Mk Genes Research Articles

Epigenetic and Single Cell Analyses Reveal Dual Fate Decision Points in Pre-Primed Hematopoietic Stem Cells during Erythro-Megakaryopoiesis

Recent single cell analyses have shown that hematopoietic differentiation is more complex than the traditional hierarchical model suggests, and that lineage commitment may occur earlier in the hierarchy than previously thought (Notta, 2016; Psaila, 2017). In particular, the relationship between bipotential megakaryocyte-erythroid progenitors (MEP) and common myeloid progenitors (CMP) is unclear in erythro-megakaryopoiesis. While it has been established that mouse MEP and CMP populations contain different proportions of megakaryocytic and erythroid lineage-committed cells, our aim was to determine when lineage-commitment occurs and whether a ‘default’ differentiation pathway exists.We established the transcriptional and epigenetic profiles of 14 flow cytometry-enriched primary murine hematopoietic populations, including hematopoietic stem/progenitor cells (HSPC) and lineage-committed populations. We performed transcriptome profiling (RNASeq), chromatin accessibility profiling (Assay for Transposable-Accessible Chromatin; ATACSeq), and DNA methylation profiling (MethylCSeq). We also performed ChIPSeq of H3K27ac on erythroblasts (EB) and immature megakaryocytes (Mk) to identify putative active enhancer elements.Principle component analysis (PCA) of the RNASeq data demonstrated variation between lineages. Primary cells and cell lines were separated by PC1 (20% of variance) while PC2 (14% of variance) separated HSPC and Mk-committed cells from EB, monocytes and granulocytes. Likewise, PCA of ATACSeq data also indicated that HSPC and Mk shared more similarity than other populations: PC1 (19% of variance) separated EB and non-EB populations while PC2 (12% of variance) separated HSPC and Mk-committed cells from EB, monocytes, granulocytes and lymphocytes (Figure 1). These data demonstrate that the transcriptional and chromatin accessibility profiles of Mk are more similar to HSPC than to other populations.We defined putative active enhancers (pAE) as the intersection of ATACSeq and H3K27ac ChIPSeq peaks in EB and Mk. We identified 2098 EB- and 6386 Mk-specific pAE, and 5989 shared pAE. To predict pAE in progenitors we overlaid EB and Mk pAE with successive ATACSeq peaks in lineage-restricted progenitors (CFU-E, CFU-Mk), followed by CMP and the Lin-Sca+Kit+ population (LSK). 97% and 89% of Mk pAE were detected in CMP and LSK, whereas only 84% and 64% of EB pAE were detected. To validate which EB and Mk pAE in LSK were active (as opposed to poised), we compared our LSK pAE with the indexing-first ChIP histone marks identified by Lara-Astiaso et al., (Science , 2014). We found that 31% of Mk-, but only 13% of EB pAE, were active in the LSK. These data indicate that the MK enhancer profile is established earlier than that of EB.Our comparison of the DNA methylation (CH3) profiles showed that, unlike the RNASeq, ATACSeq, and H3K27ac profiles, erythropoiesis was associated with an 87% decrease in CH3 from CMP and LSK sets; 15% of EB CH3 peaks were established de novo. In contrast, megakaryopoiesis was associated with a 33% increase in CH3 peaks from CMP and LSK sets; 50% of Mk CH3 peaks were established de novo. Many of these de novo methylation sites were associated with genes directing non-Mk lineages that are downregulated compared to CMP (e.g., Dach2, Sox5, Kit, Klf1, Tet1, Fog1).To determine when lineage-commitment occurs we performed single cell RNASeq (10X Genomics platform) on ~9000 cells from each of LSK, CMP, MEP, and GMP (granulocyte-macrophage progenitors) populations. The Seurat software (Sajita, 2015) was used to ‘cluster’ cells with similar expression profiles. MEP contained 5 erythroid clusters of different maturation stages (57% of cells), and 1 cluster with an Mk gene signature (5% of cells). CMP contained, among others, 8 Mk clusters (60% of cells) and 1 cluster (2% of cells) co-expressing Mk and EB genes. LSK contained 4 Mk clusters (26% of cells) but no populations expressing EB-associated genes.We conclude that the transcriptional and epigenetic Mk profile is detectable at the earliest stages of hematopoiesis. The requirement of de novo methylation and silencing of other lineage-associated factors prevents the classification of Mk as a default pathway. In contrast, the EB profile is established after most megakaryocyte progenitor cells have become committed and extensive transcriptional and epigenetic reprogramming is required to permit erythropoiesis. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Mouse Erythroid Cells Originate from a Megakaryocyte Precursor in Common Myeloid Progenitors

