D-Serine reduces the expression of the cytopathic genotoxin colibactin
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Bibliographic record
Abstract
Some Escherichia coli strains harbour the pks island, a 54 kb genomic island en-coding the biosynthesis genes for a genotoxic compound named colibactin. In eukaryotic cells, colibactin can induce DNA damage, cell cycle arrest and chro-mosomal instability. Production of colibactin has been implicated in the devel-opment of colorectal cancer (CRC). In this study, we demonstrate the inhibito-ry effect of D-Serine on the expression of the pks island in both prototypic and clinically-associated colibactin-producing strains and determine the implications for cytopathic effects on host cells. We also tested a comprehensive panel of proteinogenic L-amino acids and corresponding D-enantiomers for their ability to modulate clbB transcription. Whilst several D-amino acids exhibited the abil-ity to inhibit expression of clbB, D-Serine exerted the strongest repressing ac-tivity (>3.8-fold) and thus, we focussed additional experiments on D-Serine. To investigate the cellular effect, we investigated if repression of colibactin by D-Serine could reduce the cytopathic responses normally observed during infec-tion of HeLa cells with pks+ strains. Levels of γ-H2AX (a marker of DNA double strand breaks) were reduced 2.75-fold in cells infected with D-Serine treat-ment. Moreover, exposure of pks+ E. coli to D-Serine during infection caused a reduction in cellular senescence that was observable at 72 h post infection. The recent finding of an association between pks-carrying commensal E. coli and CRC, highlights the necessity for the development of colibactin targeting thera-peutics. Here we show that D-Serine can reduce expression of colibactin, and inhibit downstream cellular cytopathy, illuminating its potential to prevent colibactin-associated disease.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it