Comparison of Plant Metabolites in Root Exudates of Lolium perenne Infected with Different Strains of the Fungal Endophyte Epichloë festucae var. lolii
Bibliographic record
Abstract
Lolium perenne infected with the fungal endophyte Epichloë festucae var. lolii have specific, endophyte strain-dependent, chemical phenotypes in their above-ground tissues. Differences in these chemical phenotypes have been largely associated with classes of fungal-derived alkaloids which protect the plant against many insect pests. However, the use of new methodologies, such as various omic techniques, has demonstrated that many other chemical changes occur in both primary and secondary metabolites. Few studies have investigated changes in plant metabolites exiting the plant in the form of root exudates. As root exudates play an essential role in the acquisition of nutrients, microbial associations, and defense in the below-ground environment, it is of interest to understand how plant root exudate chemistry is influenced by the presence of strains of a fungal endophyte. In this study, we tested the influence of four strains of E. festucae var. lolii (E+ (also known as Lp19), AR1, AR37, NEA2), and uninfected controls (E−), on L. perenne growth and the composition of root exudate metabolites. Root exudates present in the hydroponic water were assessed by untargeted metabolomics using Accurate-Mass Quadrupole Time-of-Flight (Q–TOF) liquid chromatography–mass spectrometry (LC–MS). The NEA2 endophyte strain resulted in the greatest plant biomass and the lowest endophyte concentration. We found 84 metabolites that were differentially expressed in at least one of the endophyte treatments compared to E− plants. Two compounds were strongly associated with one endophyte treatment, one in AR37 (m/z 135.0546 RT 1.17), and one in E+ (m/z 517.1987 RT 9.26). These results provide evidence for important changes in L. perenne physiology in the presence of different fungal endophyte strains. Further research should aim to connect changes in root exudate chemical composition with soil ecosystem processes.
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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".