ABSTRACT Infection is a dynamic interplay between host and pathogen, coordinated through each organism's signaling and gene regulatory networks. The world's deadliest pathogen, Mycobacterium tuberculosis (Mtb), can exploit its network of molecular interactions with the host to elicit an infection steady state that enables it to persist asymptomatically for up to decades. Perturbations in Mtb's or the host's network activities that tip the balance of this molecular homeostasis will alter infection outcomes: either pathogenically toward a symptomatic tuberculosis (TB) disease with rampant Mtb growth and pathological inflammation that could lead to death, or protectively toward infection clearance. I will dissect host signaling and Mtb regulatory network activities for infection fate- deciding tipping-point genes that impact Mtb viability and host inflammation during infection in primary human monocyte-derived macrophages (MDMs), a major infected host cell in vivo. I will profile the host and pathogen transcriptional responses to these infection-altering perturbations to define molecular mechanisms underlying the host-pathogen interplay, and I will use this information to identify synergistic joint interventions that concurrently target host and pathogen. Identifying these tipping-point genes at the host-pathogen interface should inform new therapeutic intervention strategies that jointly target host and pathogen to elicit host protection, while also revealing fundamental insights into pathogenesis.

NARRATIVE Mycobacterium tuberculosis (Mtb) infection fate is the product of interactions between host and pathogen coordinated through biological networks. I will systematically dissect host signaling and Mtb gene regulatory network activities that impact Mtb viability and host inflammation during Mtb infection in primary human monocyte-derived macrophages (MDMs), a major infected host cell in vivo. This characterization will uniquely enable dissection of infection phenotypes in primary human host cells at an unprecedented scale and granularity, maximizing clinical relevance of biological insights.