Project Summary Precise temporal regulation of inflammatory responses is required to clear infection without damaging healthy tissue. Previous work elucidating the mechanisms involved in this regulation have focused mainly on single time points or bulk samples of cells. However, immune cells in vivo receive complex temporal combinations of stimuli during an immune response, respond with gene expression patterns that vary over time, and display heterogeneity within the population. Interferon gamma (IFNγ) is a pro-inflammatory cytokine that plays key roles in immune responses. Macrophages are immune cells that are one of the primary responders to IFNγ. During infection, macrophages may experience multiple periods of IFNγ stimulation, and employ signaling and gene expression networks to decode these varying stimuli into gene expression responses and diverse functions. GBP1 and NOS2 are two IFNγ-responsive genes that have important roles in host defense against microbes and are regulated by different network architectures and chromatin regulatory mechanisms. Mycobacterium tuberculosis (Mtb) infection is a pressing global health issue that also depends critically on macrophage responses to IFNγ. Mtb infection outcomes are heterogeneous on the cellular as well as the organismal (human) level. Previous work has shown that IFNγ signaling is essential for macrophages to kill intracellular Mtb and that this ability to kill Mtb varies between cells. This proposal uses a system that combines endogenous fluorescent gene reporters in macrophage cell lines with long-term live-cell imaging in a microfluidic device to simultaneously track expression kinetics of multiple genes in response to dynamic stimuli, as well as the outcomes of Mtb infection, in the same single cells over time. This can be used to obtain a quantitative understanding of the mechanisms underlying kinetic gene expression responses and functional heterogeneity. In Aim 1, this system is used to quantify and model single macrophage gene expression kinetics following dynamic IFNγ stimulus and to elucidate the mechanism of signal decoding. This is done by applying IFNγ stimulus of varying amplitude and duration to the macrophages and simultaneously tracking expression kinetics of three components of the GBP1 and NOS2 networks in the same single cells over time. A mathematical model will be developed to describe these responses, predict the response to perturbation, and will be tested using inducible promoters and inhibitors of chromatin regulators to perturb the decoding. Aim 2 investigates the connection between cell-to-cell variability in gene expression kinetics and heterogeneous Mtb infection outcomes. This is done by infecting fluorescent reporter macrophage cell lines with Mtb marked by a viability reporter and assaying both gene expression kinetics and infection outcomes in single cells. The completion of these aims will provide a quantitative understanding of the mechanisms by which macrophages decode dynamic IFNγ stimuli into time-variant gene expression patterns, as well as mechanistic insight into the sources of heterogeneity in the outcomes of Mtb infection.

Project Narrative Macrophages must respond to interferon-gamma (IFNγ) to fulfill their role in coordinating immune responses and in controlling Mycobacterium tuberculosis (Mtb) infection. In this project, I will combine microfluidics, quantitative modeling, and genetic engineering to quantify on a single-cell level how gene expression kinetics change in response to dynamic patterns of IFNγ, and the functional implications of these gene expression kinetics for control of Mtb infection. This will advance our understanding of macrophage signal decoding, which has applications for infectious disease and immunopathology, as well as our understanding of heterogeneity in Mtb infection, a pressing global health need.