<i>Enterococcus faecalis</i> Induces Aneuploidy and Tetraploidy in Colonic Epithelial Cells through a Bystander Effect
Bibliographic record
Abstract
Intestinal commensals are potential important contributors to the etiology of sporadic colorectal cancer, but mechanisms by which bacteria can initiate tumors remain uncertain. Herein, we describe mechanisms that link Enterococcus faecalis, a bacterium known to produce extracellular superoxide, to the acute induction of chromosomal instability. Immortalized human and nontransformed murine colonic epithelial cells, along with a mouse colonic ligation model, were used to assess the effect of E. faecalis on genomic DNA stability and damage. We found that this human intestinal commensal generated aneuploidy, tetraploidy, and gammaH2AX foci in HCT116, RKO, and YAMC cells. In addition, direct exposure of E. faecalis to these cells induced a G2 cell cycle arrest. Similar observations were noted by exposing cells to E. faecalis-infected macrophages in a dual-chamber coculture system for detecting bystander effects. Manganese superoxide dismutase, catalase, and tocopherols attenuated, and caffeine and inhibitors of glutathione synthase exacerbated, the aneugenic effects and linked the redox-active phenotype of this intestinal commensal to potentially transforming events. These findings provide novel insights into mechanisms by which E. faecalis and intestinal commensals can contribute to cellular transformation and tumorigenesis.
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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".