Evolutionary potential of the monkeypox genome arising from interactions with human APOBEC3 enzymes
Bibliographic record
Abstract
APOBEC3, an enzyme subfamily that plays a role in virus restriction by generating mutations at particular DNA motifs or mutational 'hotspots', can drive viral mutagenesis with host-specific preferential hotspot mutations contributing to pathogen variation. While previous analysis of viral genomes from the 2022 Mpox (formerly Monkeypox) disease outbreak has shown a high frequency of C>T mutations at TC motifs, suggesting recent mutations are human APOBEC3-mediated, how emerging monkeypox virus (MPXV) strains will evolve as a consequence of APOBEC3-mediated mutations remains unknown. By measuring hotspot under-representation, depletion at synonymous sites, and a combination of the two, we analyzed APOBEC3-driven evolution in human poxvirus genomes, finding varying hotspot under-representation patterns. While the native poxvirus molluscum contagiosum exhibits a signature consistent with extensive coevolution with human APOBEC3, including depletion of TC hotspots, variola virus shows an intermediate effect consistent with ongoing evolution at the time of eradication. MPXV, likely the result of recent zoonosis, showed many genes with more TC hotspots than expected by chance (over-representation) and fewer GC hotspots than expected (under-representation). These results suggest the MPXV genome: (1) may have evolved in a host with a particular APOBEC GC hotspot preference, (2) has inverted terminal repeat (ITR) regions-which may be exposed to APOBEC3 for longer during viral replication-and longer genes likely to evolve faster, and therefore (3) has a heightened potential for future human APOBEC3-meditated evolution as the virus spreads in the human population. Our predictions of MPXV mutational potential can both help guide future vaccine development and identification of putative drug targets and add urgency to the task of containing human Mpox disease transmission and uncovering the ecology of the virus in its reservoir host.
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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".