Ribosome profiling in the Symbiodiniacean dinoflagellate <i>Fugacium kawagutii</i> shows coordinated protein synthesis of enzymes in different pathways at different times of day
Bibliographic record
Abstract
Dinoflagellates respond to daily changes in light and dark by changes in cellular metabolism, yet the mechanisms used are still unclear. For example, Fugacium (previously Symbiodinium) kawagutii shows little difference in the transcriptome between day and night suggesting little transcriptional control over gene expression. Here, we have performed ribosome profiling at 2 h intervals over a daily light-dark cycle to assess the degree to which protein synthesis rates might change over the daily cycle. The number of F. kawagutii coding sequences with significant differences in the number of ribosome-protected fragments (RPF) over the 24-h cycle was 2923 using JTK_Cycle and 3655 using ECHO. The majority of the regulated transcripts showed peak translation at the onset of the dark period. The regulated sequences were assigned to different KEGG pathways and transcripts that were translated at roughly the same time were termed concurrently regulated. Both analyses revealed concurrent regulation of many transcripts whose gene products were involved in spliceosome or lysosome biogenesis with peak translation rates around the onset of the dark period, while others, involved in nitrate metabolism and ribosomal proteins, were preferentially translated around the onset of the day phase or the end of the night phase, respectively. In addition, some sequences involved in DNA synthesis were preferentially translated at the end of the day. We conclude that light-dark cycles seem able to synchronize translation of some transcripts encoding proteins involved in a range of different cellular processes, and propose that these changes may help the cells adapt and alter their metabolism as a function of the time of day.
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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".