<i>Listeria monocytogenes</i>Evades Killing by Autophagy During Colonization of Host Cells
Bibliographic record
Abstract
Listeria monocytogenes is an intracellular pathogen that is able to colonize the cytosol of macrophages. Here we examined the interaction of this pathogen with autophagy, a host cytosolic degradative pathway that constitutes an important component of innate immunity towards microbial invaders. L. monocytogenes infection induced activation of the autophagy system in macrophages. At 1 h post infection (p.i.), a population of intracellular bacteria ( approximately 37%) colocalized with the autophagy marker LC3. These bacteria were within vacuoles and were targeted by autophagy in an LLO-dependent manner. At later stages in infection (by 4 h p.i.), the majority of L. monocytogenes escaped into the cytosol and rapidly replicated. At these times, less than 10% of intracellular bacteria colocalized with LC3. We found that ActA expression was sufficient to prevent autophagy of bacteria in the cytosol of macrophages. Surprisingly, ActA expression was not strictly necessary, indicating that other virulence factors were involved. Accordingly, we also found a role for the bacterial phospholipases, PI-PLC and PC-PLC, in autophagy evasion, as bacteria lacking phospholipase expression were targeted by autophagy at later times in infection. Together, our results demonstrate that L. monocytogenes utilizes multiple mechanisms to avoid destruction by the autophagy system during colonization of macrophages.
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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".