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
Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester, M1 7DN UK ; Faculty of Life Sciences, The University of Manchester, Manchester, M13 9PL UK ; School of Computer Science, The University of Manchester, Manchester, M13 9PL UK.
School of Computer Science, The University of Manchester, Manchester, M13 9PL UK.
Metabolomics. 2016;12:109. doi: 10.1007/s11306-016-1051-4. Epub 2016 Jun 7.
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.
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.
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.
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.
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).
人类基因组规模代谢重建详细描述了人类中发生的所有已知代谢反应，因此在研究复杂疾病和表型方面具有巨大潜力。获取完整的人类代谢重建是一项持续的任务，自上次社区共同努力生成一个共识重建以来，已经有了几次更新。
我们报告了一个新的共识版本Recon 2.2，它整合了各种替代版本并进行了大量额外更新。除了重新建立一个共识重建外，其他关键目标包括对代谢物和基因进行更全面的注释，确保所有反应中的质量和电荷完全平衡，以及开发一个能在一系列碳源上正确预测ATP生成的模型。
Recon 2.2是通过人工编辑和自动错误检查相结合的方式开发的。具体且重要的人工更新包括对脂肪酸代谢、氧化磷酸化的重新规范以及电子传递链与ATP合酶活性的耦合。所有代谢物都有明确的化学式和指定的电荷，通过自动线性规划方法用于确保反应的质量和电荷完全平衡。此外，通过更新基因、蛋白质和反应之间关系的编辑，促进了与转录组学和蛋白质组学数据的更好整合。
如本文所示，Recon 2.2现在代表了迄今为止人类代谢最具预测性的模型。广泛的人工编辑使重建规模增加到5324种代谢物、7785个反应和1675个相关基因，现在这些都映射到一个单一标准。对所有反应的质量和电荷平衡的关注，以及对能量生成的更好表示，产生了一个能正确预测不同碳源上ATP产量的通量模型。
通过这些更新，我们实现了现有最完整且注释最佳的人类代谢共识重建，从而提高了该资源为人类正常和疾病状态提供新见解的能力。该模型可从生物模型数据库（http://identifiers.org/biomodels.db/MODEL1603150001）免费获取。
