Comparative quantitative proteomics to investigate the remodeling of bioenergetic pathways under iron deficiency in <b><i>Chlamydomonas reinhardtii</i></b>
Bibliographic record
Abstract
The basic question addressed in this study is how energy metabolism is adjusted to cope with iron deficiency in Chlamydomonas reinhardtii. To investigate the impact of iron deficiency on bioenergetic pathways, comparative proteomics was combined with spectroscopic as well as voltametric oxygen measurements to assess protein dynamics linked to functional properties of respiratory and photosynthetic machineries. Although photosynthetic electron transfer is largely compromised under iron deficiency, our quantitative and spectroscopic data revealed that the functional antenna size of photosystem II (PSII) significantly increased. Concomitantly, stress-related chloroplast polypeptides, like 2-cys peroxiredoxin and a stress-inducible light-harvesting protein, LhcSR3, as well as a novel light-harvesting protein and several proteins of unknown function were induced under iron-deprivation. Respiratory oxygen consumption did not decrease and accordingly, polypeptides of respiratory complexes, harboring numerous iron-sulfur clusters, were only slightly diminished or even increased under low iron. Consequently, iron-deprivation induces a transition from photoheterotrophic to primarily heterotrophic metabolism, indicating that a hierarchy for iron allocations within organelles of a single cell exists that is closely linked with the metabolic state of the cell.
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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".