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Content archived on 2024-05-29

Functional characterization of phytoplasma candidate virulence proteins that target plant cell nuclei

Objective

Phytoplasmas are insect-transmitted intracellular bacterial pathogens that infect plants in domesticated (crops) and natural habitats worldwide. Typically, they induce shoot proliferation and differentiation of floral parts into leafy structures, suggesting interference with basic cellular and developmental pathways.

The applicant has led a consortium that sequenced the 724 kbp genome of aster yellows phytoplasma strain witches¿ broom (AY-WB), and is involved in two further phytoplasma sequencing programmes. Analysis of the AY-WB sequence identified 58 candidate virulence proteins, of which 8 have nuclear localization signals (NLSs). Two of these proteins (A11 and A30) target nuclei in plant cells.

The objective of this proposal is to functionally characterize those candidate virulence proteins that target plant nuclei, with the hypothesis that they could change gene expression profiles through interactions with transcription factors and regulatory sequences. This work takes advantage of the broad host range of AY-WB that includes Nicotiana benthamiana, tomato, and Arabidopsis.

The specific aims of the proposal are:
- to determine the localization of all AY-WB NLS-containing proteins in plants;
- to conduct expression-profiling experiments on plants exposed to A11 and A30;
- to assess whether A11 and A30 bind regulatory sequences and transcription factors and how this may affect host susceptibility.

Relative to other work on bacterial virulence in plants, the work is distinctive in focusing on virulence factors that target nuclei and on intracellular bacterial pathogens. Finally, this project will transfer research experience and knowledge obtained during a seven-year career in the USA to the John Innes Centre, Norwich, UK.

Call for proposal

FP6-2004-MOBILITY-12
See other projects for this call

Coordinator

JOHN INNES CENTRE
EU contribution
No data
Total cost
No data