Evolution of Patchily Distributed Proteins Shared between Eukaryotes and Prokaryotes: Dictyostelium as a Case Study
Bibliographic record
Abstract
Protein families are often patchily distributed in the tree of life; they are present in distantly related organisms, but absent in more closely related lineages. This could either be the result of lateral gene transfer between ancestors of organisms that encode them, or losses in the lineages that lack them. Here a novel approach is developed to study the evolution of patchily distributed proteins shared between prokaryotes and eukaryotes. Proteins encoded in the genome of cellular slime mold Dictyostelium discoideum and a restricted number of other lineages, including at least one prokaryote, were identified. Analyses of the phylogenetic distribution of 49 such patchily distributed protein families showed conflicts with organismal phylogenies; 25 are shared with the distantly related amoeboflagellate Naegleria (Excavata), whereas only two are present in the more closely related Entamoeba. Most protein families show unexpected topologies in phylogenetic analyses; eukaryotes are polyphyletic in 85% of the trees. These observations suggest that gene transfers have been an important mechanism for the distribution of patchily distributed proteins across all domains of life. Further studies of this exchangeable gene fraction are needed for a better understanding of the origin and evolution of eukaryotic genes and the diversification process of eukaryotes.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".