Studying sleep orthologs in Epsilonproteobacteria through an evolutionary lens: Investigating sleep mysteries through phylogenomics
Bibliographic record
Abstract
ABSTRACT The current study employed phylogenomic methods to examine the evolutionary role and significance of sleep-related genes in Sulfurimonas paralvinellae of the Epsilonproteobacteria class. This has facilitated the identification of conserved sleep orthologs, including DnaK, serine hydroxymethyltransferase, and potassium channel family proteins, exhibiting sequence similarities ranging from 39.13% to 61.45%. These findings align with prior research indicating that chaperones and ion channels are conserved during sleep. This was demonstrated by the observation that proteins with fewer domains exhibited more significant conservation than others, such as adenylate kinase, which is substantial under selective pressure. Distinct adaptations in bifunctional protein - serine/threonine kinases and phosphatases were linked to S. paralvinellae , an extremophilic organism adapted to high-pressure and/or high-temperature conditions, indicating functional divergence influenced by the organism’s environment. The Gene Ontology study results indicated catalytic activity, potassium channel function, and cellular processes, underscoring the significance of ion channels in regulating the sleep-wake cycle. Furthermore, the categories not recognized as particularly significant for the over-represented genes encompassed metabolic and signal transduction categories, suggesting enhanced functional flexibility within this protein subfamily. The findings emphasize that orthologous interactions are complex and influenced by subfunctionalization and neofunctionalization of ecology and evolution. These findings enhance the existing understanding of the evolution of sleep-related genes and their association with metabolic and environmental changes, providing a foundation for subsequent experimental investigations and cross-taxonomic comparisons.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".