%0 Journal Article
%T Genome-level transcription data of Yersinia pestis analyzed with a New metabolic constraint-based approach
%A Ali Navid
%A Eivind Almaas
%J BMC Systems Biology
%D 2012
%I BioMed Central
%R 10.1186/1752-0509-6-150
%X We applied GX-FBA to a genome-scale model of metabolism in the gram negative bacterium Yersinia pestis and analyzed its metabolic response to (i) variations in temperature known to induce virulence, and (ii) antibiotic stress. Without imposition of any a priori behavioral constraints, our results show strong agreement with reported phenotypes. Our analyses also lead to novel insights into how Y. pestis uses metabolic adjustments to counter different forms of stress.Comparisons of GX-FBA predicted metabolic states with fluxomic measurements and different reported post-stress phenotypes suggest that mass conservation constraints and network connectivity can be an effective representative of metabolic flux regulation in constraint-based models. We believe that our approach will be of aid in the in silico evaluation of cellular goals under different conditions and can be used for a variety of analyses such as identification of potential drug targets and their action.The recent progress in genome sequencing techniques has led to the development of genome-level models of metabolism that have been analyzed using constraint-based approaches, such as flux-balance analysis (FBA) [1,2]. The success of FBA stems from the fact that, unlike kinetic models, FBA aims to identify optimal metabolic steady-state activity patterns that satisfy constraints imposed by mass balance, the metabolic network structure, and the availability of nutrients. The most common cellular task to be optimized (the system¡¯s objective function) is that of growth, although other choices are possible depending on the selective environment of the cell [3,4]. The FBA framework has been applied to many genome-level models (see e.g., [5-11]) with great success, as well as the systematic prediction of genetic knockout phenotypes [12,13], the global organization of metabolic fluxes [14], and the discovery of novel regulatory interactions [15]. However, fulfillment of systems biology¡¯s goal to generate models that
%K Flux balance analysis
%K Gene-expression
%K Yersinia pestis
%K Stress response
%K Metabolism
%U http://www.biomedcentral.com/1752-0509/6/150