PLoS Computational Biology (Mar 2008)

Uncovering a macrophage transcriptional program by integrating evidence from motif scanning and expression dynamics.

  • Stephen A Ramsey,
  • Sandy L Klemm,
  • Daniel E Zak,
  • Kathleen A Kennedy,
  • Vesteinn Thorsson,
  • Bin Li,
  • Mark Gilchrist,
  • Elizabeth S Gold,
  • Carrie D Johnson,
  • Vladimir Litvak,
  • Garnet Navarro,
  • Jared C Roach,
  • Carrie M Rosenberger,
  • Alistair G Rust,
  • Natalya Yudkovsky,
  • Alan Aderem,
  • Ilya Shmulevich

DOI
https://doi.org/10.1371/journal.pcbi.1000021
Journal volume & issue
Vol. 4, no. 3
p. e1000021

Abstract

Read online

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.