Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic <i>Escherichia coli</i> Strain Nissle 1917
<i>Escherichia coli</i> Nissle 1917 (EcN) is an intestinal probiotic that is effective for the treatment of intestinal disorders, such as inflammatory bowel disease and ulcerative colitis. EcN is a representative Gram-negative probiotic in biomedical research and is an intensively studie...
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| Format: | Article |
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MDPI AG
2021-02-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/22/4/2122 |
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| author | Dohyeon Kim Youngshin Kim Sung Ho Yoon |
| author_facet | Dohyeon Kim Youngshin Kim Sung Ho Yoon |
| author_sort | Dohyeon Kim |
| collection | DOAJ |
| description | <i>Escherichia coli</i> Nissle 1917 (EcN) is an intestinal probiotic that is effective for the treatment of intestinal disorders, such as inflammatory bowel disease and ulcerative colitis. EcN is a representative Gram-negative probiotic in biomedical research and is an intensively studied probiotic. However, to date, its genome-wide metabolic network model has not been developed. Here, we developed a comprehensive and highly curated EcN metabolic model, referred to as iDK1463, based on genome comparison and phenome analysis. The model was improved and validated by comparing the simulation results with experimental results from phenotype microarray tests. iDK1463 comprises 1463 genes, 1313 unique metabolites, and 2984 metabolic reactions. Phenome data of EcN were compared with those of <i>Escherichia coli</i> intestinal commensal K-12 MG1655. iDK1463 was simulated to identify the genetic determinants responsible for the observed phenotypic differences between EcN and K-12. Further, the model was simulated for gene essentiality analysis and utilization of nutrient sources under anaerobic growth conditions. These analyses provided insights into the metabolic mechanisms by which EcN colonizes and persists in the gut. iDK1463 will contribute to the system-level understanding of the functional capacity of gut microbes and their interactions with microbiota and human hosts, as well as the development of live microbial therapeutics. |
| first_indexed | 2024-03-09T00:41:03Z |
| format | Article |
| id | doaj.art-d9ddd8ba6eb44af6aed89d9f726aa039 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-09T00:41:03Z |
| publishDate | 2021-02-01 |
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| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-d9ddd8ba6eb44af6aed89d9f726aa0392023-12-11T17:51:26ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-02-01224212210.3390/ijms22042122Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic <i>Escherichia coli</i> Strain Nissle 1917Dohyeon Kim0Youngshin Kim1Sung Ho Yoon2Department of Bioscience and Biotechnology, Konkuk University, Seoul 05029, KoreaDepartment of Bioscience and Biotechnology, Konkuk University, Seoul 05029, KoreaDepartment of Bioscience and Biotechnology, Konkuk University, Seoul 05029, Korea<i>Escherichia coli</i> Nissle 1917 (EcN) is an intestinal probiotic that is effective for the treatment of intestinal disorders, such as inflammatory bowel disease and ulcerative colitis. EcN is a representative Gram-negative probiotic in biomedical research and is an intensively studied probiotic. However, to date, its genome-wide metabolic network model has not been developed. Here, we developed a comprehensive and highly curated EcN metabolic model, referred to as iDK1463, based on genome comparison and phenome analysis. The model was improved and validated by comparing the simulation results with experimental results from phenotype microarray tests. iDK1463 comprises 1463 genes, 1313 unique metabolites, and 2984 metabolic reactions. Phenome data of EcN were compared with those of <i>Escherichia coli</i> intestinal commensal K-12 MG1655. iDK1463 was simulated to identify the genetic determinants responsible for the observed phenotypic differences between EcN and K-12. Further, the model was simulated for gene essentiality analysis and utilization of nutrient sources under anaerobic growth conditions. These analyses provided insights into the metabolic mechanisms by which EcN colonizes and persists in the gut. iDK1463 will contribute to the system-level understanding of the functional capacity of gut microbes and their interactions with microbiota and human hosts, as well as the development of live microbial therapeutics.https://www.mdpi.com/1422-0067/22/4/2122<i>Escherichia coli</i> Nissle 1917probioticsmetabolic network modelphenome analysisflux balance analysis |
| spellingShingle | Dohyeon Kim Youngshin Kim Sung Ho Yoon Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic <i>Escherichia coli</i> Strain Nissle 1917 International Journal of Molecular Sciences <i>Escherichia coli</i> Nissle 1917 probiotics metabolic network model phenome analysis flux balance analysis |
| title | Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic <i>Escherichia coli</i> Strain Nissle 1917 |
| title_full | Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic <i>Escherichia coli</i> Strain Nissle 1917 |
| title_fullStr | Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic <i>Escherichia coli</i> Strain Nissle 1917 |
| title_full_unstemmed | Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic <i>Escherichia coli</i> Strain Nissle 1917 |
| title_short | Development of a Genome-Scale Metabolic Model and Phenome Analysis of the Probiotic <i>Escherichia coli</i> Strain Nissle 1917 |
| title_sort | development of a genome scale metabolic model and phenome analysis of the probiotic i escherichia coli i strain nissle 1917 |
| topic | <i>Escherichia coli</i> Nissle 1917 probiotics metabolic network model phenome analysis flux balance analysis |
| url | https://www.mdpi.com/1422-0067/22/4/2122 |
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