Uncovering a Macrophage Transcriptional Program by Integrating Evidence from Motif Scanning and Expression Dynamics: e1000021

• Published in: PLoS computational biology 2008-03, Vol.4 (3)
• Main Authors: Ramsey, Stephen A, Klemm, Sandy L, Zak, Daniel E, Kennedy, Kathleen A, Thorsson, Vesteinn, Li, Bin, Gilchrist, Mark, Gold, Elizabeth S, Johnson, Carrie D, Litvak, Vladimir, Navarro, Garnet, Roach, Jared C, Rosenberger, Carrie M, Rust, Alistair G, Yudkovsky, Natalya, Aderem, Alan, Shmulevich, Ilya
• Format: Article
• Language: English
• Subjects: Data processing; Experiments; Genes; Immune system; Infections; Methods; Proteins
• ISSN: 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1000021

Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation.