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Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments

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 locat...

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Autores principales: Ding, Tong, Case, Kyle A., Omolo, Morrine A., Reiland, Holly A., Metz, Zachary P., Diao, Xinyu, Baumler, David J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4757543/
https://www.ncbi.nlm.nih.gov/pubmed/26885654
http://dx.doi.org/10.1371/journal.pone.0149423
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author Ding, Tong
Case, Kyle A.
Omolo, Morrine A.
Reiland, Holly A.
Metz, Zachary P.
Diao, Xinyu
Baumler, David J.
author_facet Ding, Tong
Case, Kyle A.
Omolo, Morrine A.
Reiland, Holly A.
Metz, Zachary P.
Diao, Xinyu
Baumler, David J.
author_sort Ding, Tong
collection PubMed
description 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.
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spelling pubmed-47575432016-02-26 Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments Ding, Tong Case, Kyle A. Omolo, Morrine A. Reiland, Holly A. Metz, Zachary P. Diao, Xinyu Baumler, David J. PLoS One Research Article 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. Public Library of Science 2016-02-17 /pmc/articles/PMC4757543/ /pubmed/26885654 http://dx.doi.org/10.1371/journal.pone.0149423 Text en © 2016 Ding et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ding, Tong
Case, Kyle A.
Omolo, Morrine A.
Reiland, Holly A.
Metz, Zachary P.
Diao, Xinyu
Baumler, David J.
Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments
title Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments
title_full Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments
title_fullStr Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments
title_full_unstemmed Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments
title_short Predicting Essential Metabolic Genome Content of Niche-Specific Enterobacterial Human Pathogens during Simulation of Host Environments
title_sort predicting essential metabolic genome content of niche-specific enterobacterial human pathogens during simulation of host environments
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4757543/
https://www.ncbi.nlm.nih.gov/pubmed/26885654
http://dx.doi.org/10.1371/journal.pone.0149423
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