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

Javed, Mumina; Ueltzhoeffer, Viola; Heinrich, Maximilian; Siegrist, Hans Justus; Wildermuth, Ronja; Lorenz, Freia-Raphaella; Neher, Richard A.; Willmann, Matthias

doi:10.1093/jac/dky337

Cited by 11 publications

(13 citation statements)

References 19 publications

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“…This observation is contrary to a few or no VMEs observed elsewhere [23,28,29], but is not unexpected as the Rapid ResaPolymyxin Acinetobacter/Pseudomonas NP test uses a final colistin concentration of 3.75 mg l −1 and all discrepant P. aeruginosa and A. baumannii isolates had MICs close to the colistin MIC breakpoint (4 or 8 mg l −1 ) (Table 1). The discrepancy (VMEs or MEs) of the AST results in isolates with the MICs close to the breakpoint ('difficult isolates') is commonly observed in lactose non-fermenters like P. aeruginosa and A. baumannii, as well as in Enterobacterales [30][31][32][33]. It could be hypothesized that the VMEs observed in this study could be due to heteroresistant subpopulations or a low proportion of resistant subpopulations as demonstrated in a study by Rodriguez et al [31].…”

Section: Resultsmentioning

confidence: 55%

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Evaluation of the rapid ResaPolymyxin Acinetobacter/Pseudomonas NP test for rapid colistin resistance detection in lactose non-fermenting Gram-negative bacteria

Jung

Pitout

Mitton

et al. 2021

Journal of Medical Microbiology

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Introduction. Colistin is one of the last-resort antibiotics for treating multidrug-resistant (MDR) or extensively drug-resistant (XDR) lactose non-fermenting Gram-negative bacteria such as Pseudomonas aeruginosa and Acinetobacter baumannii . Gap Statement. As the rate of colistin resistance is steadily rising, there is a need for rapid and accurate antimicrobial susceptibility testing methods for colistin. The Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test has recently been developed for rapid detection of colistin resistance in P. aeruginosa and A. baumannii . Aim. The present study aimed to evaluate the performance of the Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test in comparison with the reference broth microdilution (BMD) method. Methodology. The Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test was performed using a total of 135 P . aeruginosa (17 colistin-resistant and 118 colistin-susceptible) and 66 A. baumannii isolates (32 colistin-resistant and 34 colistin-susceptible), in comparison with the reference BMD method. Results. The categorical agreement of the Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test with the reference BMD method was 97.5 % with a major error rate of 0 % (0/152) and a very major error (VME) rate of 10.2 %. The VME rate was higher (23.5 %) when calculated separately for P. aeruginosa isolates. The overall sensitivity and specificity were 89.8 and 100 %, respectively. Conclusion. The Rapid ResaPolymyxin Acinetobacter / Pseudomonas NP test performed better for A. baumannii than for P. aeruginosa .

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Section: Resultsmentioning

confidence: 55%

“…aeruginosa and A. baumannii , as well as in Enterobacterales [30–33]. It could be hypothesized that the VMEs observed in this study could be due to heteroresistant subpopulations or a low proportion of resistant subpopulations as demonstrated in a study by Rodriguez et al [31].…”

Section: Resultsmentioning

confidence: 73%

Evaluation of the rapid ResaPolymyxin Acinetobacter/Pseudomonas NP test for rapid colistin resistance detection in lactose non-fermenting Gram-negative bacteria

Jung

Pitout

Mitton

et al. 2021

Journal of Medical Microbiology

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“…If subjected to quinolones, those isolates can rapidly acquire second step mutations in parC that would then exhibit a fully resistant phenotype. An additional explanation might also be that generally MICs have a low level of reproducibility (Turnidge and Paterson 2007;Juan et al 2012;Javed et al 2018) . A non-accurate categorization due to uncertainty in testing near the MIC breakpoint can explain failure in the assignment of drug resistance by the machine learning classifiers.…”

