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Keywords:

  • Hematopoietic stem cell;
  • Self-renewal;
  • HoxB4

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

The upregulation of HoxB4 promotes self-renewal of hematopoietic stem cells (HSCs) without overriding the normal stem cell pool size. A similar enhancement of HSC self-renewal occurs when signal transducer and activator of transcription 3 (STAT3) is activated in HSCs. In this study, to gain insight into the functional organization of individual transcription factors (TFs) that have similar effects on HSCs, we investigated the molecular interplay between HoxB4 and STAT3 in the regulation of HSC self-renewal. We found that while STAT3-C or HoxB4 similarly enhanced the in vitro self-renewal and in vivo repopulating activities of HSCs, simultaneous transduction of both TFs did not have additive effects, indicating their functional redundancy in HSCs. In addition, activation of STAT3 did not cause changes in the expression levels of HoxB4. In contrast, the inhibition of STAT3 activity in HoxB4-overexpressing hematopoietic cells significantly abrogated the enhancing effects of HoxB4, and the upregulation of HoxB4 caused a ligand-independent Tyr-phosphorylation of STAT3. Microarray analysis revealed a significant overlap of the transcriptomes regulated by STAT3 and HoxB4 in undifferentiated hematopoietic cells. Moreover, a gene set enrichment analysis showed significant overlap in the candidate TFs that can recapitulate the transcriptional changes induced by HoxB4 or STAT3. Interestingly, among these common TFs were the pluripotency-related genes Oct-4 and Nanog. These results indicate that tissue-specific TFs regulating HSC self-renewal are functionally organized to play an equivalent role in transcription and provide insights into the functional convergence of multiple entries of TFs toward a conserved transcription program for the stem cell state. Stem Cells 2014;32:1313–1322


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

Hematopoietic stem cells (HSCs) constitute a rare subpopulation in hematopoietic tissues and are uniquely defined by their ability to execute self-renewing division with maintenance of their undifferentiated status. The self-renewal of HSCs underlies their ability to produce new blood cells throughout the life of the individual and regenerate the entire hematopoietic system in vivo after transplantation into myeloablated recipients; the self-renewing potential of HSCs is the key parameter of the stem cell state through which heterogeneous hematopoietic cells are hierarchically organized [1, 2]. Thus, the self-renewal of HSCs determines their regenerative activity after transplantation and their ex vivo expansion for the maintenance of their stem cell activity. With such highlighted interest in the self-renewal of HSCs, studies have focused on the intrinsic and extrinsic regulatory mechanisms that maintain the undifferentiated status and execute the self-renewing divisions of HSCs [3, 4]. Studies have shown that, in addition to the intrinsic clonal heterogeneities [5], the cell fate decisions of HSCs are influenced by complex multidimensional mechanisms, including microenvironmental and epigenetic regulatory mechanisms [6, 7], and that these regulatory signals are conveyed into key transcription factors (TFs), causing specific changes in the transcription profiles of the cells.

Thus far, various genetic studies have identified multiple families of key TFs that can similarly regulate the self-renewal of HSCs during the in vivo reconstitution of bone marrow or in vitro expansion culture [3, 4, 8]. While the significance of such multiple entries of TFs in regulating HSC self-renewal remains unclear, recent studies on global transcriptional networks in hematopoietic cells showed that the cis-elements of TFs are densely interconnected and modules of highly coexpressed genes were identified in the undifferentiated state of hematopoietic cells [9], suggesting that a complex interplay of TFs could play a role in maintaining the undifferentiated state. Moreover, global transcriptome analysis of the HSCs along with further down-stream committed cell populations revealed clusters of multiple gene sets that are highly conserved in the undifferentiated cell populations [10], suggesting that the coordinated transcription profile and molecular interplay of multiple TFs play a role in cell fate decisions in HSCs and their lineage specifications. Thus, unveiling the molecular interplay of TFs in the transcriptional architectures of HSCs and the specific transcription programs established by coordination of multiple TFs is a challenging issue in the new understanding on the regulatory mechanism of the self-renewal and maintenance of the stem cell state of HSCs.

In this study, to pursue such possibility, we investigated the potential interplay of two known stem cell-related TFs, HoxB4 and signal transducer and activator of transcription 3 (STAT3); the two TFs that belong to different families but play a similar role in HSC self-renewal. STAT3 is an intermediate signaling molecule involved in ligand-induced signals from gp130, the granulocyte colony-stimulating factor (G-CSF) receptor, and various endogenous non-receptor kinases, such as Src [11, 12]. We previously showed that STAT3 is a key TF for the self-renewal of murine HSCs during hematopoietic regeneration [13, 14]; that is, the transduction of HSCs with the constitutively activated form of STAT3 (STAT3-C) [15] led to a profound enhancement of their in vivo self-renewal and repopulating activities, whereas dominant negative inhibition of STAT3 markedly reduced the competitive repopulating activity [14]. In particular, the enhancing effect of STAT3 on HSC self-renewal was regulated in a manner dependent on physiological negative feedback controls without overriding the stem cell pool size [13].

