SINGLE CELL RESOLUTION OF THE ADULT ZEBRAFISH INTESTINE UNDER CONVENTIONAL CONDITIONS, AND IN RESPONSE TO AN ACUTE <i>VIBRIO CHOLERAE</i> INFECTION
Bibliographic record
Abstract
ABSTRACT Vibrio cholerae is an aquatic bacterium that primarily infects the gastrointestinal tract, causing the severe and potentially deadly diarrheal disease, cholera. Despite the impact of Vibrio on global health, our understanding of host mucosal responses to the pathogen at the site of infection remains limited, highlighting a critical knowledge gap that must be addressed to develop more effective prevention and treatment strategies. Using a natural infection model, we combined physiological and single-cell transcriptomic studies to characterize adult zebrafish guts raised under conventional conditions and after a challenge with Vibrio . We discovered that Vibrio causes a mild mucosal immune response characterized by T cell activation and enhanced antigen capture in the epithelium. Additionally, we discovered that Vibrio suppresses host interferon signaling, and that ectopic activation of interferon significantly alters the course of infection. Notably, we also found that the adult zebrafish gut shares many similarities with mammalian counterparts, including the presence of previously undescribed Best4+ cells, tuft cells, and a population of basal cycling cells. These discoveries provide important insights into host-pathogen interactions and emphasize the utility of zebrafish as a natural model of Vibrio infection.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".