Evidence map›Paper›PMID 36212348›Full record

ReviewFrontiers in plant science2022

ZAR1: Guardian of plant kinases.

Clare Breit-McNally, Bradley Laflamme, Racquel A Singh, Darrell Desveaux, David S Guttman

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
  2. Article
  3. A physical model links structure and function in the plant immune system.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Frontiers in plant science · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Clare Breit-McNallyDepartment of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada.
Bradley LaflammeDepartment of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada.
Racquel A SinghDepartment of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada.
Darrell DesveauxDepartment of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada.
David S GuttmanDepartment of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A key facet of innate immunity in plants entails the recognition of pathogen "effector" virulence proteins by host Nucleotide-Binding Leucine-Rich Repeat Receptors (NLRs). Among characterized NLRs, the broadly conserved ZAR1 NLR is particularly remarkable due to its capacity to recognize at least six distinct families of effectors from at least two bacterial genera. This expanded recognition spectrum is conferred through interactions between ZAR1 and a dynamic network of two families of Receptor-Like Cytoplasmic Kinases (RLCKs): ZED1-Related Kinases (ZRKs) and PBS1-Like Kinases (PBLs). In this review, we survey the history of functional studies on ZAR1, with an emphasis on how the ZAR1-RLCK network functions to trap diverse effectors. We discuss 1) the dynamics of the ZAR1-associated RLCK network; 2) the specificity between ZRKs and PBLs; and 3) the specificity between effectors and the RLCK network. We posit that the shared protein fold of kinases and the switch-like properties of their interactions make them ideal effector sensors, enabling ZAR1 to act as a broad spectrum guardian of host kinases.

Indexed as

arabidopsiseffector-triggered immunitykinasesnetworkPBLpseudokinasesZAR1ZRK

Identifiers

PMID36212348
PMCPMC9539561

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.