Analysis of eIF4E-family members in fungi contributes to their classification in eukaryotes
Bibliographic record
Abstract
The kingdom of fungi contains highly diverse species. However, fundamental processes sustaining life such as RNA metabolism are much less comparatively studied in Fungi than in other kingdoms. A key factor in the regulation of mRNA expression is the cap-binding protein eIF4E, which plays roles in mRNA nuclear export, storage, and translation. The advent of massive genomics has unveiled a constellation of eIF4E-family members across eukaryotes. However, how this protein diverged into fungal species remains largely unexplored. Here, we studied the genome of 538 species from six evolutionarily distant phyla and retrieved 1462 eIF4E cognates. The analyzed species contained 1 to 7 paralogs. We sorted all cognates in six phylogenetically coherent clades, that we termed Class I to VII (mammalian Class III was absent in Fungi). Proteins from Classes IV to VII did not match the current eIF4Es classification that is based on variations in the residues equivalent to W43 and W56 of the human protein. eIF4Es from other eukaryotes do not fit into this classification either. Thus, we have updated the eIF4E categorization based on cladistics and the presence of cap-binding amino acids to better fit eIF4E's diversity across eukaryotes. Finally, we predicted the structure of the global protein and the cap-binding pocket and experimentally tested the ability to rescue the lack of endogenous eIF4E in Saccharomyces cerevisiae of representative members of each of the six classes of fungal eIF4E.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".