A community-driven global reconstruction of human metabolism
Ines Thiele,Neil Swainston,Ronan M. T. Fleming,Andreas Hoppe,Swagatika Sahoo,Maike K. Aurich,Hulda S. Haraldsdóttir,Monica L. Mo,Ottar Rolfsson,Miranda D. Stobbe,Miranda D. Stobbe,Stefan Gretar Thorleifsson,Rasmus Agren,Christian Bölling,Sergio Bordel,Arvind K. Chavali,Paul D. Dobson,Warwick B. Dunn,Warwick B. Dunn,Lukas Endler,David Hala,Michael Hucka,Duncan Hull,Daniel Jameson,Neema Jamshidi,Jon J. Jonsson,Nick Juty,Sarah M. Keating,Intawat Nookaew,Nicolas Le Novère,Nicolas Le Novère,Naglis Malys,Naglis Malys,Alexander Mazein,Jason A. Papin,Nathan D. Price,Evgeni Selkov,Martin I. Sigurdsson,Evangelos Simeonidis,Evangelos Simeonidis,Nikolaus Sonnenschein,Kieran Smallbone,Anatoly Sorokin,Anatoly Sorokin,Johannes H. G. M. van Beek,Dieter Weichart,Igor Goryanin,Jens Nielsen,Hans V. Westerhoff,Douglas B. Kell,Pedro Mendes,Pedro Mendes,Bernhard O. Palsson,Bernhard O. Palsson +53 more
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TLDR
Recon 2, a community-driven, consensus 'metabolic reconstruction', is described, which is the most comprehensive representation of human metabolism that is applicable to computational modeling and has improved topological and functional features.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/.read more
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Metabolomics enables precision medicine: "A White Paper, Community Perspective"
Richard D. Beger,Warwick B. Dunn,Michael A. Schmidt,Steven S. Gross,Jennifer A. Kirwan,Marta Cascante,Lorraine Brennan,David S. Wishart,Matej Orešič,Thomas Hankemeier,David Broadhurst,Andrew N. Lane,Karsten Suhre,Gabi Kastenmüller,Susan Sumner,Ines Thiele,Oliver Fiehn,Oliver Fiehn,Rima Kaddurah-Daouk +18 more
TL;DR: The narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature, expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis.
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Quantitative and logic modelling of molecular and gene networks
TL;DR: This work has shown that hybrid approaches will become essential for further progress in synthetic biology and in the development of virtual organisms.
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Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community.
Farhana R. Pinu,David J. Beale,Paten Am,Konstantinos A. Kouremenos,Sanjay Swarup,Horst Joachim Schirra,David S. Wishart +6 more
TL;DR: This document envisage that this document will serve as a guide to metabolomics researchers and other members of the community wishing to perform multi-omics studies and believe that these ideas may allow the full promise of integratedmulti-omics research and, ultimately, of systems biology to be realized.
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Dietary methionine influences therapy in mouse cancer models and alters human metabolism
Xia Gao,Sydney M. Sanderson,Ziwei Dai,Michael A. Reid,Daniel E. Cooper,Min Lu,John P. Richie,Amy Ciccarella,Ana Calcagnotto,Peter G. Mikhael,Samantha J. Mentch,Juan Liu,Gene P. Ables,David G. Kirsch,David S. Hsu,Sailendra N. Nichenametla,Jason W. Locasale +16 more
TL;DR: Evidence is provided that a targeted dietary manipulation can specifically affect tumour-cell metabolism to mediate broad aspects of cancer outcome through controlled and reproducible changes to one-carbon metabolism.
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Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently
TL;DR: Improving enzymes by directed evolution requires the navigation of very large search spaces; this work surveys how to do this intelligently.
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