Marshalling the Troops: Intracellular Dynamics in Plant Pathogen Defense
Bibliographic record
Abstract
Abstract Plants have evolved sophisticated defense systems against pathogen infection. Initiation of induced defense signaling involves recognition of invading pathogens at the plant cell surface, followed by rapid transcriptional reprogramming and focused transport and delivery of antimicrobial products to the site of infection. This review chapter summarizes recent findings of the importance of intracellular dynamics in the plants defense against microbial pathogens. We first discuss events at the cell wall and apoplast, the ‘front line’ of defense against the invader. It is clear that some defense peptides and molecules secreted by the plant cell host have antimicrobial activity – until recently relatively little was known about the regulation and coordination of directed accumulation to sites of attempted pathogen attack. Molecular genetic studies on the breakdown of resistance to non‐adapted fungi have highlighted the role of proteins involved in exocytic vesicle fusion and their possible regulation by transmembrane MLO proteins. Another key process in perception and defense at the cell periphery in eukaryotes is ligand‐stimulated endocytosis of receptors for microbial proteins; an example in plants is the flagellin receptor FLS2. The second part of this chapter focuses on the role of nucleocytoplasmic trafficking across the nuclear pore complex in plant innate immunity. Current work highlights the dynamic regulation of defense proteins and the role of specific components of the nuclear pore complex and the nuclear import and export machinery in response to pathogens. The unexpected recent discovery of NB‐LRR immune receptors from different species in the nucleus points to a condensed and rapid pathway of communication between the site of perception and activation of defense genes. While the details on spatial and temporal control of these dynamic intracellular processes remain to be elucidated, it is currently an area of intense research.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".