<i>Streptococcus lutetiensis</i> Induces Autophagy via Oxidative Stress in Bovine Mammary Epithelial Cells
Bibliographic record
Abstract
Streptococcus lutetiensis, an emerging pathogen causing bovine mastitis, has not been well characterized. We reported that S. lutetiensis was pathogenic both in vivo and in vitro and caused inflammatory reactions in the mammary gland. However, roles of autophagy and oxidative stress in the pathogenesis of S. lutetiensis‐induced mastitis are unclear. In this study, an autophagy model of S. lutetiensis‐infected bovine mammary epithelial cells (bMECs) was used to assess oxidative stress and autophagy flux. Expressions of Beclin1, light chain 3II, and Sequestosome 1/p62 were elevated in bMECs after S. lutetiensis infection. In addition, autophagosome and lysosome formation confirmed autophagy occurred. Based on LysoTracker Red and acridine orange, lysosome degradation was blocked, and lower expressions of lysosomal‐associated membrane protein 2, cathepsins D, and cathepsins L confirmed lysosomal damage. Concurrently, the nuclear factor erythroid 2‐related factor 2 (Nrf2), kelch‐like ECH‐associated protein 1 (Keap1), heme oxygenase 1 (HO1), and NAD (P)H: quinone oxidoreductase 1 (NQO1), and basilic proteins associated with the Nrf2/Keap1 signaling pathway, were detected. Decreased keap1 and increased Nrf2, HO1, NQO1, and reactive oxygen species (ROS) indicated increased oxidative stress. Treatment with N‐Acetyl‐L‐cysteine (NAC), an ROS inhibitor, decreased both oxidative stress and autophagy. Therefore, we concluded that S. lutetiensis caused intracellular oxidative stress and autophagy in bMECs. In addition, crosstalk between autophagy and oxidative stress affected the autophagic flux and blocked downstream autophagy. The Nrf2‐keap1‐p62 pathway participated in this process, with ROS acting upstream of these effects, interfering with normal cell functions.
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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".