year 13, Issue 3 (July - August 2019)                   Iran J Med Microbiol 2019, 13(3): 194-209 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Rahimi N, Honarmand Jahromy S, Zare Karizi S. Evaluation of Antibiotic Resistance Pattern of Meropenem and Piperacillin- Tazobactam in Multi Drug Resistant Acinetobacter baumannii Isolates by Flow Cytometry Method. Iran J Med Microbiol. 2019; 13 (3) :194-209
URL: http://ijmm.ir/article-1-955-en.html
1- Department of Microbiology, School of Biological Sciences, Varamin- Pishva Branch, Islamic Azad University, Varamin, Iran
2- Department of Microbiology, School of Biological Sciences, Varamin-Pishva Branch, Islamic Azad University, Varamin, Iran , sahar_hj2@yahoo.com
3- Department of Genetics, School of Biological Sciences, Varamin-Pishva Branch, Islamic Azad University, Varamin, Iran
Full-Text [PDF 1041 kb]   (1331 Downloads)     |   Abstract (HTML)  (4145 Views)
Full-Text:   (3010 Views)
Introduction

Standard Antibiotic Susceptibility Test (AST) include disk diffusion, broth dilution and manual and automated alternative methods that take 18 to 24 hours to get a good result. Faster methods such as DNA and mass spectrometry-based methods do not always provide good information in antibiotic susceptibility and have limitation (11,12). This limitation can be achieved by means of a device based on identification of bacterial physiological changes in the presence of antibiotics and by using biodegradable fluorescent markers, as flow cytometry (14,15). Flow cytometry (FCM) , is a device that passes cells or micrometer particles through the point of contact where the laser beams affect them, and the light that they absorb which is based on the intrinsic or sub-physical properties of the particle itself, Scatter or diffuse, and this light can be measured (1,2). Today, flow cytometry is a tool for bacterial analysis, detection, enumeration, determining changes in cellular function, metabolic activity, cell viability and antibiotic susceptibility of bacteria (3,32). Over the past decade, the presence of Acinetobacter baumannii, especially multiple drug resistant A. baumannii (MDRAB), has been recognized as the most important pathogen and cause of hospital mortality worldwide. Rapid identification of these strains is essential for the treatment of their disease (17,18). The aim of this study was to investigate the antibiotic resistance pattern of multidrug-resistant A. baumannii isolates against meropenem and piperacillin-tazobactam using flow cytometry.
Methods

This cross-sectional descriptive study was performed on 55 A. baumannii strains randomly isolated from clinical specimens of 230 patients admitted to Milad Hospital, Tehran, from November to April 2017. Gram staining and biochemical tests were used for identifying A. baumannii strains. Antibiotic susceptibility testing was performed by disk diffusion methods according to CLSI 2017 against 7 antibiotics (Table 1). Strains that were resistant to more than two classes of antibiotics were included as MDR strains. Microdilution broth method was used to determine Minimum Inhibitory Concentration of meropenem and piperacillin-tazobactam. For Flow cytometry 10 isolates of multidrug-resistant A. baumannii were selected. The concentrations of meropenem and piperacillin-tazobactam for A. baumannii isolates were 2, 4, 8 µg/mL and 16, 64, 128 µg/mL. The incubation time of antibiotic treatment on bacterial suspension was 4 hours. Then the suspension was centrifuged and stained by 2 µg/mL of Rhodhamin123 florescent dye. The results were analyzed by Flow cytometer FACSCalibur using Side scatter (SSC), forward scatter (FSC) and green florescent light (FL1) parameters with 488-nm wavelength helium laser beam. Data analysis was performed for all methods. 
Table 1. Antibiotic resistance pattern of Acinetobacter baumannii isolates based on according to the CLSI 2017
Antimicvobial Agent SYMBOL DISK ( S I R
Meropenem (Carbapenem) (MEN) 10 >23 20_22 <19
Ciprofloxacin(FLUOROQUINOLONES (CP) 5 >21 2_6 <15
Gentamycin(AMINOGLYCOSIDES ) (GM) 10 >15 13_14 <12
Piperacillin-Tazobactam(Beta lactam) (Pip- T) 100/1 >21 18_20 <17
levofloxacin (FLUOROQUINOLONES (LVF) 5 >16 11_15 <10
Tetracyclin (Tetracycline ) (TE) 30 >15 12_14 <11
Imipenem (Carbapenem) (IMP) 10 >18 14_17 <13
 
 
Results

The average antibiotic resistance of A. baumannii strains to meropenem, ciprofloxacin, gentamicin, piperacillin -tazobactam,  levofl-oxazine, tetracycline and imipenem were 100%, 95.7%, 72.8%, 100%, 100%, 65.7% and 94.2%, respectively (Figure 1). 98% of A. baumannii isolates were included as MDR strains.

