Development of an amplicon-based NGS protocol for HIV-1 subtype B drug-resistance surveillance using degraded samples
Bibliographic record
Abstract
With the widespread use of antiretroviral therapy, HIV drug resistance (HIVDR) rates are increasing globally. Many reported cases of HIV are found in areas without readily accessible testing centres capable of processing blood samples. Blood samples received from these areas can become degraded due to storage conditions during transportation to another facility or country capable of testing. Degraded samples present challenges for HIVDR testing, due to compromised viral RNA integrity interfering with RNA amplification and sequencing. Similarly, archival samples and dried blood spots (DBS) can also pose challenges. DBS samples are a highly accessible and cost-effective sample collection method used for HIVDR testing in resource-limited settings within Canada and across the world; however, they can be difficult to process through traditional methods due to susceptibility to degradation and low input volumes. To address this, we have developed a multiplex, amplicon-based, direct-to-sequencing HIVDR testing protocol compatible with degraded samples. This approach uses a hemi-nested approach with primer pools spanning the entire pol region of the HIV-1 genome. Protocol primers also incorporated Illumina P5/P7 adaptors, single index barcodes, and unique molecular identifiers (UMIs or Primer ID). This approach allow direct sequencing of amplicons, decreasing overall cost, mitigating PCR biases, and increasing clinical throughput. Here, we show the utility of this approach, successfully targeting the entire pol gene region of the HIV-1 subtype B genome in degraded and DBS samples. Preliminary work suggests the protocol may be adaptable for other major subtypes circulating in Canada as data shows the primer pools can amplify other major HIV-1 subtypes, albeit this may require further optimization. This protocol provides a potential option for NGS-based HIV drug-resistance testing from degraded samples and phylogenetic studies, while also building towards the ultimate goal of increasing accessibility of HIV diagnostics for all Canadians.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".