The hierarchical model of hematopoiesis posits that hematopoietic stem and progenitor cells produce common myeloid progenitors (CMP). CMP can become granulocyte/monocyte progenitors (GMP) or bipotential megakaryocyte/erythroid progenitors (MEP). MEP can produce megakaryocytic (Mk) or erythroid (Ery) cells. However, we and others have shown that early mouse and human progenitor populations express many Mk genes (Heuston, Epig. Chrom., 2016), while single cell studies have identified lineage-specific colony forming cells in progenitor populations thought to be multipotent (Psaila, Genome Biol., 2016). To identify the earliest mouse Ery and Mk cells, we performed single cell RNASeq on 10000 stem and progenitor cells (Lin-Sca1+Kit+), 12000 CMP (Lin-Sca1-Kit+CD16/32-CD34+), 6000 MEP (Lin-Sca1-Kit+CD16/32-CD34-) and 8000 GMP (Lin-Sca1-Kit+CD16/32+CD34+). TSNE analysis of expression in the 4 populations identified 33 clusters, which were correlated to biological functions using gene set enrichment analysis. In LSK, no cells with an Ery RNA profile were found, while 56% of cells co-expressed Mk-associated (e.g., Meis1, Fli1) and lymphoid genes. In CMP, 12% of the cells co-expressed Ery (e.g., Gata1, Fog1) and Mk (e.g., Pf4, Cd41) genes, while 23% had an Mk-specific profile (e.g., Fli1, Cd41) enriched for platelet biology processes (p< 3E-18). Unlike traditional models, over 94% of MEP had Ery RNA profiles enriched for ribosome synthesis and heme-biology processes (p< 4E-10). To establish developmental relationships, we performed pseudotime analysis using the Monocle and Scanpy software packages. These programs model differentiation by mapping similar transcriptomes together. Map nodes indicate lineage commitment points and cells further from a node are more differentiated. Combined analysis of LSK, CMP, and MEP generated a model with a single node and 2 trajectories. LSK with Mk and lymphoid RNA profiles diverged at the node, as did 14% of CMP. 31% of CMP with an Mk RNA profile were downstream of the node. Further downstream were cells with mixed Ery/Mk profiles, and furthest from the node were MEP with Ery profiles. A separate pseudotime analysis of CMP only 2 trajectories: one with decreasing Mk- and increasing Ery RNA profiles, and a second with an early Mk endomitotic RNA profile. Pseudotime analysis of MEP only identified a linear trajectory: cells at one end expressed early Ery RNA profiles, and cells at the other end had RNA profiles similar to those of burst-forming unit-erythroid (BFU-E). We generated a predictive set of RNAs for each TSNE cluster. We used index-sorting with 11 markers (Kit, Sca1, CD34, CD16/32, CD36, CD41, CD48, CD123, CD150, CD9, Flk2) to isolate single cells for custom high-throughput multiplex qPCR. This allowed confirmation of cell frequency within TSNE clusters while identifying surface markers for prospective isolation of cell subsets. We focused on 2 populations: CMP-E, which had an Ery RNA profile (10% of clustered CMP and 12% of CMP in the qPCR assay), and CMP-MkE, which had Mk and Ery RNA profiles (12% of clustered CMP and 13% of CMP in the qPCR assay). We prospectively isolated CMP-E and CMP-MkE to compare RNASeq profiles, ATACSeq profiles, and colony forming ability against those of bulk CMP, Ery, and Mk. In CMP-E, 54% of RNAs were expressed in both CMP and ERY, while 41% were expressed only in CMP (p < 6E-72). In contrast, 41% of CMP-E ATACSeq peaks were present in CMP and ERY, while 57% of CMP-E peaks were present only in CMP (p < 1E-3). We conclude that in CMP-E, the RNASeq profile is more erythroid than the ATACSeq profile. In CMP-MkE, 89% of RNAs were expressed in both CMP and Mk, while 7% were expressed only in CMP (p < 8E-190). Likewise, 88% of CMP-MkE ATACSeq peaks were present in both CMP and Mk, while 3% were present only in CMP (p < 1E-3). We conclude that in CMP-MkE, the RNASeq and ATACSeq profiles are equivalent. In soft agar assays, 21% of CMP-E and 3% of CMP-MkE colonies contained BFU-E, compared to 9% of control colonies. We conclude that the CMP-E and CMP-MkE populations are skewed towards the ERY and MK lineages, but are not erythro-megakaryocyte restricted. Our data support a model in which there are two megakaryocyte precursor populations and no erythroid populations in LSK. A third megakaryocyte population in CMP gives rise to erythroid cells. Finally, our data show that transcriptional changes precede chromatin accessibility changes in the earliest erythroid cells. Disclosures No relevant conflicts of interest to declare.

