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Genome-scale metabolic reconstructions of multiple Escherichia coli strains highlight strain-specific adaptations to nutritional environments
- Source :
- Proceedings of the National Academy of Sciences. 110:20338-20343
- Publication Year :
- 2013
- Publisher :
- Proceedings of the National Academy of Sciences, 2013.
-
Abstract
- Genome-scale models (GEMs) of metabolism were constructed for 55 fully sequenced Escherichia coli and Shigella strains. The GEMs enable a systems approach to characterizing the pan and core metabolic capabilities of the E. coli species. The majority of pan metabolic content was found to consist of alternate catabolic pathways for unique nutrient sources. The GEMs were then used to systematically analyze growth capabilities in more than 650 different growth-supporting environments. The results show that unique strain-specific metabolic capabilities correspond to pathotypes and environmental niches. Twelve of the GEMs were used to predict growth on six differentiating nutrients, and the predictions were found to agree with 80% of experimental outcomes. Additionally, GEMs were used to predict strain-specific auxotrophies. Twelve of the strains modeled were predicted to be auxotrophic for vitamins niacin (vitamin B3), thiamin (vitamin B1), or folate (vitamin B9). Six of the strains modeled have lost biosynthetic pathways for essential amino acids methionine, tryptophan, or leucine. Genome-scale analysis of multiple strains of a species can thus be used to define the metabolic essence of a microbial species and delineate growth differences that shed light on the adaptation process to a particular microenvironment.
- Subjects :
- Systems biology
Auxotrophy
Adaptation, Biological
Biology
medicine.disease_cause
Microbiology
chemistry.chemical_compound
Species Specificity
Phylogenetics
Escherichia coli
medicine
Nutritional Physiological Phenomena
Phylogeny
Genetics
Multidisciplinary
Methionine
Models, Genetic
Catabolism
Systems Biology
Decision Trees
Computational Biology
Genetic Variation
Biological Sciences
chemistry
Genes, Bacterial
Shigella
Leucine
Adaptation
Genome, Bacterial
Metabolic Networks and Pathways
Subjects
Details
- ISSN :
- 10916490 and 00278424
- Volume :
- 110
- Database :
- OpenAIRE
- Journal :
- Proceedings of the National Academy of Sciences
- Accession number :
- edsair.doi.dedup.....1f0a5a511bc68a0c767b6928502b7961
- Full Text :
- https://doi.org/10.1073/pnas.1307797110