<i>Brachypodium</i> antifreeze protein gene products inhibit ice recrystallization, attenuate ice nucleation, and reduce immune response
Bibliographic record
Abstract
Abstract Antifreeze proteins (AFPs) from the model crop, Brachypodium distachyon , allow freeze survival and attenuate pathogen-mediated ice nucleation. Intriguingly, each Brachypodium AFP gene encodes two proteins, an autonomous AFP and a leucine-rich repeat (LRR). We present structural models suggesting that ice-binding motifs on the ~13 kDa AFPs can “spoil” nucleating arrays on the ~120 kDa bacterial ice nucleating proteins that form ice at high sub-zero temperatures, consistent with decreases in ice nucleating activity by lysates from wildtype compared to transgenic Brachypodium lines. Strikingly, the expression of Brachypodium LRRs in transgenic Arabidopsis inhibited an immune response to pathogen flagella peptides (flg22), with structural modelling suggesting this was due to affinity of the LRR domains to flg22. Thus, these genes play distinctive roles in connecting freeze survival and anti-pathogenic systems via their encoded proteins’ ability to adsorb to ice as well as attenuating bacterial ice nucleation and the host immune response.
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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) | 0.002 | 0.001 |
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".