Disk Diffusion Susceptibility Testing for the Rapid Detection of Fluconazole Resistance in Candida Isolates
2021; 41(6): 559-567
Ann Lab Med 2018; 38(6): 545-554
Published online November 28, 2018 https://doi.org/10.3343/alm.2018.38.6.545
Copyright © Korean Society for Laboratory Medicine.
Yu Jin Park, M.D.1, Duck Jin Hong, M.D.2, Eun-Jeong Yoon, Ph.D.3, Dokyun Kim, M.D.3, Min Hyuk Choi, M.D.1, Jun Sung Hong, Ph.D.3,4, Hyukmin Lee, M.D. Ph.D.3, Dongeun Yong, M.D. Ph.D.3, and Seok Hoon Jeong, M.D. Ph.D.3*
1Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.
2Department of Laboratory Medicine, Sheikh Khalifa Specialty Hospital, Ras Al Khaimah, UAE.
3Department of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University, Seoul, Korea.
4Brain Korea 21 PLUS Project for Medical Science, Yonsei University, Seoul, Korea.
Correspondence to: Corresponding author: Seok Hoon Jeong. Department of Laboratory Medicine, Research Institute of Bacterial Resistance, Gangnam Severance Hospital, Yonsei University College of Medicine, 211 Eonju-ro, Gangnam-gu, Seoul 06273, Korea. Tel: +82-2-2019-3532, Fax: +82-2-2057-8926, firstname.lastname@example.org
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
The increasing morbidity and mortality rates associated with
We collected 36 non-duplicate CR-AB clinical isolates resistant to colistin. Antimicrobial susceptibility testing, Sanger sequencing analysis, molecular typing, lipid A structure analysis, and
Despite no differences in clinical characteristics between patients with and without prior colistin treatment, resistance-causing genetic mutations were more frequent in isolates from colistin-treated patients. Distinct mutations were overlooked via the Sanger sequencing method, perhaps because of a masking effect by the colistin-susceptible AB subpopulation of CR-AB isolates lacking genetic mutations. However, modified lipid A analysis revealed colistin resistance peaks, despite the population heterogeneity, and peak levels were significantly different between the groups.
Although prior colistin use did not induce clinical or susceptibility differences, we demonstrated that identification of CR-AB by sequencing is insufficient. We propose that population heterogeneity has a masking effect, especially in colistin non-treated patients; therefore, accurate testing methods reflecting physiological alterations of the bacteria, such as phosphoethanolamine-modified lipid A identification by matrix-assisted laser desorption ionization-time of flight, should be employed.
Keywords: Colistin, Population heterogeneity,
Colistin, introduced in the 1950s to treat infections caused by gram-negative bacteria (GNB), exerts bactericidal activity by displacing the membrane-stabilizing calcium and magnesium ions and targets the polyanionic lipopolysaccharide (LPS) components [9,10]. However, because it induced nephrotoxicity and neurotoxicity, it was replaced by safer antimicrobial agents (e.g., aminoglycosides) [11,12]. Despite these potential side effects, worldwide dissemination of extensively drug-resistant GNB (XDR-GNB) has rekindled the usage of this drug in clinical settings as a last-resort treatment.
The clinical use of colistin for XDR-GNB infections has led to the development of colistin resistance (CR) in GNB species [13,14,15], and reports on the occurrence of colistin-resistant AB (CR-AB) are increasing globally . Previous
Most CR-AB clinical strains are reported to acquire resistance by
We compared CR-AB isolates recovered from patients with and without prior colistin treatment to assess whether prior colistin treatment affects CR in CR-AB isolates, patient demographics, mortality rates, or genetic mutations. Additionally, mortality rate was assessed to determine clinical characteristics.
In total, 36 non-duplicate AB clinical isolates resistant to both carbapenems and colistin were collected from a tertiary care hospital in Seoul, Korea, from April 2012 to December 2014. At the time of sample collection, 18 patients had received previous colistin treatment (Group CT), and the rest had not (Group non-CT). For comparison, AB isolates (N=11) that were resistant to carbapenems but susceptible to colistin were also studied. Bacterial species were identified by partial
The susceptibility of the isolates to colistin, meropenem, imipenem, piperacillin-tazobactam, ceftazidime, cefepime, gentamicin, tobramycin, amikacin, tetracycline, ciprofloxacin, and trimethoprim/sulfamethoxazole was determined by the disk diffusion method following the CLSI guidelines . Minimum inhibitory concentrations (MICs) of meropenem and imipenem were determined by using Etest (bioMérieux, Inc., Durham, NC, USA). Colistin MIC was determined by the broth microdilution method, following recommendations of the Joint CLSI-EUCAST Polymyxin Breakpoints Working Group . Synergistic effects of drug combinations of colistin (32–4,096 µg/mL) either with meropenem (4–256 µg/mL) or with rifampicin (0.25–32 µg/mL) were evaluated by the checkerboard method  in microtiter plates. The fractional inhibitory concentration (FIC) index of each drug combination was determined by dividing the MIC of each drug when used in combination by the MIC of each drug when used alone. The effect of a drug combination was determined by the FIC index: ≤0.5, a synergistic effect; 0.5–4.0, neutrality; and >4.0 an antagonistic effect.
