UC San Diego

CD8 + T cells are a central component of the adaptive immune system. Upon infection, a naive CD8 + T cell will differentiate into a heterogeneous population of effector T cells composed of terminal-effector and memory-precursor CD8 + T cells. Terminal-effector T cells rapidly decay after pathogens are eradicated while memory-precursor T cells survive during the contraction phase to become memory T cells, providing long-term protection from reinfection. Similar to the heterogeneity of effector T cells, memory T cells can also be divided into central-memory, effector-memory and tissue-resident memory subsets based on trafficking, location, proliferation potential and cytotoxic function. These memory subsets collaborate together to enhance the pathogen clearance and vaccine efficacy. The differentiation of a naive CD8 + T cell into a specific effector or memory subset is influenced by cell-extrinsic environmental signals and cell-intrinsic factors including transcription factors (TFs), epigenetic modification and chromatin organization. Considerable advances have been made to identify key TFs that regulate these T cell fate decisions. However, the TF-mediated transcriptional network responsible for specific subset differentiation and how epigenetic modifications and chromatin configuration modulate CD8 + T cell fate determination is still largely unknown. To address these questions, we deciphered epigenetic landscapes in effector and memory CD8 + T cells in response to bacterial infection by characterizing the genome-wide histone modification, chromatin accessibility and transcriptional program. Integrative analysis of epigenomics data showed that subset-specific enhancers established by key TFs foreshadow the specific lineage differentiation. To better identify cruicial TFs from multilayered epigenetic landscapes, we developed a webpage ranking-based algorithm (PageRank) to rank the importance of TFs from transcriptional network and identified a novel function of two TFs: YY1 and Nr3c1 to regulate terminal-effector and memory-precursor subset differentiation, respectively. By leveraging the PageRank analysis and chromatin accessibility data, we developed a computational screen to predict key TFs for tissue-resident memory T cell differentiation. Combining this approach with shRNA functional screen, we identified the role of Runx3 in programming tissue-residency signatures in non-lymphoid tissues and tumors. Finally, we discovered a novel role for the genome organizer CTCF in CD8 + T cell fate decisions illustrating the impact of chromatin organization on effector and memory T cell differentiation. Taken together, we uncovered a multi-layered regulation of chromatin state, accessibility and organization, that influences T cell fate decisions by fine-tuning transcriptional circuits. We further constructed a computational framework that integrates these high-dimensional data, facilitating identification of key transcriptional regulators and providing valuable biological insights.