to XbaI digestion. Of the 10 isolates obtained from patients with community-acquired infection, 3 fell within cluster 1 and 3 gathered in cluster 10. The ciprofloxacin-resistant isolates appeared to be diverse pulsed-field types. The levofloxacin-resistant isolates with gyrA mutations distributed into six clusters. No clear epidemiological linkage among cases could be identified in terms of their infection sites, sources of isolation, times of presentation and locations of patient residences. Discussion Most patients with E. anophelis infection were reported to suffer comorbidities, such as malignancy, diabetes mellitus, chronic renal disease, liver cirrhosis and alcohol dependence.10–14 Our study also revealed that 85.1% of patients had at least one underlying disease. The mortality rate of patients with E. anophelis infections ranged from 23.5% to 34.2%.10–14 In this study, the case-fatality rate of E. anophelis infection was 28.4% and inappropriate empirical antimicrobial therapy was an independent risk factor for mortality. These findings suggest that appropriate antimicrobial therapy is of paramount importance in the successful treatment of this MDR pathogen infection. Information about the susceptibilities of E. anophelis to antimicrobial agents is limited. E. anophelis strain NUHP1 was isolated in Singapore and exhibited resistance to ceftazidime, gentamicin, amikacin, ciprofloxacin and imipenem, but was susceptible to piperacillin, piperacillin/tazobactam and levofloxacin.12,18 Studies from the USA,11–14 Hong Kong10 and South Korea26 demonstrated that E. anophelis was usually resistant to most carbapenems, β-lactams and β-lactam/β-lactamase inhibitors. Our study also showed an extremely high rate of resistance to carbapenems, β-lactams and β-lactam/β-lactamase inhibitors. However, previous studies showed a wide range of E. anophelis susceptibility rates to piperacillin and piperacillin/tazobactam. Perrin et al.12 examined 25 Wisconsin outbreak strains caused by a common recent ancestor; all the strains were susceptible to piperacillin and two were resistant to piperacillin/tazobactam. Han et al.26 analysed 19 isolates of E. anophelis in South Korea and found that 83% and 94% were susceptible to piperacillin and piperacillin/tazobactam, respectively. Nevertheless, our study showed a piperacillin susceptibility of 17.9% and a piperacillin/tazobactam susceptibility of 26.9%. All the E. anophelis isolates in our study were susceptible to minocycline. Eight isolates from Wisconsin residents also showed a low MIC of minocycline (MIC range = 0.25–1 mg/L).13 Unfortunately, no other study has examined the effect of minocycline on E. anophelis in the literature. The isolates in this study showed a relatively high MIC of tigecycline (MIC50 = 4 mg/L; MIC90 = 8 mg/L). Only 15 isolates in this study exhibited a tigecycline MIC ≤2 mg/L. The 25 isolates from the Wisconsin outbreak showed a large zone of tigecycline inhibition (≥20 mm) in the disc diffusion assay.12 However, neither CLSI25 nor EUCAST27 provide interpretive criteria to assess E. anophelis susceptibility to tigecycline. Lau et al.10 examined 17 isolates in Hong Kong and they all were susceptible to ciprofloxacin. Perrin et al.12 evaluated 25 isolates from the Wisconsin outbreak and the rates of susceptibility to ciprofloxacin and levofloxacin were 92% and 96%, respectively. In contrast, Han et al.26 reported 29% susceptibility to levofloxacin and 22% susceptibility to ciprofloxacin in South Korea. In our study, E. anophelis susceptibility to ciprofloxacin and levofloxacin was 4.5% and 58.2%, respectively. In this study, we screened mutations in the QRDRs of gyrA, gyrB, parC and parE in all the identified E. anophelis isolates. No non-synonymous substitutions were detected in GyrB, ParC or ParE. However, we identified eight isolates with a Ser83Ile mutation and three isolates with a Ser83Arg alteration in the QRDR of GyrA. These 11 gyrA-mutant isolates were the 11 isolates that displayed high-level resistance to ciprofloxacin and levofloxacin. These findings suggest that mutations in the QRDR of gyrA confer high-level fluoroquinolone resistance in E. anophelis. Conclusions Our study shows that E. anophelis is an MDR microorganism and that inappropriate empirical antimicrobial therapy is an independent risk factor for mortality in patients with E. anophelis infections. Minocycline has the potential to be the drug of choice for patients with E. anophelis infections. Because of the wide range in susceptibilities, treatment of E. anophelis using piperacillin, piperacillin/tazobactam and fluoroquinolones should be guided by antimicrobial susceptibility testing. Additional investigations are needed to determine the optimal antimicrobial agents to treat this life-threatening infection. Funding This work was supported by grants EDPJ106075 from E-Da Hospital and MOST 106–2314-B-214–009-MY2 from the Ministry of Science and Technology, Taiwan. Transparency declarations None to declare. Supplementary data Table S1 and Figures S1 and S2 are available as Supplementary data at JAC Online. References 1 Henriques IS, Araújo S, Azevedo JS et al.   Prevalence and diversity of carbapenem-resistant bacteria in untreated drinking water in Portugal. Microb Drug Resist  2012; 18: 531– 7. Google Scholar CrossRef Search ADS PubMed  2 Jean SS, Lee WS, Chen FL et al.   Elizabethkingia meningoseptica: an important emerging pathogen causing healthcare-associated infections. J Hosp Infect  2014; 86: 244– 9. Google Scholar CrossRef Search ADS PubMed  3 da Silva PS, Pereira GH. 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Clinical Breakpoints. 2018. http://www.eucast.org/clinical_breakpoints/. © The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Antimicrobial Chemotherapy Oxford University Press

Clinical manifestations, molecular characteristics, antimicrobial susceptibility patterns and contributions of target gene mutation to fluoroquinolone resistance in Elizabethkingia anophelis

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com.