Interestingly, a similar influence on HSC self-renewal was observed with HoxB4, a member of the homeobox gene family with highly conserved homeobox domain for DNA binding. Studies have shown that overexpression of HoxB4 in hematopoietic cells caused enhanced self-renewal and regenerative activity of transplanted HSCs [16], which was also reproduced by transduction of recombinant HoxB4 proteins during ex vivo culture [17]. Studies showed that upregulation of HoxB4 in hematopoietic cells caused a similar enhancement of in vivo repopulating activities of HSCs in a manner dependent on physiological negative feedback control without overriding the stem cell pool size [16, 18, 19].

Based on the functional similarities of the two TFs in their effects on HSC self-renewal, we explored the functional organization of these TFs in HSC self-renewal. We found that the two TFs are functionally integrated, with HoxB4 signals being conveyed to STAT3. We also found a significant overlap in the resulting transcription profiles induced by the two TFs and in the TFs that can induce an analogous transcriptional profile, which included the pluripotent genes Oct-4 and Nanog. These results provide insight into the functional convergence of distantly related TFs toward the maintenance of the stem cell state.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

Animals

Mice originally obtained from the Jackson Laboratories (Bar Harbor, ME, www.jax.org) were housed in microisolator cages and provided sterilized food and acidified water. The recipient mice were 8–12-week-old C57BL/6J-Ly5.2 (B6) mice, and the donors were C57BL/6J-Pep3b-Ly5.1 (Pep3b) mice. The experiments were performed with the approval of the Animal Experiment Board of the Catholic University of Korea.

To establish the STAT3-C expressing transgenic mice, the STAT3-C gene was cloned into the CAG vector (Addgene, Cambridge, MA, www.addgene.org) for expression driven by a cytomegalovirus enhancer and beta-actin promoter. The transgenic mice were generated by standard procedures [20]. Briefly, The expression cassette was linearized and microinjected into the pronuclei of fertilized embryos from BDF1 female and transferred into oviduct of pseudopregnant female ICR mice. Genomic DNA was extracted from offspring tail biopsies. Two transgenic founder mice were identified and were mated with wild-type C57BL/6J mice. The offspring produced as a result of this mating were genotyped through PCR analysis of tail lysates and bone marrow cells.

Retroviral Vectors and Transduction of Bone Marrow Cells

The parental retroviral vector (MSCV-IRES-GFP or MIG), dominant negative form of STAT3 (dnSTAT3), and constitutively activated form of STAT3 (STAT3-C) were described [13]. HoxB4 cDNA was cloned into the MIY (MSCV-IRES-YFP) vector. For gene transfer into hematopoietic cells, 5-fluorouracil (Sigma Chemicals, St. Louis, MO, www.sigmaaldrich.com)-treated bone marrow cells (5-FU BMCs) were prestimulated for 48 hours in a serum-free medium as previously described [14], then cocultured on GPE-86 cells producing retroviral particles in the presence of 15% fetal bovine serum (FBS), 100 ng/ml mSCF (R&D, Minneapolis, MN, www.rndsystems.com), 6 ng/ml mIL-3 (R&D), and 10 ng/ml hIL-6 (R&D) as previously described [18].

In Vivo Repopulation

Transplantation of the sort-purified BMCs into congeneic recipient mice was performed as previously described [6]. The repopulation of the bone marrow by the transduced cells was assessed by measuring the proportion of GFP+/Ly5.1+ or YFP+/Ly5.1+ white blood cells in the serial peripheral blood samples. Lineages of repopulated hematopoietic cells were analyzed by immunostaining; the anti-Mac-1/Gr-1 (BD Pharmingen) antibody was used to identify myeloid cells, and the anti-TB104 or anti-B220 antibodies (BD Pharmingen, San Jose, CA, www.bdbiosciences.com) were used to identify T, and B-lymphoid cells, respectively [14].

In Vitro Expansion Cultures and Colony-Forming Assay

Transduced BMCs were cultured in Dulbecco's modified Eagle's medium with 10% FBS plus 100 ng/ml murine Steel factor, 100 ng/ml human flt3-ligand, and 50 ng/ml human thrombopoietin, or in the presence of 15% FBS and cytokines described above (mSF+mIL-3+hIL-6) for 14 days with half-medium changes. The colony-forming cells (CFC) were measured in semisolid methylcellulose media as previously described [14]. The morphology of the cultured BMCs was analyzed by Wright-Giemsa staining after cytospin.

