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Record W4413055865 · doi:10.1021/acsinfecdis.5c00268

Rapid Detection of Carbapenemase-Producing Enterobacterales Using a Luminescent Whole-Cell Biosensor

2025· article· en· W4413055865 on OpenAlexafffund
Mitchell A Jeffs, Shreyas Bhat, Josephine L Liu, Rachel A. V. Gray, Xena X. Li, Prameet M. Sheth, Christopher T. Lohans

Bibliographic record

VenueACS Infectious Diseases · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsKingston Health Sciences CentreToronto General HospitalSunnybrook Health Science CentreHealth Sciences CentreQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiosensorMicrobiologyAntibioticsAntimicrobialBiologyClinical microbiology

Abstract

fetched live from OpenAlex

Carbapenemase-producing Enterobacterales (CPE) pose an urgent global health threat due to their ability to inactivate carbapenems, a group of last-resort antibiotics. Infections caused by these pathogens are associated with poor patient outcomes, high mortality rates, and added burden to infection prevention and control programs, making early detection vital to ensure optimal antimicrobial therapy and appropriate implementation of infection control practices. In this study, we report the application of a luminescent whole-cell biosensor for the rapid detection of CPE. This biosensor provides positive test results within 2.5 h, inclusive of setup time, and has been validated with a panel of laboratory and clinical isolates producing a diverse range of carbapenemases (KPC, NDM, IMP, VIM, and OXA-48-like). The assay identified 81/83 CPE isolates tested with a sensitivity of 97.5%, including strains producing weak OXA-48-like carbapenemases, which are sometimes missed by currently used detection methods. The assay also demonstrated a specificity of 100%, with all non-CPE clinical isolates testing negative under the optimized assay conditions. Due to the rapid time-to-positivity, minimal setup requirements, and high sensitivity, this test could serve as an attractive alternative to CPE detection methods currently employed by clinical microbiology laboratories and could also facilitate CPE screening in other settings ( e.g., environmental and agricultural).

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.729

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 head0.008
GPT teacher head0.241
Teacher spread0.233 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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