• English
    • norsk
  • English 
    • English
    • norsk
  • Login
View Item 
  •   All institutions
  • Norges teknisk-naturvitenskapelige universitet
  • Publikasjoner fra CRIStin - NTNU
  • View Item
  •   All institutions
  • Norges teknisk-naturvitenskapelige universitet
  • Publikasjoner fra CRIStin - NTNU
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Genome-level transcription data of Yersinia pestis analyzed with a New metabolic constraint-based approach

Navid, Ali; Almaas, Eivind
Journal article, Peer reviewed
Thumbnail
View/Open
1752-0509-6-150.pdf (3.472Mb)
Permanent link
http://hdl.handle.net/11250/2358360
Issue date
2012
Share
Metadata
Show full item record
Collections
  • Institutt for bioteknologi og matvitenskap [483]
  • Publikasjoner fra CRIStin - NTNU [7647]
Original version
BMC Systems Biology 2012, 6(150)   10.1186/1752-0509-6-150
Abstract
Background: Constraint-based computational approaches, such as flux balance analysis (FBA), have proven

successful in modeling genome-level metabolic behavior for conditions where a set of simple cellular objectives

can be clearly articulated. Recently, the necessity to expand the current range of constraint-based methods to

incorporate high-throughput experimental data has been acknowledged by the proposal of several methods.

However, these methods have rarely been used to address cellular metabolic responses to some relevant

perturbations such as antimicrobial or temperature-induced stress. Here, we present a new method for combining

gene-expression data with FBA (GX-FBA) that allows modeling of genome-level metabolic response to a broad

range of environmental perturbations within a constraint-based framework. The method uses mRNA expression

data to guide hierarchical regulation of cellular metabolism subject to the interconnectivity of the metabolic

network.

Results: 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.

Conclusions: 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.
Publisher
BioMed Central
Journal
BMC Systems Biology

Contact Us

Search NORA
Powered by DSpace software

Service from BIBSYS
 

 

Browse this CollectionIssue DateAuthorsTitlesSubjectsDocument TypesJournalsBrowse all ArchivesArchives & CollectionsIssue DateAuthorsTitlesSubjectsDocument TypesJournals

My Account

Login

Statistics

Google Analytics StatisticsView Usage Statistics

Contact Us

Search NORA
Powered by DSpace software

Service from BIBSYS