High-throughput rapid amplicon sequencing for multilocus sequence typing of Mycoplasma ovipneumoniae from archived clinical DNA samples
Bibliographic record
Abstract
Introduction Spillover events of Mycoplasma ovipneumoniae have devastating effects on the wild sheep populations. Multilocus sequence typing (MLST) is used to monitor spillover events and the spread of M. ovipneumoniae between the sheep populations. Most studies involving the typing of M. ovipneumoniae have used Sanger sequencing. However, this technology is time-consuming, expensive, and is not well suited to efficient batch sample processing. Methods Our study aimed to develop and validate an MLST workflow for typing of M. ovipneumoniae using Nanopore Rapid Barcoding sequencing and multiplex polymerase chain reaction (PCR). We compare the workflow with Nanopore Native Barcoding library preparation and Illumina MiSeq amplicon protocols to determine the most accurate and cost-effective method for sequencing multiplex amplicons. A multiplex PCR was optimized for four housekeeping genes of M. ovipneumoniae using archived DNA samples ( N = 68) from nasal swabs. Results Sequences recovered from Nanopore Rapid Barcoding correctly identified all MLST types with the shortest total workflow time and lowest cost per sample when compared with Nanopore Native Barcoding and Illumina MiSeq methods. Discussion Our proposed workflow is a convenient and effective method for strain typing of M. ovipneumoniae and can be applied to other bacterial MLST schemes. The workflow is suitable for diagnostic settings, where reduced hands-on time, cost, and multiplexing capabilities are important.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".