Discovery of Hyperactive Antifreeze Protein from Phylogenetically Distant Beetles Questions Its Evolutionary Origin
Bibliographic record
Abstract
Beetle hyperactive antifreeze protein (AFP) has a unique ability to maintain a supercooling state of its body fluids, however, less is known about its origination. Here, we found that a popular stag beetle Dorcus hopei binodulosus (Dhb) synthesizes at least 6 isoforms of hyperactive AFP (DhbAFP). Cold-acclimated Dhb larvae tolerated −5 °C chilled storage for 24 h and fully recovered after warming, suggesting that DhbAFP facilitates overwintering of this beetle. A DhbAFP isoform (~10 kDa) appeared to consist of 6−8 tandem repeats of a 12-residue consensus sequence (TCTxSxNCxxAx), which exhibited 3 °C of high freezing point depression and the ability of binding to an entire surface of a single ice crystal. Significantly, these properties as well as DNA sequences including the untranslated region, signal peptide region, and an AFP-encoding region of Dhb are highly similar to those identified for a known hyperactive AFP (TmAFP) from the beetle Tenebrio molitor (Tm). Progenitor of Dhb and Tm was branched off approximately 300 million years ago, so no known evolution mechanism hardly explains the retainment of the DNA sequence for such a long divergence period. Existence of unrevealed gene transfer mechanism will be hypothesized between these two phylogenetically distant beetles to acquire this type of hyperactive AFP.
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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) | 0.000 | 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".