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Recon 2.2: from reconstruction to model of human metabolism
INTRODUCTION: The human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last commu...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896983/ https://www.ncbi.nlm.nih.gov/pubmed/27358602 http://dx.doi.org/10.1007/s11306-016-1051-4 |
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author | Swainston, Neil Smallbone, Kieran Hefzi, Hooman Dobson, Paul D. Brewer, Judy Hanscho, Michael Zielinski, Daniel C. Ang, Kok Siong Gardiner, Natalie J. Gutierrez, Jahir M. Kyriakopoulos, Sarantos Lakshmanan, Meiyappan Li, Shangzhong Liu, Joanne K. Martínez, Veronica S. Orellana, Camila A. Quek, Lake-Ee Thomas, Alex Zanghellini, Juergen Borth, Nicole Lee, Dong-Yup Nielsen, Lars K. Kell, Douglas B. Lewis, Nathan E. Mendes, Pedro |
author_facet | Swainston, Neil Smallbone, Kieran Hefzi, Hooman Dobson, Paul D. Brewer, Judy Hanscho, Michael Zielinski, Daniel C. Ang, Kok Siong Gardiner, Natalie J. Gutierrez, Jahir M. Kyriakopoulos, Sarantos Lakshmanan, Meiyappan Li, Shangzhong Liu, Joanne K. Martínez, Veronica S. Orellana, Camila A. Quek, Lake-Ee Thomas, Alex Zanghellini, Juergen Borth, Nicole Lee, Dong-Yup Nielsen, Lars K. Kell, Douglas B. Lewis, Nathan E. Mendes, Pedro |
author_sort | Swainston, Neil |
collection | PubMed |
description | INTRODUCTION: The human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed. OBJECTIVES: We report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources. METHODS: Recon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions. RESULTS: Recon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources. CONCLUSION: Through these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-016-1051-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4896983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-48969832016-06-27 Recon 2.2: from reconstruction to model of human metabolism Swainston, Neil Smallbone, Kieran Hefzi, Hooman Dobson, Paul D. Brewer, Judy Hanscho, Michael Zielinski, Daniel C. Ang, Kok Siong Gardiner, Natalie J. Gutierrez, Jahir M. Kyriakopoulos, Sarantos Lakshmanan, Meiyappan Li, Shangzhong Liu, Joanne K. Martínez, Veronica S. Orellana, Camila A. Quek, Lake-Ee Thomas, Alex Zanghellini, Juergen Borth, Nicole Lee, Dong-Yup Nielsen, Lars K. Kell, Douglas B. Lewis, Nathan E. Mendes, Pedro Metabolomics Short Communication INTRODUCTION: The human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed. OBJECTIVES: We report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources. METHODS: Recon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions. RESULTS: Recon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources. CONCLUSION: Through these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-016-1051-4) contains supplementary material, which is available to authorized users. Springer US 2016-06-07 2016 /pmc/articles/PMC4896983/ /pubmed/27358602 http://dx.doi.org/10.1007/s11306-016-1051-4 Text en © The Author(s) 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. |
spellingShingle | Short Communication Swainston, Neil Smallbone, Kieran Hefzi, Hooman Dobson, Paul D. Brewer, Judy Hanscho, Michael Zielinski, Daniel C. Ang, Kok Siong Gardiner, Natalie J. Gutierrez, Jahir M. Kyriakopoulos, Sarantos Lakshmanan, Meiyappan Li, Shangzhong Liu, Joanne K. Martínez, Veronica S. Orellana, Camila A. Quek, Lake-Ee Thomas, Alex Zanghellini, Juergen Borth, Nicole Lee, Dong-Yup Nielsen, Lars K. Kell, Douglas B. Lewis, Nathan E. Mendes, Pedro Recon 2.2: from reconstruction to model of human metabolism |
title | Recon 2.2: from reconstruction to model of human metabolism |
title_full | Recon 2.2: from reconstruction to model of human metabolism |
title_fullStr | Recon 2.2: from reconstruction to model of human metabolism |
title_full_unstemmed | Recon 2.2: from reconstruction to model of human metabolism |
title_short | Recon 2.2: from reconstruction to model of human metabolism |
title_sort | recon 2.2: from reconstruction to model of human metabolism |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896983/ https://www.ncbi.nlm.nih.gov/pubmed/27358602 http://dx.doi.org/10.1007/s11306-016-1051-4 |
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