Over-expression of Cyclic Nucleotide-Gated Ion Channel 2 (CNGC2) triggers hypersensitivity to virulent pathogens and elevated Ca <sup>2+</sup>
Bibliographic record
Abstract
Abstract The Arabidopsis Cyclic Nucleotide-Gated Ion Channel 2 (CNGC2), also known as Defense No Death 1 (DND1), is the most extensively studied plant CNGC and has been implicated in diverse physiological processes, including floral transition, responses to heat and humidity, and hormone signaling. Its role in immunity has received particular attention due to the autoimmunity phenotype observed in the cngc2/dnd1 knockout mutants. Interestingly, despite this hyperactivation of immunity, the mutant also exhibits impaired hypersensitive cell death—a hallmark of effector-triggered immunity (ETI)—as well as reduced reactive oxygen species (ROS) production and diminished Ca²⁺ influx in response to pathogen-associated molecular patterns (PAMPs) such as the bacterial flagellin peptide flg22. These contradictory phenotypes highlight the complex biological functions of CNGC2. To date, most studies have focused on loss-of-function mutants. In this study, we performed a detailed characterization of CNGC2 overexpression lines to gain deeper insight into its role in immunity. Remarkably, overexpression of CNGC2 led to heightened susceptibility to two taxonomically distinct pathogens, despite the plants displaying wild-type morphology. Overexpression of CNGC2 rescued several cngc2 mutant phenotypes, including morphological defects and delayed flowering, yet these plants were also hypersensitive to elevated external Ca²⁺ levels. Furthermore, they exhibited attenuated responses to flg22, suggesting that CNGC2 does not act as a simple positive or negative regulator of immunity. Our findings reveal an essential role for CNGC2 where a balanced expression level is critical for maintaining Ca²⁺ homeostasis between the apoplast and cytosol, thereby influencing the generation of Ca²⁺ signals essential for immune responses.
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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) | 0.000 | 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 | 0.001 |
| 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 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".