Single Cell RNASeq Demonstrates That Mouse Erythroid Cells Are the Last Lineage to Emerge

The hierarchical model of hematopoiesis posits that hematopoietic stem cells (HSC) give rise to myeloid progenitors (CMP), that can become further restricted to bipotential granulocyte/monocyte progenitors (GMP) or megakaryocyte/erythroid progenitors (MEP). We and others have shown that this model may not accurately depict hematopoiesis. Recent studies have shown that shown that populations of mouse hematopoietic stem and progenitor cells (LSK) have a strong megakaryocyte (Mk) transcriptional profile (Heuston, 2018, Epig. & Chrom.), and single cell studies have identified lineage committed cells in progenitor populations thought to be multipotent. For example, we recently reported that human MEP contain 3 populations: erythroid (Ery) primed, Mk primed, and bipotential (Psaila, 2016; Gen. Bio.).To determine when Mk and Ery cells emerge during mouse hematopoiesis, we performed single cell RNASeq on 10000 LSK, 12000 CMP, 6000 MEP and 8000 GMP cells. Clustering analysis (Satija, 2018, Nat. Biotech.) of all 4 populations identified 33 transcriptionally distinct clusters. In 30 of 33 clusters, 85% of cells were from a single defined population (e.g. MEP). LSK and CMP clusters grouped closely together.We used gene set profiling (Gene Set Enrichment Analysis, GO and KEGG) to correlate transcriptional profiles of clusters with specific hematopoietic lineages and cellular activities. In LSK, the most common transcriptional profiles correlated with active cell cycling. Mk-associated genes (Meis1, Myct1, and Fli1), were co-expressed with lymphoid genes in 56% of all LSK. Consistent with previous studies, we conclude that cells with Mk transcriptional profiles are abundant in LSK. No cells with an Ery RNA signature were observed in LSK.23% of all CMP cells expressed Mk genes (e.g., Pf4, Itga2b, and Fli1) and were enriched for processes involved in platelet biology (p < 3E-18). 12% of CMP had an Ery RNA signature (low expression of Gata1, Klf1, and Nfe2) and decreased Mk gene expression (e.g., Gata2 and Gfi1b, [p < 3E-18]) compared to other CMP clusters. The high ratio of Gata2/Gata1 expression (1.90) suggests that this cluster contained immature Ery cells.More than 94% of all mouse MEP had Ery RNA signatures. Clusters could be distinguished by gene expression (e.g., Gata1, Klf1, Tfrc) and biological processes (ribosome synthesis and heme-biology processes [p < 4 E-10]). Based on the transcriptional profiles, we determined the most mature erythroid cells in MEP were late BFU-E.To compare the differentiation of Mk and Ery cells, we pooled our LSK, CMP, and MEP data for analysis using the Monocle software package. GMP contained only clusters expressing granulocytic or monocytic genes and were excluded from the analysis. Monocle arranges cells into trajectories based on their transcriptional profiles, with more differentiated cells positioned further from a common node (Xiaojie, 2017, bioRxiv). We found that LSK cells near the node had overlapping lymphoid and Mk transcriptional profiles. Closest to the node, we found 38% of CMP expressed a profile similar to LSK. An additional 45% of CMP formed one trajectory with lymphoid and granulocyte RNA signatures. Another 17% of CMP formed a second trajectory, with cells expressing an Mk signature closest to the node, cells with a mixed Ery/Mk signature further along the trajectory, and MEP cells with Ery-only signatures furthest from the node. To clarify the Mk/Ery divergence, we focused our analysis on the CMP populations expressing Mk RNAs (Figure1). We observed cells in G1/S phase with an immature Mk signature to the left of the node where the trajectories diverge. On the right, cells with immature Mk signatures were nearest the node and cells with a mixed Ery/Mk signature were at the end of the trajectory (upper right; Mk/Ery). Along the second trajectory, rapidly cycling G2/M Mk cells with an early endomitosis-associated RNA signature (e.g., Pf4, Gp1bb, Gp9, and Vwf) were located at the end of the trajectory (lower right; Mk early endomitosis).Our data are consistent with a model in which two waves of Mk differentiation begin in LSK and progresses to CMP. The Mk lineage is divided in CMP, producing cells that begin endomitosis and cells that have an Mk-repressing/Ery-activating cell program that gives rise to the Ery lineage. We conclude that the erythroid lineage is derived from an Mk-like precursor and is the last lineage to be specified in mouse hematopoiesis. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Comprehensive Molecular Profiling of FLT3-Mutated Acute Myeloid Leukemia (AML) Patients Treated within the Ratify Trial (Alliance C10603)

