Work

Dynamic transcription factor activity profiles reveal key regulatory interactions during megakaryocytic and erythroid differentiation

Year: 2014

Type: article

Abstract: The directed differentiation toward erythroid (E) or megakaryocytic (MK) lineages by the MK-E progenitor (MEP) could enhance the ex vivo generation of red blood cells and platelets for therapeutic transfusions. The lineage choice at the MEP bifurcation is controlled in large part by activity within the intracellular signal transduction network, the output of which determines the activity of transcription factors (TFs) and ultimately gene expression. Although many TFs have been implicated, E or MK differentiation is a complex process requiring multiple days, and the dynamics of TF activities during commitment and terminal maturation are relatively unexplored. Herein, we applied a living cell array for the large-scale, dynamic quantification of TF activities during MEP bifurcation. A panel of hematopoietic TFs (GATA-1, GATA-2, SCL/TAL1, FLI-1, NF-E2, PU.1, c-Myb) was characterized during E and MK differentiation of bipotent K562 cells. Dynamic TF activity profiles associated with differentiation towards each lineage were identified, and validated with previous reports. From these activity profiles, we show that GATA-1 is an important hub during early hemin- and PMA-induced differentiation, and reveal several characteristic TF interactions for E and MK differentiation that confirm regulatory mechanisms documented in the literature. Additionally, we highlight several novel TF interactions at various stages of E and MK differentiation. Furthermore, we investigated the mechanism by which nicotinamide (NIC) promoted terminal MK maturation using an MK-committed cell line, CHRF-288-11 (CHRF). Concomitant with its enhancement of ploidy, NIC strongly enhanced the activity of three TFs with known involvement in terminal MK maturation: FLI-1, NF-E2, and p53. Dynamic profiling of TF activity represents a novel tool to complement traditional assays focused on mRNA and protein expression levels to understand progenitor cell differentiation.

Source: Biotechnology and Bioengineering

DOI: 10.1002/bit.25262