Dissecting nitrogen starvation signaling in Chlamydomonas: Insights from arginine-fed transcriptome profiling
Bibliographic record
Abstract
Nitrogen (N) acquisition from environmental sources is critical for most organisms. In plants and other photosynthetic eukaryotes, the limitation of available N induces global changes in gene expression; yet, the underlying regulatory mechanisms remain largely unknown. Chlamydomonas reinhardtii primarily utilizes inorganic N sources but also thrives on organic N sources like arginine. Our recent characterization of the molecular and physiological responses of arginine-fed Chlamydomonas cultures reveals a stark resemblance to the responses invoked by N starvation. To determine if arginine feeding triggers full-scale N starvation responses in the absence of metabolic N limitation, we compared the transcriptomes of arginine-fed cultures with those of early and late stages of N starvation. Our analysis shows that arginine-fed cells maintain both the N starvation-induced upregulation of N scavenging genes and genome-wide downregulation of genes involved in energy-producing carbon flow during exponential growth . Our study defines the N starvation-triggered gene regulatory network in two tiers: the early response involves N scavenging within the first two hours, and the late response includes the rerouting of energy-producing carbon flow into the biosynthesis of energy storage molecules. This regulation operates independently of growth, allowing cells to balance N and carbon budgets regardless of growth status. Our findings pave the way for future research on the triggers of N starvation responses in photosynthetic eukaryotic organisms and the strategies to enhance the production of starvation-associated high-value products in microalgae .
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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) | 0.000 | 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 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".