The impact of viable but non-culturable Legionella pneumophila on detection and disinfection: Searching for viability markers to aid in pathogen risk management
Bibliographic record
Abstract
The introduction of drinking water safety plans in Alberta has resulted in increased attention towards water-based, opportunistic pathogens like Legionella pneumophila, which grow in premise plumbing biofilms and cannot be controlled through drinking water treatment alone. Currently, there are neither specific standards nor regulatory guidelines to control Legionella spp. in Canadian drinking water systems and current culture-based detection is limited by inaccuracy, 10 day incubation periods, and an inability to measure VBNC cells. Thus, it was the objective of this project to improve upon the poor reliability of L. pneumophila detection by examining viability assays that correlate with amoeba infectivity data, which could be coupled with a novel IMS-FCM detection system, in hopes of providing a better, timely estimate of public health risk. Experiments using the novel IMS-FCM detection system revealed sensitivity to L. pneumophila below the recommended action level guidelines given by Public Health Ontario (<100 CFU L-1) for healthcare centres. Dose-response curves were created for L. pneumophila exposed to UV, heat, or monochloramine to evaluate disinfectant efficacy, measured as 4 log10 reductions in culturable cells. UV dose-response curves varied significantly depending on the presence of visible light, which is thought to induce light-activated DNA damage repair machinery, resulting in significant reductions in disinfection efficacy when corrected for. The role of protozoan hosts in L. pneumophila disinfection and human pathogenicity was also examined, with particular focus on amoeba co-cultures of VBNC cells. Correlating L. pneumophila growth in amoebae with activity assays revealed CTC and ATP-based assays that may provide an appropriate measure for public health risk management action, such as when coupled to novel molecular, flow cytometry-based detection systems. The current research has demonstrated the need for an accurate, rapid L. pneumophila detection system for risk management that needs to address near point of use to control aerosol risks from this pathogen. In particular, the potential usefulness of ATP-CTC coupled viability assays for quantifying active, infectious cells was a novel finding of this research, which appear to be a risk to public health. For example, with point of use UV disinfection up to recommended guidelines of 16 mJ cm-2, current culture-based detection would be unable to identify VBNC cells that remain infectious to A. polyphaga hosts and potentially human lung macrophages. The development of water safety plans through QMRA modelling must account
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".