Copper resistance in <i>Legionella pneumophila</i> : role of genetic factors and host cells
Bibliographic record
Abstract
Abstract Copper is frequently found in drinking water due to its presence in the natural environment and the widespread usage of copper pipes. This toxic metal has a well-known antimicrobial activity, an activity harnessed in copper-silver ionization (CSI) to eliminate the opportunistic pathogen Legionella pneumophila from engineered water systems. Despite utilizing the antimicrobial properties of copper in Legionella control, little is known about how copper containing environments affect L. pneumophila populations. The goal of this study is to understand how L. pneumophila responds to copper within a hot water distribution system (HWDS) environment. To answer this question, different sequence types and regulatory mutants were exposed to copper to compare their survival. L. pneumophila isolates of 4 sequence types from 3 different HWDSs exhibited a wide diversity of phenotypes after copper stress. The Δ letA and Δ letS mutants were sensitive to copper, indicating that the LetAS two component system is important for copper resistance. Additionaly, transmissive phase cultures were more resistant to copper than replicative phase cultures. Therefore, the regulation of entry into transmissive phase by the LetAS system is essential for L. pneumophila’ s ability to survive copper stress. In a water system, L. pneumophila replicates within eukaryotic hosts. When cocultured with the host ciliate Tetrahymena pyriformis , L. pneumophila was more resistant to copper than when the bacteria were in a monoculture. No difference in L. pneumophila replication inside of hosts in cocultures with or without copper was observed. This result confirms that the presence of host cells protects L. pneumophila from copper stress. Therefore, presence of host cells in water system may limit the efficacy of copper-based control strategies.
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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 | 0.001 | 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".