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., Martinez, 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. and Mendes, Pedro (2016) Recon 2.2: from reconstruction to model of human metabolism. Metabolomics, 12 7: . doi:10.1007/s11306-016-1051-4

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.
Martinez, 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
Title Recon 2.2: from reconstruction to model of human metabolism
Journal name Metabolomics   Check publisher's open access policy
ISSN 1573-3890
Publication date 2016-07-01
Year available 2016
Sub-type Letter to editor, brief commentary or brief communication
DOI 10.1007/s11306-016-1051-4
Open Access Status DOI
Volume 12
Issue 7
Total pages 7
Place of publication New York, NY, United States
Publisher Springer New York LLC
Collection year 2017
Language eng
Formatted abstract
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 (
Keyword Human
Systems biology
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Letter to editor, brief commentary or brief communication
Collections: HERDC Pre-Audit
Australian Institute for Bioengineering and Nanotechnology Publications
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