This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Supplemental material
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowReprints and Permissions
Right arrow Copyright Information
Right arrow Books from ASM Press
Right arrow MicrobeWorld
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mazumdar, V.
Right arrow Articles by Segrè, D.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mazumdar, V.
Right arrow Articles by Segrè, D.

 Previous Article  |  Next Article 

Journal of Bacteriology, January 2009, p. 74-90, Vol. 191, No. 1
0021-9193/09/$08.00+0     doi:10.1128/JB.01123-08
Copyright © 2009, American Society for Microbiology. All Rights Reserved.

Metabolic Network Model of a Human Oral Pathogen{triangledown} ,{ddagger}

Varun Mazumdar,1 Evan S. Snitkin,1 Salomon Amar,2*,{dagger} and Daniel Segrè1,3*,{dagger}

Program in Bioinformatics,1 School of Dental Medicine,2 Department of Biology and Department of Biomedical Engineering, Boston University, Boston, Massachusetts 022153

Received 11 August 2008/ Accepted 5 September 2008

The microbial community present in the human mouth is engaged in a complex network of diverse metabolic activities. In addition to serving as energy and building-block sources, metabolites are key players in interspecies and host-pathogen interactions. Metabolites are also implicated in triggering the local inflammatory response, which can affect systemic conditions such as atherosclerosis, obesity, and diabetes. While the genome of several oral pathogens has been sequenced, quantitative understanding of the metabolic functions of any oral pathogen at the system level has not been explored yet. Here we pursue the computational construction and analysis of the genome-scale metabolic network of Porphyromonas gingivalis, a gram-negative anaerobe that is endemic in the human population and largely responsible for adult periodontitis. Integrating information from the genome, online databases, and literature screening, we built a stoichiometric model that encompasses 679 metabolic reactions. By using flux balance approaches and automated network visualization, we analyze the growth capacity under amino-acid-rich medium and provide evidence that amino acid preference and cytotoxic by-product secretion rates are suitably reproduced by the model. To provide further insight into the basic metabolic functions of P. gingivalis and suggest potential drug targets, we study systematically how the network responds to any reaction knockout. We focus specifically on the lipopolysaccharide biosynthesis pathway and identify eight putative targets, one of which has been recently verified experimentally. The current model, which is amenable to further experimental testing and refinements, could prove useful in evaluating the oral microbiome dynamics and in the development of novel biomedical applications.


* Corresponding author. Mailing address for D. Segrè: Boston University, Bioinformatics Program, 44 Cummington St. (LSEB 909), Boston, MA 02215. Phone: (617) 358-2301. Fax: (617) 353-4814. E-mail: dsegre{at}bu.edu. Mailing address for S. Amar: Boston University, School of Dental Medicine, 650 Albany Street, X343, Boston, MA 02118. Phone: (617) 638-4983. Fax: (617) 663-8549. E-mail: samar{at}bu.edu

{triangledown} Published ahead of print on 17 October 2008.

{ddagger} Supplemental material for this article may be found at http://jb.asm.org/.

{dagger} S.A. and D.S. contributed equally to this study.


Journal of Bacteriology, January 2009, p. 74-90, Vol. 191, No. 1
0021-9193/09/$08.00+0     doi:10.1128/JB.01123-08
Copyright © 2009, American Society for Microbiology. All Rights Reserved.




This article has been cited by other articles:

  • Zhulin, I. B. (2009). It Is Computation Time for Bacteriology!. J. Bacteriol. 191: 20-22 [Full Text]