Comprehensive Molecular Profiling of FLT3-Mutated Acute Myeloid Leukemia (AML) Patients Treated within the Ratify Trial (Alliance C10603)

Generation of Megakaryocytic Progenitors from Human Embryonic Stem Cells in a Feeder- and Serum-Free Medium

BackgroundThe production of human platelets from embryonic stem cells in a defined culture system is a prerequisite for the generation of platelets for therapeutic use. As an important step towards this goal, we report the differentiation of human embryonic stem cells (hESCs) towards the megakaryocyte (Mk) lineage using a ‘spin embryoid body’ method in serum-free differentiation medium.Methodology and Principal FindingsImmunophenotypic analyses of differentiating hESC identified a subpopulation of cells expressing high levels of CD41a that expressed other markers associated with the Mk lineage, including CD110, CD42b and CD61. Differentiated cells were sorted on the basis of their expression of CD41a, CD34 and CD45 and assessed for Mk colony formation, expression of myeloid and Mk genes and ability to endoreplicate DNA. In a collagen-based colony assay, the CD41a+ cells sorted from these differentiation cultures produced 100–800 Mk progenitors at day 13 and 25–160 Mk progenitors at day 20 of differentiation per 100,000 cells assayed. Differentiated Mk cells produced platelet-like particles which expressed CD42b and were activated by ADP, similar to platelets generated from precursors in cord blood. These studies were complemented by real time PCR analyses showing that subsets of cells enriched for CD41a+ Mk precursors expressed high levels of Mk associated genes such as PF4 and MPL. Conversely, high levels of myeloid and erythroid related transcripts, such as GATA1, TAL1/SCL and PU.1, were detected in sorted fractions containing CD34+ and CD45+ cells.ConclusionsWe describe a serum- and feeder-free culture system that enabled the generation of Mk progenitors from human embryonic stem cells. These cells formed colonies that included differentiated Mks that fragmented to form platelet-like particles. This protocol represents an important step towards the generation of human platelets for therapeutic use.

Abstract 5010: Microarray analysis of gene expression profiling of essential thromocythemia (ET) and post-ET MF (myelofibrosis) derived megakaryocytic cells

