OsCIPK2 mediated rice root microorganisms and metabolites to improve plant nitrogen uptake
Bibliographic record
Abstract
Crop roots are colonized by large numbers of microorganisms, collectively known as the root-microbiome, which modulate plant growth, development and contribute to elemental nutrient uptake. In conditions of nitrogen limitation, the over-expressed Calcineurin B-like interacting protein kinase 2 (OsCIPK2) gene with root-specific promoter (RC) has been shown to enhance growth and nitrogen uptake in rice. Analysis of root-associated bacteria through high-throughput sequencing revealed that OsCIPK2 has a significant impact on the diversity of the root microbial community under low nitrogen stress. The quantification of nifH gene expression demonstrated a significant enhancement in nitrogen-fixing capabilities in the roots of RC transgenetic rice. Synthetic microbial communities (SynCom) consisting of six nitrogen-fixing bacterial strains were observed to be enriched in the roots of RC, leading to a substantial improvement in rice growth and nitrogen uptake in nitrogen-deficient soils. Forty and twenty-three metabolites exhibiting differential abundance were identified in the roots and rhizosphere soils of RC transgenic rice compared to wild-type (WT) rice. These findings suggest that OSCIPK2 plays a role in restructuring the microbial community in the roots through the regulation of metabolite synthesis and secretion. Further experiments involving the exogenous addition of citric acid revealed that an optimal concentration of this compound facilitated the growth of nitrogen-fixing bacteria and substantially augmented their population in the soil, highlighting the importance of citric acid in promoting nitrogen fixation under conditions of low nitrogen availability. These findings suggest that OsCIPK2 plays a role in enhancing nitrogen uptake by rice plants from the soil by influencing the assembly of root microbial communities, thereby offering valuable insights for enhancing nitrogen utilization in rice cultivation.
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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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".