TThe results of antibiotic MIC of isolates showed that the mean MIC of Meropenem antibiotic was 105.14 with a standard deviation of 84.101 and for the piperacillin-tazobactam antibiotic 1236.11 with a standard deviation of 774.124. 37/37% of the strains had MIC 64 µg/mL for Micropenem and only 90/90% of isolates had MIC of 8 µg/mL. For piperacillin-tazobactam the highest MIC was 1024 μg/mL and higher.
In Flow cytometry section at concentrations of 2, 4 and 8 μg/ml of meropenem antibiotic, the cell death rate was 1.96%, 1.44% and 0.59%, respectively (Figure 2).
At concentrations of 16, 64 and 128 μg/mL of piperacillin–tazobactam antibiotic, the cell death rate was 1.96%, 1.44% and 0.59%, respectively (Figure 2).
The results of flow cytometry to determine the resistance pattern of 10 MDR isolates of A. baumannii, showed that more than 98% of cells survived the effects of meropenem and piperacillin-tazobactam and all isolates showed resistance to meropenem and piperacillin tazobactam. Comparison of the results of antibiotic resistance pattern determination with all three methods and the Category agreement (CA) between methods were finally 100% for both antibiotics.
 
Figure1: Antibiotic resistance profile of Acinetobacter baumannii isolates
Figure1: Antibiotic resistance profile of Acinetobacter baumannii isolates

Figure 2. Histogram of Flow cytometry analysis for meropenem
Figure 2. Histogram of Flow cytometry analysis for meropenem

Figure 3. Histogram of Flow cytometry analysis for Piperacilin –Tazobactam
Figure 3. Histogram of Flow cytometry analysis for Piperacilin –Tazobactam


 
Discussion

Previous studies in Iran have shown that carbapenem resistance of A. baumannii strains is increasing. In a systematic study by Moradi et al. In 2015, the rate of resistance to meropenem and imipenem antibiotics between 2001- 2007 increased by 64.3% and 51.1% to 81.5% and 76.5% between 2012 and 2013, respectively (24). Excessive resistance to carbapenem, which was also reported 100% in this study, is a serious alarm for the treatment of infections associated with A. baumannii. One of the most important reasons is using inappropriate antibiotics. Also, quick and accurate tests to determine the antibiotic susceptibility of the bacteria and the need for rapid administration of an initial antimicrobial empirical treatment is very important when the physician is awaiting the results of sensitivity testing with standard time-consuming. Flow cytometry can analyze diverse microbial populations in a suspension and showing microbial diversity in a short time. In this study the results obtained by flow cytometer in measuring antibiotic resistance pattern were obtained 4 hours after preparation of microbial suspension resulting from overnight culture on bacterial colonies. More than 98% of bacterial cells survived after exposure to different concentrations of meropenem and piperacillin-tazobactam that was in agreement with the results of disk diffusion and MIC method for determination of antibiotic resistance pattern of A. baumannii isolates (CA 100%). This illustrates the importance of using a flow cytometer as a rapid and sensitive method to determine the antibiotic resistance pattern of bacterial isolates. However, the use of other antibiotics such as gentamicin, which in this study showed less resistance, and the determination of antibiotic resistance pattern of higher number of bacterial strains by flow cytometry is suggested in future studies.
 
Acknowledgments

The authors would like to thank Mr. Omid Hosseini, technician of Research Laboratory of Shahid Beheshti University who helped them in this study.
  The authors reported no conflict of interest.
 