Abstract Patients with ET eventually transform into Post- ET MF in most cases after several years. The underlying mechanism of the transformation is still unknown. ET and Post-ET MF is characterized by abnormal megakaryocytic proliferation. Therefore we have performed microarray analysis of gene expression profiles to compare megakaryocytes derived from patients with Post-ET MF to ET. CD 34+ cells were obtained from peripheral blood, then cultured with Serum-Free Medium of stem cell factor (100 ng/mL) and thrombopoietin (TPO 100 ng/mL), and added murine bone marrow stromal cell line OP9 as feeder layer. Megakaryocytes were then obtained by MACS selection of CD 61+ cells after 10 days culture. Then oligonucleotide microarray analysis was performed by PhalanxBio Inc. (Palo, Alto, Ca). Gene expression profiling was achieved by using the comparative cycle threshold (CT) method of relative quantification (the calibration samples were MK pools from 10 ET patients with GAPDH used as internal controls). SLR (Signal log ratio) was then calculated for comparative analysis of 2 patients with post-ET MF to a pool of ET patients. The results of post-ET MF compared with ET were as follows: 1) with analysis of 4544 genes, SLR &amp;lt;−1 were 6.58 %, and 10.12 % were &amp;gt;1, 2) in apoptosis genes, over expressed genes were IGF-1R, CFLAR, NFKBA,(GLR between 1-1.5) down-regulated genes were BAX, LGALSI, PPPIR 15A, CASP3 (GLR between -0.5 to -0.1), 3) in cell cycle controlling genes, over expressed were IL8, INSIG1, IGF-1R, BCL3(GLR between 1 to 1.5), down-regulated were PPPIR15A (GLR = -0.7). 4) in megakaryocyte-important development genes, growth factor genes including PDGF A, C were up-regulated (GLR=1.8), and VEG B was down-regulated (GLR = -1. 4):; growth factor receptor genes including IL1R 1and 2, CXCR4, IL8, PF4 were up-regulated (GLR between 1-2), IL3RA, KIT were down-regulated (GLR between -1.6 to -3); cell cycle regulator genes including CCND1, 3, RASGRP3 were up-regulated (GLR between 1 to 2.5), CDK4 was down-regulated (GLR = -1); transcription regulators including CEBPE, CEBPG were up-regulated (GLR-1.5); all Signal transducers including all STAT 1-5, MAK14 were up-regulated (GLR between 1.5 to 2.4). There are 20 up-regulated genes and 20 down-regulated genes which need further analysis for their function. These preliminary analyses of MK genes comparison between Post ET-MF and ET suggest that many anti-apoptosis, cell cycle regulator genes, growth factor genes, growth factor receptor genes and all of the signal transducer genes for the MK development genes were up-regulated while many of the pro-apoptosis genes were down-regulated. Further work to dissect the genes using the microarray analysis for the mechanism for the transformation of ET into ET-MF will be important for understanding this disease. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5010. doi:10.1158/1538-7445.AM2011-5010

A systems-biology analysis of isogenic megakaryocytic and granulocytic cultures identifies new molecular components of megakaryocytic apoptosis

BackgroundThe differentiation of hematopoietic stem cells into platelet-forming megakaryocytes is of fundamental importance to hemostasis. Constitutive apoptosis is an integral, yet poorly understood, facet of megakaryocytic (Mk) differentiation. Understanding Mk apoptosis could lead to advances in the treatment of Mk and platelet disorders.ResultsWe used a Gene-ontology-driven microarray-based transcriptional analysis coupled with protein-level and activity assays to identify genes and pathways involved in Mk apoptosis. Peripheral blood CD34+ hematopoietic progenitor cells were induced to either Mk differentiation or, as a negative control without observable apoptosis, granulocytic differentiation. Temporal gene-expression data were analyzed by a combination of intra- and inter-culture comparisons in order to identify Mk-associated genes. This novel approach was first applied to a curated set of general Mk-related genes in order to assess their dynamic transcriptional regulation. When applied to all apoptosis associated genes, it revealed a decrease in NF-κB signaling, which was explored using phosphorylation assays for IκBα and p65 (RELA). Up-regulation was noted among several pro-apoptotic genes not previously associated with Mk apoptosis such as components of the p53 regulon and TNF signaling. Protein-level analyses probed the involvement of the p53-regulated GADD45A, and the apoptosis signal-regulating kinase 1 (ASK1). Down-regulation of anti-apoptotic genes, including several of the Bcl-2 family, was also detected.ConclusionOur comparative approach to analyzing dynamic large-scale transcriptional data, which was validated using a known set of Mk genes, robustly identified candidate Mk apoptosis genes. This led to novel insights into the molecular mechanisms regulating apoptosis in Mk cells.

