Ancient Complexity, Opisthokont Plasticity, and Discovery of the 11th Subfamily of Arf <scp>GAP</scp> Proteins
Bibliographic record
Abstract
The organelle paralogy hypothesis is one model for the acquisition of nonendosymbiotic organelles, generated from molecular evolutionary analyses of proteins encoding specificity in the membrane traffic system. GTPase activating proteins (GAPs) for the ADP-ribosylation factor (Arfs) GTPases are additional regulators of the kinetics and fidelity of membrane traffic. Here we describe molecular evolutionary analyses of the Arf GAP protein family. Of the 10 subfamilies previously defined in humans, we find that 5 were likely present in the last eukaryotic common ancestor. Of the 3 most recently derived subfamilies, 1 was likely present in the ancestor of opisthokonts (animals and fungi) and apusomonads (flagellates classified as the sister lineage to opisthokonts), while 2 arose in the holozoan lineage. We also propose to have identified a novel ancient subfamily (ArfGAPC2), present in diverse eukaryotes but which is lost frequently, including in the opisthokonts. Surprisingly few ancient domains accompanying the ArfGAP domain were identified, in marked contrast to the extensively decorated human Arf GAPs. Phylogenetic analyses of the subfamilies reveal patterns of single and multiple gene duplications specific to the Holozoa, to some degree mirroring evolution of Arf GAP targets, the Arfs. Conservation, and lack thereof, of various residues in the ArfGAP structure provide contextualization of previously identified functional amino acids and their application to Arf GAP biology in general. Overall, our results yield insights into current Arf GAP biology, reveal complexity in the ancient eukaryotic ancestor and integrate the Arf GAP family into a proposed mechanism for the evolution of nonendosymbiotic organelles.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".