Type of Study: Original Research Article | Subject: Antibiotic Resistance
Received: 2019/08/9 | Accepted: 2019/11/22 | ePublished: 2019/11/22

References
1. Veal DA, Deere D, Ferrari B, Piper J, Attfield PV. Fluorescence staining and flow cytometry for monitoring microbial cells. Journal of Immunological Methods. 2000; 243:220-191. [DOI:10.1016/S0022-1759(00)00234-9]
2. Nuding S, Zabel LT. Detection, identification, and susceptibility testing of bacteria by flow cytometry. Journal of Bacteriology & Parasitology. 2013; S5-005. Doi: 10(4172):2155-9597 [DOI:10.4172/2155-9597.S5-005]
3. Kansanaho H, Isonen-Sjölund N, Pietilä K, Airaksinen M, Isonen T. Patient counselling profile in a Finnish pharmacy. Patient Education and Counseling. 2002; 47(1):77-82. [DOI:10.1016/S0738-3991(01)00180-X]
4. Huang TH, Ning X, Wang X, Murthy N, Tzeng YL, Dickson RM. Rapid cytometric antibiotic susceptibility testing utilizing adaptive multidimensional statistical metrics. Analytical chemistry. 2015; 87(3):1941-9. [DOI:10.1021/ac504241x] [PMID] [PMCID]
5. Wu L, Wang S, Song Y, Wang X, Yan X. Applications and challenges for single-bacteria analysis by flow cytometry. Science China Chemistry. 2016; 59(1):30-9. [DOI:10.1007/s11426-015-5518-3]
6. Fraser D, Kaern M. A chance at survival: gene expression noise and phenotypic diversification strategies. Molecular Microbiology. 2009; 71(6):1333-40. [DOI:10.1111/j.1365-2958.2009.06605.x] [PMID]
7. Rainey PB, Beaumont HJ, Ferguson GC, Gallie J, Kost C, Libby E, et al. The evolutionary emergence of stochastic phenotype switching in bacteria. 2011. 2011; 10(Suppl 1):S14. [DOI:10.1186/1475-2859-10-S1-S14] [PMID] [PMCID]
8. Paau AS Cowles JR, Oro J. Flow-microfluorometric analysis of Escherichia coli, Rhizobium meliloti, and Rhizobium japonicum at different stages of the growth cycle. Canadian journal of microbiology. 1977; 23(9):1165-9. [DOI:10.1139/m77-175] [PMID]
9. Hutter KJ, Eipel H. Microbial determinations by flow cytometry. Microbiology. 1979; 113(2):369-75. [DOI:10.1099/00221287-113-2-369] [PMID]
10. Haugland RP. Handbook of fluorescent probes and research chemicals. Eugene: Molecular Probes Inc.; 1996.
11. Shapiro HM. Microbial analysis at the single-cell level: tasks and techniques. Journal of Microbiological Methods. 2000; 42(1):3-16. [DOI:10.1016/S0167-7012(00)00167-6]
12. Sack U, Tárnok A, Rothe G. Cellular diagnostics: basic principles, methods and clinical applications of flow cytometry. Basel: Karger Medical and Scientific Publishers; 2009. [DOI:10.1159/isbn.978-3-8055-8556-9]
13. Suller M, Stark J, Lloyd D. A flow cytometric study of antibiotic-induced damage and evaluation as a rapid antibiotic susceptibility test for methicillin-resistant Staphylococcus aureus. The Journal of antimicrobial chemotherapy. 1997; 40(1):77-83. [DOI:10.1093/jac/40.1.77] [PMID]
14. Mason D, Allman R, Stark J, Lloyd D. Rapid estimation of bacterial antibiotic susceptibility with flow cytometry. Journal of Microscopy. 1994; 176(1):8-16. [DOI:10.1111/j.1365-2818.1994.tb03494.x] [PMID]
15. Suller M, Lloyd D. Fluorescence monitoring of antibiotic‐induced bacterial damage using flow cytometry. Cytometry: The Journal of the International Society for Analytical Cytology. 1999; 35(3):235-41. https://doi.org/10.1002/(SICI)1097-0320(19990301)35:3<235::AID-CYTO6>3.0.CO;2-0 [DOI:10.1002/(SICI)1097-0320(19990301)35:33.0.CO;2-0]
16. Gauthier C, Pierre STY, Villemure R. Rapid antimicrobial susceptibility testing of urinary tract isolates and samples by flow cytometry. Journal of Medical Microbiology.2002; 51:192-200. [DOI:10.1099/0022-1317-51-3-192] [PMID]
17. Zilberberg MD, Nathanson BH, Sulham K, Fan W, Shorr AF. Multidrug resistance, inappropriate empiric therapy, and hospital mortality in Acinetobacter baumannii pneumonia and sepsis. Critical Care. 2016; 20(1):221. [DOI:10.1186/s13054-016-1392-4] [PMID] [PMCID]
