Metabolic modeling of endosymbiont genome reduction on a temporal scale

Molecular Systems Biology

Keren Yizhak²  Tamir Tuller¹  Balázs Papp³ 

[1] Faculty of mathematics and computer science, Weizmann Institute of science, Rehovot, Israel;The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel;Institute of Biochemistry, Biological Research Center, Szeged, Hungary

关键词: constraint‐based modeling;    endosymbiont;    evolution;    metabolism;   

DOI  :  10.1038/msb.2011.11

来源: Wiley

【 摘 要 】

A fundamental challenge in Systems Biology is whether a cell-scale metabolic model can predict patterns of genome evolution by realistically accounting for associated biochemical constraints. Here, we study the order in which genes are lost in an in silico evolutionary process, leading from the metabolic network of Eschericia coli to that of the endosymbiont Buchnera aphidicola. We examine how this order correlates with the order by which the genes were actually lost, as estimated from a phylogenetic reconstruction. By optimizing this correlation across the space of potential growth and biomass conditions, we compute an upper bound estimate on the model's prediction accuracy (R=0.54). The model's network-based predictive ability outperforms prediction

【 授权许可】

CC BY-NC-SA   
Copyright © 2011 EMBO and Macmillan Publishers Limited

Creative Commons Attribution License, which permits distribution, and reproduction in any medium, provided the original author and source are credited. This license does not permit commercial exploitation without specific permission.