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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 (2023). PorinPredict: In Silico Identification of OprD Loss from WGS Data for Improved Genotype-Phenotype Predictions of P. aeruginosa Carbapenem Resistance. Microbiology Spectrum, 11(2):e0358822.

Abstract

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.

Abstract

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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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Medical Microbiology
Dewey Decimal Classification:610 Medicine & health
570 Life sciences; biology
Scopus Subject Areas:Life Sciences > Physiology
Physical Sciences > Ecology
Life Sciences > General Immunology and Microbiology
Life Sciences > Genetics
Health Sciences > Microbiology (medical)
Life Sciences > Cell Biology
Health Sciences > Infectious Diseases
Uncontrolled Keywords:Pseudomonas aeruginosa; antimicrobial resistance; carbapenem resistance; genotype-phenotype predictions; inactivating mutations; meropenem resistance; outer membrane porin; outer membrane porin OprD; surveillance; whole-genome sequencing
Language:English
Date:13 April 2023
Deposited On:18 Dec 2023 12:00
Last Modified:29 Jun 2024 01:41
Publisher:American Society for Microbiology
ISSN:2165-0497
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1128/spectrum.03588-22
PubMed ID:36715510
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)