Development of Amplified Fragment Length Polymorphism-Derived Functional Strain-Specific Markers To Assess the Persistence of 10 Bacterial Strains in Soil Microcosms
Bibliographic record
Abstract
To augment the information on commercial microbial products, we investigated the persistence patterns of high-priority bacterial strains from the Canadian Domestic Substance List (DSL). Specific DNA markers for each of the 10 DSL bacterial strains were developed using the amplified fragment length polymorphism (AFLP) technique, and the fates of DSL strains introduced in soil were assessed by real-time quantitative PCR (qPCR). The results indicated that all DNA markers had high specificity at the functional strain level and that detection of the target microorganisms was sensitive at a detection limitation range from 1.3 × 10² to 3.25 × 10⁵ CFU/g of dry soil. The results indicated that all introduced strains showed a trend toward a declining persistence in soil and could be categorized into three pattern types. The first type was long-term persistence exemplified by Pseudomonas stutzeri (ATCC 17587) and Pseudomonas denitrificans (ATCC 13867) strains. In the second pattern, represented by Bacillus subtilis (ATCC 6051) and Escherichia hermannii (ATCC 700368), the inoculated strain populations dropped dramatically below the detection threshold after 10 to 21 days, while in the third pattern there was a gradual decrease, with the population falling below the detectable level within the 180-day incubation period. These patterns indicate a selection effect of a microbial community related to the ecological function of microbial strains introduced in soil. As a key finding, the DSL strains can be quantitatively tracked in soil with high sensitivity and specificity at the functional strain level. This provides the basic evidence for further risk assessment of the priority DSL strains.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".