Chitooligosaccharide receptors modulate root microbiota to enhance symbiosis and growth in Medicago
Bibliographic record
Abstract
Plant roots interact with beneficial microbes, such as arbuscular mycorrhizal fungi (AMF), to aid in nutrient uptake. The interaction with AMF is initiated by plant Lysin motif (LysM) receptor-like kinases, CERK1 and LYR4 in Medicago truncatula, that detect AMF signals such as chitooligosaccharides (COs). However, the broader role of AMF-detecting receptors in shaping the root microbial community is largely unknown, and the impact of these receptor-mediated microbial communities on the AMF symbiosis is yet to be determined. This study examines the effects of CERK1 and LYR4 mutations on the root bacterial community, showing that these receptors have significant effects on shaping the bacterial community. Using bacteria isolated from wild-type roots, we created a synthetic bacterial community (SynCom), CO-SynCom. Plants inoculated with CO-SynCom exhibited significantly enhanced growth and AMF colonization in a manner dependent on the CO receptors LYR4 and CERK1, likely due to CERK1- and LYR4-mediated changes in hormone-related pathways and activation of symbiosis signaling. Our results highlight the essential role of plant symbiotic receptors in shaping root microbiota and offer valuable insights into optimizing plant-microbe interactions to enhance symbiosis and support sustainable agriculture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".