Characterization of the Calmodulin-Like Protein Family in <i>Chara braunii</i> and their Conserved Interaction with the Calmodulin-Binding Transcription Activator Family
Bibliographic record
Abstract
Calcium sensor proteins play important roles by detecting changes in intracellular calcium and relaying that information onto downstream targets through protein-protein interaction. Very little is known about calcium sensors from plant species that predate land colonization and the evolution of embryophytes. Here, we examined the genome of the multicellular algae, Chara braunii, for orthologs to the evolutionarily conserved calcium sensor calmodulin (CaM) and for CaM-like (CML) proteins. We identified one CaM and eight CML isoforms that range in size from 16.4 to 21.3 kDa and are predicted to have between two to four calcium-binding (EF-hand) domains. Using recombinant protein, we tested whether CbCaM and CbCML1-CbCML7 possess biochemical properties of typical calcium sensors. CbCaM and the CbCMLs all displayed high-affinity calcium binding with estimated global KD,app values in the physiological µM range. In response to calcium binding, CbCaM and the CbCMLs exhibited varying degrees of increase in exposed hydrophobicity, suggesting that different calcium-induced conformational changes occur among isoforms. We found many examples of putative CaM targets encoded in the C. braunii genome and explored the ability of CbCaM and CbCMLs to interact in planta with a representative putative target, a C. braunii CaM-binding transcription factor (CbCAMTA1). CbCaM, CbCML2 and CbCML4 each associated with the C-terminal region of CbCAMTA1. Collectively, our data support the hypothesis that complex calcium signaling and sensing networks involving CaM and CMLs evolved early in the green lineage. Similarly, it seems likely that calcium-mediated regulation of transcription occurs in C. braunii via CAMTAs and is an ancient trait predating embryophytic emergence.
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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".