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Proteomic signatures uncover phenotypic plasticity of susceptible and resistant genotypes by wall remodelers in rice blast.

Arunima SinhaKanika NarulaLatika BholaAtreyee SenguptaPooja ChoudharyPragya NalwaMohit KumarEman ElagameyNiranjan ChakrabortySubhra Chakraborty
Published in: Plant, cell & environment (2024)
Molecular communication between macromolecules dictates extracellular matrix (ECM) dynamics during pathogen recognition and disease development. Extensive research has shed light on how plant immune components are activated, regulated and function in response to pathogen attack. However, two key questions remain largely unresolved: (i) how does ECM dynamics govern susceptibility and disease resistance, (ii) what are the components that underpin these phenomena? Rice blast, caused by Magnaporthe oryzae adversely affects rice productivity. To understand ECM regulated genotype-phenotype plasticity in blast disease, we temporally profiled two contrasting rice genotypes in disease and immune state. Morpho-histological, biochemical and electron microscopy analyses revealed that increased necrotic lesions accompanied by electrolyte leakage governs disease state. Wall carbohydrate quantification showed changes in pectin level was more significant in blast susceptible compared to blast resistant cultivar. Temporally resolved quantitative disease- and immune-responsive ECM proteomes identified 308 and 334 proteins, respectively involved in wall remodelling and integrity, signalling and disease/immune response. Pairwise comparisons between time and treatment, messenger ribonucleic acid expression, diseasome and immunome networks revealed novel blast-related functional modules. Data demonstrated accumulation of α-galactosidase and phosphatase were associated with disease state, while reactive oxygen species, induction of Lysin motif proteins, CAZymes and extracellular Ca-receptor protein govern immune state.
Keyphrases
  • extracellular matrix
  • immune response
  • electronic health record
  • dna methylation
  • single cell
  • climate change
  • machine learning
  • small molecule
  • mass spectrometry
  • combination therapy
  • data analysis