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Báo cáo y học: "A network perspective on the evolution of metabolism by gene duplication"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: A network perspective on the evolution of metabolism by gene duplication. | Open Access Research A network perspective on the evolution of metabolism by gene duplication Juan Javier Díaz-Mejía Ernesto Perez-Rueda and Lorenzo Segovia Address Departamento de Ingeniería Celular y Biocatálisis Instituto de Biotecnología Universidad Nacional Autónoma de México. Av. Universidad 2001 Col. Chamilpa Cuernavaca Morelos CP 62210 México. Correspondence Lorenzo Segovia. Email lorenzo@ibt.unam.mx Published 27 February 2007 Genome Biology 2007 8 R26 doi 10.1 186 gb-2007-8-2-r26 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2007 8 2 R26 Received 19 July 2006 Revised 23 October 2006 Accepted 27 February 2007 2007 Díaz-Mejía et al. licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Gene duplication followed by divergence is one of the main sources of metabolic versatility. The patchwork and stepwise models of metabolic evolution help us to understand these processes but their assumptions are relatively simplistic. We used a network-based approach to determine the influence of metabolic constraints on the retention of duplicated genes. Results We detected duplicated genes by looking for enzymes sharing homologous domains and uncovered an increased retention of duplicates for enzymes catalyzing consecutive reactions as illustrated by the ligases acting in the biosynthesis of peptidoglycan. As a consequence metabolic networks show a high retention of duplicates within functional modules and we found a preferential biochemical coupling of reactions that partially explains this bias. A similar situation was found in enzyme-enzyme interaction networks but not in interaction networks of non-enzymatic proteins or gene transcriptional regulatory