Transcriptional responses of the marine green alga <i>Micromonas pusilla</i> and an infecting prasinovirus under different phosphate conditions
Bibliographic record
Abstract
Summary Prasinophytes are widespread marine algae for which responses to nutrient limitation and viral infection are not well understood. We studied the picoprasinophyte, Micromonas pusilla , grown under phosphate‐replete (0.65 ± 0.07 d −1 ) and 10‐fold lower (low)‐phosphate (0.11 ± 0.04 d −1 ) conditions, and infected by the phycodnavirus MpV‐SP1. Expression of 17% of Micromonas genes in uninfected cells differed by >1.5‐fold ( q < 0.01) between nutrient conditions, with genes for P‐metabolism and the uniquely‐enriched Sel1‐like repeat (SLR) family having higher relative transcript abundances, while phospholipid‐synthesis genes were lower in low‐P than P‐replete. Approximately 70% (P‐replete) and 30% (low‐P) of cells were lysed 24 h post‐infection, and expression of ≤5.8% of host genes changed relative to uninfected treatments. Host genes for CAZymes and glycolysis were activated by infection, supporting importance in viral production, which was significantly lower in slower growing (low‐P) hosts. All MpV‐SP1 genes were expressed, and our analyses suggest responses to differing host‐phosphate backgrounds involve few viral genes, while the temporal program of infection involves many more, and is largely independent of host‐phosphate background. Our study (i) identifies genes previously unassociated with nutrient acclimation or viral infection, (ii) provides insights into the temporal program of prasinovirus gene expression by hosts and (iii) establishes cell biological aspects of an ecologically important host‐prasinovirus system that differ from other marine algal‐virus systems.
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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".