Combining Environmental Investigation and a Dual-Analytical Strategy to Isolate the Legionella longbeachae Strain Linked to Two Occupational Cases of Legionellosis
Bibliographic record
Abstract
Legionella has a global distribution, mainly in aquatic and man-made environments. Under the right conditions, this bacterium is a notorious human pathogen responsible for severe pulmonary illnesses. Legionellosis outbreaks are reported around the world, and exposure to water droplet aerosols containing Legionella pneumophila is usually the mechanism of its transmission. Even if L. pneumophila causes most outbreaks, Legionella longbeachae also accounts for some cases. Unlike most other Legionella strains, L. longbeachae is typically found in soil. Given the wide diversity and high concentration of microorganisms found in soil, isolating L. longbeachae by culture can be challenging. Because the chances of successfully isolating the strain are low, it is often not even attempted. This study reports the strategies used to successfully isolate L. longbeachae strain that was responsible of the two occupational legionellosis in Quebec. Fifteen random samples were collected from the soil of the metal recycling plant where the diagnosed workers were employed, covering 1.5% of the accessible surface of the plant. All samples were analyzed with both the quantitative polymerase chain reaction (qPCR) and culture methods. Four qPCR detection systems targeting Legionella spp, L. pneumophila, L. pneumophila serogroup 1, and L. longbeachae were used. Acid, heat, and acid/heat treatments were used for the culture method. For the qPCR method, all samples were positives for Legionella spp but only four were positives for L. longbeachae. For the culture method, only one isolate could be confirmed to be L. longbeachae. However, that strain proves to be the same one that caused the occupational legionellosis. Detecting the presence of L. longbeachae using the qPCR method made it possible to target the right samples to enable the cultivable strain of L. longbeachae to be isolated from the soil of the metal recycling plant. The complementarity of the two methods was established. This paper demonstrated the advantages of selecting the proper sampling and analytical strategies to achieve the isolation of the strain responsible for the infections. It also highlights for the first time in Quebec the potential occupational risks associated with L. longbeachae from soil and should motivate questioning soil exposures when all sources of water contamination have been eliminated from the causal analysis of legionellosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".