Anemonefish use sialic acid metabolism as Trojan horse to avoid giant sea anemone stinging
Bibliographic record
Abstract
Abstract Anemonefish association with giant sea anemone is an iconic example of mutualistic symbiosis. Living inside the sea anemone without triggering the firing of highly toxic nematocysts present at the surface of sea anemone tentacles provides a unique shelter to the fish, which in return, by its territorial aggressiveness, protects the sea anemone from predators. The mechanisms by which the fish avoids triggering nematocysts discharge remain elusive. One hypothesis proposes that absence of sialic acids might disable nematocysts discharge. Here, we verified four predictions about the role of sialic acids in anemonefish protection: (i) sialic acid levels are lower in anemonefish mucus than in non-symbiotic and sensitive damselfish mucus; (ii) this decrease is specific to mucus and not observed in other organs; (iii) during post-embryonic development the levels of sialic acids are inversely correlated with the level of protection; (iv) the levels of sialic acids are minimal in sea anemone mucus. Taken together, our results allow us to propose a general model, in which anemonefish specifically regulates the level of sialic acids in their mucus to avoid nematocysts discharge. Our analysis also highlights several genes implicated in sialic acid removal as potential targets for allowing protection. Interestingly, our results also suggest that unrelated juveniles of damselfish ( Dascyllus trimaculatus ) capable to live in proximity with giant sea anemone may use the same mechanisms. Altogether, our data suggest that clownfish use sialic acids as a Trojan horse system to downplay the defenses of the sea anemones and illustrate the convergent tinkering used by fish to allow a mutualistic association with their hosts. Significance statement The mutualistic relationship between anemonefish and giant sea anemones, where the fish shelter among the anemone’s tentacles while defending it from predators, is a classic example of symbiosis. However, how the fish avoids triggering the anemone’s venomous nematocysts has remained a mystery. This study reveals that the fish decrease the levels of sialic acids in their mucus, potentially preventing nematocyst discharge. This finding shed light on the mechanisms underlying this symbiotic relationship. Moreover, the discovery that unrelated damselfish may employ similar strategies underscores the broader significance of convergent adaptations in facilitating similar mutualistic associations in marine fishes.
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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".