Evolution of Bacterial-Like Phosphoprotein Phosphatases in Photosynthetic Eukaryotes Features Ancestral Mitochondrial or Archaeal Origin and Possible Lateral Gene Transfer
Bibliographic record
Abstract
Protein phosphorylation is a reversible regulatory process catalyzed by the opposing reactions of protein kinases and phosphatases, which are central to the proper functioning of the cell. Dysfunction of members in either the protein kinase or phosphatase family can have wide-ranging deleterious effects in both metazoans and plants alike. Previously, three bacterial-like phosphoprotein phosphatase classes were uncovered in eukaryotes and named according to the bacterial sequences with which they have the greatest similarity: Shewanella-like (SLP), Rhizobiales-like (RLPH), and ApaH-like (ALPH) phosphatases. Utilizing the wealth of data resulting from recently sequenced complete eukaryotic genomes, we conducted database searching by hidden Markov models, multiple sequence alignment, and phylogenetic tree inference with Bayesian and maximum likelihood methods to elucidate the pattern of evolution of eukaryotic bacterial-like phosphoprotein phosphatase sequences, which are predominantly distributed in photosynthetic eukaryotes. We uncovered a pattern of ancestral mitochondrial (SLP and RLPH) or archaeal (ALPH) gene entry into eukaryotes, supplemented by possible instances of lateral gene transfer between bacteria and eukaryotes. In addition to the previously known green algal and plant SLP1 and SLP2 protein forms, a more ancestral third form (SLP3) was found in green algae. Data from in silico subcellular localization predictions revealed class-specific differences in plants likely to result in distinct functions, and for SLP sequences, distinctive and possibly functionally significant differences between plants and nonphotosynthetic eukaryotes. Conserved carboxyl-terminal sequence motifs with class-specific patterns of residue substitutions, most prominent in photosynthetic organisms, raise the possibility of complex interactions with regulatory proteins.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".