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PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance

The increasing integration of genomics into routine clinical diagnostics requires reliable computational tools to identify determinants of antimicrobial resistance (AMR) from whole-genome sequencing data. Here, we developed PorinPredict, a bioinformatic tool that predicts defects of the Pseudomonas...

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Autores principales: Biggel, Michael, Johler, Sophia, Roloff, Tim, Tschudin-Sutter, Sarah, Bassetti, Stefano, Siegemund, Martin, Egli, Adrian, Stephan, Roger, Seth-Smith, Helena M. B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10100854/
https://www.ncbi.nlm.nih.gov/pubmed/36715510
http://dx.doi.org/10.1128/spectrum.03588-22
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author Biggel, Michael
Johler, Sophia
Roloff, Tim
Tschudin-Sutter, Sarah
Bassetti, Stefano
Siegemund, Martin
Egli, Adrian
Stephan, Roger
Seth-Smith, Helena M. B.
author_facet Biggel, Michael
Johler, Sophia
Roloff, Tim
Tschudin-Sutter, Sarah
Bassetti, Stefano
Siegemund, Martin
Egli, Adrian
Stephan, Roger
Seth-Smith, Helena M. B.
author_sort Biggel, Michael
collection PubMed
description The increasing integration of genomics into routine clinical diagnostics requires reliable computational tools to identify determinants of antimicrobial resistance (AMR) from whole-genome sequencing data. Here, we developed PorinPredict, a bioinformatic tool that predicts defects of the Pseudomonas aeruginosa outer membrane porin OprD, which are strongly associated with reduced carbapenem susceptibility. PorinPredict relies on a database of intact OprD variants and reports inactivating mutations in the coding or promoter region. PorinPredict was validated against 987 carbapenemase-negative P. aeruginosa genomes, of which OprD loss was predicted for 454 out of 522 (87.0%) meropenem-nonsusceptible and 46 out of 465 (9.9%) meropenem-susceptible isolates. OprD loss was also found to be common among carbapenemase-producing isolates, resulting in even further increased MICs. Chromosomal mutations in quinolone resistance-determining regions and OprD loss commonly co-occurred, likely reflecting the restricted use of carbapenems for multidrug-resistant infections as recommended in antimicrobial stewardship programs. In combination with available AMR gene detection tools, PorinPredict provides a robust and standardized approach to link P. aeruginosa phenotypes to genotypes. IMPORTANCE Pseudomonas aeruginosa is a major cause of multidrug-resistant nosocomial infections. The emergence and spread of clones exhibiting resistance to carbapenems, a class of critical last-line antibiotics, is therefore closely monitored. Carbapenem resistance is frequently mediated by chromosomal mutations that lead to a defective outer membrane porin OprD. Here, we determined the genetic diversity of OprD variants across the P. aeruginosa population and developed PorinPredict, a bioinformatic tool that enables the prediction of OprD loss from whole-genome sequencing data. We show a high correlation between predicted OprD loss and meropenem nonsusceptibility irrespective of the presence of carbapenemases, which are a second widespread determinant of carbapenem resistance. Isolates with resistance determinants to other antibiotics were disproportionally affected by OprD loss, possibly due to an increased exposure to carbapenems. Integration of PorinPredict into genomic surveillance platforms will facilitate a better understanding of the clinical impact of OprD modifications and transmission dynamics of resistant clones.
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spelling pubmed-101008542023-04-14 PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance Biggel, Michael Johler, Sophia Roloff, Tim Tschudin-Sutter, Sarah Bassetti, Stefano Siegemund, Martin Egli, Adrian Stephan, Roger Seth-Smith, Helena M. B. Microbiol Spectr Research Article The increasing integration of genomics into routine clinical diagnostics requires reliable computational tools to identify determinants of antimicrobial resistance (AMR) from whole-genome sequencing data. Here, we developed PorinPredict, a bioinformatic tool that predicts defects of the Pseudomonas aeruginosa outer membrane porin OprD, which are strongly associated with reduced carbapenem susceptibility. PorinPredict relies on a database of intact OprD variants and reports inactivating mutations in the coding or promoter region. PorinPredict was validated against 987 carbapenemase-negative P. aeruginosa genomes, of which OprD loss was predicted for 454 out of 522 (87.0%) meropenem-nonsusceptible and 46 out of 465 (9.9%) meropenem-susceptible isolates. OprD loss was also found to be common among carbapenemase-producing isolates, resulting in even further increased MICs. Chromosomal mutations in quinolone resistance-determining regions and OprD loss commonly co-occurred, likely reflecting the restricted use of carbapenems for multidrug-resistant infections as recommended in antimicrobial stewardship programs. In combination with available AMR gene detection tools, PorinPredict provides a robust and standardized approach to link P. aeruginosa phenotypes to genotypes. IMPORTANCE Pseudomonas aeruginosa is a major cause of multidrug-resistant nosocomial infections. The emergence and spread of clones exhibiting resistance to carbapenems, a class of critical last-line antibiotics, is therefore closely monitored. Carbapenem resistance is frequently mediated by chromosomal mutations that lead to a defective outer membrane porin OprD. Here, we determined the genetic diversity of OprD variants across the P. aeruginosa population and developed PorinPredict, a bioinformatic tool that enables the prediction of OprD loss from whole-genome sequencing data. We show a high correlation between predicted OprD loss and meropenem nonsusceptibility irrespective of the presence of carbapenemases, which are a second widespread determinant of carbapenem resistance. Isolates with resistance determinants to other antibiotics were disproportionally affected by OprD loss, possibly due to an increased exposure to carbapenems. Integration of PorinPredict into genomic surveillance platforms will facilitate a better understanding of the clinical impact of OprD modifications and transmission dynamics of resistant clones. American Society for Microbiology 2023-01-30 /pmc/articles/PMC10100854/ /pubmed/36715510 http://dx.doi.org/10.1128/spectrum.03588-22 Text en Copyright © 2023 Biggel et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research Article
Biggel, Michael
Johler, Sophia
Roloff, Tim
Tschudin-Sutter, Sarah
Bassetti, Stefano
Siegemund, Martin
Egli, Adrian
Stephan, Roger
Seth-Smith, Helena M. B.
PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance
title PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance
title_full PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance
title_fullStr PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance
title_full_unstemmed PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance
title_short PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance
title_sort porinpredict: in silico identification of oprd loss from wgs data for improved genotype-phenotype predictions of p. aeruginosa carbapenem resistance
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10100854/
https://www.ncbi.nlm.nih.gov/pubmed/36715510
http://dx.doi.org/10.1128/spectrum.03588-22
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