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Record W4200251363 · doi:10.1128/mbio.03137-21

OXA-23 β-Lactamase Overexpression in Acinetobacter baumannii Drives Physiological Changes Resulting in New Genetic Vulnerabilities

2021· article· en· W4200251363 on OpenAlexafffund
Jennifer M. Colquhoun, Marjan Farokhyfar, Anna R. Hutcheson, Alexander C. Anderson, Christopher R. Bethel, Robert A. Bonomo, Anthony J. Clarke, Philip N. Rather

Bibliographic record

VenuemBio · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsWilfrid Laurier UniversityUniversity of Guelph
FundersNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaNational Institute of Allergy and Infectious DiseasesU.S. Department of Veterans Affairs
KeywordsAcinetobacter baumanniiMicrobiologyBiologyComputational biologyBacteriaGeneticsPseudomonas aeruginosa

Abstract

fetched live from OpenAlex

Acinetobacter baumannii has become a serious pathogen in both hospital and community settings. The β-lactam class of antibiotics is a primary treatment option for A. baumannii infections, and expression of β-lactamases is the most frequent mechanism of resistance in this bacterium. New approaches to treating multidrug-resistant A. baumannii strains are needed. In this study, we demonstrate that overexpressing the OXA-23 β-lactamase leads to significant collateral changes, where peptidoglycan structure is altered. We have identified genes that become selectively essential in OXA-23-expressing strains and confirmed the relationship between altered peptidoglycan and OXA-23 expression by demonstrating that OXA-23 overexpression sensitizes cells to genetic and chemical inhibition of peptidoglycan synthesis. This work paves the way for the identification of new antimicrobial targets, where inhibitors would selectively kill β-lactamase-expressing strains.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.265
Teacher spread0.246 · 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 teacher head, 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

Citations32
Published2021
Admission routes2
Has abstractyes

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