Recon 2.2: from reconstruction to model of human metabolism

被引:200
作者
Swainston, Neil [1 ,2 ,3 ]
Smallbone, Kieran [3 ]
Hefzi, Hooman [4 ,5 ]
Dobson, Paul D. [3 ]
Brewer, Judy [6 ,7 ]
Hanscho, Michael [8 ,9 ]
Zielinski, Daniel C. [4 ]
Ang, Kok Siong [10 ,11 ]
Gardiner, Natalie J. [2 ]
Gutierrez, Jahir M. [4 ,5 ]
Kyriakopoulos, Sarantos [11 ]
Lakshmanan, Meiyappan [11 ]
Li, Shangzhong [4 ,5 ]
Liu, Joanne K. [13 ]
Martinez, Veronica S. [12 ]
Orellana, Camila A. [12 ]
Quek, Lake-Ee [12 ]
Thomas, Alex [5 ,13 ]
Zanghellini, Juergen [9 ]
Borth, Nicole [8 ,9 ]
Lee, Dong-Yup [10 ,11 ]
Nielsen, Lars K. [12 ]
Kell, Douglas B. [1 ,14 ]
Lewis, Nathan E. [5 ,15 ]
Mendes, Pedro [1 ,3 ,16 ]
机构
[1] Univ Manchester, Manchester Inst Biotechnol, Manchester Ctr Synthet Biol Fine & Special Chem S, Manchester M1 7DN, Lancs, England
[2] Univ Manchester, Fac Life Sci, Manchester M13 9PL, Lancs, England
[3] Univ Manchester, Sch Comp Sci, Manchester M13 9PL, Lancs, England
[4] Univ Calif San Diego, Dept Bioengn, La Jolla, CA 92093 USA
[5] Univ Calif San Diego, Sch Med, Novo Nordisk Fdn Ctr Biosustainabil, La Jolla, CA 92093 USA
[6] Harvard Extens Sch, 51 Brattle St, Cambridge, MA 02138 USA
[7] MIT, Comp Sci & Artificial Intelligence Lab, 32 Vassar St, Cambridge, MA 02139 USA
[8] Univ Nat Resources & Life Sci, Dept Biotechnol, Vienna, Austria
[9] Austrian Ctr Ind Biotechnol, Vienna, Austria
[10] Natl Univ Singapore, Dept Chem & Biomol Engn, 4 Engn Dr 4, Singapore 117585, Singapore
[11] ASTAR, Bioproc Technol Inst, 20 Biopolis Way,06-01, Singapore 138668, Singapore
[12] Univ Queensland, AIBN, Corner Coll & Cooper Rd Bldg 75, Brisbane, Qld 4072, Australia
[13] Univ Calif San Diego, Bioinformat & Syst Biol Program, La Jolla, CA 92093 USA
[14] Univ Manchester, Sch Chem, Manchester M13 9PL, Lancs, England
[15] Univ Calif San Diego, Dept Pediat, La Jolla, CA 92093 USA
[16] UConn Hlth, Ctr Quantitat Med, 263 Farmington Ave, Farmington, CT 06030 USA
基金
英国生物技术与生命科学研究理事会; 美国国家卫生研究院;
关键词
Human; Metabolism; Modelling; Reconstruction; Model; Systems biology; GENOME-SCALE MODELS; GLOBAL RECONSTRUCTION; NETWORK; PREDICTION; CHEBI;
D O I
10.1007/s11306-016-1051-4
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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).
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页数:7
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