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Record W3195877138 · doi:10.1093/jxb/erab285

MAMP and DAMP signaling contributes resistance to <i>Fusarium graminearum</i> in Arabidopsis

2021· article· en· W3195877138 on OpenAlexafffund
Nimrat Manes, Elizabeth K. Brauer, Shelley R. Hepworth, Rajagopal Subramaniam

Bibliographic record

VenueJournal of Experimental Botany · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsCarleton UniversityAgriculture and Agri-Food Canada
FundersGovernment of Saskatchewan
KeywordsBiologyArabidopsisDampInnate immune systemGenePattern recognition receptorImmune systemChitinCell biologySignal transductionReceptorMicrobiologyGeneticsBiochemistryMutant

Abstract

fetched live from OpenAlex

Plants perceive externally produced microbe-associated molecular patterns (MAMPs) and endogenously produced danger-associated molecular patterns (DAMPs) to activate inducible immunity. While several inducible immune responses have been observed during Fusarium graminearum infection, the identity of the signaling pathways involved is only partly known. We screened 227 receptor kinase and innate immune response genes in Arabidopsis to identify nine genes with a role in F. graminearum resistance. Resistance-promoting genes included the chitin receptors LYK5 and CERK1, and the reactive oxygen species (ROS)-producing NADPH oxidase RbohF, which were required for full inducible immune responses during infection. Two of the genes identified in our screen, APEX and the PAMP-induced peptide 1 (PIP1) DAMP receptor RLK7, repressed F. graminearum resistance. Both RbohF and RLK7 were required for full chitin-induced immune responses and PIP1 precursor expression was induced by chitin and F. graminearum infection. Together, this indicates that F. graminearum resistance is mediated by MAMP and DAMP signaling pathways and that chitin-induced signaling is enhanced by PIP1 perception and ROS production.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.159

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.242
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2021
Admission routes2
Has abstractyes

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