Mitogen-Activated Protein Kinase Signaling in Plant-Interacting Fungi: Distinct Messages from Conserved Messengers
Bibliographic record
Abstract
Mitogen-activated protein kinases (MAPKs) are evolutionarily conserved proteins that function as key signal transduction components in fungi, plants, and mammals. During interaction between phytopathogenic fungi and plants, fungal MAPKs help to promote mechanical and/or enzymatic penetration of host tissues, while plant MAPKs are required for activation of plant immunity. However, new insights suggest that MAPK cascades in both organisms do not operate independently but that they mutually contribute to a highly interconnected molecular dialogue between the plant and the fungus. As a result, some pathogenesis-related processes controlled by fungal MAPKs lead to the activation of plant signaling, including the recruitment of plant MAPK cascades. Conversely, plant MAPKs promote defense mechanisms that threaten the survival of fungal cells, leading to a stress response mediated in part by fungal MAPK cascades. In this review, we make use of the genomic data available following completion of whole-genome sequencing projects to analyze the structure of MAPK protein families in 24 fungal taxa, including both plant pathogens and mycorrhizal symbionts. Based on conserved patterns of sequence diversification, we also propose the adoption of a unified fungal MAPK nomenclature derived from that established for the model species Saccharomyces cerevisiae. Finally, we summarize current knowledge of the functions of MAPK cascades in phytopathogenic fungi and highlight the central role played by MAPK signaling during the molecular dialogue between plants and invading fungal pathogens.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".