A series of PCR experiments (primer information available upon request) were conducted to detect the OXA carbapenemase genes
Genes associated with CR in AB (
Lipopolysaccharides and lipid A components were extracted from whole bacterial cells using Tri-reagent and mild acid hydrolysis, and were subjected to negative-ion matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (Bruker Daltonik GmbH, Leipzig, Germany) in negative reflection mode. For comparison, three randomly selected CS-AB isolates were used as controls.
Pulsed-field gel electrophoresis (PFGE) was conducted with
MLST experiments were performed following the Bartual scheme . Sequences of seven housekeeping genes (
All variables were evaluated for Gaussian distribution using the Shapiro-Wilk test. Differences were tested with the Fisher exact test for categorical data and with the Mann-Whitney U test for continuous data. Univariate and multivariate analyses were carried out using logistic regression to investigate the association between CR, mortality rate, and potential covariates. The presence of variance inflation factors was examined for all parameters of the multiple regression model.
The characteristics of patients infected or colonized by CR-AB are presented in Table 1. To determine whether prior colistin treatment had any relevant effect on patient outcome, Groups CT and non-CT were compared.
To determine the characteristics associated with higher survival rates, the “within 30-days deceased group” (13/36) was compared with the “alive group” (23/36) (Table 2). Only bloodstream infection and APACHE II scores significantly differed between groups.
MLST showed that all CR-AB isolates belonged to CC92. Among these, 91.7% (33/36) were identified as ST191 (Fig. 1). All isolates from Group non-CT belonged to ST191, whereas the three non-ST191 isolates were retrieved from Group CT. The 36 CR-AB isolates were assigned to 13 PFGE types (pulsotypes A to N) on the basis of banding patterns. With the exception of pulsotype A1, isolates of pulsotypes A, F, and H did not show any CR-related genetic mutations, and the majority (16/18) of the host patients belonged to Group non-CT. However, isolates of pulsotypes B, C, E, and G showed genetic mutations, and most (8/10) of the host patients belonged to Group CT.
All isolates with genetic mutations had mutated
Lipid A MALDI-TOF mass spectra of CR-AB isolates showed distinct profiles (Fig. 2). Common intensity peaks at m/z 1729, 1912, and 2139 were found in both CS-AB and CR-AB, indicating normal hexa-, hepta-, and octa-acylated lipid A, whereas in some isolates, the hexa- and octa-acylated lipid A peaks were completely changed to phosphoethanolaminated lipid A (hexa-acylated: 1/36, octa-acylated: 9/36). In each isolate, intensities of other lipid A components were compared with that of the hepta-acylated lipid A peak (Table 3), which was set as 100% because some hexa- and octa-acylated peaks were completely lost, and therefore were not suitable as reference peaks.
Peak intensity was significantly higher at two phosphoethanolamine (PE)-modified hexa-, hepta- and octa-acylated lipid A (
The lipid A composition determined by MALDI-TOF M/S divided the CR-AB strains into strains harboring
In our comparison of the characteristics of CR-AB clinical isolates recovered from CT and non-CT patients, no specific patient trait was found relevant to the clinical outcome. As for the mortality rate, the APACHE II score and bloodstream infections were two noteworthy markers that should be taken into consideration when managing CR-AB-infected patients. These findings were expected because the APACHE II scoring system is designed to measure disease severity in patients admitted to ICUs, and because bloodstream infections have a negative impact on patient outcome . Although there were no significant differences in terms of patient characteristics, the causative CR-AB isolates presented obvious differences associated with CR, such as altered lipid A components, as indicated by MALDI-TOF M/S and genetic mutations associated with outer membrane modification.
