In Cold‐Hardy Insects, Seasonal, Temperature, and Reversible Phosphorylation Controls Regulate Sarco/Endoplasmic Reticulum Ca<sup>2+</sup>‐ATPase (SERCA)
Bibliographic record
Abstract
Winter cold hardiness of insects typically involves one of two major strategies for survival below 0 degrees C: freeze avoidance and freeze tolerance. The two strategies have some common features, including the accumulation of high concentrations of cryoprotectant polyols and the frequent occurrence of diapause. Entry into the hypometabolic state of diapause requires coordinated suppression of major ATP-consuming metabolic processes, and ion motive ATPases are important targets for regulation. This study documents the suppression of sarco/endoplasmic reticulum Ca(2+)-ATPase (SERCA) activity in the overwintering larvae of two cold-hardy species, the freeze-avoiding gall moth Epiblema scudderiana and the freeze-tolerant gall fly Eurosta solidaginis. Activity was reduced despite a lack of change in SERCA protein levels in E. solidaginis larvae over the winter and a six- to eightfold increase in SERCA protein in E. scudderiana. This implicated posttranslational modification as the mechanism of SERCA suppression, and in vitro incubations indicated that enzyme phosphorylation by protein kinases A, G, or C strongly reduced enzyme activity. A stable reduction in SERCA activity was also seen in cold-acclimated larvae of both species compared with 15 degrees C controls, with significant changes in the kinetic parameters of the E. scudderiana enzyme (e.g., K(m) ATP was 3.2-fold higher in -20 degrees C-acclimated larvae) that were consistent with reduced enzyme function at low temperature. Epiblema scudderiana SERCA was also subject to regulation by differential temperature effects (Arrhenius activation energy increased by approximately threefold below 10 degrees C) and by seasonal changes in the levels of a SERCA inhibitor protein, phospholamban.
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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".