ISSN
0305-7453
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1460-2091
D.O.I.
10.1093/jac/dky197
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Abstract

Abstract Objectives Elizabethkingia anophelis has recently emerged as a cause of life-threatening infections in humans. We aimed to investigate the clinical and molecular characteristics of E. anophelis. Methods A clinical microbiology laboratory database was searched to identify patients with Elizabethkingia infections between 2005 and 2016. Isolates were re-identified and their species were confirmed using 16S rRNA gene sequencing. Patients with E. anophelis infections were included in this study. Clinical information, antimicrobial susceptibility and mutations in DNA gyrase and topoisomerase IV were analysed. Results A total of 67 patients were identified to have E. anophelis infections, including 47 men and 20 women, with a median age of 61 years. Comorbidity was identified in 85.1% of the patients. Among the 67 E. anophelis isolates, 40 (59.7%) were isolated from blood. The case fatality rate was 28.4%. Inappropriate empirical antimicrobial therapy was an independent risk factor for mortality (adjusted OR = 10.01; 95% CI = 1.20–83.76; P = 0.034). The isolates were ‘not susceptible’ to multiple antibiotics. All the isolates were susceptible to minocycline. Susceptibilities to ciprofloxacin and levofloxacin were 4.5% and 58.2%, respectively. Mutations in DNA gyrase subunit A were identified in 11 isolates that exhibited high-level fluoroquinolone resistance. Conclusions Minocycline has the potential to be the drug of choice in patients with E. anophelis infections. Additional investigations are needed to determine the optimal antimicrobial agents to treat this life-threatening infection. Introduction Elizabethkingia is a genus of aerobic, non-fermenting, non-motile, catalase-positive, oxidase-positive, indole-positive and Gram-negative bacilli that are distributed in the natural environments of soil and water.1–3 Since its first isolation in 1959 by Elizabeth O. King,4,Elizabethkingia has been sporadically reported to cause human infections.1–5 In addition to the previously known Elizabethkingia meningoseptica, Elizabethkingia miricola and Elizabethkingia anophelis,6 three novel species, namely, Elizabethkingia bruuniana, Elizabethkingia ursingii and Elizabethkingia occulta, were proposed to be new members of the Elizabethkingia genus recently.7 Among these species, E. anophelis has emerged recently as a cause of life-threatening infection in humans, particularly in immunocompromised patients.8–14 Several outbreaks of E. anophelis infections have been reported in Africa,8 Singapore,9 Hong Kong10 and the USA.11–14 Elizabethkingia species are often resistant to multiple antibiotics but are variably susceptible to fluoroquinolones.15,16 The major mechanisms for fluoroquinolone resistance include gene alterations in the QRDRs of DNA gyrase (GyrA and GyrB) and topoisomerase IV (ParC and ParE), reduced drug accumulation by decreased entry or increased efflux, and plasmid-mediated quinolone resistance protein Qnr.17 However, information concerning the mechanisms of fluoroquinolone resistance in E. anophelis is limited.12,18–21 Despite being increasingly recognized as an emerging infectious agent, few data describe the clinical manifestations, antimicrobial susceptibility and mechanisms of antimicrobial resistance in E. anophelis. In this study, we report the clinical and molecular characteristics of E. anophelis infections in humans. We also examine antimicrobial susceptibility and investigate the contributions of mutations in the QRDRs to fluoroquinolone resistance in clinical isolates of E. anophelis. Materials and methods Ethics This study was conducted in accordance with the Declaration of Helsinki and national and institutional standards. This study was approved by the Institutional Review Board of E-Da Hospital (EMRP-106-105). The need for patient informed consent was waived by the Institutional Review Board because the retrospective analysis of routine blood cultures posed no more than minimal risk of harm to the subjects. Study setting and study design This study was performed at a 1000 bed university-affiliated medical centre in Taiwan. The clinical laboratory database was searched for microbial cultures that contained Elizabethkingia species from January 2005 to December 2016. These isolates were routinely collected from patients according to clinical requirements and then stored as glycerol stocks at −80°C. The Elizabethkingia species were re-identified using 16S rRNA gene sequencing. Clinical conditions (such as shock) were recorded during the episode of E. anophelis infection. Laboratory data were collected within three days surrounding the time of Elizabethkingia isolation. Empirical antimicrobial therapy was considered inappropriate when the isolate was not susceptible to the treatment agents. 