Characterization of photosynthetic ferredoxin from the Antarctic alga <i>Chlamydomonas</i> sp. <scp>UWO</scp>241 reveals novel features of cold adaptation
Bibliographic record
Abstract
The objective of this work was to characterize photosynthetic ferredoxin from the Antarctic green alga Chlamydomonas sp. UWO241, a key enzyme involved in distributing photosynthetic reducing power. We hypothesize that ferredoxin possesses characteristics typical of cold-adapted enzymes, namely increased structural flexibility and high activity at low temperatures, accompanied by low stability at moderate temperatures. To address this objective, we purified ferredoxin from UWO241 and characterized the temperature dependence of its enzymatic activity and protein conformation. The UWO241 ferredoxin protein, RNA, and DNA sequences were compared with homologous sequences from related organisms. We provide evidence for the duplication of the main ferredoxin gene in the UWO241 nuclear genome and the presence of two highly similar proteins. Ferredoxin from UWO241 has both high activity at low temperatures and high stability at moderate temperatures, representing a novel class of cold-adapted enzymes. Our study reveals novel insights into how photosynthesis functions in the cold. The presence of two distinct ferredoxin proteins in UWO241 could provide an adaptive advantage for survival at cold temperatures. The primary amino acid sequence of ferredoxin is highly conserved among photosynthetic species, and we suggest that subtle differences in sequence can lead to significant changes in activity at low temperatures.
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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".