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

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.

Transcriptional Regulation of Platelet Formation: Harnessing the Complexity for Efficient Platelet Production In Vitro

“…This data was used to build regulatory networks using bespoke software. The results, for example, confirmed the mutually activating interaction between TAL1 and GATA1 [200].…”

Fibronectin Promotes the Malignancy of Glioma Stem-Like Cells Via Modulation of Cell Adhesion, Differentiation, Proliferation and Chemoresistance

“…A TATA-box promoter (TA) drove the expression of firefly luciferase downstream of p53-specific binding sites in multiple copies of a cis -acting enhancer element in a p53 reporter plasmid (Bellis et al, 2013 ). A p53 reporter plasmid together with lentiviral packaging vectors (pMDLGagPol, pRSV-Rev, pIVS-VSV-G) and jetPRIME (Polyplus-transfection, Illkirch, France; Duncan et al, 2014 ) were co-transfected into HEK-293T cells to produce lentivirus. Supernatants were collected after 48 h and centrifuged to remove cell debris.…”

Hyperglycaemia suppresses microRNA expression in platelets to increase P2RY12 and SELP levels in type 2 diabetes mellitus

“…Cells were differentiated by using 20 ng/ml phorbol-12-myristate-13-acetate (PMA) for seven days. The differentiation of these cells was followed via the surface CD41 and CD61 percent positivities and mean fluorescence intensity (MFI) values by flow cytometry similarly to a former publication (28). For immunophenotyping, MK cells were incubated with anti-CD41-PE or anti-CD61-PE and CD45-FITC antibodies (BD) for 15 min in the dark at RT.…”

“…Investigation of platelet activation level via surface P-selectin expression was performed as previously described (28). Briefly, 40 µl of whole blood samples were fixed in 1 ml 1 % PFA and kept at RT for 1 h. Platelets were identified by a FITC-conjugated monoclonal antibody to GPIX (CD42a-FITC).…”