1. Metabolic Modeling of Common Escherichia coli Strains in Human Gut Microbiome
- Author
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Yuqi Zhao, Yue-Dong Gao, and Jing-Fei Huang
- Subjects
Article Subject ,lcsh:Medicine ,Biology ,medicine.disease_cause ,Genome ,Models, Biological ,General Biochemistry, Genetics and Molecular Biology ,Deep sequencing ,Human gut ,Genetic variation ,medicine ,Escherichia coli ,Humans ,Microbiome ,Gene ,Genetics ,General Immunology and Microbiology ,Microbiota ,lcsh:R ,High-Throughput Nucleotide Sequencing ,General Medicine ,Gastrointestinal Tract ,Flux (metabolism) ,Genome, Bacterial ,Metabolic Networks and Pathways ,Research Article - Abstract
The recent high-throughput sequencing has enabled the composition ofEscherichia colistrains in the human microbial community to be profiled en masse. However, there are two challenges to address: (1) exploring the genetic differences betweenE. colistrains in human gut and (2) dynamic responses ofE. colito diverse stress conditions. As a result, we investigated theE. colistrains in human gut microbiome using deep sequencing data and reconstructed genome-wide metabolic networks for the three most commonE. colistrains, includingE. coliHS, UTI89, and CFT073. The metabolic models show obvious strain-specific characteristics, both in network contents and in behaviors. We predicted optimal biomass production for three models on four different carbon sources (acetate, ethanol, glucose, and succinate) and found that these stress-associated genes were involved in host-microbial interactions and increased in human obesity. Besides, it shows that the growth rates are similar among the models, but the flux distributions are different, even inE. colicore reactions. The correlations between human diabetes-associated metabolic reactions in theE. colimodels were also predicted. The study provides a systems perspective onE. colistrains in human gut microbiome and will be helpful in integrating diverse data sources in the following study.
- Published
- 2014
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