<i>Giardia</i> spp.-induced microbiota dysbiosis disrupts intestinal mucin glycosylation
Bibliographic record
Abstract
Infection with the protozoan parasite Giardia duodenalis (syn. intestinalis, lamblia) has been associated with intestinal mucus disruptions and microbiota dysbiosis. The mechanisms remain incompletely understood. Mucus consists primarily of densely glycosylated mucin glycoproteins. Mucin O-glycans influence mucus barrier properties and mucin–microbe interactions and are frequently altered during disease. In this study, we observed time-dependent and regiospecific alterations to intestinal mucin glycosylation patterns and the expression of mucin-associated glycosyltransferase genes during Giardia infection. Glycosylation alterations were observed in Giardia-infected mice in the upper small intestine, the site of parasite colonization, and in the distal colon, where active trophozoites were absent. Alterations occurred as early as day 2 post-infection and persisted in mice after parasite clearance. We also observed small intestinal goblet cell hyperplasia and thinning of the distal colon mucus barrier during early infection, and microbiota alterations and altered production of cecal SCFAs. Giardia-induced alterations to mucin glycosylation were at least in part dependent on microbiota dysbiosis, as transplantation of a dysbiotic mucosal microbiota collected from Giardia-infected mice recapitulated some alterations. This study describes a novel mechanism by which Giardia alters intestinal mucin glycosylation, and implicates the small intestinal microbiota in regulation of mucin glycosylation patterns throughout the gastrointestinal tract.
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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".