Comparative, genome-scale transcriptional analysis of CHRF-288-11 and primary human megakaryocytic cell cultures provides novel insights into lineage-specific differentiation

Little is known about the transcriptional events underlying megakaryocytic (Mk) differentiation. We sought to identify genes and pathways previously unassociated with megakaryopoiesis and to evaluate the CHRF-288-11 (CHRF) megakaryoblastic cell line as a model system for investigating megakaryopoiesis. Using DNA microarrays, Q-RT-PCR, and protein-level assays, we compared the dynamic gene expression pattern of phorbol ester-induced differentiation of CHRF cells to cytokine-induced Mk differentiation of human mobilized peripheral blood CD34(+) cells. Transcriptional patterns of well-known Mk genes were similar between the two systems. CHRF cells constitutively express some early Mk genes including GATA-1. Expression patterns of apoptosis-related genes suggested that increased p53 activity is involved in Mk apoptosis, and this was confirmed by p53-DNA-binding activity data and flow-cytometric analysis of the p53 target gene BBC3. Certain Rho and G-protein-coupled-receptor signaling pathway components were upregulated, including genes not previously associated with Mk cells. Ontological analysis revealed upregulation of defense-response genes, including both known and candidate platelet-derived contributors to inflammation. Upregulation of interferon-responsive genes occurred in the cell line, but not in the primary cells, likely due to a known genetic mutation in the JAK2/STAT5 signaling pathway. This analysis of megakaryopoiesis, which integrates dynamic gene expression data with protein abundance and activity assays, has identified a number of genes and pathways that may help govern megakaryopoiesis. Furthermore, the transcriptional data support the hypothesis that CHRF cells resemble an early Mk phenotype and, with certain limitations, exhibit genuine transcriptional features of Mk differentiation upon treatment with phorbol esters.

Expression analysis of primary mouse megakaryocyte differentiation and its application in identifying stage-specific molecular markers and a novel transcriptional target of NF-E2

AbstractMegakaryocyte (MK) differentiation is well described in morphologic terms but its molecular counterparts and the basis for platelet release are incompletely understood. We profiled mRNA expression in populations of primary mouse MKs representing successive differentiation stages. Genes associated with DNA replication are highly expressed in young MKs, in parallel with endomitosis. Intermediate stages are characterized by disproportionate expression of genes associated with the cytoskeleton, cell migration, and G-protein signaling, whereas terminally mature MKs accumulate hemostatic factors, including many membrane proteins. We used these expression profiles to extract a reliable panel of molecular markers for MKs of early, intermediate, or advanced differentiation and establish the value of this marker panel using mouse models of defective thrombopoiesis resulting from absence of GATA1, NF-E2, or tubulin β1. Computational analysis of the promoters of late-expressed MK genes identified new candidate targets for NF-E2, a critical transcriptional regulator of platelet release. One such gene encodes the kinase adaptor protein LIMS1/PINCH1, which is highly expressed in MKs and platelets and significantly reduced in NF-E2–deficient cells. Transactivation studies and chromatin immunoprecipitation implicate Lims1 as a direct target of NF-E2 regulation. Attribution of stage-specific genes, in combination with various applications, thus constitutes a powerful way to study MK differentiation and platelet biogenesis.

MicroRNAs 155, -221 and -222 Control Megakaryopoiesis at Progenitor and Precursor Level through Ets-1 Multitargeting.

It is generally accepted that microRNAs (miRs) control basic biological functions, such as cell proliferation and differentiation. However, only few targets of the ~ 300 known mammalian miRs have been validated so far, thus hampering delineation of miR-based control circuitries. Particularly, little is known on miR function in mammalian hematopoiesis. We have investigated by microarray and Northern blot evalutation miR expression profiles in human megakarypoiesis, as evaluated in cord blood hematopoietic progenitor cell (HPC) unilineage culture through the megakaryopoietic (MK) differentiation-maturation pathway. These studies indicated that miR-155, -221 and -222 are abundant in HPCs, but sharply decline during megakaryopoiesis. The decline may favour megakaryopoiesis by unblocking translation of key functional target protein(s). Bioinformatic analysis predicted that miR-155, -221 and -222 target Ets-1, a transcription factor up-regulated in Mk differentiation, which transactivates relevant Mk genes (e.g., TPO receptor, PF4, CD42 and von Willebrand factor). Consistently, in megakaryocytic cells the increase of Ets-1 protein expression coincides with the miR-155, -221 and -222 decrease. To find out whether Ets-1 mRNA is a possible target of miR-155, -221 and -222, we cloned segments of the 3′UTR of the Ets-1 gene downstream of a firefly luciferase ORF. Luciferase assay confirmed a direct interaction between each of these miRs and the 3′UTR of Ets-1. Functional studies showed that enhanced expression of these three miRs impairs proliferation, differentiation and maturation of MK cells, at least in part via enhanced degradation of Ets1 mRNA and down-modulation of Ets-1 protein. Similar results were obtained by RNA interference against Ets-1. Finally, HPCs transfected with miR-155, -221, and -222 showed a significant reduction of their Mk clonogenic capacity, suggesting that down-modulation of these miRs favours MK progenitor recruitment and commitment. Altogether, these studies indicate that a novel regulatory circuitry, based on miR-155, -221, -222 multitargeting Ets-1 mRNA leading in turn to transactivation of Mk-specific genes, plays a key role in the control of megakaryopoiesis at both progenitor and precursor level.

