Phylogenetic evidence of extensive spatial mixing of diverse HIV-1 group M lineages within Cameroon but not between its neighbours
Bibliographic record
Abstract
Abstract From the perspective of developing relevant interventions for treating HIV and controlling its spread, it is particularly important to comprehensively understand the underlying diversity of the virus, especially in countries where the virus has been present and evolving since the cross-species transmission event that triggered the global pandemic. Here, we generate and phylogenetically analyse sequences derived from the gag-protease (2010 bp; n = 115), partial integrase (345 bp; n = 36), and nef (719 bp; n = 321) genes of HIV-1 group M (HIV-1M) isolates sampled between 2000 and 2022 from two cosmopolitan cities and 40 remote villages of Cameroon. While 52.4% of all sequenced viruses belonged to circulating recombinant form (CRF) 02_AG (CRF02_AG), the remainder were highly diverse, collectively representing seven subtypes and sub-subtypes, eight CRFs, and 36 highly divergent lineages that fall outside the established HIV-1M classification. Additionally, in 77 samples for which at least two genes were typed, 31% of the studied viruses apparently had fragments from viruses belonging to different clades. Furthermore, we found that the distribution of HIV-1M populations is similar between different regions of Cameroon. In contrast, HIV-1M demographics in Cameroon differ significantly from those in its neighbouring countries in the Congo Basin (CB). In phylogenetic trees, viral sequences cluster according to the countries where they were sampled, suggesting that while there are minimal geographical or social barriers to viral dissemination throughout Cameroon, there is strongly impeded dispersal of HIV-1M lineages between Cameroon and other locations of the CB. This suggests that the apparent stability of highly diverse Cameroonian HIV-1M populations may be attributable to the extensive mixing of human populations within the country and the concomitant trans-national movements of major lineages with very similar degrees of fitness; coupled with the relatively infrequent inter-national transmission of these lineages from neighbouring countries in the CB.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".