Most of the CR-AB isolates from Group non-CT did not show any genetic mutations, whereas the revised lipid A component was characterized by shifted lipid A component peaks in MALDI-TOF M/S. Two potential hypotheses explain these unexpected results. First, the isolates may be a hetero-population composed of subpopulations of CR-AB and CS-AB lacking any evident genetic mutation, thus presenting with so-called heteroresistance . Heteroresistance may be the primary stage, which in the presence of colistin, results in the proliferation of resistant subpopulations, and may prolong the treatment period or even lead to mortality [3,15,36,37]. The major subpopulation of CS-AB possibly produces erroneous colistin susceptibility data when using commercially automated systems and disk diffusion tests , whereas multiplication of the minor CR-AB subpopulation results in at least little growth in the presence of high concentrations of colistin by broth dilution, resulting in high MICs [3,36]. The different density of subpopulations might mask genetic mutations in CR-AB strains analyzed by Sanger sequencing. Similar findings have been demonstrated in
Regardless of the population heterogeneity, CR-AB was detectable by MALDI-TOF M/S, based on distinct spectra of modified lipid A compositions. Modification of lipid A by the addition of PE to the hexa-, hepta-, and octa-acylated lipid A has been suggested as a major mechanism of CR in AB. Similarly, even though some isolates exhibited unmodified lipid A peaks in this study, CR-AB displayed shifted peaks of one or two PE additives to the three lipid A moieties. Interestingly, the relative peak levels of PE-modified compared with unmodified lipid A components were much more elevated in Group CT. Notably, the relative peak levels of the two PE modified hepta-acylated lipid A moieties clearly separated the two groups.
Most of the CR-AB isolates from both groups showed a synergistic effect of colistin upon addition of meropenem or rifampin: synergism of both combinations was observed for most isolates, without any noticeable difference between combinations or between groups. Thus, combination treatment with either meropenem or rifampin should be considered for both CT and non-CT patients.
Out study has some limitations. As its main scope was to determine characteristics of CR-AB in clinical isolates and did not entail confirmation of heteroresistance, we could not confirm heteroresistant AB. Our data were collected from a single center in Korea, so the findings may not be generalized to other institutions. The limited number of CR-AB isolates precludes definitive conclusions on heterogeneous AB populations and CR.
Our study demonstrated that although there were no differences in clinical characteristics between Groups CT and non-CT, there were pathological differences, including those involving characteristics useful in diagnosing CR-AB. Population heterogeneity masked resistance-causing genetic mutations, traditionally determined by Sanger sequencing, especially in Group non-CT; therefore, to identify CR, accurate testing methods reflecting physiological alteration of the bacteria, such as PE-modified lipid A identification by MALDI-TOF M/S, should be carried out. Since colistin heteroresistance is common in patients without prior drug treatment and can be caused by better bacterial fitness in the colistin-free environment, lipid A analysis shows clearer results for CR-AB isolates. Broth microdilution was found to accurately determine CR in AB regardless of population heterogeneity, which prevented exact susceptibility interpretation because of the subpopulations of CR-AB. Furthermore, combination treatment, specifically with meropenem and rifampicin, should be considered for the treatment of CR-AB infections.
No potential conflicts of interest relevant to this article were reported.
The Research Program funded by the Korean Centers for Disease Control and Prevention (2016ER230100#) supported this work.
Dendrogram showing cluster analysis of SmaI-digested pulsed-field gel electrophoresis patterns from colistin-resistant
Mass spectrometry of lipid A extracted from colistin-susceptible isolates and CR-AB. (A) ATCC 17978, wild type CS-AB. (B) CR-AB18, Group non-CT. (C) CR-AB14, Group CT. The mass (m/z) of peaks only detected in CR-AB strains is indicated in bold.
