A targeted tiled amplicon sequencing approach for clade and subclade level differentiation of monkeypox virus from wastewater
Bibliographic record
Abstract
Wastewater-based surveillance (WBS) has modernized in recent years and emerged as an important tool for the monitoring of viral pathogens, including monkeypox virus (MPXV). Here we describe a novel targeted amplicon sequencing method developed for clade and subclade characterization of MPXV from municipal wastewater. This new method addresses the limitations of PCR-based methods and the challenges of sequencing a pathogen displaying low viral load in municipal wastewater samples. A tiled amplicon scheme composed of 11 primer pairs targeting a 4.2 kb portion of the inverted terminal repeat (ITR) region of the MPXV genome was designed and tested. In silico analysis demonstrated high accuracy for clade and subclade calls using the full target region, with specific amplicons also exhibiting strong performance individually. An MPXV consensus sequence representing the entire target region was successfully sequenced from a wastewater sample and differentiated from positive controls by a distinct deletion within a short homopolymeric region. Notably, clade-informing data was also achieved from partial sequences recovered from lower abundance samples. This study presents a new sequencing method targeting MPXV with enhanced genomic resolution compared to existing PCR-based approaches, providing critical genomic-level information informing MPXV surveillance and public health interventions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".