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Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora
BACKGROUND: There is little published regarding metabolism of Salinispora species. In continuation with efforts performed towards this goal, this study is focused on new insights into the metabolism of the three-identified species of Salinispora using constraints-based modeling. At present, only one...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341766/ https://www.ncbi.nlm.nih.gov/pubmed/30665399 http://dx.doi.org/10.1186/s12918-019-0683-1 |
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author | Contador, Carolina A. Rodríguez, Vida Andrews, Barbara A. Asenjo, Juan A. |
author_facet | Contador, Carolina A. Rodríguez, Vida Andrews, Barbara A. Asenjo, Juan A. |
author_sort | Contador, Carolina A. |
collection | PubMed |
description | BACKGROUND: There is little published regarding metabolism of Salinispora species. In continuation with efforts performed towards this goal, this study is focused on new insights into the metabolism of the three-identified species of Salinispora using constraints-based modeling. At present, only one manually curated genome-scale metabolic model (GSM) for Salinispora tropica strain CNB-440(T) has been built despite the role of Salinispora strains in drug discovery. RESULTS: Here, we updated, and expanded the scope of the model of Salinispora tropica CNB-440(T), and GSMs were constructed for two sequenced type strains covering the three-identified species. We also constructed a Salinispora core model that contains the genes shared by 93 sequenced strains and a few non-conserved genes associated with essential reactions. The models predicted no auxotrophies for essential amino acids, which was corroborated experimentally using a defined minimal medium (DMM). Experimental observations suggest possible sulfur accumulation. The Core metabolic content shows that the biosynthesis of specialised metabolites is the less conserved subsystem. Sets of reactions were analyzed to explore the differences between the reconstructions. Unique reactions associated to each GSM were mainly due to genome sequence data except for the ST-CNB440 reconstruction. In this case, additional reactions were added from experimental evidence. This reveals that by reaction content the ST-CNB440 model is different from the other species models. The differences identified in reaction content between models gave rise to different functional predictions of essential nutrient usage by each species in DMM. Furthermore, models were used to evaluate in silico single gene knockouts under DMM and complex medium. Cluster analysis of these results shows that ST-CNB440, and SP-CNR114 models are more similar when considering predicted essential genes. CONCLUSIONS: Models were built for each of the three currently identified Salinispora species, and a core model representing the conserved metabolic capabilities of Salinispora was constructed. Models will allow in silico metabolism studies of Salinispora strains, and help researchers to guide and increase the production of specialised metabolites. Also, models can be used as templates to build GSMs models of closely related organisms with high biotechnology potential. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-019-0683-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6341766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63417662019-01-24 Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora Contador, Carolina A. Rodríguez, Vida Andrews, Barbara A. Asenjo, Juan A. BMC Syst Biol Research Article BACKGROUND: There is little published regarding metabolism of Salinispora species. In continuation with efforts performed towards this goal, this study is focused on new insights into the metabolism of the three-identified species of Salinispora using constraints-based modeling. At present, only one manually curated genome-scale metabolic model (GSM) for Salinispora tropica strain CNB-440(T) has been built despite the role of Salinispora strains in drug discovery. RESULTS: Here, we updated, and expanded the scope of the model of Salinispora tropica CNB-440(T), and GSMs were constructed for two sequenced type strains covering the three-identified species. We also constructed a Salinispora core model that contains the genes shared by 93 sequenced strains and a few non-conserved genes associated with essential reactions. The models predicted no auxotrophies for essential amino acids, which was corroborated experimentally using a defined minimal medium (DMM). Experimental observations suggest possible sulfur accumulation. The Core metabolic content shows that the biosynthesis of specialised metabolites is the less conserved subsystem. Sets of reactions were analyzed to explore the differences between the reconstructions. Unique reactions associated to each GSM were mainly due to genome sequence data except for the ST-CNB440 reconstruction. In this case, additional reactions were added from experimental evidence. This reveals that by reaction content the ST-CNB440 model is different from the other species models. The differences identified in reaction content between models gave rise to different functional predictions of essential nutrient usage by each species in DMM. Furthermore, models were used to evaluate in silico single gene knockouts under DMM and complex medium. Cluster analysis of these results shows that ST-CNB440, and SP-CNR114 models are more similar when considering predicted essential genes. CONCLUSIONS: Models were built for each of the three currently identified Salinispora species, and a core model representing the conserved metabolic capabilities of Salinispora was constructed. Models will allow in silico metabolism studies of Salinispora strains, and help researchers to guide and increase the production of specialised metabolites. Also, models can be used as templates to build GSMs models of closely related organisms with high biotechnology potential. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-019-0683-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-21 /pmc/articles/PMC6341766/ /pubmed/30665399 http://dx.doi.org/10.1186/s12918-019-0683-1 Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Contador, Carolina A. Rodríguez, Vida Andrews, Barbara A. Asenjo, Juan A. Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora |
title | Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora |
title_full | Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora |
title_fullStr | Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora |
title_full_unstemmed | Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora |
title_short | Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora |
title_sort | use of genome-scale models to get new insights into the marine actinomycete genus salinispora |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341766/ https://www.ncbi.nlm.nih.gov/pubmed/30665399 http://dx.doi.org/10.1186/s12918-019-0683-1 |
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