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Systems infection biology: a compartmentalized immune network of pig spleen challenged with Haemophilus parasuis.

Authors :
Ming Zhao
Liu, Xiang-dong
Li, Xin-yun
Chen, Hong-bo
Jin, Hui
Rui Zhou
Zhu, Meng-jin
Zhao, Shu-hong
Source :
BMC Genomics. 2013, Vol. 14 Issue 1, p1-13. 13p. 4 Charts, 5 Graphs.
Publication Year :
2013

Abstract

Background: Network biology (systems biology) approaches are useful tools for elucidating the host infection processes that often accompany complex immune networks. Although many studies have recently focused on Haemophilus parasuis, a model of Gram-negative bacterium, little attention has been paid to the host's immune response to infection. In this article, we use network biology to investigate infection with Haemophilus parasuis in an in vivo pig model. Results: By targeting the spleen immunogenome, we established an expression signature indicative of H. parasuis infection using a PCA/GSEA combined method. We reconstructed the immune network and estimated the network topology parameters that characterize the immunogene expressions in response to H. parasuis infection. The results showed that the immune network of H. parasuis infection is compartmentalized (not globally linked). Statistical analysis revealed that the reconstructed network is scale-free but not small-world. Based on the quantitative topological prioritization, we inferred that the C1R-centered clique might play a vital role in responding to H. parasuis infection. Conclusions: Here, we provide the first report of reconstruction of the immune network in H. parasuis-infected porcine spleen. The distinguishing feature of our work is the focus on utilizing the immunogenome for a network biology-oriented analysis. Our findings complement and extend the frontiers of knowledge of host infection biology for H. parasuis and also provide a new clue for systems infection biology of Gram-negative bacilli in mammals. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14712164
Volume :
14
Issue :
1
Database :
Academic Search Index
Journal :
BMC Genomics
Publication Type :
Academic Journal
Accession number :
86956719
Full Text :
https://doi.org/10.1186/1471-2164-14-46