Literature DB >> 20709733

Comparative analysis of metabolic networks provides insight into the evolution of plant pathogenic and nonpathogenic lifestyles in Pseudomonas.

Aziz Mithani1, Jotun Hein, Gail M Preston.   

Abstract

Plant pathogenic pseudomonads such as Pseudomonas syringae colonize plant surfaces and tissues and have been reported to be nutritionally specialized relative to nonpathogenic pseudomonads. We performed comparative analyses of metabolic networks reconstructed from genome sequence data in order to investigate the hypothesis that P. syringae has evolved to be metabolically specialized for a plant pathogenic lifestyle. We used the metabolic network comparison tool Rahnuma and complementary bioinformatic analyses to compare the distribution of 1,299 metabolic reactions across nine genome-sequenced strains of Pseudomonas, including three strains of P. syringae. The two pathogenic Pseudomonas species analyzed, P. syringae and the opportunistic human pathogen P. aeruginosa, each displayed a high level of intraspecies metabolic similarity compared with nonpathogenic Pseudomonas. The three P. syringae strains lacked a significant number of reactions predicted to be present in all other Pseudomonas strains analyzed, which is consistent with the hypothesis that P. syringae is adapted for growth in a nutritionally constrained environment. Pathway predictions demonstrated that some of the differences detected in metabolic network comparisons could account for differences in amino acid assimilation ability reported in experimental analyses. Parsimony analysis and reaction neighborhood approaches were used to model the evolution of metabolic networks and amino acid assimilation pathways in pseudomonads. Both methods supported a model of Pseudomonas evolution in which the common ancestor of P. syringae had experienced a significant number of deletion events relative to other nonpathogenic pseudomonads. We discuss how the characteristic metabolic features of P. syringae could reflect adaptation to a pathogenic lifestyle.

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Year:  2010        PMID: 20709733     DOI: 10.1093/molbev/msq213

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  21 in total

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Journal:  Curr Opin Biotechnol       Date:  2011-04-12       Impact factor: 9.740

2.  Evolutionary plasticity in the allosteric regulator-binding site of pyruvate kinase isoform PykA from Pseudomonas aeruginosa.

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3.  Pseudomonas syringae naturally lacking the canonical type III secretion system are ubiquitous in nonagricultural habitats, are phylogenetically diverse and can be pathogenic.

Authors:  Moudjahidou Demba Diallo; Caroline L Monteil; Boris A Vinatzer; Christopher R Clarke; Catherine Glaux; Caroline Guilbaud; Cécile Desbiez; Cindy E Morris
Journal:  ISME J       Date:  2012-01-12       Impact factor: 10.302

4.  CrcZ and CrcX regulate carbon source utilization in Pseudomonas syringae pathovar tomato strain DC3000.

Authors:  Melanie J Filiatrault; Paul V Stodghill; Janet Wilson; Bronwyn G Butcher; Hanrong Chen; Christopher R Myers; Samuel W Cartinhour
Journal:  RNA Biol       Date:  2013-01-25       Impact factor: 4.652

Review 5.  Pseudomonas savastanoi pv. savastanoi: some like it knot.

Authors:  Cayo Ramos; Isabel M Matas; Leire Bardaji; Isabel M Aragón; Jesús Murillo
Journal:  Mol Plant Pathol       Date:  2012-07-17       Impact factor: 5.663

6.  MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models.

Authors:  Piotr Zakrzewski; Marnix H Medema; Albert Gevorgyan; Andrzej M Kierzek; Rainer Breitling; Eriko Takano
Journal:  PLoS One       Date:  2012-12-14       Impact factor: 3.240

7.  Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics.

Authors:  Lea A I Vaas; Johannes Sikorski; Victoria Michael; Markus Göker; Hans-Peter Klenk
Journal:  PLoS One       Date:  2012-04-20       Impact factor: 3.240

8.  Comparative genomic analysis of four representative plant growth-promoting rhizobacteria in Pseudomonas.

Authors:  Xuemei Shen; Hongbo Hu; Huasong Peng; Wei Wang; Xuehong Zhang
Journal:  BMC Genomics       Date:  2013-04-22       Impact factor: 3.969

9.  Wide screening of phage-displayed libraries identifies immune targets in planta.

Authors:  Cristina Rioja; Saskia C Van Wees; Keith A Charlton; Corné M J Pieterse; Oscar Lorenzo; Susana García-Sánchez
Journal:  PLoS One       Date:  2013-01-25       Impact factor: 3.240

10.  CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways.

Authors:  Gamze Abaka; Türker Bıyıkoğlu; Cesim Erten
Journal:  Bioinformatics       Date:  2013-07-01       Impact factor: 6.937

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