Association of genetic polymorphisms of MK, IL-4, p16, p21, p53 genes and human gastric cancer in Taiwan

Aims To assess gastric cancer risk and clinical–pathological factors associated with genetic polymorphisms of MK, IL-4, p16, p21 and p53 genes. Methods A retrospective study was conducted for 123 patients who had recently developed primary gastric cancer. Clinical data and pathological findings were collected, genetic polymorphisms of MK, IL-4, p16, p21 and p53 genes were analysed, and the associations of genetic polymorphisms with gastric cancer carcinogenesis were evaluated. Results There was significant association of genetic polymorphisms between gastric cancer and control groups in p53 genes. After further stratification of the cancer group into different clinical–pathologic parameters, there were significant associations in the sex and LN involvement groups in MK gene; alcohol consumption group in p16 gene; age and cell differentiation groups in p21 gene; age and tumour location groups in p53 gene; but we fail to find any significant association with IL-4 gene polymorphisms. Conclusions Genetic susceptibility testing is a tool to evaluate the association of genetic polymorphisms with gastric cancer carcinogenesis.

Midkine regulates pleiotrophin organ-specific gene expression: Evidence for transcriptional regulation and functional redundancy within the pleiotrophin/midkine developmental gene family

Midkine (MK) and the highly related cytokine pleiotrophin (PTN) constitute the PTN/MK developmental gene family. The Mk and Ptn genes are essential for normal development of the catecholamine and renin–angiotensin pathways and the synthesis of different collagens. It is not known whether the Ptn and Mk genes regulate each other or whether PTN and MK are functionally redundant in development. We have now compared the levels of expression of Ptn and Mk in genetically deficient Mk −/− and Ptn −/− mice and found highly significant increases in Ptn gene expression in spinal cord, dorsal root ganglia, eye, heart, aorta, bladder, and urethra, but not in brain, bone marrow, testis, and lung of Mk −/− mice compared with wild type mice; a remarkable ∼230-fold increase in Ptn expression levels was found in heart of Mk −/− mice and highly significant but lesser increases were found in six other organs. Differences in levels of Mk gene expression in Ptn −/− mice could not be detected in any of the organs tested. The data demonstrate that MK regulates Ptn gene expression with a high degree of organ specificity, suggesting that Ptn gene expression follows Mk gene expression in development, that the increase in Ptn gene expression is compensatory for the absence of MK in Mk −/− mice, that PTN and MK share a high degree of functional redundancy, and that MK may be very important in the development of heart in mouse.

GATA-1Low mice respond more readily than their normal littermates to in vivo perturbations of erythropoiesis

The observation that megakaryocytes (Mk) are consistently detected in secondary cultures of individual day 5 BFU-E-derived colonies stimulated with thrombopoietin (TPO) (22±9 Mk cells/single colony), indicates that hemopoietic cells remain bipotent for the erythroid (E) and Mk pathway after the BFU-E stage. In fact, a cell precursor expressing on the cell surface both E (Ter-119) and Mk (4A5 and 2D5) antigens was identified in the marrow of normal mice and in the marrow and spleen of mice recovering from phenylhydrazine (PHZ)-induced anemia (Vannuchi et al., Blood, in press). Ter-119+/4A5+ cells are candidate as the last bipotent (E/Mk) cells because they express some E (α-globin) and Mk (GpIIb) genes by RT-PCR and progress into fully differentiated E and Mk cells when cultured in the presence of either EPO or TPO, respectively. To further understand the biology of Ter-119+/4A5+ cells, their number was measured in mice genetically unable to up-regulate Gata-1 expression (McDevitt et al., PNAS, 1997, 94: 6781). The Gata-1low mice are profoundly thrombocytopenic but have a normal hematocrit (Hct). The spleens of these mice are 2.5-fold bigger than normal and contain many megakaryocytes and erythroid cells at different maturation stages. Also the number of Ter119+/4A5+ cells in these spleens is ≈5-fold higher than in wild-type animals. Gata1low mice recovered faster than their normal littermate from PHZ-induced anemia (Hct of 48% at day 5 instead than at day 7 from the induction of anemia). They also responded more readily to treatment with EPO (10 U/mouse): their hematocrit increased more than the hematocrit of their normal littermate in response to EPO (68% vs 55%). In both cases, the number of Ter119+/4A5+ cells in the spleen increased more than the increase observed in normal mice treated in the same fashion (>7 times vs 3–5 times). These results confirm that the block in differentiation of the Gata-1low mice is late and downstream of the bipotent cell and support the concept of Ter119+/4A5+ cells as the last bipotent cell precursor.

