Research

Identification of signaling components required for the prediction of cytokine release in RAW 264.7 macrophages

Sylvain Pradervand^{* 1,2} , Mano R Maurya^{* 1,2} and Shankar Subramaniam^1,2,3

¹Bioinformatics and Data Coordination Laboratory, Alliance for Cellular Signaling, San Diego Supercomputer Center, University of California at San Diego, Gilman Drive, La Jolla, CA 92093, USA

²Department of Bioengineering, University of California at San Diego, Gilman Drive, La Jolla, CA 92093, USA

³Department of Chemistry and Biochemistry, University of California at San Diego, Gilman Drive, La Jolla, CA 92093, USA

author email corresponding author email* Contributed equally

Genome Biology 2006, 7:R11doi:10.1186/gb-2006-7-2-r11

Published:	20 February 2006

Subject areas: Immunology, Bioinformatics, Cell biology

Abstract

Background

Release of immuno-regulatory cytokines and chemokines during inflammatory response is mediated by a complex signaling network. Multiple stimuli produce different signals that generate different cytokine responses. Current knowledge does not provide a complete picture of these signaling pathways. However, using specific markers of signaling pathways, such as signaling proteins, it is possible to develop a 'coarse-grained network' map that can help understand common regulatory modules for various cytokine responses and help differentiate between the causes of their release.

Results

Using a systematic profiling of signaling responses and cytokine release in RAW 264.7 macrophages made available by the Alliance for Cellular Signaling, an analysis strategy is presented that integrates principal component regression and exhaustive search-based model reduction to identify required signaling factors necessary and sufficient to predict the release of seven cytokines (G-CSF, IL-1α, IL-6, IL-10, MIP-1α, RANTES, and TNFα) in response to selected ligands. This study provides a model-based quantitative estimate of cytokine release and identifies ten signaling components involved in cytokine production. The models identified capture many of the known signaling pathways involved in cytokine release and predict potentially important novel signaling components, like p38 MAPK for G-CSF release, IFNγ- and IL-4-specific pathways for IL-1a release, and an M-CSF-specific pathway for TNFα release.

Conclusion

Using an integrative approach, we have identified the pathways responsible for the differential regulation of cytokine release in RAW 264.7 macrophages. Our results demonstrate the power of using heterogeneous cellular data to qualitatively and quantitatively map intermediate cellular phenotypes.