Heme oxygenase activates calcium release from the endoplasmic reticulum of bovine mammary epithelial cells to promote TFEB entry into the nucleus to reduce the intracellular load of Mycoplasma bovis
Bibliographic record
Abstract
Heme oxygenase HO-1 (HMOX) regulates cellular inflammation and apoptosis, but its role in regulation of autophagy in Mycoplasma bovis infection is unknown. The objective was to determine how the HO-1/CO- Protein kinase RNA-like endoplasmic reticulum kinase (PERK)-Ca2+- transcription factor EB (TFEB) signaling axis induces autophagy and regulates clearance of M. bovis by bovine mammary epithelial cells (bMECs). M. bovis inhibited autophagy and lysosomal biogenesis in bMECs and suppressed HO-1 protein and expression of related proteins, namely nuclear factor erythroid 2-related factor 2 (Nrf2) and Kelch-like ECH-associated protein 1 (keap1). Activation of HO-1 and its production of carbon monoxide (CO) were required for induction of autophagy and clearance of intracellular M. bovis. Furthermore, when HO-1 was deficient, CO sustained cellular autophagy. HO-1 activation increased intracellular calcium (Ca2+) and cytosolic localization activity of TFEB via PERK. Knockdown of PERK or chelation of intracellular Ca2+ inhibited HO-1-induced M. bovis autophagy and clearance. M. bovis infection affected nuclear localization of lysosomal TFEB in the MiT/TFE transcription factor subfamily, whereas activation of HO-1 mediated dephosphorylation and intranuclear localization of TFEB, promoting autophagy, lysosomal biogenesis and autophagic clearance of M. bovis. Nuclear translocation of TFEB in HO-1 was critical to induce M. bovis transport and survival of infected bMECs. Furthermore, the HO-1/CO-PERK-Ca2+-TFEB signaling axis induced autophagy and M. bovis clearance, providing a viable approach to treat persistent M. bovis infections.
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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".