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Record W4410743623 · doi:10.1111/1348-0421.13227

Lytic Transglycosylase Deficiency Increases Susceptibility to β‐lactam Antibiotics But Reduces Susceptibility to Vancomycin in <i>Escherichia coli</i>

2025· article· en· W4410743623 on OpenAlexfundno aff
Kazuya Ishikawa, Ryosuke Nakagawa, Kazuyuki Furuta, Chikara Kaito

Bibliographic record

VenueMicrobiology and Immunology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceKeio University
KeywordsLytic cycleEscherichia coliAntibioticsMicrobiologyVancomycinBiologyBeta-lactamEnterobacteriaceaeBacteriaGeneticsStaphylococcus aureusGene

Abstract

fetched live from OpenAlex

In Staphylococcus aureus, a gram-positive pathogen, vancomycin-resistant strains become susceptible to β-lactam antibiotics, referred to as the "seesaw effect." However, in gram-negative bacteria, the phenomenon is less clear. Here, we analyzed the gene-knockout effects of eight lytic transglycosylases (slt, mltA, mltB, mltC, mltD, mltE, mltF, mltG) on antibiotic sensitivity in Escherichia coli. Knockout of both slt and mltG increased sensitivity to β-lactam antibiotics and reduced sensitivity to vancomycin. The β-lactam antibiotic sensitivity and vancomycin resistance of the slt-knockout mutant were abolished by the introduction of the wild-type slt gene but remained unchanged by the introduction of the mutant slt gene encoding an amino acid substitution variant of the transglycosylase catalytic centre. The double-knockout strain for slt and mltB was more sensitive to ampicillin and more resistant to vancomycin than each single-knockout strain. The double-knockout strain for slt and mltG was more sensitive to ampicillin and more resistant to vancomycin than each single-knockout strain. These results suggest that loss of lytic transglycosylase activity causes β-lactam antibiotic sensitivity and vancomycin resistance in E. coli.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.241
Teacher spread0.235 · 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.

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

Citations5
Published2025
Admission routes1
Has abstractyes

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