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Record W3092687430 · doi:10.1099/mgen.0.000454

Azithromycin resistance mutations in Streptococcus pneumoniae as revealed by a chemogenomic screen

2020· article· en· W3092687430 on OpenAlex
Hélène Gingras, Kévin Patron, Philippe Leprohon, Marc Ouellette

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMicrobial Genomics · 2020
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
Keywords23S ribosomal RNAStreptococcus pneumoniaeMutagenesisAzithromycinBiologyGlutamineMutantGeneRibosomal RNAMutationGeneticsMicrobiologyPhenotypeRibosomal proteinBacterial geneticsAntibioticsRNAEscherichia coliRibosomeAmino acid

Abstract

fetched live from OpenAlex

We report on the combination of chemical mutagenesis, azithromycin selection and next-generation sequencing (Mut-Seq) for the identification of small nucleotide variants that decrease the susceptibility of Streptococcus pneumoniae to the macrolide antibiotic azithromycin. Mutations in the 23S ribosomal RNA or in ribosomal proteins can confer resistance to macrolides and these were detected by Mut-Seq. By concentrating on recurrent variants, we could associate mutations in genes implicated in the metabolism of glutamine with decreased azithromycin susceptibility among S. pneumoniae mutants. Glutamine synthetase catalyses the transformation of glutamate and ammonium into glutamine and its chemical inhibition is shown to sensitize S. pneumoniae to antibiotics. A mutation affecting the ribosomal-binding site of a putative ribonuclease J2 is also shown to confer low-level resistance. Mut-Seq has the potential to reveal chromosomal changes enabling high resistance as well as novel events conferring more subtle phenotypes.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.823
Threshold uncertainty score1.000

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 head0.013
GPT teacher head0.248
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