Plasma Exosomes Modulate Signalling in Rainbow Trout Hepatocytes
Bibliographic record
Abstract
Exosomes are a subtype of cell‐secreted extracellular vesicles, approximately 40–100 nm in diameter, that are formed from endosomal compartments. Exosomes carry a payload of proteins and RNA and are thought to play a role in inter‐tissue communication, including regulation of cellular function. Most of these studies are in mammalian models and very little is known about the role of exosomes in lower vertebrates. Recently we showed that the intracellular chaperone heat shock protein 70 (Hsp70) is exported into the plasma of rainbow trout ( Oncorhynchus mykiss ) in exosomes. Here we tested the hypothesis that plasma exosomes play a role in cell to cell communication and that this is mediated by Hsp70. To determine this, plasma exosomes were tagged with a fluorescent lipophilic dye (DiD) and their uptake monitored in trout hepatocytes in primary culture. Exosomes were taken up by hepatocytes over a 24 h period, but the physiological implications were unclear. We also examined whether exosomes modulate the phosphorylation status of key secondary signalling messengers. Indeed, exosome addition significantly increased phosphorylation of p42/44 MAPK, but not p38 MAPK or cAMP response element‐binding protein (CREB) within 20 min, in trout hepatocytes. Interestingly, when these vesicles were incubated with anti‐Hsp70 antibody, the exosome‐induced increase in p42/p44 MAPK phosphorylation was abolished. This suggests that Hsp70 may be a key player in exosome‐mediated cell to cell signalling in rainbow trout. Overall, this novel finding underscores a key role for exosomes in modulating cellular function during stress in fish. Support or Funding Information This study was supported by the Natural Sciences and Engineering Research Council of Canada Discovery Grant to MMV and Post‐Graduate Fellowship to EF.
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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".