A receptor kinase gene of the LysM type is involved in legume perception of rhizobial signals
Bibliographic record
Abstract
Abstract Plants belonging to the legume family develop nitrogen-fixing root nodules in symbiosis with bacteria commonly known as rhizobia. The legume host encodes all of the functions necessary to build the specialized symbiotic organ, the nodule, but the process is elicited by the bacteria1, 2, 3. Molecular communication initiates the interaction, and signals, usually flavones, secreted by the legume root induce the bacteria to produce a lipochitin-oligosaccharide signal molecule (Nod-factor), which in turn triggers the plant organogenic process4, 5, 6, 7. An important determinant of bacterial host specificity is the structure of the Nod-factor, suggesting that a plant receptor is involved in signal perception and signal transduction initiating the plant developmental response8, 9. Here we describe the cloning of a putative Nod-factor receptor kinase gene (NFR5) from Lotus japonicus. NFR5 is essential for Nod-factor perception and encodes an unusual transmembrane serine/threonine receptor-like kinase required for the earliest detectable plant responses to bacteria and Nod-factor. The extracellular domain of the putative receptor has three modules with similarity to LysM domains known from peptidoglycan-binding proteins and chitinases. Together with an atypical kinase domain structure this characterizes an unusual receptor-like kinase.
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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".