16S rRNA gene sequencing Total DNA from each isolate was prepared using a Wizard Genomic DNA Purification Kit (Promega, Madison, WI, USA). PCR was performed using a GeneAmp PCR System 9700 (Applied Biosystems, Foster City, CA, USA) and the amplicons were sequenced using an Applied Biosystems 3730xl DNA Analyzer. The primers used to amplify internal fragments of the 16S rRNA gene and for sequencing are listed in Table S1 (available as Supplementary data at JAC Online).22,23 The assembled sequences were compared with the 16S rRNA sequences of each type strain: E. meningoseptica KC1913T, E. miricola G4074T, E. anophelis R26T, E. bruuniana G0146T, E. ursingii G4122T and E. occulta G4070T. The species was considered identified if the isolate possessed >99.5% 16S rRNA sequence identity to the type strain.24 Antimicrobial susceptibility testing The MICs of antibiotics were determined using Sensititre 96-well broth microdilution panels (Thermo Fisher Scientific/Trek Diagnostics Systems, Oakwood Village, OH, USA). The susceptibilities were evaluated according to the interpretive standards for ‘other non-Enterobacteriaceae’ from the CLSI guidelines.25 Identification of mutations in the QRDRs The primers and PCR conditions for the amplification of QRDRs in gyrA, gyrB, parC and parE are listed in Table S1. The sequences were aligned with the sequences of E. anophelis strain NUHP1 (GenBank accession number = CP007547).18 PFGE All the isolates were digested by XbaI and subjected to PFGE according to a previously described protocol.10 The digested DNA fragments were separated by a Contour-clamped Homogeneous Electric Field Mapper XA Chiller system (Bio-Rad, Hercules, CA, USA). A dendrogram was constructed using the unweighted pair-group method with the arithmetic mean algorithm by GelCompar II software (version 6; Applied Maths, Sint-Martens-Latem, Belgium). The isolates were defined as having a clonal relationship when they shared ≥85% similarity between the fragment patterns of their DNA. Data analysis The data were analysed using Statistical Product and Service Solutions (SPSS) version 24.0 (IBM, Armonk, NY, USA). Categorical variables were analysed using the χ2 test or Fisher exact tests, as appropriate. To identify the risk factors for mortality, variables that could contribute to death and were associated with a level of significance <0.20 in univariate analyses were included in a logistic regression model for multivariate analysis using backward stepwise methods by likelihood ratio. The OR, 95% CI and P value were calculated for each factor. A two-tailed P < 0.05 indicated that a difference was statistically significant. Results Characteristics and clinical manifestations Over the 12 year investigation period, 99 non-duplicated isolates of Elizabethkingia species were collected by the clinical microbiology laboratory. Three died after the stored isolates were thawed. The distribution of Elizabethkingia species according to the year and site of isolation is shown in Figure S1. Of the 96 isolates, 67 were identified as E. anophelis, 20 were identified as E. meningoseptica, 6 were identified as E. bruuniana and 3 were unidentified species. Among the 67 E. anophelis isolates, 40 (59.7%) were isolated from blood, 8 (11.9%) were isolated from the respiratory tract and 7 (10.4%) were isolated from the tips of central venous catheters. Regarding the acquisition of infection, 10 (14.9%) were categorized as community-acquired infections and 57 (85.1%) were categorized as healthcare-associated infections (Table 1). Table 1. Demographic characteristics, clinical information and prognosis of 67 patients with E. anophelis infection Age (years)   Range  3–89   median  61   mean ± SD  62.8 ± 19.9  Sex, n (%)   male  47 (70.1)   female  20 (29.9)  Comorbidity, n (%)  57 (85.1)   diabetes mellitus  17 (25.4)   cardiovascular disease  25 (37.3)   end-stage renal disease  4 (6)   malignancy  30 (44.8)   liver cirrhosis  5 (7.5)   alcohol dependence  2 (3)   COPD  8 (11.9)   cerebrovascular disease  10 (14.9)  Site of isolation, n (%)   blood  40 (59.7)   respiratory tract  8 (11.9)   tip of central venous catheters  7 (10.4)   bile  4 (6)   urine  3 (4.5)   wound  2 (3)   ascites  2 (3)   pleural effusion  1 (1.5)  Type of infection acquisition, n (%)   community-acquired infection  10 (14.9)   healthcare-associated infection  57 (85.1)  Laboratory data   white blood cell count (cells/mm3)  13 214 ± 9488   haemoglobin (g/dL)  10.2 ± 2.1   platelet count (×1000 cells/mm3)  226 100 ± 124 277   serum creatinine (mg/dL)  1.92 ± 1.86  Shocka, n (%)  31 (46.3)  Admission to ICU, n (%)  33 (49.3)  Inappropriate