Australasian Microarray & Associated Technologies Association, AMATA

Samuel C. Forster, Jodee A. Gould and Paul J. Hertzog

The innate immune system acts as the first line of defence crucial in pathogen detection, immediate response to cancer and other stresses and initiation of the adaptive immune system. The Type 1 Interferons (IFN), produced in the innate response to pathogen detection, elicit numerous molecular and cellular responses. While the potential for use as therapeutics is well documented the nature of associated off-target effects limits their clinical applications. The endogenous signals must be finely tuned to confer effective host response without toxicity associated with unregulated responses. Indeed IFN signaling is also a target for therapeutic suppression in autoimmune disease.

The growing availability of chromatin immunoprecipitation (ChIP) sequencing (ChIP-Seq) and ChIP based microarray (ChIP-chip) techniques introduces the potential to understand the diversity and interactions of transcriptions factors activated by the various signal transduction pathways activated by IFN. Importantly the data availability from ChIP-Seq and ChIP-chip experiments inverts the traditional notion of transcription factor binding site prediction based on small samples of validated binding sites. We present a novel computational method designed to enable biologically relevant interpretation of large transcription factor binding site populations identified through ChIP-sequence and ChIP-chip datasets. This analysis method and associated software, collectively known as CHAMP, is based on the biological knowledge that transcription factors form numerous complexes containing a variety of associated factors all potentially impacting the ability to bind a particular regulatory element.

Application to the innate immune system has resulted in a novel understanding of the transcriptional nature of the immune response. This insight has the potential to facilitate the identification of selected pathways activated or repressed in a disease, therapeutic response or patient population. Overall this information will improve our understanding of signaling networks in disease and development of more targeted therapies. In addition to the innate immune system the CHAMP approach has wider implications in the analysis of numerous transcription factor binding sites associated withother biological responses.