Identification of a rapidly‐spreading triple mutant for high‐level metabolic insecticide resistance in <i>Anopheles gambiae</i> provides a real‐time molecular diagnostic for antimalarial intervention deployment
Bibliographic record
Abstract
Studies of insecticide resistance provide insights into the capacity of populations to show rapid evolutionary responses to contemporary selection. Malaria control remains heavily dependent on pyrethroid insecticides, primarily in long lasting insecticidal nets (LLINs). Resistance in the major malaria vectors has increased in concert with the expansion of LLIN distributions. Identifying genetic mechanisms underlying high-level resistance is crucial for the development and deployment of resistance-breaking tools. Using the Anopheles gambiae 1000 genomes (Ag1000g) data we identified a very recent selective sweep in mosquitoes from Uganda which localized to a cluster of cytochrome P450 genes. Further interrogation revealed a haplotype involving a trio of mutations, a nonsynonymous point mutation in Cyp6p4 (I236M), an upstream insertion of a partial Zanzibar-like transposable element (TE) and a duplication of the Cyp6aa1 gene. The mutations appear to have originated recently in An. gambiae from the Kenya-Uganda border, with stepwise replacement of the double-mutant (Zanzibar-like TE and Cyp6p4-236 M) with the triple-mutant haplotype (including Cyp6aa1 duplication), which has spread into the Democratic Republic of Congo and Tanzania. The triple-mutant haplotype is strongly associated with increased expression of genes able to metabolize pyrethroids and is strongly predictive of resistance to pyrethroids most notably deltamethrin. Importantly, there was increased mortality in mosquitoes carrying the triple-mutation when exposed to nets cotreated with the synergist piperonyl butoxide (PBO). Frequencies of the triple-mutant haplotype remain spatially variable within countries, suggesting an effective marker system to guide deployment decisions for limited supplies of PBO-pyrethroid cotreated LLINs across African countries.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".