Microorganisms have evolved to occupy certain environmental niches, and the metabolic genes essential for growth in these locations are retained in the genomes. Many microorganisms inhabit niches located in the human body, sometimes causing disease, and may retain genes essential for growth in locations such as the bloodstream and urinary tract, or growth during intracellular invasion of the hosts' macrophage cells. Strains of Escherichia coli (E. coli) and Salmonella spp. are thought to have evolved over 100 million years from a common ancestor, and now cause disease in specific niches within humans. Here we have used a genome scale metabolic model representing the pangenome of E. coli which contains all metabolic reactions encoded by genes from 16 E. coli genomes, and have simulated environmental conditions found in the human bloodstream, urinary tract, and macrophage to determine essential metabolic genes needed for growth in each location. We compared the predicted essential genes for three E. coli strains and one Salmonella strain that cause disease in each host environment, and determined that essential gene retention could be accurately predicted using this approach. This project demonstrated that simulating human body environments such as the bloodstream can successfully lead to accurate computational predictions of essential/important genes.
|Original language||English (US)|
|State||Published - Feb 2016|
Bibliographical noteFunding Information:
We would also like to thank Dr(s). William R. Harcombe, Guy Plunkett III, Bob Mau, and Eric Cabot for insightful discussions regarding gene essentiality within the genomes of members of the family Enterobacteriaceae. This work was partially funded by the Department of Food Science and Nutrition and the College of Food, Agricultural and Natural Resource Sciences at the University of Minnesota-Twin Cities (DJB), and partially by the Global Food Ventures Graduate Student Fellowship from the University of Minnesota-Twin Cities (ZPM), and the Schlumberger Faculty for the Future Graduate Student Fellowship (MAO).
© 2016 Ding et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.