empirical antimicrobial therapy, n (%)  50 (74.6)  Outcome, n (%)   survived  48 (71.6)   died  19 (28.4)  Age (years)   Range  3–89   median  61   mean ± SD  62.8 ± 19.9  Sex, n (%)   male  47 (70.1)   female  20 (29.9)  Comorbidity, n (%)  57 (85.1)   diabetes mellitus  17 (25.4)   cardiovascular disease  25 (37.3)   end-stage renal disease  4 (6)   malignancy  30 (44.8)   liver cirrhosis  5 (7.5)   alcohol dependence  2 (3)   COPD  8 (11.9)   cerebrovascular disease  10 (14.9)  Site of isolation, n (%)   blood  40 (59.7)   respiratory tract  8 (11.9)   tip of central venous catheters  7 (10.4)   bile  4 (6)   urine  3 (4.5)   wound  2 (3)   ascites  2 (3)   pleural effusion  1 (1.5)  Type of infection acquisition, n (%)   community-acquired infection  10 (14.9)   healthcare-associated infection  57 (85.1)  Laboratory data   white blood cell count (cells/mm3)  13 214 ± 9488   haemoglobin (g/dL)  10.2 ± 2.1   platelet count (×1000 cells/mm3)  226 100 ± 124 277   serum creatinine (mg/dL)  1.92 ± 1.86  Shocka, n (%)  31 (46.3)  Admission to ICU, n (%)  33 (49.3)  Inappropriate empirical antimicrobial therapy, n (%)  50 (74.6)  Outcome, n (%)   survived  48 (71.6)   died  19 (28.4)  a Shock was defined as systolic pressure of <90 mm Hg, a reduction of 40 mm Hg in the systolic blood pressure from the baseline or a condition requiring inotropic agents to maintain blood pressure during the episode of E. anophelis infection. Table 1. Demographic characteristics, clinical information and prognosis of 67 patients with E. anophelis infection Age (years)   Range  3–89   median  61   mean ± SD  62.8 ± 19.9  Sex, n (%)   male  47 (70.1)   female  20 (29.9)  Comorbidity, n (%)  57 (85.1)   diabetes mellitus  17 (25.4)   cardiovascular disease  25 (37.3)   end-stage renal disease  4 (6)   malignancy  30 (44.8)   liver cirrhosis  5 (7.5)   alcohol dependence  2 (3)   COPD  8 (11.9)   cerebrovascular disease  10 (14.9)  Site of isolation, n (%)   blood  40 (59.7)   respiratory tract  8 (11.9)   tip of central venous catheters  7 (10.4)   bile  4 (6)   urine  3 (4.5)   wound  2 (3)   ascites  2 (3)   pleural effusion  1 (1.5)  Type of infection acquisition, n (%)   community-acquired infection  10 (14.9)   healthcare-associated infection  57 (85.1)  Laboratory data   white blood cell count (cells/mm3)  13 214 ± 9488   haemoglobin (g/dL)  10.2 ± 2.1   platelet count (×1000 cells/mm3)  226 100 ± 124 277   serum creatinine (mg/dL)  1.92 ± 1.86  Shocka, n (%)  31 (46.3)  Admission to ICU, n (%)  33 (49.3)  Inappropriate empirical antimicrobial therapy, n (%)  50 (74.6)  Outcome, n (%)   survived  48 (71.6)   died  19 (28.4)  Age (years)   Range  3–89   median  61   mean ± SD  62.8 ± 19.9  Sex, n (%)   male  47 (70.1)   female  20 (29.9)  Comorbidity, n (%)  57 (85.1)   diabetes mellitus  17 (25.4)   cardiovascular disease  25 (37.3)   end-stage renal disease  4 (6)   malignancy  30 (44.8)   liver cirrhosis  5 (7.5)   alcohol dependence  2 (3)   COPD  8 (11.9)   cerebrovascular disease  10 (14.9)  Site of isolation, n (%)   blood  40 (59.7)   respiratory tract  8 (11.9)   tip of central venous catheters  7 (10.4)   bile  4 (6)   urine  3 (4.5)   wound  2 (3)   ascites  2 (3)   pleural effusion  1 (1.5)  Type of infection acquisition, n (%)   community-acquired infection  10 (14.9)   healthcare-associated infection  57 (85.1)  Laboratory data   white blood cell count (cells/mm3)  13 214 ± 9488   haemoglobin (g/dL)  10.2 ± 2.1   platelet count (×1000 cells/mm3)  226 100 ± 124 277   serum creatinine (mg/dL)  1.92 ± 1.86  Shocka, n (%)  31 (46.3)  Admission to ICU, n (%)  33 (49.3)  Inappropriate empirical antimicrobial therapy, n (%)  50 (74.6)  Outcome, n (%)   survived  48 (71.6)   died  19 (28.4)  a Shock was defined as systolic pressure of <90 mm Hg, a reduction of 40 mm Hg in the systolic blood pressure from the baseline or a condition requiring inotropic agents to maintain blood pressure during the episode of E. anophelis infection. These non-repeated 67 E. anophelis samples were isolated from 67 consecutive patients (Table 1). Of these patients, 47 (70.1%) were men and 20 (29.9%) were women, with a median age of 61 years. Comorbidity was identified in 85.1% of patients. The most prevalent underlying disease was malignancy (44.8%). Antibiotics that were empirically used included β-lactams (41.8%), β-lactam/β-lactamase inhibitors (23.9%), levofloxacin (34.3%), ciprofloxacin (13.4%), carbapenems (16.4%), aminoglycosides (9%), tigecycline (9%), vancomycin (9%) and colistin (3%), either singly or in combination. Inappropriate empirical antimicrobial therapy was identified in 74.6% of patients. The overall mortality rate of patients with E. anophelis infection was 28.4%. Factors associated with mortality Univariate analysis showed that