Genetic control of early Mycobacterium tuberculosis inflammatory responses

About This Grant

Summary The inflammatory disease tuberculosis (TB) remains a major cause of mortality worldwide. The long treatment times required for drug therapy highlight the urgent need for new approaches to protect against TB disease. Complicating treatment efforts is the heterogeneity of disease states observed in humans. To address these knowledge gaps, we are using the Collaborative Cross (CC) a mammalian genetics resource that comprises of over 70 mosaic strains of mice, created by intercrossing 8 genetically distinct founder strains. Using the CC, we are identifying unique models of distinct TB disease states. However, cell-type complexity in animals complicates our understanding of the underlying mechanisms. In particular, a critical knowledge gap exists in our understanding of how early infection events drive distinct TB disease trajectories. These early host-Mtb interactions are almost exclusively with airway resident alveolar macrophages (AMs) that are functionally distinct from myeloid-derived macrophages but challenging to study. To overcome this experimental limitation, we developed fetal liver-derived alveolar-like macrophages (FLAMs), a genetically tractable ex vivo AM model that mimics lung AM function. This proposal will create an indexed library of FLAMs derived from the CC panel to test they hypothesis that heterogeneous Mtb-AM interactions contribute to distinct trajectories of TB disease. In Aim 1 we will create and validate the CC-FLAM library by barcoding FLAMs across CC strains, enabling tracking of genotype-specific responses during infection. In Aim 2 we will employ single-cell RNA sequencing and quantitative trait locus (QTL) mapping to define transcriptional networks and genetic loci associated with inflammatory cytokine production, comparing these findings with published disease-outcome QTLs. The work will identify mechanistic drivers of AM heterogeneity linked to TB progression, offering insights into patient risk of disease. By integrating genetic heterogeneity with ex vivo and in vivo models, this exploratory study lays the groundwork for developing therapies targeting early host-pathogen interactions while developing an innovative CC-FLAM platform that will be broadly useful to dissect pulmonary inflammation in other respiratory diseases.