Systems Biology of Microbial Infection

hOst-PathOgen InteractIOn In the past, most studies have focused on either the side of the pathogen or the host. Tierney et al. (2012) try to overcome this limitation using Next Generation Sequencing (RNA-Seq analysis) to monitor the gene expression of the host and the pathogen simultaneously. They analyze and model the interaction of mouse bone marrow-derived dendritic cells with the pathogenic yeast Candida albicans, and infer a gene regulatory network comprising genes and proteins of both host and pathogen. Durmus‚ Tekir et al. (2012) study more than 23,000 protein–protein interactions that characterize the strategies of interaction of the human host with viral, bacterial, and some fungal pathogens utilizing the database pathogen-host-search-interaction-tool (PHISTO). Binder et al. (2012) modeled the population dynamics of Borrelia burgdorferi using an ordinary differential equation approach taking into account the dissemination of bacteria to different tissues as well as cellular phagocytic activity during the innate immune response. By comparing different model scenarios with experimental data on infected mice, they aim at understanding why an almost cleared population of these bacteria can recover and reach a size that is even larger than the initial population before entering the chronic phase. Applying an agent-based modeling approach that treats cells as discrete objects in space with dynamic properties, Tokarski et al. (2012) simulated the interactions of conidia of the human-pathogenic fungus A. fumigatus with migrating human neutrophils. Based on the analysis of time-lapse microscopy image data, different scenarios of phagocyte migration are explored and evaluated with regard to the clearance efficiency.