Commensal-Pathogen Competition Impacts Host Viability
Bibliographic record
Abstract
ABSTRACT While the structure and regulatory networks that govern the activity of the type-six secretion system (T6SS) of Vibrio cholerae are becoming increasingly clear, we know less about the role of the T6SS in disease. Under laboratory conditions, V. cholerae uses the T6SS to outcompete many Gram-negative species, including other V. cholerae strains and human commensal bacteria. However, the role of these interactions has not been resolved in an in-vivo setting. We used the Drosophila melanogaster model of cholera to define the contribution of the T6SS to V. cholerae pathogenesis. Here, we demonstrate that interactions between the T6SS and host commensals impact pathogenesis. Inactivation of the T6SS, or removal of commensal bacteria attenuates disease severity. Re-introduction of the Gram-negative commensal bacterium Acetobacter pasteurianus into a germ-free host is sufficient to restore T6SS-dependent pathogenesis. Together, our data demonstrate that the T6SS acts on commensal bacteria to promote the pathogenesis of V. cholerae .
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".