<i>Lotus japonicus</i> Cytokinin Receptors Work Partially Redundantly to Mediate Nodule Formation
Bibliographic record
Abstract
Previous analysis of the Lotus histidine kinase1 (Lhk1) cytokinin receptor gene has shown that it is required and also sufficient for nodule formation in Lotus japonicus. The L. japonicus mutant carrying the loss-of-function lhk1-1 allele is hyperinfected by its symbiotic partner, Mesorhizobium loti, in the initial absence of nodule organogenesis. At a later time point following bacterial infection, lhk1-1 develops a limited number of nodules, suggesting the presence of an Lhk1-independent mechanism. We have tested a hypothesis that other cytokinin receptors function in at least a partially redundant manner with LHK1 to mediate nodule organogenesis in L. japonicus. We show here that L. japonicus contains a small family of four cytokinin receptor genes, which all respond to M. loti infection. We show that within the root cortex, LHK1 performs an essential role but also works partially redundantly with LHK1A and LHK3 to mediate cell divisions for nodule primordium formation. The LHK1 receptor is also presumed to partake in mediating a feedback mechanism that negatively regulates bacterial infections at the root epidermis. Interestingly, the Arabidopsis thaliana AHK4 receptor gene can functionally replace Lhk1 in mediating nodule organogenesis, indicating that the ability to perform this developmental process is not determined by unique, legume-specific properties of LHK1.
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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".