Molecular regulation of virulence in <i>Legionella pneumophila</i>
Bibliographic record
Abstract
Legionella pneumophila is a gram-negative bacteria found in natural and anthropogenic aquatic environments such as evaporative cooling towers, where it reproduces as an intracellular parasite of cohabiting protozoa. If L. pneumophila is aerosolized and inhaled by a susceptible person, bacteria may colonize their alveolar macrophages causing the opportunistic pneumonia Legionnaires' disease. L. pneumophila utilizes an elaborate regulatory network to control virulence processes such as the Dot/Icm Type IV secretion system and effector repertoire, responding to changing nutritional cues as their host becomes depleted. The bacteria subsequently differentiate to a transmissive state that can survive in the environment until a replacement host is encountered and colonized. In this review, we discuss the lifecycle of L. pneumophila and the molecular regulatory network that senses nutritional depletion via the stringent response, a link to stationary phase-like metabolic changes via alternative sigma factors, and two-component systems that are homologous to stress sensors in other pathogens, to regulate differentiation between the intracellular replicative phase and more transmissible states. Together, we highlight how this prototypic intracellular pathogen offers enormous potential in understanding how molecular mechanisms enable intracellular parasitism and pathogenicity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".