<scp>TIR</scp>‐<scp>NB</scp>‐<scp>LRR</scp> immune receptor <scp>SOC</scp>3 pairs with truncated <scp>TIR</scp>‐<scp>NB</scp> protein <scp>CHS</scp>1 or <scp>TN</scp>2 to monitor the homeostasis of E3 ligase <scp>SAUL</scp>1
Bibliographic record
Abstract
Intracellular nucleotide binding (NB) and leucine-rich repeat (NLR) proteins function as immune receptors to recognize effectors from pathogens. They often guard host proteins that are the direct targets of those effectors. Recent findings have revealed that a typical NLR sometimes cooperates with another atypical NLR for effector recognition. Here, by using the CRISPR/Cas9 gene editing method, knockout analysis and biochemical assays, we uncovered differential pairings of typical Toll Interleukin1 receptor (TIR) type NLR (TNL) receptor SOC3 with atypical truncated TIR-NB (TN) proteins CHS1 or TN2 to guard the homeostasis of the E3 ligase SAUL1. Overaccumulation of SAUL1 is monitored by the SOC3-TN2 pair, while SAUL1's disappearance is guarded by the SOC3-CHS1 pair. SOC3 forms a head-to-head genomic arrangement with CHS1 and TN2, indicative of transcriptional co-regulation. Such intricate cooperative interactions can probably enlarge the recognition spectrum and increase the functional flexibility of NLRs, which can partly explain the overwhelming occurrence of NLR gene clustering in higher plants.
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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 | 0.008 | 0.073 |
| Meta-epidemiology (narrow) | 0.010 | 0.009 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.012 | 0.005 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.001 | 0.020 |
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; both teacher heads agree on what is shown here.
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".