Evidence map›Paper›PMID 42496748›Full record

ReviewPlant cell reports2026

Phosphorylation networks as regulatory hubs in plant stress signaling: kinase dynamics, crosstalk, and network plasticity.

Teja Manda, Delight Hwarari, Raphael Dzinyela

Abstract readReview
PubMed Publisher
In one paragraph

Review in Plant cell reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Teja MandaState Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, 213007, China.
Delight HwarariState Key Laboratory of Tree Genetics and Breeding, Nanjing Forestry University, Nanjing, 213007, China.
Raphael DzinyelaDepartment of Chemistry and Biochemistry, Stephenson Life Sciences Research Center, University of Oklahoma, Norman, OK, 73019, USA. Raphael.dzinyela@ou.edu.ORCID https://orcid.org/0000-0003-4869-6337

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Agriculture faces significant limitations from climate change, soil degradation, and a wide range of abiotic and biotic stresses that continually threaten global food security. Although transcriptional and hormonal regulatory networks have been extensively studied, post-translational modifications (PTMs), particularly phosphorylation, remain comparatively underexplored despite their central role in rapid stress signaling. In this review, we synthesize recent advances in phosphoproteomics, kinase network mapping, and systems biology to highlight phosphorylation as a key regulatory hub in plant stress responses. Drawing from both model species and crops, we emphasize major kinase families, including MAPKs, CDPKs, RLKs, and SnRK1/TOR, which translate calcium signatures, reactive oxygen species (ROS) waves, and cellular energy status into precise physiological outputs. We also discuss how multi-omics integration, precision breeding, synthetic biology, and microbiome engineering can leverage phosphorylation dynamics to advance climate-smart agriculture. By outlining phosphorylation networks as functional regulators, this work underscores their translational potential for developing resilient crops that can maintain yield under environmental extremes.

Indexed as

PlantsProtein KinasesSignal TransductionStress, PhysiologicalPhosphorylationPlant ProteinsProtein Processing, Post-TranslationalPlant ProteinsProtein KinasesPhosphoproteomicsPhosphorylationPost-translational modificationProtein kinasesStress signaling

Identifiers

PMID42496748

What Socratic holds

Textmetadata
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 Socratic graph.