A system-level approach for deciphering the transcriptional response to prion infection.
BACKGROUND
Deciphering the response of a complex biological system to an insulting event, at the gene expression level, requires adopting theoretical models that are more sophisticated than a one-to-one comparison (i.e. t-test). Here, we investigate the ability of a novel reverse engineering approach (System Response Inference) to unveil non-obvious transcriptional signatures of the system response induced by prion infection.


RESULTS
To this end, we analyze previously published gene expression data, from which we extrapolate a putative full-scale model of transcriptional gene-gene dependencies in the mouse central nervous system. Then, we use this nominal model to interpret the gene expression changes caused by prion replication, aiming at selecting the genes primarily influenced by this perturbation. Our method sheds light on the mode of action of prions by identifying key transcripts that are the most likely to be responsible for the overall transcriptional rearrangement from a nominal regulatory network. As a first result of our inference, we have been able to predict known targets of prions (i.e. PrP(C)) and to unveil the potential role of previously unsuspected genes.


BACKGROUND
altafini@sissa.it


BACKGROUND
Supplementary data are available at Bioinformatics online.
Institute of Molecular Systems Biology, ETH, Wolfgang-Pauli-Strasse 16, 8093 Zurich, Switzerland.
Mattia
M
Zampieri
Giuseppe
G
Legname
Daniel
D
Segrè
Claudio
C
Altafini
D000818:Animals; D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D006801:Humans; D051379:Mice; D008957:Models, Genetic; D017096:Prion Diseases / Q000235:genetics*; D011328:Prions / Q000378:metabolism*; D014158:Transcription, Genetic
D011328:Prions