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Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits
Salmonella strains are traditionally classified into serovars based on their surface antigens. While increasing availability of whole-genome sequences has allowed for more detailed subtyping of strains, links between genotype, serovar, and host remain elusive. Here we reconstruct genome-scale metabo...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138749/ https://www.ncbi.nlm.nih.gov/pubmed/30218022 http://dx.doi.org/10.1038/s41467-018-06112-5 |
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author | Seif, Yara Kavvas, Erol Lachance, Jean-Christophe Yurkovich, James T. Nuccio, Sean-Paul Fang, Xin Catoiu, Edward Raffatellu, Manuela Palsson, Bernhard O. Monk, Jonathan M. |
author_facet | Seif, Yara Kavvas, Erol Lachance, Jean-Christophe Yurkovich, James T. Nuccio, Sean-Paul Fang, Xin Catoiu, Edward Raffatellu, Manuela Palsson, Bernhard O. Monk, Jonathan M. |
author_sort | Seif, Yara |
collection | PubMed |
description | Salmonella strains are traditionally classified into serovars based on their surface antigens. While increasing availability of whole-genome sequences has allowed for more detailed subtyping of strains, links between genotype, serovar, and host remain elusive. Here we reconstruct genome-scale metabolic models for 410 Salmonella strains spanning 64 serovars. Model-predicted growth capabilities in over 530 different environments demonstrate that: (1) the Salmonella accessory metabolic network includes alternative carbon metabolism, and cell wall biosynthesis; (2) metabolic capabilities correspond to each strain’s serovar and isolation host; (3) growth predictions agree with 83.1% of experimental outcomes for 12 strains (690 out of 858); (4) 27 strains are auxotrophic for at least one compound, including l-tryptophan, niacin, l-histidine, l-cysteine, and p-aminobenzoate; and (5) the catabolic pathways that are important for fitness in the gastrointestinal environment are lost amongst extraintestinal serovars. Our results reveal growth differences that may reflect adaptation to particular colonization sites. |
format | Online Article Text |
id | pubmed-6138749 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61387492018-09-17 Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits Seif, Yara Kavvas, Erol Lachance, Jean-Christophe Yurkovich, James T. Nuccio, Sean-Paul Fang, Xin Catoiu, Edward Raffatellu, Manuela Palsson, Bernhard O. Monk, Jonathan M. Nat Commun Article Salmonella strains are traditionally classified into serovars based on their surface antigens. While increasing availability of whole-genome sequences has allowed for more detailed subtyping of strains, links between genotype, serovar, and host remain elusive. Here we reconstruct genome-scale metabolic models for 410 Salmonella strains spanning 64 serovars. Model-predicted growth capabilities in over 530 different environments demonstrate that: (1) the Salmonella accessory metabolic network includes alternative carbon metabolism, and cell wall biosynthesis; (2) metabolic capabilities correspond to each strain’s serovar and isolation host; (3) growth predictions agree with 83.1% of experimental outcomes for 12 strains (690 out of 858); (4) 27 strains are auxotrophic for at least one compound, including l-tryptophan, niacin, l-histidine, l-cysteine, and p-aminobenzoate; and (5) the catabolic pathways that are important for fitness in the gastrointestinal environment are lost amongst extraintestinal serovars. Our results reveal growth differences that may reflect adaptation to particular colonization sites. Nature Publishing Group UK 2018-09-14 /pmc/articles/PMC6138749/ /pubmed/30218022 http://dx.doi.org/10.1038/s41467-018-06112-5 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Seif, Yara Kavvas, Erol Lachance, Jean-Christophe Yurkovich, James T. Nuccio, Sean-Paul Fang, Xin Catoiu, Edward Raffatellu, Manuela Palsson, Bernhard O. Monk, Jonathan M. Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits |
title | Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits |
title_full | Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits |
title_fullStr | Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits |
title_full_unstemmed | Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits |
title_short | Genome-scale metabolic reconstructions of multiple Salmonella strains reveal serovar-specific metabolic traits |
title_sort | genome-scale metabolic reconstructions of multiple salmonella strains reveal serovar-specific metabolic traits |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138749/ https://www.ncbi.nlm.nih.gov/pubmed/30218022 http://dx.doi.org/10.1038/s41467-018-06112-5 |
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