Abbreviations: Hexa, hexa-acylated lipid A; Hepta, hepta-acylated lipid A; Octa, octa-acylated lipid A; PE, phosphoethanolamine; C, carbon; CS-AB, colistin-susceptible
Baseline characteristics of study patients
|Variables||All patients (N=36)||CT||Non-CT||Univariate an||alysis|
|(N=18)||(N=18)||OR (95% CI)|
|Age (yr)||53.9 ± 27.4||66.5 (16.0–72.0)||67.5 (44.0–71.0)||0.624||1.01 (0.98–1.03)||0.626|
|Male sex*||21 (58.3%)||12 (66.7%)||9 (50.0%)||0.499||2 (0.53–8.03)||0.313|
|Bloodstream infection||7 (19.4%)||4 (22.2%)||3 (16.7%)||0.7 (0.12–3.73)||0.674|
|Respiratory infection||25 (69.4%)||11 (61.1%)||14 (77.8%)||2.23 (0.53–10.41)||0.283|
|Other||4 (11.1%)||3 (16.7%)||1 (5.6%)|
|Ventilator care*||28 (77.8%)||15 (83.3%)||13 (72.2%)||0.688||1.92 (0.39–10.89)||0.427|
|History of colistin treatment||18 (50.0%)||18 (100%)||0 (0%)|
|Treatment duration (day)||18.9 ± 13.1||18.0 (7.0–29.0)||0.0 (0.0–0.0)|
|30-day mortality||13 (36.1%)||7 (38.9%)||6 (33.3%)||0.999||1.27 (0.32–5.12)||0.729|
|APACHE II||12.6 ± 4.2||13.2 ± 4.2||11.9 ± 4.3||0.92 (0.78–1.08)||0.339|
|ICU stay during isolate recovery||29 (80.6%)||14 (38.9%)||15 (41.7%)|
|ICU admission history*||35 (97.2%)||17 (94.4%)||18 (100.0%)||0.999|
Univariate and multivariate analyses of risk factors for 30-day mortality
|Variables||Death (N=13)||Survival (N=23)||Univariate analysis||Multivariate analysis|
|OR (95% CI)||OR (95% CI)|
|Age (yr)||66.0 (4.0–71.0)||67.0 (50.5–71.5)||0.419||1.02 (0.99–1.05)||0.142|
|Male sex*||5 (38.5%)||10 (43.5%)||0.999||1.23 (0.31–5.17)||0.770|
|Respiratory infection||7 (53.8%)||18 (78.3%)||3.09 (0.72–14.23)||0.134|
|Other||0 (0.0%)||4 (17.4%)|
|History of colistin treatment*||7 (53.8%)||11 (47.8%)||0.999||1.27 (0.32–5.12)||0.729|
|Treatment duration (day)||21.7 ± 18.5||17.2 ± 8.9||0.562||0.97 (0.89–1.05)||0.471|
|ICU admission history*||13 (100.0%)||22 (95.7%)||0.999||NA||0.995|
|ST191||13 (100.0%)||20 (87.0%)|
|ST357||0 (0.0%)||1 (4.3%)|
|ST858||0 (0.0%)||1 (4.3%)|
|ST872||0 (0.0%)||1 (4.3%)|
Genetic characteristics and lipid A composition of colistin-resistant
|Colistin-susceptible ||Colistin-resistant |
|CT (N=18)||Non-CT (N=18)|
|Relative percentage of each lipid A component peak (%)*|
|Hexa+1-PE||0 (0–1.0)||21.2 (8.3–146.9)||24.3 (2.1–78.5)||0.448|
|Hepta||100 (100–100)||100 (100–100)||100 (100–100)||-|
|Octa||9.1 (2.2–12.9)||5.5 (0–11.6)||6.6 (0–12.6)||0.355|
|Octa+1-PE||0 (0–0)||47.3 (15.2–137.7)||58.9 (25.7–316.7)||0.393|
|Isolates with genetic mutations, N (%)|
| ||4 (22.2%)||2 (11.1%)||0.658|
| ||1 (5.6%)||0 (0%)||1.000|
Lipid A composition with genetic
|Relative percentage of each lipid A component peak (%)*||Genetic mutation not detected (N = 21)||Genetic mutation detected (N = 15)|
|Hexa||15.8 (10.8–19.2)||11.9 (10.3–13.5)||8.7 (2.0–11.3)||0.099|
|Hexa+1-PE||19.2 (17.4–22.0)||14.7 (10.6–18.9)||20.8 (16.7–23.5)||0.588|
|Hexa+2-PE||5.0 (3.0–6.4)||4.1 (0.7–7.4)||0.7 (0.0–3.6)||0.074|
|Hepta||21 (100.0%)||15 (100.0%)||-||7 (100.0%)||2 (100.0%)||6 (100.0%)||0.247|
|Hepta+1-PE||175.9 (140.8–179.9)||131.6 (118.5–144.7)||196.4 (136.8–219.5)||0.381|
|Hepta+2-PE||31.4 (29.4–34.8)||27.1 (22.0–32.2)||33.9 (11.4–42.6)||0.944|
|Octa||5.6 (0.0–10.0)||6.0 (3.2–7.5)||0.686||6.0 (5.1–6.7)||3.4 (1.6–5.1)||7.5 (0.0–8.2)||0.479|
|Octa+1-PE||71.3 (44.6–85.4)||42.8 (31.8–70.1)||0.127||51.5 ± 29.4||19.9 ± 4.5||65.0 ± 27.4||0.458|
|Octa+2-PE+4C-H2O||21.1 (4.4–46.4)||15.8 (15.3–16.2)||45.5 (32.1–58.2)||0.201|