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Record W3197822718 · doi:10.3389/fmars.2021.716124

Contrasting Proteomic Responses of Adult and Larval Coral to High Temperatures

2021· article· en· W3197822718 on OpenAlexaff
Crystal J. McRae, Anderson B. Mayfield, Wen‐Bin Huang, Isabelle M. Côté, Tung‐Yung Fan

Bibliographic record

VenueFrontiers in Marine Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsSimon Fraser University
FundersMinistry of Science and Technology, Taiwan
KeywordsCoralBiologyHolobiontDinoflagellateEcologyAnthozoaLarvaSymbiodiniumProteomeStylophora pistillataCoral reefEcosystemSymbiosisBioinformaticsBacteria

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.209
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2021
Admission routes1
Has abstractyes

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