A community-driven global reconstruction of human metabolism

Ines Thiele; Neil Swainston; Ronan M.T. Fleming; Andreas Hoppe; Swagatika Sahoo; Maike K. Aurich; Hulda Haraldsdottir; Monica L. Mo; Ottar Rolfsson; Miranda D. Stobbe; Stefan G. Thorleifsson; Rasmus Agren; Christian Bölling; Sergio Bordel; Arvind K. Chavali; Paul Dobson; Warwick B. Dunn; Lukas Endler; David Hala; Michael Hucka; Duncan Hull; Daniel Jameson; Neema Jamshidi; Jon J. Jonsson; Nick Juty; Sarah Keating; Intawat Nookaew; Nicolas Le Novère; Naglis Malys; Alexander Mazein; Jason A. Papin; Nathan D. Price; Evgeni Selkov; Martin I. Sigurdsson; Evangelos Simeonidis; Nikolaus Sonnenschein; Kieran Smallbone; Anatoly Sorokin; Johannes H.G.M. Van Beek; Dieter Weichart; Igor Goryanin; Jens Nielsen; Hans V. Westerhoff; Douglas B. Kell; Pedro Mendes; Bernhard O. Palsson

doi:10.1038/nbt.2488

A community-driven global reconstruction of human metabolism

Ines Thiele, Neil Swainston, Ronan M.T. Fleming, Andreas Hoppe, Swagatika Sahoo, Maike K. Aurich, Hulda Haraldsdottir, Monica L. Mo, Ottar Rolfsson, Miranda D. Stobbe, Stefan G. Thorleifsson, Rasmus Agren, Christian Bölling, Sergio Bordel, Arvind K. Chavali, Paul Dobson, Warwick B. Dunn, Lukas Endler, David Hala, Michael HuckaDuncan Hull, Daniel Jameson, Neema Jamshidi, Jon J. Jonsson, Nick Juty, Sarah Keating, Intawat Nookaew, Nicolas Le Novère, Naglis Malys, Alexander Mazein, Jason A. Papin, Nathan D. Price, Evgeni Selkov, Martin I. Sigurdsson, Evangelos Simeonidis, Nikolaus Sonnenschein, Kieran Smallbone, Anatoly Sorokin, Johannes H.G.M. Van Beek, Dieter Weichart, Igor Goryanin, Jens Nielsen, Hans V. Westerhoff, Douglas B. Kell, Pedro Mendes, Bernhard O. Palsson

Research output: Contribution to journal › Article › peer-review

650 Scopus citations

Abstract

Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ∼2× more reactions and ∼1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.

Original language	English (US)
Pages (from-to)	419-425
Number of pages	7
Journal	Nature biotechnology
Volume	31
Issue number	5
DOIs	https://doi.org/10.1038/nbt.2488
State	Published - May 2013
Externally published	Yes

ASJC Scopus subject areas

Applied Microbiology and Biotechnology
Bioengineering
Molecular Medicine
Biotechnology
Biomedical Engineering

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10.1038/nbt.2488

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Thiele, I., Swainston, N., Fleming, R. M. T., Hoppe, A., Sahoo, S., Aurich, M. K., Haraldsdottir, H., Mo, M. L., Rolfsson, O., Stobbe, M. D., Thorleifsson, S. G., Agren, R., Bölling, C., Bordel, S., Chavali, A. K., Dobson, P., Dunn, W. B., Endler, L., Hala, D., ... Palsson, B. O. (2013). A community-driven global reconstruction of human metabolism. Nature biotechnology, 31(5), 419-425. https://doi.org/10.1038/nbt.2488

