Microbiomes of clownfish and their symbiotic host anemone converge before their first physical contact
Bibliographic record
Abstract
Abstract Background One of the most charismatic, and yet not completely resolved example of mutualistic interaction is the partnership of clownfish and its symbiotic sea anemone. The mechanism explaining this tolerance currently relies on the molecular mimicry of clownfish epithelial mucus, which could serve as camouflage, preventing the anemone's nematocysts' discharge. Resident bacteria are known as key drivers of epithelial mucus chemical signature in vertebrates. A recent study has proposed a restructuration of the skin microbiota in a generalist clown fish when first contacting its symbiotic anemone. We explored a novel hypothesis by testing the effect of remote interaction on epithelial microbiota restructuration in both partners. Methods With metataxonomics, we investigated the epithelial microbiota dynamic of 18 pairs of percula clownfish ( Amphiprion percula ) and their symbiotic anemone Heteractis magnifica in remote interaction, physical interaction and control groups for both partners during a four weeks trial. Results Physical and Remote Interaction groups’ results evidence gradual epithelial microbiota convergence between both partners when fish and anemone were placed in the same water system. This convergence occurred preceding any physical contact between partners, and was maintained during the two-weeks interaction period in both contact groups. After the interaction period, community structure of both fish and anemone’s epthelial community structures maintained the interaction signature two weeks after fish-anemone pairs separation. Furthermore, the interaction signature persistence was observed both in Physical and Remote Interaction groups, thus suggesting that water-mediated chemical communication between symbiotic partners was strong enough to shift the skin microbiota durably, even after the separation of fish-anemone pairs. Finally, our results suggest that fish-anemone convergent microbiota restructuration was increasingly associated with the parallel recruitment of three Flavobacteriaceae strains closely related to a tyrosinase-producing Cellulophaga tyrosinoxydans . Conclusions Our study shows that bacterial community restructuration, in the acclimation process, does not only rely on direct physical contact. Furthermore, our results challenge, for the first time, the traditional unidirectional chemical camouflage hypothesis, as we argue that convergence of the epithelial microbiota of both partners may play essential roles in establishing mutual acceptance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 teacher head, 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".