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Systems biology of the structural proteome

BACKGROUND: The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structur...

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Autores principales: Brunk, Elizabeth, Mih, Nathan, Monk, Jonathan, Zhang, Zhen, O’Brien, Edward J., Bliven, Spencer E., Chen, Ke, Chang, Roger L., Bourne, Philip E., Palsson, Bernhard O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4787049/
https://www.ncbi.nlm.nih.gov/pubmed/26969117
http://dx.doi.org/10.1186/s12918-016-0271-6
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author Brunk, Elizabeth
Mih, Nathan
Monk, Jonathan
Zhang, Zhen
O’Brien, Edward J.
Bliven, Spencer E.
Chen, Ke
Chang, Roger L.
Bourne, Philip E.
Palsson, Bernhard O.
author_facet Brunk, Elizabeth
Mih, Nathan
Monk, Jonathan
Zhang, Zhen
O’Brien, Edward J.
Bliven, Spencer E.
Chen, Ke
Chang, Roger L.
Bourne, Philip E.
Palsson, Bernhard O.
author_sort Brunk, Elizabeth
collection PubMed
description BACKGROUND: The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology. RESULTS: Here, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository (https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/). CONCLUSIONS: Translating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism’s genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0271-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-47870492016-03-12 Systems biology of the structural proteome Brunk, Elizabeth Mih, Nathan Monk, Jonathan Zhang, Zhen O’Brien, Edward J. Bliven, Spencer E. Chen, Ke Chang, Roger L. Bourne, Philip E. Palsson, Bernhard O. BMC Syst Biol Research Article BACKGROUND: The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology. RESULTS: Here, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository (https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/). CONCLUSIONS: Translating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism’s genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0271-6) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-11 /pmc/articles/PMC4787049/ /pubmed/26969117 http://dx.doi.org/10.1186/s12918-016-0271-6 Text en © Brunk et al. 2016 Open AccessThis 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
Brunk, Elizabeth
Mih, Nathan
Monk, Jonathan
Zhang, Zhen
O’Brien, Edward J.
Bliven, Spencer E.
Chen, Ke
Chang, Roger L.
Bourne, Philip E.
Palsson, Bernhard O.
Systems biology of the structural proteome
title Systems biology of the structural proteome
title_full Systems biology of the structural proteome
title_fullStr Systems biology of the structural proteome
title_full_unstemmed Systems biology of the structural proteome
title_short Systems biology of the structural proteome
title_sort systems biology of the structural proteome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4787049/
https://www.ncbi.nlm.nih.gov/pubmed/26969117
http://dx.doi.org/10.1186/s12918-016-0271-6
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