Gut microbiota regulates intestinal goblet cell response and mucin production by influencing the TLR2-SPDEF axis in an enteric parasitic infection
Bibliographic record
Abstract
Alterations in goblet cell biology constitute one of the most effective host responses against enteric parasites. In the gastrointestinal (GI) tract, millions of bacteria influence these goblet cell responses by binding to pattern recognition receptors such as toll-like receptors (TLRs). Studies suggest that the gut microbiota also interacts bidirectionally with enteric parasites, including Trichuris muris . Here, we study the roles of T. muris -altered microbiota and the TLR2-SPDEF axis in parasitic host defense. In acute T. muris infection, we observed altered gut microbiota composition, which, when transferred to germ-free mice, resulted in increased goblet cell numbers, Th2 cytokines and Muc2 expression, as well as increased Tlr2 . Further, antibiotic (ABX)-treated TLR2 -/- mice, despite having received the same T. muris -altered microbiota, displayed diminished Th2 response, Muc2 expression, and, intriguingly, diminished SPDEF expression compared to wildtype counterparts. When infected with T. muris , SPDEF -/- mice exhibited a reduced Th2 response and altered microbial composition compared to SPDEF +/+ , particularly on day 14 post-infection, and this microbiota was sufficient to alter host goblet cell response when transferred to ABX-treated mice. Taken together, our findings suggest the TLR2-SPDEF axis, via T. muris -induced microbial changes, is an important regulator of goblet cell function and host's parasitic defense.
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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) | 0.001 | 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".