<scp>d</scp>‐Lactic acid secreted by <i>Chlorella fusca</i> primes pattern‐triggered immunity against <i>Pseudomonas syringae</i> in Arabidopsis
Bibliographic record
Abstract
Biological control agents including microbes and their products have been studied as sustainable crop protection strategies. Although aquatic microalgae have been recently introduced as a biological control agent, the underlying molecular mechanisms are largely unknown. The aim of the present study was to investigate the molecular mechanisms underlying biological control by microalga Chlorella fusca. Foliar application of C. fusca elicits induced resistance in Arabidopsis thaliana against Pseudomonas syringae pv. tomato DC3000 that activates plant immunity rather than direct antagonism. To understand the basis of C. fusca-triggered induced resistance at the transcriptional level, we conducted RNA sequencing (RNA-seq) analysis. RNA-seq data showed that, upon pathogen inoculation, C. fusca treatment primed the expression of cysteine-rich receptor-like kinases, WRKY transcription factor genes, and salicylic acid and jasmonic acid signalling-related genes. Intriguingly, the application of C. fusca primed pathogen-associated molecular pattern -triggered immunity, characterized by reactive oxygen species burst and callose deposition, upon flagellin 22 treatment. The attempts to find C. fusca determinants allowed us to identify d-lactic acid secreted in the supernatant of C. fusca as a defence priming agent. This is the first report of the mechanism of innate immune activation by aquatic microalga Chlorella in higher plants.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".