patients who received inappropriate empirical antimicrobial therapy had a significantly higher mortality rate than did those who received appropriate empirical antibiotics (P = 0.027) (Table 2). Anaemia (haemoglobin <10 g/dL) (P = 0.018) and thrombocytopenia (platelet count <100 000 cells/mm3) (P < 0.001) were associated with a higher mortality rate. A multivariate logistic regression model revealed that inappropriate empirical antimicrobial therapy was the only independent risk factor for mortality in patients infected with E. anophelis (adjusted OR = 10.01; 95% CI = 1.20–83.76; P = 0.034). Table 2. Factors associated with mortality in patients with E. anophelis infection Factor  Died (n = 19)  Survived (n = 48)  Univariate analysis, OR (95% CI)  P  Age ≥65 years  9 (47.4)  22 (45.8)  1.06 (0.37–3.08)  0.910  Male  15 (78.9)  32 (66.7)  1.88 (0.53–6.58)  0.322  Underlying disease   diabetes mellitus  6 (31.6)  11 (22.9)  1.55 (0.48–5.05)  0.538   cardiovascular diseasea  4 (21.1)  21 (43.8)  0.34 (0.10–1.19)  0.083   end-stage renal disease  1 (5.3)  3 (6.3)  0.83 (0.08–8.55)  0.999   malignancy  10 (52.6)  20 (41.7)  1.56 (0.54–4.53)  0.416   liver cirrhosisa  3 (15.8)  2 (4.2)  4.31 (0.66–28.19)  0.134   alcohol dependence  1 (5.3)  1 (2.1)  2.61 (0.16–44.01)  0.490   COPD  4 (21.1)  4 (8.3)  2.93 (0.65–13.21)  0.209   cerebrovascular disease  2 (10.5)  8 (16.7)  0.59 (0.11–3.06)  0.712  Inappropriate empirical antimicrobial therapya  18 (94.7)  32 (66.7)  9.00 (1.10–73.58)  0.027  Laboratory test   white blood cell count ≥10 000 cells/mm3  13 (68.4)  26 (54.2)  1.83 (0.60–5.63)  0.286   haemoglobin <10 g/dL  14 (73.7)  20 (41.7)  3.92 (1.22–12.65)  0.018   platelet count <100 000 cells/mm3  8 (42.1)  2 (4.2)  16.73 (3.11–90.05)  <0.001   serum creatinine ≥1.5 mg/dL  9 (47.4)  12 (25.0)  2.70 (0.89–8.21)  0.075  Factor  Died (n = 19)  Survived (n = 48)  Univariate analysis, OR (95% CI)  P  Age ≥65 years  9 (47.4)  22 (45.8)  1.06 (0.37–3.08)  0.910  Male  15 (78.9)  32 (66.7)  1.88 (0.53–6.58)  0.322  Underlying disease   diabetes mellitus  6 (31.6)  11 (22.9)  1.55 (0.48–5.05)  0.538   cardiovascular diseasea  4 (21.1)  21 (43.8)  0.34 (0.10–1.19)  0.083   end-stage renal disease  1 (5.3)  3 (6.3)  0.83 (0.08–8.55)  0.999   malignancy  10 (52.6)  20 (41.7)  1.56 (0.54–4.53)  0.416   liver cirrhosisa  3 (15.8)  2 (4.2)  4.31 (0.66–28.19)  0.134   alcohol dependence  1 (5.3)  1 (2.1)  2.61 (0.16–44.01)  0.490   COPD  4 (21.1)  4 (8.3)  2.93 (0.65–13.21)  0.209   cerebrovascular disease  2 (10.5)  8 (16.7)  0.59 (0.11–3.06)  0.712  Inappropriate empirical antimicrobial therapya  18 (94.7)  32 (66.7)  9.00 (1.10–73.58)  0.027  Laboratory test   white blood cell count ≥10 000 cells/mm3  13 (68.4)  26 (54.2)  1.83 (0.60–5.63)  0.286   haemoglobin <10 g/dL  14 (73.7)  20 (41.7)  3.92 (1.22–12.65)  0.018   platelet count <100 000 cells/mm3  8 (42.1)  2 (4.2)  16.73 (3.11–90.05)  <0.001   serum creatinine ≥1.5 mg/dL  9 (47.4)  12 (25.0)  2.70 (0.89–8.21)  0.075  a Multivariate logistic regression for mortality: liver cirrhosis, adjusted OR = 4.95 (95% CI = 0.61–40.36; P = 0.136); cardiovascular disease, adjusted OR = 0.30 (95% CI = 0.08–1.10; P = 0.069); and inappropriate empirical antimicrobial therapy, adjusted OR = 10.01 (95% CI = 1.20–83.76; P = 0.034). Table 2. Factors associated with mortality in patients with E. anophelis infection Factor  Died (n = 19)  Survived (n = 48)  Univariate analysis, OR (95% CI)  P  Age ≥65 years  9 (47.4)  22 (45.8)  1.06 (0.37–3.08)  0.910  Male  15 (78.9)  32 (66.7)  1.88 (0.53–6.58)  0.322  Underlying disease   diabetes mellitus  6 (31.6)  11 (22.9)  1.55 (0.48–5.05)  0.538   cardiovascular diseasea  4 (21.1)  21 (43.8)  0.34 (0.10–1.19)  0.083   end-stage renal disease  1 (5.3)  3 (6.3)  0.83 (0.08–8.55)  0.999   malignancy  10 (52.6)  20 (41.7)  1.56 (0.54–4.53)  0.416   liver cirrhosisa  3 (15.8)  2 (4.2)  4.31 (0.66–28.19)  0.134   alcohol dependence  1 (5.3)  1 (2.1)  2.61 (0.16–44.01)  0.490   COPD  4 (21.1)  4 (8.3)  2.93 (0.65–13.21)  0.209   cerebrovascular disease  2 (10.5)  8 (16.7)  0.59 (0.11–3.06)  0.712  Inappropriate empirical antimicrobial therapya  18 (94.7)  32 (66.7)  9.00 (1.10–73.58)  0.027  Laboratory test   white blood cell count ≥10 000 cells/mm3  13 (68.4)  26 (54.2)  1.83 (0.60–5.63)  0.286   haemoglobin <10 g/dL  14 (73.7)  20 (41.7)  3.92 (1.22–12.65)  0.018   platelet count <100 000 cells/mm3  8 (42.1)  2 (4.2)  16.73 (3.11–90.05)  <0.001   serum creatinine ≥1.5 mg/dL  9 (47.4)  12 (25.0)  2.70 (0.89–8.21)  0.075  Factor  Died (n = 19)  Survived (n = 48)  Univariate analysis, OR (95% CI)  P  Age ≥65 years  9 (47.4)  22 (45.8)  1.06 (0.37–3.08)  0.910  Male  15 (78.9)  32 (66.7)  1.88 (0.53–6.58)  0.322  Underlying disease   diabetes mellitus  6 (31.6)  11 (22.9)  1.55 (0.48–5.05)  0.538   cardiovascular diseasea  4 (21.1)  21 (43.8)  0.34 (0.10–1.19)  0.083   end-stage renal disease  1 (5.3)  3 (6.3)  0.83 (0.08–8.55)  0.999   malignancy  10 (52.6)  20 (41.7)  1.56 (0.54–4.53)  0.416   liver cirrhosisa  3 (15.8)  2 (4.2)  4.31 (0.66–28.19)  0.134   alcohol dependence  1 (5.3)  1 (2.1)  2.61 (0.16–44.01)  0.490   COPD  4 (21.1)  4 (8.3)  2.93 (0.65–13.21)  0.209   cerebrovascular disease  2 (10.5)  8 (16.7)  0.59 (0.11–3.06)  0.712  Inappropriate empirical antimicrobial therapya  18 (94.7)  32 (66.7)  9.00 (1.10–73.58)  0.027  Laboratory test   white blood cell count ≥10 000 cells/mm3  13 (68.4)  26 (54.2)  1.83 (0.60–5.63)  0.286   haemoglobin <10 g/dL  14 (73.7)  20 (41.7)  3.92 (1.22–12.65)  0.018   platelet count <100 000 cells/mm3  8 (42.1)  2 (4.2)  16.73 (3.11–90.05)  <0.001   serum creatinine ≥1.5 mg/dL  9 (47.4)  12 (25.0)  2.70 (0.89–8.21)  0.075  a Multivariate logistic regression for mortality: liver cirrhosis, adjusted OR = 4.95 (95% CI = 0.61–40.36; P = 0.136); cardiovascular disease, adjusted OR = 0.30 (95% CI = 0.08–1.10; P = 0.069); and inappropriate empirical antimicrobial therapy, adjusted OR = 10.01 (95% CI = 1.20–83.76; P = 0.034). Antimicrobial susceptibility The MICs for and susceptibilities of E. anophelis isolates are shown in Table 3. Most isolates (98.5%) were ‘not susceptible’ to carbapenems, aminoglycosides, β-lactams or β-lactam/β-lactamase inhibitors (except piperacillin and piperacillin/tazobactam). The rates of susceptibility to the antibiotics were: piperacillin, 17.9%; piperacillin/tazobactam, 26.9%; minocycline, 100%; ciprofloxacin, 4.5%; and levofloxacin, 58.2%. Both MIC50 and MIC90 values of minocycline were low (<1 mg/L). Eleven isolates exhibited MICs of both levofloxacin and ciprofloxacin >32 mg/L. The MIC of tigecycline ranged from <1 to >8 mg/L, with MIC50 and MIC90 values of 4 and 8 mg/L, respectively. Table 3. Antimicrobial MICs for and susceptibilities of 67 E. anophelis isolates Antimicrobial agent  MICa (mg/L)   Interpretation of susceptibilityb, n (%)   lowest  highest  MIC50c  MIC90d  susceptible  intermediate  resistant  Piperacillin  <16  >64  64  >64  12 (17.9)  34 (50.7)  21 (31.3)  Piperacillin/tazobactam  <8/4  >128/4  64/4  >128/4  18 (26.9)  16 (23.9)  33 (49.3)  Ticarcillin/clavulanic acid  64/2  >64/2  >64/2  >64/2  0  3 (4.5)  64 (95.5)  Ceftazidime  >16  >16  >16  >16  0  0  67 (100)  Cefepime  8  >32  >32  >32  1 (1.5)  3 (4.5)  63 (94)  Ceftriaxone  32  >32  >32  >32  0  9 (13.4)  58 (86.6)  Aztreonam  >16  >16  >16  >16  0  0  67 (100)  Ertapenem  8  >8  >8  >8  —  —  —  Imipenem  >8  >8  >8  >8  0  0  67 (100)  Meropenem  >8  >8  >8  >8  0  0  67 (100)  Doripenem  >4  >4  >4  >4  —  —  —  Gentamicin  8  >8  >8  >8  0  2 (3)  65 (97)  Tobramycin  >8  >8  >8  >8  0  0  67 (100)  Amikacin  16  >32  >32  >32  1 (1.5)  12 (17.9)  54 (80.6)  Tetracycline  >8  >8  >8  >8  0  0  67 (100)  Minocycline  <1  4  <1  <1  67 (100)  0  0  Tigecyclinee  <1  >8  4  8  —  —  —  Ciprofloxacin  <1  >32  2  >32  3 (4.5)  34 (50.7)  30 (44.8)  Levofloxacin  <1  >32  2  >32  39 (58.2)  12 (17.9)  16 (23.9)  Trimethoprim/sulfamethoxazole  <2/38  >4/76  >4/76  >4/76  9 (13.4)  —  58 (86.6)  Vancomycin  8  64  16  32  —  —  —  Antimicrobial agent  MICa (mg/L)   Interpretation of susceptibilityb, n (%)   lowest  highest  MIC50c  MIC90d  susceptible  intermediate  resistant  Piperacillin  <16  >64  64  >64  12 (17.9)  34 (50.7)  21 (31.3)  Piperacillin/tazobactam  <8/4  >128/4  64/4  >128/4  18 (26.9)  16 (23.9)  33 (49.3)  Ticarcillin/clavulanic acid  64/2  >64/2  >64/2  >64/2  0  3 (4.5)  64 (95.5)  Ceftazidime  >16  >16  >16  >16  0  0  67 (100)  Cefepime  8  >32  >32  >32  1 (1.5)  3 (4.5)  63 (94)  Ceftriaxone  32  >32  >32  >32  0  9 (13.4)  58 (86.6)  Aztreonam  >16  >16  >16  >16  0  0  67 (100)  Ertapenem  8  >8  >8  >8  —  —  —  Imipenem  >8  >8  >8  >8  0  0  67 (100)  Meropenem  >8  >8  >8  >8  0  0  67 (100)  Doripenem  >4  >4  >4  >4  —  —  —  Gentamicin  8  >8  >8  >8  0  2 (3)  65 (97)  Tobramycin  >8  >8  >8  >8  0  0  67 (100)  Amikacin  16  >32  >32  >32  1 (1.5)  12 (17.9)  54 (80.6)  Tetracycline  >8  >8  >8  >8  0  0  67 (100)  Minocycline  <1  4  <1  <1  67 (100)  0  0  Tigecyclinee  <1  >8  4  8  —  —  —  Ciprofloxacin  <1  >32  2  >32  3 (4.5)  34 (50.7)  30 (44.8)  Levofloxacin  <1  >32  2  >32  39 (58.2)  12 (17.9)  16 (23.9)  Trimethoprim/sulfamethoxazole  <2/38  >4/76  >4/76  >4/76  9 (13.4)  —  58 (86.6)  Vancomycin  8  64  16  32  —  —  —  a The MICs were determined using 96-well broth microdilution panels. b Interpretations according to the interpretive standards for ‘other non-Enterobacteriaceae’ from the CLSI guidelines. c MIC at which 50% of the isolates tested are inhibited. d MIC at which 90% of the