Surviving winter on the Qinghai-Xizang Plateau: Extensive reversible protein phosphorylation plays a dominant role in regulating hypometabolism in hibernating <i>Nanorana parkeri</i>
Bibliographic record
Abstract
Changes in protein abundance and reversible protein phosphorylation (RPP) play important roles in regulating hypometabolism but have never been documented in overwintering frogs at high altitudes. To test the hypothesis that protein abundance and phosphorylation change in response to winter hibernation, we conducted a comprehensive and quantitative proteomic and phosphoproteomic analysis of the liver of the Xizang plateau frog, Nanorana parkeri, living on the Qinghai-Xizang Plateau. In total, 5170 proteins and 5695 phosphorylation sites in 1938 proteins were quantified. Based on proteomic analysis, 674 differentially expressed proteins (438 up-regulated, 236 down-regulated) were screened in hibernating N. parkeri versus summer individuals. Functional enrichment analysis revealed that higher expressed proteins in winter were significantly enriched in immune-related signaling pathways, whereas lower expressed proteins were mainly involved in metabolic processes. A total of 4251 modified sites (4147 up-regulated, 104 down-regulated) belonging to 1638 phosphoproteins (1555 up-regulated, 83 down-regulated) were significantly changed in the liver. During hibernation, RPP regulated a diverse array of proteins involved in multiple functions, including metabolic enzymatic activity, ion transport, protein turnover, signal transduction, and alternative splicing. These changes contribute to enhancing protection, suppressing energy-consuming processes, and inducing metabolic depression. Moreover, the activities of phosphofructokinase, glutamate dehydrogenase, and ATPase were all significantly lower in winter compared to summer. In conclusion, our results support the hypothesis and demonstrate the importance of RPP as a regulatory mechanism when animals transition into a hypometabolic state.
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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 | 0.000 | 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) | 0.001 | 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".