Mycoplasma bovis inhibits autophagy in bovine mammary epithelial cells via a PTEN/PI3K-Akt-mTOR-dependent pathway
Bibliographic record
Abstract
Although autophagy can eliminate some intracellular pathogens, others, e.g., Staphylococcus aureus , Salmonella, Mycoplasma bovis , can evade it. The phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) pathway, a key regulator of autophagy, is involved in initiation and promotion of a range of pathological diseases. As the effects of M. bovis on the autophagic pathway are not well documented, our objective was to elucidate the effects of M. bovis infection on the PI3K-Akt-mTOR cellular autophagic pathway in bovine mammary epithelial cells (bMECs). Ultrastructure of bMECs infected with M. bovis was assessed with transmission electron microscopy, co-localization of LC3 puncta with M. bovis was confirmed by laser confocal microscopy, and autophagy-related indicators were quantified with Western blotting and RT-PCR. In M. bovis -infected bMECs, intracellular M. bovis was encapsulated by membrane-like structures, the expression level of LC3-II and Beclin1 protein decreased at the middle stage of infection, degradation of SQSTM1/P62 was blocked, autophagy of bMECs was inhibited, and PI3K-Akt-mTOR protein was activated by phosphorylation. Furthermore, the tumor suppressor PTEN can inhibit the PI3K-Akt signaling pathway through dephosphorylation of phosphatidylinositol 3,4,5-trisphosphate and may be important for cellular resistance to infection. In the present study, the number of intracellular M. bovis was inversely related to the change in the level of autophagy markers (e.g., LC3-II, SQSTM1/P62) within host cells induced by the low knockdown of Akt or PTEN. We concluded that M. bovis -infected bMECs alleviated cellular autophagy through a PI3K-Akt-mTOR pathway, and that PTEN acted as a protective gene regulating autophagy, a key step in controlling infection.
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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".