Contrasting Proteomic Responses of Adult and Larval Coral to High Temperatures
Bibliographic record
Abstract
Climate change-induced increases in seawater temperature continue to impact coral reef ecosystems globally. There is a consequent need to characterize the responses of corals to thermal stress to understand the molecular processes underpinning these responses and identify hallmarks of resilience. Here we used an iTRAQ approach to compare the proteomes of adult corals (Pocillopora acuta) that had been thermally conditioned at a control (26°C) or elevated temperature (29.5°C) for three reproductive cycles, as well as the larvae released by these corals. We found that larvae responded more to high-temperature exposure at the protein level than their parents and that different proteins were affected between life stages; a single protein was up-regulated at high temperatures in both adults and their offspring, and its identity is currently unknown. Similarly, different cellular pathways were affected by high-temperature exposure between the coral hosts and their dinoflagellate endosymbionts; proteins involved in translation and protein trafficking were most likely to be affected by high-temperature exposure in the former, with photosynthesis being the most thermo-sensitive process in the latter. Collectively, these findings highlight the importance of considering both life stage and the composition of the coral holobiont when using molecular-scale data to model cellular processes associated with responses to future ocean warming.
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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".