Differential alteration of plant functions by homologous fungal candidate effectors
Bibliographic record
Abstract
Abstract Rust fungi are plant pathogens that cause epidemics that threaten the production of important plant species, such as wheat, soy, coffee and poplar. Melampsora larici-populina ( Mlp ) causes the poplar rust and encodes at least 1 184 candidate effectors (CEs), however their functions are poorly known. In this study, we used Arabidopsis plants constitutively expressing CEs of Mlp to discover processes targeted by these fungal proteins. For this purpose, we sequenced the transcriptome and used mass spectrometry to analyse the metabolome of Arabidopsis plants expressing individually one of the 14 selected CEs and of a control line. We found 2 299 deregulated genes across the experiment. Among the down-regulated genes, the KEGG pathways “MAPK signaling pathway” and “Plant-pathogen interaction” were respectively over-represented in six and five of the 14 transgenic lines. Moreover, genes related to hormone response and defense were down-regulated across all transgenic lines are. We further observed that there were 680 metabolites deregulated in at least one CE-expressing transgenic line, with highly unsaturated and phenolic compounds enriched in up-regulated metabolites and peptides enriched among down-regulated metabolites. Interestingly, we found that transgenic lines expressing unrelated CEs had correlated patterns of gene and metabolite deregulation, while expression of CEs belonging to the same family deregulated different genes and metabolites. Taken together, our results indicate that the sequence of effectors and their belonging to families may not be a good predictor of their impact on the plant. Importance Rust fungi are plant pathogens that threaten the production of important crops, including wheat, soy, coffee and poplar. Effectors are used by pathogens to control the host, however in the case of Melampsora larici-populina , the causal agent of the poplar rust, and other rust fungi these proteins are poorly known. We used Arabidopsis plants expressing candidate effectors (CEs) of Mlp to better understand the interaction between this pathogen and its hosts. We found that expression of unrelated CEs led to similar patterns of gene and metabolite deregulation, while transgenic lines expressing CEs belonging to the same family showed different groups of different genes and metabolites deregulated. Thus, our results suggest that functional annotation of effectors based on sequence similarity may be misleading.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".