Literature DB >> 30137346

Colistin susceptibility test evaluation of multiple-resistance-level Pseudomonas aeruginosa isolates generated in a morbidostat device.

Mumina Javed1,2, Viola Ueltzhoeffer1, Maximilian Heinrich1,2, Hans Justus Siegrist1, Ronja Wildermuth1, Freia-Raphaella Lorenz1, Richard A Neher3, Matthias Willmann1,2.   

Abstract

Objectives: Colistin is a last-resort antibiotic against the critical-status pathogen Pseudomonas aeruginosa. There is still uncertainty regarding how to accurately measure colistin susceptibility in P. aeruginosa. Evaluation of antimicrobial susceptibility testing (AST) methods is largely hampered by the lack of resistant isolates and those around the susceptibility breakpoint. The aim of this study was to generate such strains in a morbidostat device for use in AST method evaluation.
Methods: A morbidostat device was used to cultivate susceptible clinical strains into isolates with a wide range of colistin MICs. Subsequently, five commercial AST methods were compared against the gold standard broth microdilution (BMD) method: MICRONAUT-S, SensiTest, Sensititre, Rapid Polymyxin Pseudomonas and Etest.
Results: A total of 131 P. aeruginosa isolates were used for colistin susceptibility test evaluation (100 colistin susceptible and 31 colistin resistant). The 31 colistin-resistant isolates evolved resistance in the morbidostat to different MIC ranges (4-512 mg/L, 100% resistance generation efficacy). The categorical agreement (CA) rates for MICRONAUT-S, SensiTest and Rapid Polymyxin Pseudomonas were 94.7%, 93.9% and 92.4%, respectively. The Sensititre achieved the highest CA score (96.9%), whereas the Etests had the lowest CA score (84%). The very major discrepancy (VMD) rates for all tests were between 3.2% and 67.7%. Conclusions: The morbidostat device can efficiently provide laboratories with colistin-resistant strains for test evaluation. Although CA rates were high for commercial AST methods except for Etests, none met the ≤1.5% CLSI limit for VMD rates. Performance was generally inferior when using isolates with low-level resistance.

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Year:  2018        PMID: 30137346     DOI: 10.1093/jac/dky337

Source DB:  PubMed          Journal:  J Antimicrob Chemother        ISSN: 0305-7453            Impact factor:   5.790


  4 in total

1.  Contribution of Time, Taxonomy, and Selective Antimicrobials to Antibiotic and Multidrug Resistance in Wastewater Bacteria.

Authors:  Hannah K Gray; Keith K Arora-Williams; Charles Young; Edward Bouwer; Meghan F Davis; Sarah P Preheim
Journal:  Environ Sci Technol       Date:  2020-12-01       Impact factor: 9.028

2.  Manual Reading of Sensititre Broth Microdilution System Panels Improves Accuracy of Susceptibility Reporting for Polymyxin Antibiotics.

Authors:  Michelle M Bellerose; Andrew E Clark; Jung-Ho Youn; Rebecca A Weingarten; Chelsea M Crooks; John P Dekker; Karen M Frank
Journal:  J Clin Microbiol       Date:  2021-08-18       Impact factor: 5.948

3.  Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics.

Authors:  Ariane Khaledi; Aaron Weimann; Monika Schniederjans; Ehsaneddin Asgari; Tzu-Hao Kuo; Antonio Oliver; Gabriel Cabot; Axel Kola; Petra Gastmeier; Michael Hogardt; Daniel Jonas; Mohammad Rk Mofrad; Andreas Bremges; Alice C McHardy; Susanne Häussler
Journal:  EMBO Mol Med       Date:  2020-02-12       Impact factor: 12.137

4.  Evaluation of Rapid Polymyxin Pseudomonas test in clinical Pseudomonas aeruginosa isolates with various degrees of multidrug resistance.

Authors:  Javier Sánchez-López; José Luis Cortés-Cuevas; María Díez-Aguilar; Carla López-Causapé; Rafael Cantón; María Isabel Morosini
Journal:  JAC Antimicrob Resist       Date:  2021-07-24
  4 in total

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