isolates tested are inhibited. e The MICs of tigecycline: <1, n = 3 (4.5%); 2, n = 12 (17.9%); 4, n = 27 (40.3%); 8, n = 18 (26.9%); and >8, n = 7 (10.4%). Table 3. Antimicrobial MICs for and susceptibilities of 67 E. anophelis isolates Antimicrobial agent  MICa (mg/L)   Interpretation of susceptibilityb, n (%)   lowest  highest  MIC50c  MIC90d  susceptible  intermediate  resistant  Piperacillin  <16  >64  64  >64  12 (17.9)  34 (50.7)  21 (31.3)  Piperacillin/tazobactam  <8/4  >128/4  64/4  >128/4  18 (26.9)  16 (23.9)  33 (49.3)  Ticarcillin/clavulanic acid  64/2  >64/2  >64/2  >64/2  0  3 (4.5)  64 (95.5)  Ceftazidime  >16  >16  >16  >16  0  0  67 (100)  Cefepime  8  >32  >32  >32  1 (1.5)  3 (4.5)  63 (94)  Ceftriaxone  32  >32  >32  >32  0  9 (13.4)  58 (86.6)  Aztreonam  >16  >16  >16  >16  0  0  67 (100)  Ertapenem  8  >8  >8  >8  —  —  —  Imipenem  >8  >8  >8  >8  0  0  67 (100)  Meropenem  >8  >8  >8  >8  0  0  67 (100)  Doripenem  >4  >4  >4  >4  —  —  —  Gentamicin  8  >8  >8  >8  0  2 (3)  65 (97)  Tobramycin  >8  >8  >8  >8  0  0  67 (100)  Amikacin  16  >32  >32  >32  1 (1.5)  12 (17.9)  54 (80.6)  Tetracycline  >8  >8  >8  >8  0  0  67 (100)  Minocycline  <1  4  <1  <1  67 (100)  0  0  Tigecyclinee  <1  >8  4  8  —  —  —  Ciprofloxacin  <1  >32  2  >32  3 (4.5)  34 (50.7)  30 (44.8)  Levofloxacin  <1  >32  2  >32  39 (58.2)  12 (17.9)  16 (23.9)  Trimethoprim/sulfamethoxazole  <2/38  >4/76  >4/76  >4/76  9 (13.4)  —  58 (86.6)  Vancomycin  8  64  16  32  —  —  —  Antimicrobial agent  MICa (mg/L)   Interpretation of susceptibilityb, n (%)   lowest  highest  MIC50c  MIC90d  susceptible  intermediate  resistant  Piperacillin  <16  >64  64  >64  12 (17.9)  34 (50.7)  21 (31.3)  Piperacillin/tazobactam  <8/4  >128/4  64/4  >128/4  18 (26.9)  16 (23.9)  33 (49.3)  Ticarcillin/clavulanic acid  64/2  >64/2  >64/2  >64/2  0  3 (4.5)  64 (95.5)  Ceftazidime  >16  >16  >16  >16  0  0  67 (100)  Cefepime  8  >32  >32  >32  1 (1.5)  3 (4.5)  63 (94)  Ceftriaxone  32  >32  >32  >32  0  9 (13.4)  58 (86.6)  Aztreonam  >16  >16  >16  >16  0  0  67 (100)  Ertapenem  8  >8  >8  >8  —  —  —  Imipenem  >8  >8  >8  >8  0  0  67 (100)  Meropenem  >8  >8  >8  >8  0  0  67 (100)  Doripenem  >4  >4  >4  >4  —  —  —  Gentamicin  8  >8  >8  >8  0  2 (3)  65 (97)  Tobramycin  >8  >8  >8  >8  0  0  67 (100)  Amikacin  16  >32  >32  >32  1 (1.5)  12 (17.9)  54 (80.6)  Tetracycline  >8  >8  >8  >8  0  0  67 (100)  Minocycline  <1  4  <1  <1  67 (100)  0  0  Tigecyclinee  <1  >8  4  8  —  —  —  Ciprofloxacin  <1  >32  2  >32  3 (4.5)  34 (50.7)  30 (44.8)  Levofloxacin  <1  >32  2  >32  39 (58.2)  12 (17.9)  16 (23.9)  Trimethoprim/sulfamethoxazole  <2/38  >4/76  >4/76  >4/76  9 (13.4)  —  58 (86.6)  Vancomycin  8  64  16  32  —  —  —  a The MICs were determined using 96-well broth microdilution panels. b Interpretations according to the interpretive standards for ‘other non-Enterobacteriaceae’ from the CLSI guidelines. c MIC at which 50% of the isolates tested are inhibited. d MIC at which 90% of the isolates tested are inhibited. e The MICs of tigecycline: <1, n = 3 (4.5%); 2, n = 12 (17.9%); 4, n = 27 (40.3%); 8, n = 18 (26.9%); and >8, n = 7 (10.4%). Mutations in the QRDRs Replacements of serine by isoleucine (Ser83Ile; AGC→ATC) and arginine (Ser83Arg; AGC→AGA) at position 83 in the QRDR of GyrA were identified in eight and three isolates, respectively. All of these 11 isolates exhibited levofloxacin and ciprofloxacin resistance (both MICs >32 mg/L). No non-synonymous substitutions were observed in the QRDRs of GyrB, ParC or ParE in any isolate. PFGE The PFGE dendrogram is shown in Figure S2. One isolate was resistant to XbaI digestion. Of the 10 isolates obtained from patients with community-acquired infection, 3 fell within cluster 1 and 3 gathered in cluster 10. The ciprofloxacin-resistant isolates appeared to be diverse pulsed-field types. The levofloxacin-resistant isolates with gyrA mutations distributed into six clusters. No clear epidemiological linkage among cases could be identified in terms of their infection sites, sources of isolation, times of presentation and locations of patient residences. Discussion Most patients with E. anophelis infection were reported to suffer comorbidities, such as malignancy, diabetes mellitus, chronic renal disease, liver cirrhosis and alcohol dependence.10–14 Our study also revealed that 85.1% of patients had at least one underlying disease. The mortality rate of patients with E. anophelis infections ranged from 23.5% to 34.2%.10–14 In this study, the case-fatality rate of E. anophelis infection was 28.4% and inappropriate empirical antimicrobial therapy was an independent risk factor for mortality. These findings suggest that appropriate antimicrobial therapy is of paramount importance in