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Our laboratory has a long-standing interest in B cell antigen receptor (BCR) signaling and how BCR dependent processes regulate specific cell fate decisions. In the bone marrow, we have been working to understand how signals initiated through the pre-BCR, in conjunction with those delivered through the IL-7 receptor, coordinate cell cycle progression with immunoglobulin light chain gene recombination. These studies resulted in discovery of the epigenetic reader BRWD1 as critical for both regulating Ig-kappa accessibility and in coordinating broad transcriptional programs in early and late B lymphopoiesis. Recently, we have demonstrated that the pre-BCR initiates an IRF4-CXCR4 feedforward loop and that it is CXCR4 that directly signals Ig-kappa recombination. These latter findings fundamentally rewrite the canonical model of B lymphopoiesis. Furthermore, they are the first demonstration of a direct and independent role for CXCR4 in driving an important biological process. In the periphery, we have focused on the molecular control of germinal centers (GCs). Recently, we have recently defined two novel B cell populations within the dark zone that both allow compartmentalization of fundamental GC functions and reveal the molecular programs of the GC cycle. This new three population model fundamentally rewrites the GC paradigm. In all these areas, we have derived novel in vivo models, and have performed directed in vitro studies, to obtain definitive insights into these processes.
Our translational studies have focused on how in situ adaptive immune responses drive tubulointerstitial inflammation in human lupus nephritis. For these studies, we have used deep machine learning to develop novel image analysis tools to quantify and identify functional relationships between different T cell and antigen presenting cell populations in situ. Remarkably, this bioinformatics platform approaches the sensitivity and specificity of two-photon excitation microscopy (TPEM). However, unlike TPEM, it can be applied to the study of human disease. We have also used single cell technologies to understand B cell selection at sites of inflammation and determine the interrelationships between transcriptional state and antigenic specificity.