Sponge Behavior and the Chemical Basis of Responses: A Post-Genomic View
Bibliographic record
Abstract
Sponges perceive and respond to a range of stimuli. How they do this is still difficult to pin down despite now having transcriptomes and genomes of an array of species. Here we evaluate the current understanding of sponge behavior and present new observations on sponge activity in situ. We also explore biosynthesis pathways available to sponges from data in genomes/transcriptomes of sponges and other non-bilaterians with a focus on exploring the role of chemical signaling pathways mediating sponge behavior and how such chemical signal pathways may have evolved. Sponge larvae respond to light but opsins are not used, nor is there a common photoreceptor molecule or mechanism used across sponge groups. Other cues are gravity and chemicals. In situ recordings of behavior show that both shallow and deep-water sponges move a lot over minutes and hours, and correlation of behavior with temperature, pressure, oxygen, and water movement suggests that at least one sponge responds to changes in atmospheric pressure. The sensors for these cues as far as we know are individual cells and, except in the case of electrical signaling in Hexactinellida, these most likely act as independent effectors, generating a whole-body reaction by the global reach of the stimulus to all parts of the animal. We found no evidence for use of conventional neurotransmitters such as serotonin and dopamine. Intriguingly, some chemicals synthesized by symbiont microbes could mean other more complex signaling occurs, but how that interplay might happen is not understood. Our review suggests chemical signaling pathways found in sponges do not reflect loss of a more complex set.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".