Amino acid availability determines plant immune homeostasis in the rhizosphere microbiome
Bibliographic record
Abstract
Abstract Microbes possess conserved microbe-associated molecular patterns (MAMPs) such as flagellin that are recognized by plant receptors to induce immunity. Despite containing the same MAMPs as pathogens, commensals thrive in the plant rhizosphere microbiome indicating they must suppress or evade host immunity. The beneficial bacteria Pseudomonas capeferrum WCS358 can suppress Arabidopsis root immunity via acidification by secreting gluconic acid. While gluconic acid is sufficient to suppress immunity, we found that it is not necessary in a second beneficial strain Pseudomonas simiae WCS417, which produces more gluconic acid than WCS358. To uncover mechanisms that contribute to the suppression of Arabidopsis immunity, we performed a forward genetic screen in EMS-mutagenized P. simiae WCS417 using a flagellin-inducible CYP71A12 pro :GUS reporter as an Arabidopsis immune readout. We identified a mutant that cannot suppress flagellin-elicited CYP71A12 pro :GUS expression or acidify the rhizosphere. Next generation sequencing revealed a mutation in the catabolic site of an ornithine carbamoyltransferase argF , which is required for arginine biosynthesis. The mutant could be complemented by expression of argF from a plasmid, and a Δ argF mutant could not suppress immunity. Fungal pathogens can use alkalization through production of ammonia and glutamate, the arginine biosynthetic precursors, to promote their own growth and virulence. Therefore, we hypothesized that the biosynthesis of specific amino acids may be necessary to reduce levels of ammonia and glutamate to prevent rhizosphere alkalization and bacterial overgrowth. Genetically blocking arginine, glutamine, or proline biosynthesis, or by adding corresponding exogenous amino acids, resulted in rhizosphere alkalization. Interestingly, exogenous amino acids caused bacterial overgrowth in a gluconic acid-deficient mutants. Our findings show that bacterial amino acid biosynthesis contributes to acidification by preventing accumulation of glutamate precursors and the resulting alkalization. Collectively this work shows that by regulating nutrient availability, plants have the potential to regulate their immune homeostasis in the rhizosphere microbiome.
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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".