Arabidopsis calmodulin‐like proteins CML13 and CML14 interact with proteins that have IQ domains
Bibliographic record
Abstract
Abstract In response to Ca 2+ signals, the evolutionarily‐conserved Ca 2+ sensor calmodulin (CaM) regulates protein targets via direct interaction. Plants possess many CaM‐like (CML) proteins, but their binding partners and functions are mostly unknown. Here, using Arabidopsis CML13 as ‘bait’ in a yeast two‐hybrid screen, we isolated putative targets from three, unrelated protein families, namely, IQD proteins, calmodulin‐binding transcriptional activators (CAMTAs) and myosins, all of which possess tandem isoleucine‐glutamine (IQ) structural domains. Using the split‐luciferase complementation assay in planta and the yeast 2‐hybrid system, CML13 and CML14 showed a preference for interaction with tandem over single IQ domains. Relative to CaM, CML13 and CML14 displayed weaker signals when tested with the non‐IQ, CaM‐binding domain of glutamate decarboxylase or the single IQ domains of CNGC20 (cyclic‐nucleotide gated channel‐20) or IQM1 (IQ motif protein1). We examined IQD14 as a representative tandem IQ‐protein and found that only CaM, CML13 and CML14 interacted with IQD14 among 12 CaM/CMLs tested. CaM, CML13 and CML14 bound in vitro to IQD14 in the presence or absence of Ca 2+ . Binding affinities were in the nM range and were higher when two tandem IQ domains from IQD14 were present. Green fluorescent protein‐tagged versions of CaM, CML13 and CML14 localized to both the cytosol and nucleus in plant cells but were partially relocalized to the microtubules when co‐expressed with IQD14 tagged with mCherry. These and other data are discussed in the context of possible roles for these CMLs in gene regulation via CAMTAs and cytoskeletal activity via myosins and IQD proteins.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".