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Using Bioinformatics and Molecular Biology to Streamline Construction of Effector Libraries for Phytopathogenic Pseudomonas syringae Strains.
Jayaraman, Jay; Halane, Morgan K; Choi, Sera; McCann, Honour C; Sohn, Kee Hoon.
Affiliation
  • Jayaraman J; Department of Life Sciences, Pohang University of Science and Technology, Pohang, Republic of Korea.
  • Halane MK; The New Zealand Institute for Plant & Food Research Ltd, Auckland, New Zealand.
  • Choi S; Department of Life Sciences, Pohang University of Science and Technology, Pohang, Republic of Korea.
  • McCann HC; Department of Life Sciences, Pohang University of Science and Technology, Pohang, Republic of Korea.
  • Sohn KH; New Zealand Institute for Advanced Study, Massey University, Auckland, New Zealand.
Methods Mol Biol ; 1991: 1-12, 2019.
Article in En | MEDLINE | ID: mdl-31041757
ABSTRACT
The war between plants and their pathogens is endless, with plant resistance genes offering protection against pathogens until the pathogen evolves a way to overcome this resistance. Given how quickly new pathogen strains can arise and defeat plant defenses, it is critical to more rapidly identify and examine the specific genomic characteristics new virulent strains have gained which give them the upper hand. An indispensable tool is bioinformatics. Genome sequencing has advanced rapidly in the last decade, and labs are frequently uploading high-quality genomes of various organisms, including plant pathogenic bacteria such as Pseudomonas syringae. Pseudomonas syringae strains inject several effector proteins into host cells which often overcome host defenses. Probing online genomes provides a way to quickly and accurately predict effector repertoires of Pseudomonas, enabling the cloning of complete effector libraries of newly emerged strains. Here, we describe detailed protocols to rapidly clone bioinformatically predicted P. syringae effectors for various screening applications.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Plant Diseases / Bacterial Proteins / Arabidopsis / Computational Biology / Pseudomonas syringae / Host-Pathogen Interactions Type of study: Prognostic_studies Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2019 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Plant Diseases / Bacterial Proteins / Arabidopsis / Computational Biology / Pseudomonas syringae / Host-Pathogen Interactions Type of study: Prognostic_studies Language: En Journal: Methods Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2019 Document type: Article