Genetic Characterization of a Panel of Diverse HIV-1 Isolates at Seven International Sites
Bibliographic record
Abstract
HIV-1 subtypes and drug resistance are routinely tested by many international surveillance groups. However, results from different sites often vary. A systematic comparison of results from multiple sites is needed to determine whether a standardized protocol is required for consistent and accurate data analysis. A panel of well-characterized HIV-1 isolates (N = 50) from the External Quality Assurance Program Oversight Laboratory (EQAPOL) was assembled for evaluation at seven international sites. This virus panel included seven subtypes, six circulating recombinant forms (CRFs), nine unique recombinant forms (URFs) and three group O viruses. Seven viruses contained 10 major drug resistance mutations (DRMs). HIV-1 isolates were prepared at a concentration of 107 copies/ml and compiled into blinded panels. Subtypes and DRMs were determined with partial or full pol gene sequences by conventional Sanger sequencing and/or Next Generation Sequencing (NGS). Subtype and DRM results were reported and decoded for comparison with full-length genome sequences generated by EQAPOL. The partial pol gene was amplified by RT-PCR and sequenced for 89.4%-100% of group M viruses at six sites. Subtyping results of majority of the viruses (83%-97.9%) were correctly determined for the partial pol sequences. All 10 major DRMs in seven isolates were detected at these six sites. The complete pol gene sequence was also obtained by NGS at one site. However, this method missed six group M viruses and sequences contained host chromosome fragments. Three group O viruses were only characterized with additional group O-specific RT-PCR primers employed by one site. These results indicate that PCR protocols and subtyping tools should be standardized to efficiently amplify diverse viruses and more consistently assign virus genotypes, which is critical for accurate global subtype and drug resistance surveillance. Targeted NGS analysis of partial pol sequences can serve as an alternative approach, especially for detection of low-abundance DRMs.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".