New insights in copper handling strategies in the green alga <i>Chlamydomonas reinhardtii</i> under low-iron condition
Bibliographic record
Abstract
Copper (Cu) is a redox-active transition element critical to various metabolic processes. These functions are accomplished in tandem with Cu-binding ligands, mainly proteins. The main goal of this work was to understand the mechanisms that govern the intracellular fate of Cu in the freshwater green alga, Chlamydomonas reinhardtii, and more specifically to understand the mechanisms underlying Cu detoxification by algal cells in low-Fe conditions. We show that Cu accumulation was up to 51-fold greater for algae exposed to Cu in low-Fe medium as compared to the replete-Fe growth medium. Using the stable isotope 65Cu as a tracer, we studied the subcellular distribution of Cu within the various cell compartments of C. reinhardtii. These data were coupled with metallomic and proteomic approaches to identify potential Cu-binding ligands in the heat-stable proteins and peptides fraction of the cytosol. Cu was mostly found in the organelles (78%), and in the heat-stable proteins and peptides (21%) fractions. The organelle fraction appeared to also be the main target compartment of Cu accumulation in Fe-depleted cells. As Fe levels in the medium were shown to influence Cu homeostasis, we found that C. reinhardtii can cope with this additional stress by utilizing different Cu-binding ligands. Indeed, in addition to expected Cu-binding ligands such as glutathione and phytochelatins, 25 proteins were detected that may also play a role in the Cu-detoxification processes in C. reinhardtii. Our results shed new light on the coping mechanisms of C. reinhardtii when exposed to environmental conditions that induce high rates of Cu accumulation.
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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 | 0.001 |
| 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".