AbstractMuch of human history has been dictated by the invisible force of pathogens and infections remain a leadingcause of ailment, mortality, and loss of food source or livelihood. In part, this is because our understanding ofinfection is stymied by the significant variability that exists in patient/host response to infection due to thepatient?s unique genetic makeup, as well as the variability in pathogen genomes. This variability determinessusceptibility, duration of infection, treatment options, and often, future response to pathogens. Controlled teststo understand the sources of these variabilities cannot be performed on humans due to ethical and practicalreasons. An in vitro model is therefore needed that will allow precise control/ tuning of different factorsinfluencing infection outcome. In this proposal, we aim to build a set of droplet microfluidic and molecularbiology tools that will allow us to address the issue of variability in infection outcome. Knowing the sources ofvariability and their genetic underpinnings will help fight infection better, improve patient outcome, reduce costof care and formulate better treatment strategies in future.We will use custom droplet microfluidics, time-lapse imaging and droplet sorting to: Aim 1: Encapsulate singlepathogen cell with single host cell in order to isolate, infect, and image their interaction over time in arepresentative micro-environment recreated in drops. We will use human macrophage cells as host andCandida albicans for pathogen, as model systems. Host and pathogen cells will be labelled with fluorescentreporters. Fluorescence and cell morphology will be used to determine infection outcome; Aim 2: Usemicrofluidics to sort infection droplets into two groups based on interaction outcome: Group A, where host cellhas successfully overcome pathogen, with pathogen cell undergoing lysis, and Group B, where the pathogenpersists resulting in the host cell?s death. We will perform bulk RNA-seq on each group to identify host genesresponsible for successful infection suppression in Group A and pathogen genes that likely cause increasedvirulence in Group B; Aim 3: Build microfluidic and molecular biology tools to profile host-pathogentranscriptomics at single-cell resolution to characterize infection outcome at systems level. The workflow iscustomizable, modular, and collectively our proposed platform may be used to profile infection in other hostor pathogen species at superior control, statistical resolution (~105 host-pathogen pairs), and at low cost(~$0.1/pair).
Novel microfluidic platform to profile host-pathogen interaction under controlled infection and single cell resolution
University of Chicago