Transcriptional network dynamics in macrophage activation.
Transcriptional regulatory networks govern cell differentiation and the cellular response to external stimuli. However, mammalian model systems have not yet been accessible for network analysis. Here, we present a genome-wide network analysis of the transcriptional regulation underlying the mouse macrophage response to bacterial lipopolysaccharide (LPS). Key to uncovering the network structure is our combination of time-series cap analysis of gene expression with in silico prediction of transcription factor binding sites. By integrating microarray and qPCR time-series expression data with a promoter analysis, we find dynamic subnetworks that describe how signaling pathways change dynamically during the progress of the macrophage LPS response, thus defining regulatory modules characteristic of the inflammatory response. In particular, our integrative analysis enabled us to suggest novel roles for the transcription factors ATF-3 and NRF-2 during the inflammatory response. We believe that our system approach presented here is applicable to understanding cellular differentiation in higher eukaryotes.
Nilsson
Roland
R
Center for Genomics and Bioinformatics, Karolinska Institutet, Stockholm, Sweden.
Bajic
Vladimir B
VB
Suzuki
Harukazu
H
di Bernardo
Diego
D
Björkegren
Johan
J
Katayama
Shintaro
S
Reid
James F
JF
Sweet
Matthew J
MJ
Gariboldi
Manuela
M
Carninci
Piero
P
Hayashizaki
Yosihide
Y
Hume
David A
DA
Tegner
Jesper
J
Ravasi
Timothy
T
D000465:Algorithms; D000818:Animals; D001665:Binding Sites / Q000187:drug effects; D001853:Bone Marrow / Q000187:drug effects / Q000378:metabolism; D002478:Cells, Cultured; D005786:Gene Expression Regulation; D008070:Lipopolysaccharides / Q000494:pharmacology; D008262:Macrophage Activation / Q000187:drug effects; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis; D011401:Promoter Regions, Genetic; D024363:Transcription Initiation Site / Q000187:drug effects; D014158:Transcription, Genetic
D008070:Lipopolysaccharides