The Medina laboratory uses a systems biology strategy to investigate host factors contributing to disease severity. Leveraging the established CHILE human cohort, conducting multi-omic analyses, including transcriptomics, metabolomics, cytokine and antibody profiling and immune functional assays, to characterize longitudinal host immune responses. They support the development and refinement of deep learning models, iteratively tested and validated with human derived data, and contributes to experimental design and analyses of in vivo model data. Systems-level approaches are integrated to identify novel correlates of protection against influenza virus.

The goal of the Tan group is to model the defining features of human influenza immunity following primary infection or vaccination, using the mouse model and leveraging multimodal and computational methodologies. The quality of protection, such as disease severity and durability, against influenza is based on mechanisms by which immunity is initially established. To provide a multidimensional perspective, the Tan team develops novel mouse models that recapitulate human comorbidities and disease, and capture the breadth of the preexisting immunity, to characterize novel correlates of immune protection.

As members of FLU-CODE the Sekaly team focuses on how the host environment shapes the development of innate and adaptive immune responses that modulate viral-induced pathogenesis and promote viral clearance. They utilize a multi-pronged strategy that emphasizes the phenotypic, effector function and molecular characterization of innate immune cells, as well as in the cellular arm of the immune response. They employ high-dimensional flow cytometry and single cell Multiome to define innate and cellular immune responses to discriminate individuals capable of controlling infection from those who experience severe disease.