Recent progress using systems biology approaches to better understand molecular mechanisms of immunity

Abstract

The immune system is composed of multiple dynamic molecular and cellular networks, the complexity of which has been revealed by decades of exacting reductionist research. However, understanding of the immune system sufficient to anticipate its response to novel perturbations requires a more integrative or systems approach to immunology. While methods for unbiased high-throughput data acquisition and computational integration of the resulting datasets are still relatively new, they have begun to substantially enhance our understanding of immunological phenomena. Such approaches have expanded our view of interconnected signaling and transcriptional networks and have highlighted the function of non-linear processes such as spatial regulation and feedback loops. In addition, advances in single cell measurement technology have demonstrated potential sources and functions of response heterogeneity in system behavior. The success of the studies reviewed here often depended upon integration of one or more systems biology approaches with more traditional methods. We hope these examples will inspire a broader range of immunologists to probe questions in a quantitative and integrated manner, advancing collective efforts to understand the immune "system".

Keywords: Computational modeling; Global analysis; Heterogeneity; High-throughput; Signaling networks; Single-cell analysis; Transcriptional networks.

Figure 1

Contributions of systems biology approaches to our current understanding of immune activation. Global, quantitative and computational methods have been successfully used to elucidate complex non-linear processes involved in the regulation of responses downstream of immune receptor triggering. Some examples include (a) spatial regulation of signaling intermediates (33), (b) impact of component concentration variation (74), (c) signaling feedback loops (76), (d) pathway cross-talk (25), (e) transcriptional regulatory circuits (37), (f) network interference by miRNAs (53), and (g) global regulation of gene expression through chromatin modifications (81).