The complex interplay between host and pathogen determines if an individual controls infection or progresses to disease. While abundant evidence suggests that genetic diversity contributes to the variety of outcomes, the combined effect of variation in the host and pathogen remains unclear. We developed a “dual-genome” system to unravel genetic interactions between Mycobacterium tuberculosis (Mtb) and its mammalian host that drive outcome to infection. Host variation was modeled using a collection of ~100 recombinant inbred mouse strains, including the Collaborative Cross panel, the BxD recombinant inbred panel and a series of targeted single-gene knockouts. Bacterial variation was concurrently generated using whole-genome knockout libraries and panels of diverse Mtb clinical isolates, each of which contained a molecular barcode to allow parallel assessment of multiple Mtb variants in each of the diverse host backgrounds.
The disease spectrum of CC and BXD mice infected with Mtb libraries exceeded that seen in parental strains and standard inbred lines. Metrics of disease that are tightly linked in the standard C57BL/6J resistant model such as bacterial burden, dissemination, weight loss and inflammation were genetically separable in the diverse strains. We identified individual polymorphic host genome regions (QTLs) underlying lung and spleen bacterial load and host control of infection independently in the CC and BXD panels.
We additionally separated the clinical disease traits into intermediate phenotypes by determining the relative fitness of thousands of bacterial mutants in the mouse panels. QTLs underlying differential bacterial fitness modules were identified, many of which mapped to the same host region as the clinical disease metrics. In addition to these overlapping “master loci”, we identified further QTLs impacting the requirement of various bacterial genes, including virulence factors, nutrient acquisition and oxidative radical generation.
Overall, the strategy of using bacterial fitness profiles as reporters of the underlying host microenvironment is a sensitive and specific method for identifying disease-modifying host polymorphisms, demonstrating the power of a dual-genome systems genetics approach to understand the fundamental drivers of susceptibility to infection.