All roads lead to Rome: inter-origin variation in metabolomics reprogramming of the northern shrimp exposed to global changes leads to a comparable physiological status
Bibliographic record
Abstract
Impacts of global ocean changes on species have historically been investigated at the whole-organism level. However, acquiring an in-depth understanding of the organisms’ cellular metabolic responses is paramount to better define their sensitivity to environmental challenges. This is particularly relevant for species that experience highly different environmental conditions across their distribution range as local acclimatization or adaptation can influence their responses to rapid global ocean changes. We aimed at shedding light on the cellular mechanisms underpinning the sensitivity to combined ocean warming (OW) and acidification (OA) in the northern shrimp Pandalus borealis , from four different geographic origins defined by distinctive environmental regimes in the northwest Atlantic: i.e. St. Lawrence Estuary (SLE), Eastern Scotian Shelf (ESS), Esquiman Channel (EC) and Northeast Newfoundland Coast (NNC). We characterized targeted metabolomics profiles of the muscle of shrimp exposed to three temperatures (2, 6 or 10°C) and two pH levels (7.75 or 7.40). Overall, shrimp metabolomics profiles were modulated by a significant interaction between temperature, pH and origin. Temperature drove most of the metabolomics reprogramming, confirming that P. boreali s is more sensitive to OW than OA. Inter-origin differences in metabolomics profiles were also observed, with temperature*pH interactions impacting only shrimp from SLE and ESS, pH affecting only shrimp from SLE and temperature impacting shrimp from all origins. Temperature influenced metabolomics pathways related to the tricarboxylic acid cycle (TCA) and amino acid metabolism, resulting mainly in an accumulation of TCA intermediates and tyrosine. Temperature*pH and pH in isolation only affected amino acid metabolism, leading to amino acids accumulation under low pH. However, the ratio of ATP : ADP remained constant across conditions in shrimp from all origins suggesting that their energetic status is not affected by OW and OA. Still, the accumulation of TCA intermediates and tyrosine suggests the possible enhancement of immune responses under future OW and OA conditions. Our findings suggest that shrimp from SLE are more sensitive at the molecular level, compared to others, to future complex environmental conditions. This underlines the importance of investigating intraspecific variation in mechanisms of responses to combined drivers when trying to define species’ sensitivity to global ocean changes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".