Unraveling inter-species differences in hagfish slime skein deployment
Bibliographic record
Abstract
ABSTRACT Hagfishes defend themselves from fish predators by producing defensive slime consisting of mucous and thread components that interact synergistically with seawater to pose a suffocation risk to their attackers. Deployment of the slime occurs in a fraction of a second and involves hydration of mucous vesicles as well as unraveling of the coiled threads to their full length of ∼150 mm. Previous work showed that unraveling of coiled threads (or ‘skeins’) in Atlantic hagfish requires vigorous mixing with seawater as well as the presence of mucus, whereas skeins from Pacific hagfish tend to unravel spontaneously in seawater. Here, we explored the mechanisms that underlie these different unraveling modes, and focused on the molecules that make up the skein glue, a material that must be disrupted for unraveling to proceed. We found that Atlantic hagfish skeins are also held together with a protein glue, but compared with Pacific hagfish glue, it is less soluble in seawater. Using SDS-PAGE, we identified several soluble proteins and glycoproteins that are liberated from skeins under conditions that drive unraveling in vitro. Peptides generated by mass spectrometry of five of these proteins and glycoproteins mapped strongly to 14 sequences assembled from Pacific hagfish slime gland transcriptomes, with all but one of these sequences possessing homologs in the Atlantic hagfish. Two of these sequences encode unusual acidic proteins that we propose are the structural glycoproteins that make up the skein glue. These sequences have no known homologs in other species and are likely to be unique to hagfishes. Although the ecological significance of the two modes of skein unraveling described here are unknown, they may reflect differences in predation pressure, with selection for faster skein unraveling in the Eptatretus lineage leading to the evolution of a glue that is more soluble.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".