Thiele, I, Swainston, N, Fleming, RMT, Hoppe, A, Sahoo, S, Aurich, MK, Haraldsdottir, H, Mo, ML, Rolfsson, O, Stobbe, MD, Thorleifsson, SG, Agren, R, Bölling, C, Bordel, S, Chavali, AK, Dobson, P, Dunn, WB, Endler, L, Hala, D, Hucka, M, Hull, D, Jameson, D, Jamshidi, N, Jonsson, JJ, Juty, N, Keating, S, Nookaew, I, Le Novère, N, Malys, N, Mazein, A, Papin, JA, Price, ND, Selkov, E, Sigurdsson, MI, Simeonidis, E, Sonnenschein, N, Smallbone, K, Sorokin, A, Van Beek, JHGM, Weichart, D, Goryanin, I, Nielsen, J, Westerhoff, HV, Kell, DB, Mendes, P & Palsson, BO 2013, 'A community-driven global reconstruction of human metabolism', Nature biotechnology, vol. 31, no. 5, pp. 419-425. https://doi.org/10.1038/nbt.2488

@article{4fedcc8528c44c6680e7b55bf4c21ce8,

title = "A community-driven global reconstruction of human metabolism",

abstract = "Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ∼2× more reactions and ∼1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.",

author = "Ines Thiele and Neil Swainston and Fleming, {Ronan M.T.} and Andreas Hoppe and Swagatika Sahoo and Aurich, {Maike K.} and Hulda Haraldsdottir and Mo, {Monica L.} and Ottar Rolfsson and Stobbe, {Miranda D.} and Thorleifsson, {Stefan G.} and Rasmus Agren and Christian B{\"o}lling and Sergio Bordel and Chavali, {Arvind K.} and Paul Dobson and Dunn, {Warwick B.} and Lukas Endler and David Hala and Michael Hucka and Duncan Hull and Daniel Jameson and Neema Jamshidi and Jonsson, {Jon J.} and Nick Juty and Sarah Keating and Intawat Nookaew and {Le Nov{\`e}re}, Nicolas and Naglis Malys and Alexander Mazein and Papin, {Jason A.} and Price, {Nathan D.} and Evgeni Selkov and Sigurdsson, {Martin I.} and Evangelos Simeonidis and Nikolaus Sonnenschein and Kieran Smallbone and Anatoly Sorokin and {Van Beek}, {Johannes H.G.M.} and Dieter Weichart and Igor Goryanin and Jens Nielsen and Westerhoff, {Hans V.} and Kell, {Douglas B.} and Pedro Mendes and Palsson, {Bernhard O.}",

note = "Funding Information: I.T. was supported, in part, by a Marie Curie International Reintegration Grant (249261) within the 7th European Community Framework Program. I.T., O.R., S.G.T. and M.A. were supported by the European Research Council grant proposal number 232816. S.S. and H.H. were supported by a Rannis research grant (100406022). Authors from Manchester thank the Biotechnology and Biological Sciences Research Council (BBSRC), and Engineering and Physical Sciences Research Council for their funding of the Manchester Centre for Integrative Systems Biology (grant BB/C008219/1), H.W. for Bioprocessing Research Industry Club grants, and P.M. and N. Swainston for support from the European Union FP7 project UNICELLSYS (grant agreement 201142). The Knut and Alice Wallenberg Foundation supported R.A., S.B. and I.N.; D.J. thanks the BBSRC for funding of Systems Approaches to Biological Research grants BB/F005938 and BB/F00561X. A.H. and C.B. were supported by the German Federal Ministry for Education and Research within the Virtual Liver Network (grant numbers 0315756 and 0315741). A.K.C. and J.A.P. acknowledge funding from the US National Institutes of Health (grant GM088244), National Science Foundation (grant 0643548) and Cystic Fibrosis Research Foundation (grant 1060). N.D.P. was supported by a National Cancer Institute to Independence Award in Cancer Research. I.G. thanks the Science and Technology Facilities Council for Scottish Bioinformatics Research Network funding. M.H. and P.M. thank the US National Institute of General Medical Sciences for support under grants R01GM070923 and R01GM080219. M.D.S. thanks the BioRange programme (project SP1.2.4) of The Netherlands Bioinformatics Centre for support under a Besluit Subsidies Investeringen Kennisinfrastructuur grant through The Netherlands Genomics Initiative.",

year = "2013",

month = may,

doi = "10.1038/nbt.2488",

language = "English (US)",

volume = "31",

pages = "419--425",

journal = "Nature biotechnology",

issn = "1087-0156",

publisher = "Nature Publishing Group",

number = "5",

}

TY - JOUR

T1 - A community-driven global reconstruction of human metabolism

AU - Thiele, Ines

AU - Swainston, Neil

AU - Fleming, Ronan M.T.

