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Record W4387114306 · doi:10.1128/msphere.00162-23

Vaborbactam increases meropenem susceptibility in <i>Pseudomonas aeruginosa</i> clinical isolates displaying MexXY and AmpC upregulation

2023· article· en· W4387114306 on OpenAlexfundno aff
Mariana Castanheira, Timothy B Doyle, Cory Hubler, Sean DeVries, Dee Shortridge

Bibliographic record

VenuemSphere · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
FundersMedical Center, University of RochesterNational Institutes of HealthIdorsia PharmaceuticalsWockhardtTenNor TherapeuticsAstellas Foundation for Research on Metabolic DisordersBasilea PharmaceuticaAstellas PharmaNorth Bristol NHS TrustShionogiMeiji Seika PharmaUniversity of QueenslandPfizerMelinta TherapeuticsEntasis TherapeuticsAlbany College of Pharmacy and Health SciencesAchaogenAmplyxRoivant SciencesNational University of SingaporeNabriva TherapeuticsGenePOCUniversity of Texas Southwestern Medical CenterMedicines CompanyUniversity of North TexasNovartisHarvard UniversityF. Hoffmann-La RocheWayne State UniversityMedpaceGlaxoSmithKlineAllerganCidara TherapeuticsUniversity of Southern CaliforniaTufts Medical CenterBayerBeth Israel Deaconess Medical Center
KeywordsPseudomonas aeruginosaMeropenemMicrobiologyBiologyPseudomonadaceaeGeneAntibioticsBacteriaAntibiotic resistanceGenetics

Abstract

fetched live from OpenAlex

ABSTRACT To evaluate the resistance mechanisms among Pseudomonas aeruginosa clinical isolates exhibiting meropenem (MEM) MIC values higher than meropenem-vaborbactam (MEV). P. aeruginosa clinical isolates collected in US hospitals from 2014 to 2019 were susceptibility tested. Whole-genome and transcriptome sequencing were performed. Results were analyzed for strain typing, acquired β-lactamases, and mutations in chromosomal genes; gene expression was measured for known β-lactam resistance contributors. Results were compared to a control group of 10 P . aeruginosa isolates displaying MIC values at 8 mg/L for meropenem ± vaborbactam (MEM = MEV). Out of 88 isolates displaying MEM > MEV, 33 (37.5%) isolates had reproducibly lower MIC values for meropenem-vaborbactam compared to meropenem when retested. The expression of mexX , mexY , mexZ , and ampC was significantly greater among a higher percentage of the MEM > MEV isolates. Furthermore, the association of mexXY and ampC overexpression was detected in 17/33 MEM > MEV isolates and only 1/10 MEM = MEV isolate. In addition, the Pseudomonas -derived cephalosporinase amino acid substitution R79Q was detected among 33.3% of the isolates displaying MEM > MEV, and none of the isolates displayed MEM = MEV. Other resistance mechanisms were not observed or were equally observed in both groups. In rare cases, vaborbactam plays a role in lowering the meropenem MIC values in P. aeruginosa clinical isolates likely due to the inhibition of the AmpC gene that was overexpressed in the presence of upregulation of MexXY with or without alterations in the AmpC gene. IMPORTANCE Pseudomonas aeruginosa isolates are intrinsically resistant to multiple antimicrobial agents and meropenem is an important therapeutic option to treat infections caused by this organism. Meropenem-vaborbactam activity is similar to that of meropenem alone against P. aeruginosa isolates. Isolates belonging to this species that display lower meropenem-vaborbactam compared to meropenem are rare. We initiated this study to understand the resistance mechanisms that could lead to lower meropenem-vaborbactam MIC values when compared to meropenem alone. We documented that isolates displaying lower meropenem-vaborbactam exhibited overexpression of MexXY and AmpC. In addition, isolates displaying the R79Q PDC (AmpC) mutation were more likely to display lower meropenem-vaborbactam when compared to isolates displaying the same MIC values for these agents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.299
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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