A rodent model for Wilms tumors: embryonal kidney neoplasms induced by N-nitroso-N'-methylurea.

Embryonal kidney cell tumors develop in rats given the alkylating agent N-nitroso-N'-methylurea as neonates. These tumors resemble the childhood Wilms tumors in their histopathology. Deletions and mutations in the Wilms tumor suppressor gene, WT1, are present in up to 6% of childhood nephroblastomas. To investigate the role of WT1 in rat kidney tumorigenesis, we studied the genetic alterations in WT1 and its target genes. Point mutations were found in WT1 cDNA in 7 of 18 kidney tumors. Mesenchymal tumors contained G-->A transition mutations in codons 128, 364, and 372, typical of the methylating action of N-nitroso-N'-methylurea on DNA. Each of the four nephroblastomas contained the same T-->A mutation at codon 111 of WT1, reflective of transversion mutagenesis by N-nitroso-N'-methylurea in vivo. Like Wilms tumors, mRNA levels of WT1, IGF2, Pax-2, and MK genes were higher than newborn kidney in the majority of the tumors. The histopathology of the rat kidney tumors and the genetic alterations are reminiscent of those observed in Wilms tumors, establishing this as a relevant model system for the human disease.

Cloning and sequence of the Xenopus laevis homologue of the midkine cDNA

The Xenopus laevis (XI) homologue of the midkine-encoding gene ( MK) has been isolated and sequenced from a X. laevis cDNA library made from the head region of stage-22 embryo. The nucleotide and deduced amino-acid sequences show a high degree of conservation with the avian and mammalian MK and pleiotrophin ( PTN) genes and gene products. Highly conserved domains may indicate important regions for the function of the MK and PTN proteins.

Changes in Hox1.6, c-jun, and Oct-3 Gene Expressions Are Associated with Teratocarcinoma F9 Cell Differentiation in Three Different Ways of Induction

To obtain information on the mechanism of teratocarcinoma cell differentiation, the expression of genes having a specific role in gene regulation was examined using three different methods of inducing differentiation: drug treatments with retinoic acid (RA) and sodium butyrate, and a genetic approach using ts mutants. The RAR-β and MK genes were induced specifically by RA treatment, which indicates that these two genes are solely RA responsive. By contrast, a change in c-jun, Hox1.6, and Oct-3 gene expression was observed in all three methods of F9 cell differentiation. These findings suggest that these three genes, whether down-or up-regulated, play an important and key role during teratocarcinoma cell differentiation.

Pleiotrophin gene expression is highly restricted and is regulated by platelet-derived growth factor

Pleiotrophin (PTN) is a growth and neurite extension promoting polypeptide which is highly expressed in brain and in tissues derived from mesenchyme. The PTN gene is developmentally regulated and is closely related to the MK and RI-HB genes, both of which are developmentally regulated and induced by retinoic acid. We now have screened 17 cell lines and report that expression of the PTN gene in these cells is restricted to embryo fibroblasts and intestinal smooth muscle cells. However, NIH 3T3 cells stimulated by the platelet-derived growth factor (PDGF) express a marked increase in levels of PTN mRNA whereas retinoic acid failed to increase levels of PTN mRNA in NIH 3T3 cells or in F9 embryonal carcinoma cells within 72 hours of exposure. The results suggest that expression of the PTN gene is highly restricted and that the PTN gene is a new member of the PDGF-induced cytokine family.