Control of fluxes in metabolic networks
Year: 2016
Type: preprint
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.
Source: Genome Research
Authors: Georg Basler, Zoran Nikoloski, Abdelhalim Larhlimi, Albert-László Barabási, Yang-Yu Liu
Institutions: Estación Experimental del Zaidín, University of California, Berkeley, Max Planck Institute of Molecular Plant Physiology, Laboratoire d'informatique de Nantes Atlantique, Université de Nantes, Nantes Université, Brigham and Women's Hospital, Northeastern University, Dana-Farber Cancer Institute, Dana-Farber Brigham Cancer Center, Harvard University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Awards: G1022204393, G1221413972, Integrative Modeling and Engineering of Pseudomonas putida for Green Chemistry, G2973790809, G3207356259, Integrative Genomics of Acute Asthma Control, G393177772, The control principles of complex systems, G5702163051, G7191832816, Genomic Analysis of Network Perturbations in Human Disease
OpenAlex ID: W7075329552