MétaCan
Menu
Back to cohort
Record W4297457254 · doi:10.1371/journal.pbio.3001808

Low levels of tetracyclines select for a mutation that prevents the evolution of high-level resistance to tigecycline

2022· article· en· W4297457254 on OpenAlexfundno aff
Jennifer Jagdmann, Dan I. Andersson, Hervé Nicoloff

Bibliographic record

VenuePLoS Biology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
FundersFP7 HealthUniversiteit AntwerpenGenome Institute of SingaporeUppsala UniversitetVetenskapsrådetVrije Universiteit BrusselKnut och Alice Wallenbergs StiftelseUniversity of WashingtonLunds UniversitetUniversité Paris-Est Créteil Val-de-MarneInstitut National de la Recherche AgronomiqueInstitut National de la Santé et de la Recherche MédicaleMcMaster UniversityInternational Center for Genetic Engineering and Biotechnology
KeywordsTigecyclineTetRBiologyEffluxGeneticsEscherichia coliMutationTetracyclineMutantGeneMicrobiologyRepressorAntibioticsGene expression

Abstract

fetched live from OpenAlex

In a collection of Escherichia coli isolates, we discovered a new mechanism leading to frequent and high-level tigecycline resistance involving tandem gene amplifications of an efflux pump encoded by the tet(A) determinant. Some isolates, despite carrying a functional tet(A), could not evolve high-level tigecycline resistance by amplification due to the presence of a deletion in the TetR(A) repressor. This mutation impaired induction of tetA(A) (encoding the TetA(A) efflux pump) in presence of tetracyclines, with the strongest effect observed for tigecycline, subsequently preventing the development of tet(A) amplification-dependent high-level tigecycline resistance. We found that this mutated tet(A) determinant was common among tet(A)-carrying E. coli isolates and analysed possible explanations for this high frequency. First, while the mutated tet(A) was found in several ST-groups, we found evidence of clonal spread among ST131 isolates, which increases its frequency within E. coli databases. Second, evolution and competition experiments revealed that the mutation in tetR(A) could be positively selected over the wild-type allele at sub-inhibitory concentrations of tetracyclines. Our work demonstrates how low concentrations of tetracyclines, such as those found in contaminated environments, can enrich and select for a mutation that generates an evolutionary dead-end that precludes the evolution towards high-level, clinically relevant tigecycline resistance.

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 score0.080
Threshold uncertainty score0.367

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 head0.028
GPT teacher head0.282
Teacher spread0.254 · 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

Citations12
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePLoS BiologySame topicAntibiotic Resistance in BacteriaFrench-language works237,207