A dynamic network of transcription in LPS-treated human subjects.

TitleA dynamic network of transcription in LPS-treated human subjects.
Publication TypeJournal Article
Year of Publication2009
AuthorsSeok J, Xiao W, Moldawer LL, Davis RW, Covert MW
JournalBMC Syst Biol
Volume3
Pagination78
Date Published2009
ISSN1752-0509
KeywordsGene Expression Regulation, Gene Regulatory Networks, Humans, Inflammation, Leukocytes, Lipopolysaccharides, Systems Biology, Transcription Factors, Transcription, Genetic
Abstract

BACKGROUND: Understanding the transcriptional regulatory networks that map out the coordinated dynamic responses of signaling proteins, transcription factors and target genes over time would represent a significant advance in the application of genome wide expression analysis. The primary challenge is monitoring transcription factor activities over time, which is not yet available at the large scale. Instead, there have been several developments to estimate activities computationally. For example, Network Component Analysis (NCA) is an approach that can predict transcription factor activities over time as well as the relative regulatory influence of factors on each target gene.

RESULTS: In this study, we analyzed a gene expression data set in blood leukocytes from human subjects administered with lipopolysaccharide (LPS), a prototypical inflammatory challenge, in the context of a reconstructed regulatory network including 10 transcription factors, 99 target genes and 149 regulatory interactions. We found that the computationally estimated activities were well correlated to their coordinated action. Furthermore, we found that clustering the genes in the context of regulatory influences greatly facilitated interpretation of the expression data, as clusters of gene expression corresponded to the activity of specific factors or more interestingly, factor combinations which suggest coordinated regulation of gene expression. The resulting clusters were therefore more biologically meaningful, and also led to identification of additional genes under the same regulation.

CONCLUSION: Using NCA, we were able to build a network that accounted for between 8-11% genes in the known transcriptional response to LPS in humans. The dynamic network illustrated changes of transcription factor activities and gene expressions as well as interactions of signaling proteins, transcription factors and target genes.

DOI10.1186/1752-0509-3-78
PubMed URLhttp://www.ncbi.nlm.nih.gov/pubmed/19638230?dopt=Abstract
PMCPMC2729748
Alternate JournalBMC Syst Biol
PubMed ID19638230