Speaker
Description
Most adults are infected with the Epstein-Barr virus (EBV), which infects B cells and establishes lifelong latency. EBV achieves this by hijacking B cell-intrinsic transcriptional programs, which ultimately promotes B cell survival, including that of atypical memory B cells (ABCs), a population associated with autoimmune disease. Here, we aim to construct an ODE model of B cell fate trajectories following EBV infection, with the goal of quantifying the dynamics of cell state changes that lead to successful infection as well as to the emergence of ABCs. Our approach uses scRNA-seq data collected during the early stages of EBV infection in B cells to quantify how cell state proportions evolve over time. We then apply a SINDy-based model discovery framework to infer interpretable ODEs describing transitions between cell states. Ultimately, beyond the specifics of studying the influence of EBV on B cell fate, we aim to build a generalizable pipeline that translates scRNA-seq data into interpretable, dynamic models of cell fate trajectories.
