Speaker — Manu, Assistant Professor in the University of North Dakota Department of Biology
Title — Understanding hematopoietic cell-fate specification using both top-down and bottom-up modeling approaches
Abstract — Cell-fate decisions during hematopoiesis are controlled by densely interconnected gene regulatory networks (GRNs) composed of tens to hundreds of genes. The structure of these complex networks and the rules by which they direct hematopoietic cell-fate decisions are not well understood. One particular challenge is that DNA-sequence level regulatory logic is not known for most genes. We developed an approach for inferring regulatory logic using sequence-based thermodynamic models, which, given DNA sequence and TF expression levels, simulate gene regulation to predict transcription rate. We identified 3 novel enhancers of Cebpa, which is necessary for neutrophil development, and inferred models of their regulatory logic using our methodology. The models predicted that Cebpa enhancers have a complex and fail-safe regulatory architecture, featuring activation by overlapping combinations of multiple TFs. These predictions were verified by site-directed mutagenesis experiments. Besides uncovering the regulatory logic of an important hematopoietic gene, these results demonstrate that the mechanisms encapsulated in such models are sufficiently general to correctly predict both mammalian and invertebrate gene expression. Another important problem we address is how cell-intrinsic GRNs interpret cell-extrinsic cytokine signals to make cell-fate decisions. We constructed a coupled differential equation model of a 12-gene GRN, including key lineage-specifying TFs, cytokine signaling effectors, and cytokine receptors. The model quantitatively recapitulates experimentally observed gene expression trajectories during erythrocyte-neutrophil differentiation and can predict the consequences of genetic perturbations. The inferred model is consistent with known regulatory linkages and reveals a highly interconnected GRN structure featuring pervasive antagonism, where erythrocyte genes repress neutrophil genes and vice versa, and positive feedback between TFs and cytokine signaling. These studies demonstrate the viability and utility of modeling developmental GRNs with a combination of DNA-sequence level (bottom-up) and dynamic network-level (top-down) approaches.
Host — Geetu Tuteja