18. Visca P, Seifert H, Towner KJ. Acinetobacter infection-an emerging threat to human health. IUBMB life. 2011; 63(12):1048-54. https://doi.org/10.1002/iub.534 [DOI:10.1002/iub.600] [PMID]
19. McConnell MJ, Actis L, Pachón J. Acinetobacter baumannii: human infections, factors contributing to pathogenesis and animal models. FEMS Microbiology Review. 2013; 37(2):130-55. [DOI:10.1111/j.1574-6976.2012.00344.x] [PMID]
20. Falagas ME, Karveli EA.The changing global epidemiology of Acinetobacter baumannii infections: a development with major public health implications. Clinical Microbiology and Infection. 2007; 13(2):117-9. [DOI:10.1111/j.1469-0691.2006.01596.x] [PMID]
21. Falagas ME, Bliziotis IA, Siempos II. Attributable mortality of Acinetobacter baumannii infections in critically ill patients: a systematic review of matched cohort and case-control studies. Critical Care. 2006; 10(2):R48. [DOI:10.1186/cc4869] [PMID] [PMCID]
22. Karbasizade V, Heidari L. Antimicrobial resistance of Acinetobacter baumannii isolated from Intensive Care Units of Isfahan hospitals, Iran. Journal of Isfahan Medical School. 2012; 30(191).
23. Ardebili A, Lari AR, Talebi M. Correlation of ciprofloxacin resistance with the AdeABC efflux system in Acinetobacter baumannii clinical isolates. Annals of Laboratory Medicine. 2014; 34(6):433-8. [DOI:10.3343/alm.2014.34.6.433] [PMID] [PMCID]
24. Moradi J, Hashemi FB, Bahador A. Antibiotic resistance of Acinetobacter baumannii in Iran: a systemic review of the published literature. Osong Public Health and Research Perspectives.2015;6(2):79-86. [DOI:10.1016/j.phrp.2014.12.006] [PMID] [PMCID]
25. Ghasemian R, Ahanjan M, Fatehi E, Shokri M. Prevalence and antibiotic resistance pattern of Acinetobacter isolated from patients admitted in ICUs in Mazandaran, Northern Iran. Global Journal of Health Science. 2016; 11(8):112-9. [DOI:10.5539/gjhs.v8n11p112]
26. Heinemann JA, Ankenbauer RG, Amábile-Cuevas CF. Do antibiotics maintain antibiotic resistance? Drug Discovery Today. 2000; 5(5):195-204. [DOI:10.1016/S1359-6446(00)01483-5]
27. Comas J,Vives-Rego J. Assessment of the effects of gramicidin, formaldehyde, and surfactants on Escherichia coli by flow cytometry using nucleic acid and membrane potential dyes. Cytometry.1997; 29:58-64. https://doi.org/10.1002/(SICI)1097-0320(19970901)29:1<58::AID-CYTO6>3.0.CO;2-9 [DOI:10.1002/(SICI)1097-0320(19970901)29:13.0.CO;2-9]
28. Walberg M, Steent HB. Flow cytometric monitoring of bacterial susceptibility to antibiotics. Methods in Cell Biology. 2001; 64:553-66. [DOI:10.1016/S0091-679X(01)64029-9]
29. Soejima T, Minami JI, Iwatsuki K. The exclusive use of flow cytometry to evaluate the antibiotic-susceptibility. Biochimica et Biophysica Acta (BBA)-General Subjects. 2012; 1820(12):1980-6. [DOI:10.1016/j.bbagen.2012.09.003] [PMID]
30. Saint-Ruf C, Crussard S, Franceschi C, Orenga S, Ouattara J, Ramjeet M, et al. Antibiotic susceptibility testing of the gram-negative bacteria based on flow cytometry. Frontiers in Microbiology. 2016; 7:1121. [DOI:10.3389/fmicb.2016.01121] [PMID] [PMCID]
31. Huang TH, Ning X, Wang X, Murthy N, Tzeng YL, Dickson RM. Rapid cytometric antibiotic susceptibility testing utilizing adaptive multidimensional statistical metrics. Analytical Chemistry. 2015; 87(3):1941-9. [DOI:10.1021/ac504241x] [PMID] [PMCID]
32. Huang TH, Tzeng Y, Land Dickson R. FAST: Rapid Determinations of Antibiotic Susceptibility Phenotypes using Label-Free. Cytometry Cytometry A . 2018; 93(6):63948. [DOI:10.1002/cyto.a.23370] [PMID] [PMCID]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2022 CC BY-NC 4.0 | Iranian Journal of Medical Microbiology

Designed & Developed by : Yektaweb | Publisher: Farname Inc