Home LiteratureArticle Details
PMID: 19396373 Published · ppublish English Journal Article Research Support, U.S. Gov't, Non-P.H.S.

Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001.

Molecular bioSystems ·Vol. 5 ·No. 4 ·2009-04-00 ·Pages 368-75

Navid A, Almaas E

Abstract

The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one of the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from the literature. Our model demonstrates excellent agreement with Y. pestis' known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses that may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

MeSH Terms
Genes, Bacterial Genome, Bacterial Metabolic Networks and Pathways/genetics Models, Theoretical Phenotype Yersinia pestis/classification,genetics,metabolism
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Navid Ali
Biosciences & Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, California 94550-0808, USA.
Almaas Eivind
Article Info
Journal
Molecular bioSystems
Abbr.
Mol Biosyst
ISSN
1742-2051
Published
2009-04-00
Epub
2009-00-26
Pages
368-75
Language
English
Region
England
NLM ID
101251620
Subset
IM
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: [email protected]