m6A reader proteins: the executive factors in modulating viral replication and host immune response
Bibliographic record
Abstract
N6-Methyladenosine (m6A) modification is the most abundant covalent modification of RNA. It is a reversible and dynamic process induced by various cellular stresses including viral infection. Many m6A methylations have been discovered, including on the genome of RNA viruses and on RNA transcripts of DNA viruses, and these methylations play a positive or negative role on the viral life cycle depending on the viral species. The m6A machinery, including the writer, eraser, and reader proteins, achieves its gene regulatory role by functioning in an orchestrated manner. Notably, data suggest that the biological effects of m6A on target mRNAs predominantly depend on the recognition and binding of different m6A readers. These readers include, but are not limited to, the YT521-B homology (YTH) domain family, heterogeneous nuclear ribonucleoproteins (HNRNPs), insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs), and many others discovered recently. Indeed, m6A readers have been recognized not only as regulators of RNA metabolism but also as participants in a variety of biological processes, although some of these reported roles are still controversial. Here, we will summarize the recent advances in the discovery, classification, and functional characterization of m6A reader proteins, particularly focusing on their roles and mechanisms of action in RNA metabolism, gene expression, and viral replication. In addition, we also briefly discuss the m6A-associated host immune responses in viral infection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".