High-Throughput Short Sequence Typing Schemes for Pseudomonas aeruginosa and Stenotrophomonas maltophilia Pure Culture and Environmental DNA
Bibliographic record
Abstract
Molecular typing techniques are utilized to determine genetic similarities between bacterial isolates. However, the use of environmental DNA profiling to assess epidemiologic links between patients and their environment has not been fully explored. This work reports the development and validation of two high-throughput short sequence typing (HiSST) schemes targeting the opportunistic pathogens Pseudomonas aeruginosa and Stenotrophomonas maltophilia, along with a modified SM2I selective medium for the specific isolation of S. maltophilia. These HiSST schemes are based on four discriminative loci for each species and demonstrate high discriminating power, comparable to pairwise whole-genome comparisons. Each scheme includes species-specific PCR primers for precise differentiation from closely related taxa, without the need for upstream culture-dependent methods. For example, the primers targeting the bvgS locus make it possible to distinguish P. aeruginosa from the very closely related Pseudomonas paraeruginosa sp. nov. The selected loci included in the schemes are adapted to massive parallel amplicon sequencing technology. An R-based script implemented in the DADA2 pipeline was assembled to facilitate HiSST analyses for efficient and accurate genotyping of P. aeruginosa and S. maltophilia. We demonstrate the performance of both schemes through in silico validations, assessments against reference culture collections, and a case study involving environmental samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".