Role of a LORELEI- like gene from Phaseolus vulgaris during a mutualistic interaction with Rhizobium tropici
Bibliographic record
Abstract
Reactive oxygen species (ROS), produced by NADPH oxidases known as RBOHs in plants, play a key role in plant development, biotic and abiotic stress responses, hormone signaling, and reproduction. Among the subfamily of receptor-like kinases referred to as CrRLK, there is FERONIA (FER), a regulator of RBOHs, and FER requires a GPI-modified membrane protein produced by LORELEI (LRE) or LORELEI-like proteins (LLG) to reach the plasma membrane and generate ROS. In Arabidopsis, AtLLG1 is involved in interactions with microbes as AtLLG1 interacts with the flagellin receptor (FLS2) to trigger the innate immune response, but the role of LLGs in mutualistic interactions has not been examined. In this study, two Phaseolus vulgaris LLG genes were identified, PvLLG2 that was expressed in floral tissue and PvLLG1 that was expressed in vegetative tissue. Transcripts of PvLLG1 increased during rhizobial nodule formation peaking during the early period of well-developed nodules. Also, P. vulgaris roots expressing pPvLLG1:GFP-GUS showed that this promoter was highly active during rhizobium infections, and very similar to the subcellular localization using a construct pLLG1::PvLLG1-Neon. Compared to control plants, PvLLG1 silenced plants had less superoxide (O2-) at the root tip and elongation zone, spotty hydrogen peroxide (H2O2) in the elongation root zone, and significantly reduced root hair length, nodule number and nitrogen fixation. Unlike control plants, PvLLG1 overexpressing plants showed superoxide beyond the nodule meristem, and significantly increased nodule number and nodule diameter. PvLLG1 appears to play a key role during this mutualistic interaction, possibly due to the regulation of the production and distribution of ROS in roots.
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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 | 0.000 |
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".