Linking Mycobacterium Tuberculosis infection outcomes with transcriptional networks in genetically diverse mouse macrophages

Project Summary: Tuberculosis (TB), like many infectious diseases, demonstrates striking variation between individuals in its clinical manifestation. People infected with the causative agent, Mycobacterium Tuberculosis, range in disease state from completely asymptomatic infection to life-threatening disseminated disease. Even though many infected individuals do not develop symptoms and most resolve the infection with treatment, TB is perennially the leading cause of death by a single infectious agent with an annual death toll of more than one million people. A major goal of TB research is to understand the basis of the variability in infection outcomes. Such an understanding will help in identifying ways to improve treatments and tip the scale away from pathological inflammation lung damage toward healthy resolution of infection. One important factor that contributes to the outcome of TB is the genetic background of the infected individual. Many studies have addressed the role of natural genetic variants in determining TB outcomes in both humans and mice. However, relatively few studies have investigated these associations in the context of macrophages, a central cell type of interest in TB. This project will explore the relationship between genetic variants, transcriptional responses, and Mtb infection phenotypes in macrophages derived from genetically diverse Collaborative Cross (CC) mice. In preliminary studies, I associated variants in the Stat2 locus with the strength of type I interferon signaling in stimulated CC macrophages. Therefore, I hypothesize that polymorphisms, such as those in Stat2, underlying variation in transcriptional responses are responsible for heterogeneity in bacterial control in CC macrophages. I will test this hypothesis using a novel tool developed to specifically investigate the role of natural genetic variation in determining macrophage phenotypes. This hypothesis will be tested in three specific aims which will both generate novel genetic association and determine the mechanism of previously identified associations. I will use an exploratory approach in the first aim to discover what the genetic and transcriptional determinants of Mtb restriction are in this population of macrophages. This approach is likely to discover novel mechanistic insights into how macrophage respond to Mtb infection. In the second and third aims, I will delineate the mechanism by which polymorphisms in Stat2, a mediator of type I interferon signaling, alter its function. The second and third aim will test an updated model of the recognition of DNA by STAT2 which I generated by combining macrophage genetic association studies and structural modeling. In the proposed studies, I will utilize and continue to develop an innovative new tool, the CC macrophage library. I will incorporate genetic, biochemical, and systems approaches to discover and characterize associations of polymorphisms and transcriptional networks with Mtb infection outcomes. The results of these studies will provide insight into innate immune processes and will be important to consider for future studies into TB and other infectious diseases using the Collaborative Cross.