Project description:We utilize gene expression and open chromatin footprinting data to build a gene regulatory network of key transcription factors that capture the cell and time-specific regulatory programs specified during human myeloid differentiation.
Project description:We utilize gene expression and open chromatin footprinting data to build a gene regulatory network of key transcription factors that capture the cell and time-specific regulatory programs specified during human myeloid differentiation.
Project description:We utilize gene expression and open chromatin footprinting data to build a gene regulatory network of key transcription factors that capture the cell and time-specific regulatory programs specified during human myeloid differentiation.
Project description:We utilize gene expression and open chromatin footprinting data to build a gene regulatory network of key transcription factors that capture the cell and time-specific regulatory programs specified during human myeloid differentiation.
Project description:Human neutrophilic granulocytes form the largest pool of innate immune cells for host defense against bacterial and fungal pathogens. The dynamic changes that accompany the metamorphosis from a proliferating myeloid progenitor cell in the bone marrow into a mature non-dividing polymorphonuclear blood cell have remained poorly defined. Using mass spectrometry-based quantitative proteomics combined with transcriptomic data, we report on the dynamic changes of 5 developmental stages in the bone marrow and blood. Integration of transcriptomic and proteomic unveiled highly dynamic and differential interactions between RNA and protein kinetics during human neutrophil development which could be linked to functional maturation of typical end-stage blood neutrophil killing activities.
Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Time course microarray data for Th17 differentiation, including Th0 control