Mapping of <i>Shigella flexneri</i>’s tissue distribution and type III secretion apparatus activity during infection of the large intestine of guinea pigs
Bibliographic record
Abstract
Shigella spp. are bacterial pathogens that invade the human colonic mucosa using a type III secretion apparatus (T3SA), a proteinaceous device activated upon contact with host cells. Active T3SAs translocate proteins that carve the intracellular niche of Shigella spp. Nevertheless, the activation state of the T3SA has not been addressed in vivo. Here, we used a green fluorescent protein transcription-based secretion activity reporter (TSAR) to provide a spatio-temporal description of S. flexneri T3SAs activity in the colon of Guinea pigs. First, we observed that early mucus release is triggered in the vicinity of luminal bacteria with inactive T3SA. Subsequent mucosal invasion showed bacteria with active T3SA associated with the brush border, eventually penetrating into epithelial cells. From 2 to 8 h post-challenge, the infection foci expanded, and these intracellular bacteria displayed homogeneously high-secreting activity, while extracellular foci within the lamina propria featured bacteria with low secretion activity. We also found evidence that within lamina propria macrophages, bacteria reside in vacuoles instead of accessing the cytosol. Finally, bacteria were cleared from tissues between 8 and 24 h post-challenge, highlighting the hit-and-run colonization strategy of Shigella. This study demonstrates how genetically encoded reporters can contribute to deciphering pathogenesis in vivo.
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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) | 0.000 | 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 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".