2022 / 01

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DOI: 10.24075/brsmu.2022.001

ORIGINAL RESEARCH

Meropenem-induced reduction in colistin susceptibility in Pseudomonas aeruginosa strain ATCC 27853

Savinova TA, Bocharova YuA, Chaplin AV, Korostin DO, Shamina OV, Mayanskiy NA, Chebotar IV
About authors

Pirogov Russian National Research Medical University, Moscow, Russia

Correspondence should be addressed: Tatiana A. Savinova
Ostrovityanova, 1, Moscow, 117997, Russia; moc.liamg@avonivasainat

About paper

Funding: the study was supported by the Russian Science Foundation (Project 20-15-00235).

Acknowledgements: the authors thank the Center of Precision Genome Editing and Genetic Technologies for Biomedicine of Pirogov Russian National Research Medical University for their advice on the methodology of the study.

Author contribution: Savinova TA — formal analysis of sequencing data, manuscript preparation; Bocharova YuA — methodology, formal analysis; Chaplin AV — formal analysis of sequencing data; Korostin DO — methodology, data validation; Shamina OV — methodology; Mayansky NA, Chebotar IV — concept; manuscript editing.

Received: 2021-12-27 Accepted: 2022-01-10 Published online: 2022-01-19
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  1. Bou R, Lorente L, Aguilar A, Perpinan J, Ramos P, Peris M, et al. Hospital economic impact of an outbreak of Pseudomonas aeruginosa infections. J Hosp Infect. 2009; 71 (2): 138–42. Available from: https://doi.org/10.1016/j.jhin.2008.07.018.
  2. World Health Organization (WHO). Global Priority List of AntibioticGeneva, Switzerland: 2017. Available at: http://www.who.int/ medicines/publications/WHO-PPL-Short_Summary_25Feb-ET_ NM_WHO.pdf (accessed Novemder 2021).
  3. Breidenstein EB, de la Fuente-Nunez C, Hancock RE. Pseudomonas aeruginosa: all roads lead to resistance. Trends Microbiol. 2011; 19 (8): 419–26. Available from: https://doi. org/10.1016/j.tim.2011.04.005
  4. Baym M, Lieberman TD, Kelsic ED, Chait R, Gross R, Yelin I, et al. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 2016; 353 (6304): 1147–51. Available from: https://doi. org/10.1126/science.aag0822.
  5. Pal C, Papp B, Lazar V. Collateral sensitivity of antibiotic-resistant microbes. Trends Microbiol. 2015; 23 (7): 401–40. Available from: https://doi.org/10.1016/j.tim.2015.02.009.
  6. Gnanadhas DP, Marathe SA, Chakravortty D. Biocides–resistance, cross-resistance mechanisms and assessment. Expert Opin Investig Drugs, 2013; 22 (2): 191–06. Available from: https://doi. org/10.1517/13543784.2013.748035.
  7. European Committee for Antimicrobial Susceptibility Testing (EUCAST) of the European Society of Clinical Microbiology and Infectious Diseases (ESCMID). Determination of minimum inhibitory concentrations (MICs) of antibacterial agents by agar dilution. Clin Microbiol Infect. 2000; 6 (9): 509–15. Available from: https://doi.org/10.1046/j.1469-0691.2000.00142.x.
  8. Clinical and Laboratory Standards Institute (CLSI). Performance Standards for Antimicrobial Susceptibility Testing. Available from: http://em100.edaptivedocs.net/dashboard.aspx (accessed November 2021).
  9. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012; 19: 455–77. Available from: https://doi.org/10.1089/cmb.2012.0021.
  10. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013; 29 (8): 1072-5. Available from: https://doi.org/10.1093/ bioinformatics/btt086.
  11. Marcais G, Delcher AL, Phillippy AM, Coston R, Salzberg SL, Zimin A. MUMmer4: A fast and versatile genome alignment system. PLoS Comput Biol. 2018; 14 (1): e1005944. Available from: https://doi.org/10.1371/journal.pcbi.1005944.
  12. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014; 42: D206–14. Available from: https://doi.org/10.1093/nar/gkt1226.
  13. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014; 30 (14): 2068–9. Available from: https://doi.org/10.1093/bioinformatics/btu153.
  14. Seemann T. Snippy: fast bacterial variant calling from NGS reads. GitHub. 2015. Available from: https://github.com/tseemann/ snippy (accessed November 2021).
  15. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012; 6 (2): 80–92. Available from: https://doi.org/10.4161/fly.19695.
  16. Feldgarden M, Brover V, Haft DH, Prasad AB, Slotta DJ, Tolstoy I, et al. Validating the AMRFinder Tool and Resistance Gene Database by Using Antimicrobial Resistance GenotypePhenotype Correlations in a Collection of Isolates. Antimicrob Agents Chemother. 2019; 63 (11): e00483-19. Available from: https://doi.org/10.1128/AAC.00483-19.
  17. Bortolaia V, Kaas RS, Ruppe E, Roberts MC, Schwarz S, Cattoir V, et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother. 2020; 75 (12): 3491–500. Available from: https://doi.org/10.1093/jac/dkaa345.
  18. Sader HS, Huband MD, Castanheira M, Flamm RK. Pseudomonas aeruginosa antimicrobial susceptibility results from four years (2012 to 2015) of the international network for optimal resistance monitoring program in the United States. Antimicrob Agents Chemother. 2017; 61 (3): e02252–16. Available from: https://doi. org/10.1128/AAC.02252-16.
  19. Chevalier S, Bouffartigues E, Bodilis J, Maillot O, Lesouhaitier O, Feuilloley MGJ, et al. Structure, function and regulation of Pseudomonas aeruginosa porins. FEMS Microbiol Rev. 2017; 41 (5): 698–722. Available from: https://doi.org/10.1093/femsre/fux020.
  20. Zahedi Bialvaei A, Rahbar M, Hamidi-Farahani R, Asgari A, Esmailkhani A, Mardani Dashti Y, et al. Expression of RND efflux pumps mediated antibiotic resistance in Pseudomonas aeruginosa clinical strains. Microbial Pathog. 2021; 153: 104789. Available from: https://doi.org/10.1016/j.micpath.2021.104789.
  21. Barrow K, Kwon DH. Alterations in two-component regulatory systems of phoPQ and pmrAB are associated with polymyxin B resistance in clinical isolates of Pseudomonas aeruginosa. Antimicrob Agents Chemother. 2009; 53 (12): 5150–4. Available from: https://doi.org/10.1128/AAC.00893-09 .
  22. Miller AK, Brannon MK, Stevens L, Johansen HK, Selgrade SE, Miller SI, et al. PhoQ mutations promote lipid A modification and polymyxin resistance of Pseudomonas aeruginosa found in colistin-treated cystic fibrosis patients. Antimicrob Agents Chemother. 2011; 55 (12): 5761–9. Available from: https://doi.org/10.1128/AAC.05391-11.