Arbuscular mycorrhizal fungi enhance plant phosphorus uptake through stimulating hyphosphere soil microbiome functional profiles for phosphorus turnover
Bibliographic record
Abstract
Summary The extraradical hyphae of arbuscular mycorrhizal (AM) fungi are colonized by different bacteria in natural and agricultural systems, but the mechanisms by which AM fungi interact with the hyphosphere soil microbiome and influence soil organic phosphorus (P) mobilization remain unclear. We grew Medicago in two‐compartment microcosms, inoculated with Rhizophagus irregularis , or not, in the root compartment and set up P treatments (without P, with P addition as KH 2 PO 4 or nonsoluble phytate) in the hyphal compartment. We studied the processes of soil P turnover and characterized the microbiome functional profiles for P turnover in the hyphosphere soil by metagenomic sequencing. Compared with the bulk soil, the hyphosphere soil of R. irregularis was inhabited by a specific bacterial community and their functional profiles for P turnover was stimulated. At the species level, the shift in hyphosphere soil microbiome was characterized by the recruitment of the genome bin2.39 harbouring both gcd and phoD genes and genome bin2.97 harbouring the phoD gene, which synergistically drove nonsoluble phytate mobilization in the hyphosphere soil. Our results suggest that AM fungi recruits a specific hyphosphere soil microbiome and stimulated their functional profiles for P turnover to enhance utilization of phytate.
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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 | 0.000 |
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".