Nucleocytoplasmic partitioning of tobacco N receptor is modulated by <scp>SGT</scp>1
Bibliographic record
Abstract
SGT1 (Suppressor of G2 allele of SKP1) is required to maintain plant disease Resistance (R) proteins with Nucleotide-Binding (NB) and Leucine-Rich Repeat (LRR) domains in an inactive but signaling-competent state. SGT1 is an integral component of a multi-protein network that includes RACK1, Rac1, RAR1, Rboh, HSP90 and HSP70, and in rice the Mitogen-Activated Protein Kinase (MAPK), OsMAPK6. Tobacco (Nicotiana tabacum) N protein, which belongs to the Toll-Interleukin Receptor (TIR)-NB-LRR class of R proteins, confers resistance to Tobacco Mosaic Virus (TMV). Following transient expression in planta, we analyzed the functional relationship between SGT1, SIPK - a tobacco MAPK6 ortholog - and N, using mass spectrometry, confocal microscopy and pathogen assays. Here, we show that tobacco SGT1 undergoes specific phosphorylation in a canonical MAPK target-motif by SIPK. Mutation of this motif to mimic SIPK phosphorylation leads to an increased proportion of cells displaying SGT1 nuclear accumulation and impairs N-mediated resistance to TMV, as does phospho-null substitution at the same residue. Forced nuclear localization of SGT1 causes N to be confined to nuclei. Our data suggest that one mode of regulating nucleocytoplasmic partitioning of R proteins is by maintaining appropriate levels of SGT1 phosphorylation catalyzed by plant MAPK.
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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) | 0.001 | 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".