the successful treatment of this MDR pathogen infection. Information about the susceptibilities of E. anophelis to antimicrobial agents is limited. E. anophelis strain NUHP1 was isolated in Singapore and exhibited resistance to ceftazidime, gentamicin, amikacin, ciprofloxacin and imipenem, but was susceptible to piperacillin, piperacillin/tazobactam and levofloxacin.12,18 Studies from the USA,11–14 Hong Kong10 and South Korea26 demonstrated that E. anophelis was usually resistant to most carbapenems, β-lactams and β-lactam/β-lactamase inhibitors. Our study also showed an extremely high rate of resistance to carbapenems, β-lactams and β-lactam/β-lactamase inhibitors. However, previous studies showed a wide range of E. anophelis susceptibility rates to piperacillin and piperacillin/tazobactam. Perrin et al.12 examined 25 Wisconsin outbreak strains caused by a common recent ancestor; all the strains were susceptible to piperacillin and two were resistant to piperacillin/tazobactam. Han et al.26 analysed 19 isolates of E. anophelis in South Korea and found that 83% and 94% were susceptible to piperacillin and piperacillin/tazobactam, respectively. Nevertheless, our study showed a piperacillin susceptibility of 17.9% and a piperacillin/tazobactam susceptibility of 26.9%. All the E. anophelis isolates in our study were susceptible to minocycline. Eight isolates from Wisconsin residents also showed a low MIC of minocycline (MIC range = 0.25–1 mg/L).13 Unfortunately, no other study has examined the effect of minocycline on E. anophelis in the literature. The isolates in this study showed a relatively high MIC of tigecycline (MIC50 = 4 mg/L; MIC90 = 8 mg/L). Only 15 isolates in this study exhibited a tigecycline MIC ≤2 mg/L. The 25 isolates from the Wisconsin outbreak showed a large zone of tigecycline inhibition (≥20 mm) in the disc diffusion assay.12 However, neither CLSI25 nor EUCAST27 provide interpretive criteria to assess E. anophelis susceptibility to tigecycline. Lau et al.10 examined 17 isolates in Hong Kong and they all were susceptible to ciprofloxacin. Perrin et al.12 evaluated 25 isolates from the Wisconsin outbreak and the rates of susceptibility to ciprofloxacin and levofloxacin were 92% and 96%, respectively. In contrast, Han et al.26 reported 29% susceptibility to levofloxacin and 22% susceptibility to ciprofloxacin in South Korea. In our study, E. anophelis susceptibility to ciprofloxacin and levofloxacin was 4.5% and 58.2%, respectively. In this study, we screened mutations in the QRDRs of gyrA, gyrB, parC and parE in all the identified E. anophelis isolates. No non-synonymous substitutions were detected in GyrB, ParC or ParE. However, we identified eight isolates with a Ser83Ile mutation and three isolates with a Ser83Arg alteration in the QRDR of GyrA. These 11 gyrA-mutant isolates were the 11 isolates that displayed high-level resistance to ciprofloxacin and levofloxacin. These findings suggest that mutations in the QRDR of gyrA confer high-level fluoroquinolone resistance in E. anophelis. Conclusions Our study shows that E. anophelis is an MDR microorganism and that inappropriate empirical antimicrobial therapy is an independent risk factor for mortality in patients with E. anophelis infections. Minocycline has the potential to be the drug of choice for patients with E. anophelis infections. Because of the wide range in susceptibilities, treatment of E. anophelis using piperacillin, piperacillin/tazobactam and fluoroquinolones should be guided by antimicrobial susceptibility testing. Additional investigations are needed to determine the optimal antimicrobial agents to treat this life-threatening infection. Funding This work was supported by grants EDPJ106075 from E-Da Hospital and MOST 106–2314-B-214–009-MY2 from the Ministry of Science and Technology, Taiwan. Transparency declarations None to declare. Supplementary data Table S1 and Figures S1 and S2 are available as Supplementary data at JAC Online. References 1 Henriques IS, Araújo S, Azevedo JS et al.   Prevalence and diversity of carbapenem-resistant bacteria in untreated drinking water in Portugal. Microb Drug Resist  2012; 18: 531– 7. Google Scholar CrossRef Search ADS PubMed  2 Jean SS, Lee WS, Chen FL et al.   Elizabethkingia meningoseptica: an important emerging pathogen causing healthcare-associated infections. J Hosp Infect  2014; 86: 244– 9. Google Scholar CrossRef Search ADS PubMed  3 da Silva PS, Pereira GH. 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Clinical Breakpoints. 2018. http://www.eucast.org/clinical_breakpoints/. © The Author(s) 2018. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Journal of Antimicrobial ChemotherapyOxford University Press

Published: May 28, 2018

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