AU - Hoppe, Andreas

AU - Sahoo, Swagatika

AU - Aurich, Maike K.

AU - Haraldsdottir, Hulda

AU - Mo, Monica L.

AU - Rolfsson, Ottar

AU - Stobbe, Miranda D.

AU - Thorleifsson, Stefan G.

AU - Agren, Rasmus

AU - Bölling, Christian

AU - Bordel, Sergio

AU - Chavali, Arvind K.

AU - Dobson, Paul

AU - Dunn, Warwick B.

AU - Endler, Lukas

AU - Hala, David

AU - Hucka, Michael

AU - Hull, Duncan

AU - Jameson, Daniel

AU - Jamshidi, Neema

AU - Jonsson, Jon J.

AU - Juty, Nick

AU - Keating, Sarah

AU - Nookaew, Intawat

AU - Le Novère, Nicolas

AU - Malys, Naglis

AU - Mazein, Alexander

AU - Papin, Jason A.

AU - Price, Nathan D.

AU - Selkov, Evgeni

AU - Sigurdsson, Martin I.

AU - Simeonidis, Evangelos

AU - Sonnenschein, Nikolaus

AU - Smallbone, Kieran

AU - Sorokin, Anatoly

AU - Van Beek, Johannes H.G.M.

AU - Weichart, Dieter

AU - Goryanin, Igor

AU - Nielsen, Jens

AU - Westerhoff, Hans V.

AU - Kell, Douglas B.

AU - Mendes, Pedro

AU - Palsson, Bernhard O.

N1 - Funding Information: I.T. was supported, in part, by a Marie Curie International Reintegration Grant (249261) within the 7th European Community Framework Program. I.T., O.R., S.G.T. and M.A. were supported by the European Research Council grant proposal number 232816. S.S. and H.H. were supported by a Rannis research grant (100406022). Authors from Manchester thank the Biotechnology and Biological Sciences Research Council (BBSRC), and Engineering and Physical Sciences Research Council for their funding of the Manchester Centre for Integrative Systems Biology (grant BB/C008219/1), H.W. for Bioprocessing Research Industry Club grants, and P.M. and N. Swainston for support from the European Union FP7 project UNICELLSYS (grant agreement 201142). The Knut and Alice Wallenberg Foundation supported R.A., S.B. and I.N.; D.J. thanks the BBSRC for funding of Systems Approaches to Biological Research grants BB/F005938 and BB/F00561X. A.H. and C.B. were supported by the German Federal Ministry for Education and Research within the Virtual Liver Network (grant numbers 0315756 and 0315741). A.K.C. and J.A.P. acknowledge funding from the US National Institutes of Health (grant GM088244), National Science Foundation (grant 0643548) and Cystic Fibrosis Research Foundation (grant 1060). N.D.P. was supported by a National Cancer Institute to Independence Award in Cancer Research. I.G. thanks the Science and Technology Facilities Council for Scottish Bioinformatics Research Network funding. M.H. and P.M. thank the US National Institute of General Medical Sciences for support under grants R01GM070923 and R01GM080219. M.D.S. thanks the BioRange programme (project SP1.2.4) of The Netherlands Bioinformatics Centre for support under a Besluit Subsidies Investeringen Kennisinfrastructuur grant through The Netherlands Genomics Initiative.

PY - 2013/5

Y1 - 2013/5

N2 - Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ∼2× more reactions and ∼1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.

AB - Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven, consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared with its predecessors, the reconstruction has improved topological and functional features, including ∼2× more reactions and ∼1.7× more unique metabolites. Using Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.

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U2 - 10.1038/nbt.2488

DO - 10.1038/nbt.2488

M3 - Article

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AN - SCOPUS:84877315835

SN - 1087-0156

VL - 31

SP - 419

EP - 425

JO - Nature biotechnology

JF - Nature biotechnology

IS - 5

ER -

A community-driven global reconstruction of human metabolism

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