An endophytic microbe from an unusual volcanic swamp corn seeks and inhabits root hair cells to extract rock phosphate
Bibliographic record
Abstract
In the animal microbiome, localization of microbes to specific cell types is well established, but there are few such examples within the plant microbiome which includes endophytes. Endophytes are non-pathogenic microbes that inhabit plants. Root hairs are single cells, equivalent to the nutrient-absorbing intestinal microvilli of animals, used by plants to increase the root surface area for nutrient extraction from soil including phosphorus (P). There has been significant interest in the microbiome of intestinal microvilli but less is known about the root hair microbiome. Here we describe a bacterial endophyte (3F11) from Zea nicaraguensis, a wild corn discovered in a Nicaraguan swamp above rock-P lava flowing from the San Cristobal volcano. Rock-P is insoluble and a major challenge for plants. Following seed coating and germination on insoluble-P, the endophyte colonized epidermal surfaces, ultimately colonizing root hairs intracellularly. The endophyte promoted root hair growth and secreted acids to solubilize rock-P for uptake by a larger root hair surface. The most interesting observation was that a seed-coated endophyte targeted and colonized a critical cell type, root hair cells, consistent with earlier studies. The endophyte maintained its targeting ability in two evolutionary divergent hosts, suggesting that the host recognition machinery is conserved.
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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) | 0.000 | 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 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".