title: Control of fluxes in metabolic networks.
abstract: Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism.
authors.affiliation: Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, USA; Department of Environmental Protection, Estación Experimental del Zaidín CSIC, Granada, 18008 Spain;
authors.forename: Georg
authors.initials: G
authors.lastname: Basler
authors.affiliation: Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, Potsdam, 14476 Germany;
authors.forename: Zoran
authors.initials: Z
authors.lastname: Nikoloski
authors.affiliation: Laboratoire d'Informatique de Nantes Atlantique, Université de Nantes, Nantes, 44322 France;
authors.forename: Abdelhalim
authors.initials: A
authors.lastname: Larhlimi
authors.affiliation: Center for Complex Network Research and Departments of Physics, Computer Science, and Biology, Northeastern University, Boston, Massachusetts 02115, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA; Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts 02215, USA.
authors.forename: Albert-László
authors.initials: AL
authors.lastname: Barabási
authors.affiliation: Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA; Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts 02215, USA.
authors.forename: Yang-Yu
authors.initials: YY
authors.lastname: Liu
mesh_terms: D000818:Animals; D001419:Bacteria / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology; D019143:Evolution, Molecular; D005658:Fungi / Q000235:genetics / Q000378:metabolism; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D015398:Signal Transduction