Penicillin induces alterations in glutamine metabolism in Streptococcus pneumoniae
Bibliographic record
Abstract
Penicillin is a bactericidal antibiotic that inhibits the synthesis of the peptidoglycan by targeting penicillin-binding proteins. This study aimed to assess through transcriptional profiling the stress response of S. pneumoniae strains after exposure to lethal penicillin concentrations to understand further the mode of action of penicillin. Two experimental designs (time-course and dose-response) were used for monitoring the effect of penicillin on the transcriptional profile. The expression of some genes previously shown to be modulated by penicillin was altered, including ciaRH, pstS and clpL. Genes of the glnRA and glnPQ operons were among the most downregulated genes in the three strains. These genes are involved in glutamine synthesis and uptake and LC-MS work confirmed that penicillin treatment increases the intracellular glutamine concentrations. Glutamine conferred a protective role against penicillin when added to the culture medium. Glutamine synthetase encoded by glnA catalyses the transformation of glutamate and ammonium into glutamine and its chemical inhibition by the inhibitor L-methionine sulfoximine is shown to sensitize S. pneumoniae to penicillin, including penicillin-resistant clinical isolates. In summary, a combination of RNA-seq and metabolomics revealed that penicillin interferes with glutamine metabolism suggesting strategies that could eventually be exploited for combination therapy or for reversal of 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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".