Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine.
Nontyphoidal Salmonella strains (NTS) are among the most common foodborne enteropathogens and constitute a major cause of global morbidity and mortality, imposing a substantial burden on global health. The increasing antibiotic resistance of NTS bacteria has attracted a lot of research on understand...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-03-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1012869 |
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| author | Evangelia Vayena Lea Fuchs Homa Mohammadi Peyhani Konrad Lagoda Bidong Nguyen Wolf-Dietrich Hardt Vassily Hatzimanikatis |
| author_facet | Evangelia Vayena Lea Fuchs Homa Mohammadi Peyhani Konrad Lagoda Bidong Nguyen Wolf-Dietrich Hardt Vassily Hatzimanikatis |
| author_sort | Evangelia Vayena |
| collection | DOAJ |
| description | Nontyphoidal Salmonella strains (NTS) are among the most common foodborne enteropathogens and constitute a major cause of global morbidity and mortality, imposing a substantial burden on global health. The increasing antibiotic resistance of NTS bacteria has attracted a lot of research on understanding their modus operandi during infection. Growth in the gut lumen is a critical phase of the NTS infection. This might offer opportunities for intervention. However, the metabolic richness of the gut lumen environment and the inherent complexity and robustness of the metabolism of NTS bacteria call for modeling approaches to guide research efforts. In this study, we reconstructed a thermodynamically constrained and context-specific genome-scale metabolic model (GEM) for S. Typhimurium SL1344, a model strain well-studied in infection research. We combined sequence annotation, optimization methods and in vitro and in vivo experimental data. We used GEM to explore the nutritional requirements, the growth limiting metabolic genes, and the metabolic pathway usage of NTS bacteria in a rich environment simulating the murine gut. This work provides insight and hypotheses on the biochemical capabilities and requirements of SL1344 beyond the knowledge acquired through conventional sequence annotation and can inform future research aimed at better understanding NTS metabolism and identifying potential targets for infection prevention. |
| format | Article |
| id | doaj-art-e08f2519f5794c89870f9805b9f8c2d2 |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-e08f2519f5794c89870f9805b9f8c2d22025-08-20T01:55:22ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582025-03-01213e101286910.1371/journal.pcbi.1012869Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine.Evangelia VayenaLea FuchsHoma Mohammadi PeyhaniKonrad LagodaBidong NguyenWolf-Dietrich HardtVassily HatzimanikatisNontyphoidal Salmonella strains (NTS) are among the most common foodborne enteropathogens and constitute a major cause of global morbidity and mortality, imposing a substantial burden on global health. The increasing antibiotic resistance of NTS bacteria has attracted a lot of research on understanding their modus operandi during infection. Growth in the gut lumen is a critical phase of the NTS infection. This might offer opportunities for intervention. However, the metabolic richness of the gut lumen environment and the inherent complexity and robustness of the metabolism of NTS bacteria call for modeling approaches to guide research efforts. In this study, we reconstructed a thermodynamically constrained and context-specific genome-scale metabolic model (GEM) for S. Typhimurium SL1344, a model strain well-studied in infection research. We combined sequence annotation, optimization methods and in vitro and in vivo experimental data. We used GEM to explore the nutritional requirements, the growth limiting metabolic genes, and the metabolic pathway usage of NTS bacteria in a rich environment simulating the murine gut. This work provides insight and hypotheses on the biochemical capabilities and requirements of SL1344 beyond the knowledge acquired through conventional sequence annotation and can inform future research aimed at better understanding NTS metabolism and identifying potential targets for infection prevention.https://doi.org/10.1371/journal.pcbi.1012869 |
| spellingShingle | Evangelia Vayena Lea Fuchs Homa Mohammadi Peyhani Konrad Lagoda Bidong Nguyen Wolf-Dietrich Hardt Vassily Hatzimanikatis Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine. PLoS Computational Biology |
| title | Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine. |
| title_full | Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine. |
| title_fullStr | Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine. |
| title_full_unstemmed | Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine. |
| title_short | Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine. |
| title_sort | metabolic network reconstruction as a resource for analyzing salmonella typhimurium sl1344 growth in the mouse intestine |
| url | https://doi.org/10.1371/journal.pcbi.1012869 |
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