Giardia duodenalis stabilizes HIF-1α and induces glycolytic alterations in intestinal epithelial cells
Bibliographic record
Abstract
The gastrointestinal epithelium relies on activation of the hypoxia-inducible factor (HIF) to promote cell survival and maintain bioenergetic homeostasis during hypoxia. While many pathogens can activate HIF, the effects of enteric protozoa on HIF activation in gastrointestinal epithelial cells remain unclear. Giardia duodenalis , a prevalent protozoan enteropathogen, causes intestinal barrier dysfunction characterized by epithelial malabsorption, mucus depletion, altered mucin glycosylation, and microbiota dysbiosis. Findings from the present study reveal an epithelial hypoxic signature upon Giardia infection. Human intestinal epithelial cells were exposed to vehicle or Giardia duodenalis isolate GS/M under normoxic (21% O 2 ) or hypoxic (1% O 2 ) conditions. In normoxia, infected cells displayed a time-dependent increase in HIF-1α protein expression, the oxygen-dependent subunit of HIF-1. In normoxia, Giardia infection upregulated HIF-1 target genes involved in cellular stress (i.e., VEGFA , ANKRD37 , GADD45A ) and glycolysis (i.e., HK2 , LDHA ). This was accompanied by changes in the abundance of glycolytic intermediates (i.e., glucose-6-phosphate, pyruvate, lactate). Although infection in hypoxia failed to augment the hypoxia-induced HIF-1α stabilization, HIF-1 target genes were still upregulated, albeit to a lesser degree. These findings indicate that Giardia induces a transient epithelial hypoxic response in normoxic conditions, revealing a hitherto unrecognized epithelial rescue response to this intestinal parasite.
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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) | 0.001 | 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".