Section: Discussionmentioning

confidence: 99%

Fighting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics

Khaledi

Weimann

Schniederjans

et al. 2019

Preprint

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The growing importance of antibiotic resistance on clinical outcomes and cost of care underscores the need for optimization of current diagnostics. For a number of bacterial species antimicrobial resistance can be unambiguously predicted based on their genome sequence. In this study, we sequenced the genomes and transcriptomes of 414 drug-resistant clinical Pseudomonas aeruginosa isolates. By training machine learning classifiers on information about the presence or absence of genes, their sequence variation, and gene expression profiles, we generated predictive models and identified biomarkers of susceptibility or resistance to four commonly administered antimicrobial drugs. Using these data types alone or in combination resulted in high (0.8-0.9) or very high (>0.9) sensitivity and predictive values, where the relative contribution of the different categories of biomarkers strongly depended on the antibiotic. For all drugs except for ciprofloxacin, gene expression information substantially improved diagnostic performance. Our results pave the way for the development of a molecular resistance profiling tool that reliably predicts antimicrobial susceptibility based on genomic and transcriptomic markers.The implementation of a molecular susceptibility test system in routine clinical microbiology diagnostics holds promise to provide earlier and more detailed information on antibiotic resistance profiles of bacterial pathogens and thus could change how physicians treat bacterial infections.

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“…After comparison against broth microdilution (BMD) and other commercial tests with positive results (Javed et al, 2018), antibiotic susceptibility testing was determined using MICRONAUT MIC-Strip (MERLIN Diagnostika Gmbh, Bornheim, Germany): a commercial broth microdilution system FIGURE 1 | Experimental set up presented as a flow chart. The XDR strain PA77, ST 308, was cultivated in the morbidostat in 20 ml LB medium under four drug conditions: 2-500 mg/L colistin only (Condition 1), a combination of 2-500 mg/L colistin and 50 mg/L metronidazole (Condition 2) and 50 mg/L metronidazole only (Condition 3).…”

Section: Colistin Susceptibility Of Pa77 and Isolates Cultivated In Morbidostatmentioning

confidence: 99%

Transcriptomic Basis of Serum Resistance and Virulence Related Traits in XDR P. aeruginosa Evolved Under Antibiotic Pressure in a Morbidostat Device

et al. 2021

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Colistin is a last resort antibiotic against the critical status pathogen Pseudomonas aeruginosa. Virulence and related traits such as biofilm formation and serum resistance after exposure to sub-inhibitory levels of colistin have been underexplored. We cultivated P. aeruginosa in a semi-automated morbidostat device with colistin, metronidazole and a combination of the two antibiotics for 21 days, and completed RNA-Seq to uncover the transcriptional changes over time. Strains became resistant to colistin within this time period. Colistin-resistant strains show significantly increased biofilm formation: the cell density in biofilm increases under exposure to colistin, while the addition of metronidazole can remove this effect. After 7 days of colistin exposure, strains develop an ability to grow in serum, suggesting that colistin drives bacterial modifications conferring a protective effect from serum complement factors. Of note, strains exposed to colistin showed a decrease in virulence, when measured using the Galleria mellonella infection model. These phenotypic changes were characterized by a series of differential gene expression changes, particularly those related to LPS modifications, spermidine synthesis (via speH and speE) and the major stress response regulator rpoS. Our results suggest a clinically important bacterial evolution under sub-lethal antibiotic concentration leading to potential for significant changes in the clinical course of infection.

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

Cited by 11 publications

References 19 publications

Evaluation of the rapid ResaPolymyxin Acinetobacter/Pseudomonas NP test for rapid colistin resistance detection in lactose non-fermenting Gram-negative bacteria

Evaluation of the rapid ResaPolymyxin Acinetobacter/Pseudomonas NP test for rapid colistin resistance detection in lactose non-fermenting Gram-negative bacteria

Fighting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics

Transcriptomic Basis of Serum Resistance and Virulence Related Traits in XDR P. aeruginosa Evolved Under Antibiotic Pressure in a Morbidostat Device

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