Literature DB >> 19576777

Gene Ontology for type III effectors: capturing processes at the host-pathogen interface.

Magdalen Lindeberg1, Alan Collmer.   

Abstract

Disease development is determined by the interplay of host defense processes and pathogen factors that subvert defenses and remodel the host for parasitic benefit. The goal of the Plant-Associated Microbe Gene Ontology (PAMGO) interest group is the development of Gene Ontology (GO) terms that capture the range of biological processes occurring between hosts and symbionts (from mutualists to pathogens). Here, the application of the new GO terms to type III effector proteins (T3Es) from the plant pathogen Pseudomonas syringae serves as an example to systematically document the available extensive data and to reveal shared aspects of interactions with various host plants. Extending the comparison to T3Es deployed by animal pathogens further highlights how GO can uncover the common strategies employed by diverse symbionts as they exploit the host niche. Future application of GO terms to gene products mediating pathogenic or mutualistic interactions involving other microbes will enhance researchers' abilities to identify fundamental patterns among diverse systems and generate new hypotheses based on associations among annotations.

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Year:  2009        PMID: 19576777     DOI: 10.1016/j.tim.2009.04.001

Source DB:  PubMed          Journal:  Trends Microbiol        ISSN: 0966-842X            Impact factor:   17.079


  6 in total

1.  The what, where, how and why of gene ontology--a primer for bioinformaticians.

Authors:  Louis du Plessis; Nives Skunca; Christophe Dessimoz
Journal:  Brief Bioinform       Date:  2011-02-17       Impact factor: 11.622

2.  Development of an Ontology for Periodontitis.

Authors:  Asami Suzuki; Takako Takai-Igarashi; Jun Nakaya; Hiroshi Tanaka
Journal:  J Biomed Semantics       Date:  2015-07-01

3.  Information Management of Genome Enabled Data Streams for Pseudomonas syringae on the Pseudomonas-Plant Interaction (PPI) Website.

Authors:  Magdalen Lindeberg
Journal:  Genes (Basel)       Date:  2011-11-02       Impact factor: 4.096

4.  Effective identification of bacterial type III secretion signals using joint element features.

Authors:  Yejun Wang; Ming'an Sun; Hongxia Bao; Qing Zhang; Dianjing Guo
Journal:  PLoS One       Date:  2013-04-04       Impact factor: 3.240

5.  T3_MM: a Markov model effectively classifies bacterial type III secretion signals.

Authors:  Yejun Wang; Ming'an Sun; Hongxia Bao; Aaron P White
Journal:  PLoS One       Date:  2013-03-05       Impact factor: 3.240

6.  Real time live imaging of phytopathogenic bacteria Xanthomonas campestris pv. campestris MAFF106712 in 'plant sweet home'.

Authors:  Chiharu Akimoto-Tomiyama; Ayako Furutani; Hirokazu Ochiai
Journal:  PLoS One       Date:  2014-04-15       Impact factor: 3.240

  6 in total

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