Transcriptomic diversification along the monocyte-macrophage continuum.

Abstract

Current models of innate immune responses describe hard wired, gene-centric signalling networks, with limited capacity to define the molecular mechanisms underpinning transcriptomic diversity. It is well established that a transcriptional spectrum of responses accompanies acute macrophage activation, however it is unclear whether this spectrum originates in monocytes and to what extent it continues throughout reinfection. The contribution of molecular mechanisms such as enhancers and alternative transcription start sites is also undetermined. Given the critical roles that myeloid cells play in directing acute infection and priming adaptive immunity, it is important the regulation of their responses be understood.

This thesis employed bioinformatic analysis of Cap Analysis Gene Expression (CAGE) and microarray data to describe transcriptional diversity along the monocyte-macrophage continuum. Using CAGE to map transcription start sites for capped RNAs, this thesis has shown that pathogen-specific transcriptional diversification commences early in monocyte infection (Chapters Three and Four) and continues throughout acute macrophage infection (Chapter Five). Transcriptomic diversity during acute infection was the product of kinetic and pathogen-specific engagement of distinct transcription start sites. Engagement of multiple transcription start sites drove responsiveness by regulating expression amplitude in functionally focused inflammatory gene sets and diversifying secondary response networks via expression of distinct protein isoforms. Chapter Six extended these studies of acute infection, demonstrating that transcriptional phenotypes continue to diversify during reinfection. These findings highlight the importance of studying innate immune responses at the isoform level and prompt the need to revise current models of innate immune signalling, such that monocyte-macrophage biology should no longer be modelled as a series of static states, but rather, as a continually evolving continuum.