Q-RT-PCR Analysis

RNAs were extracted from the sorted cells (GFP+Lin−Sca-1+), converted into cDNA using random hexamers and SuperScript II (Invitrogen, Carlsbad, CA, www.invitrogen.com), and linearly amplified with iQ SYBR Green Supermix (BIO-RAD, Hercules, CA, www.bio-rad.com) using primers for HoxB4, 5′GCACGGTAAACCCCAATTA3′ and 5′GGCAACTTGTGGTCTTTTTT3′, and for JunB, 5′CAGTTACTCTCCAGCCTCTG3′ and 5′CACTTGCTCCCTTAGGAGAC3′.

The threshold cycle (Ct) value for each gene was normalized to the Ct value of GAPDH. The relative mRNA expression was calculated using the formula; 2ΔΔCt, where ΔCt = Ctsample − CtGAPDH and ΔΔCt = ΔCtsample − ΔCtreference group.

Microarray Analysis

RNA extracts were linearly amplified and hybridized to an oligonucleotide DNA microarray as described previously [21]. Briefly, double-stranded DNA template was amplified by a modified Eberwine method of the T7 RNA polymerase-based linear amplification protocol using the T7 MEGAscript kit (Ambion, Austin, TX). Labeled cRNA targets were hybridized to oligonucleotide microarrays spotted with the Illumina's MEEBO Mouse Genome set (70 mers), which included 38,467 probes (Illumina, San Diego, CA, www.illumina.com). After scanning with an Axon scanner, the arrays were analyzed using the GenePix Pro 4.1 software (Axon Instruments, Inverurie, Scotland, www.ason.u-net.com). The data collected were submitted to the BioArray Software Environment database at the Microarray Core Facility of The Catholic University of Korea (http://genomics.catholic.ac.kr/). The scanned images were processed and normalized using the method of Linear Models for Microarray Data and the R-package for statistics for microarray analysis. The hierarchical clustering was performed using the Pearson's correlation coefficient as a distance measure with the average linkage option. The TreeView programs were used for the visualization of the data.

For gene set enrichment analysis (GSEA) (PMID: 16199517), a curated ChEA (chromatin-immunoprecipitation [ChIP] enrichment analysis) database, the experimentally validated list of TF targets from a web-based public resource of the ChIP-chip and ChIP-seq database (PMID: 20709693), was used with GSEA to identify TFs whose targets are coordinately upregulated in the HoxB4- and STAT3-activated expression profiles. In GSEA, each of the genes was calculated for the extent of differential expression between HoxB4- or STAT3-activated and control profiles (signal-to-noise ratio or SNR) and then sorted in order of differential expression. The Kolmogorov-Smirnov statistics was used to calculate the significance level of enrichment for a gene set toward the upregulation in HoxB4- or STAT3-activated versus control profiles.

Western Blot Analysis

Cells were lysed in 2× Laemmli buffer, and the lysates were electrophoresed, subjected to immunoblotting using an anti-mouse STAT3 antibody (K-15, Santa Cruz Biotech, Santa Cruz, CA, www.scbt.om) or anti-mouse phospho-STAT3 (Y705) (clone 9E12, Millipore, Billerica, MA, www.millipore.com), and visualized with ECL (Amersham, Buckinghamshire, U.K., www.gelifesciences.com).

Statistical Analysis

The differences between the groups were evaluated using the Student's t test (p < .05). The significance of the overlap between the over- and under-expressed genes in the HoxB4- and STAT3-activated expression profiles was measured using the Fisher's exact test. To calculate the significance level of the gene set enrichments, the Kolmogorov-Smirnov statistics was used, and the significance was determined by 1,000 permutation tests for each gene set.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

To explore the functional relationship of HoxB4 and STAT3 for HSC self-renewal, we postulated two possible relationships, one in which each factor plays its own independent role in the promotion of HSC self-renewal and one in which the two TFs are functionally integrated with common biological effects on HSC self-renewal (Fig. 1A).

image

Figure 1. Cotransduction of HoxB4 and STAT3-C does not exert additive effects to promote hematopoietic stem cell (HSC) self-renewal. (A): Hypothetical models for the functional integration of HoxB4 and STAT3 with either independent target gene activation (left) or integration of two factors for the activation of overlapping target genes (right). (B): Schematic illustration of retroviral vectors used for the study. (C): Experimental scheme to test model for independent function of HoxB4 and STAT3. (D): Representative flow cytometry profile of single- (GFP+ or YFP+) or double-transduced (GFP+/YFP+) cells. (E, F): Effects of simultaneous transduction of HoxB4 and STAT3-C on the in vivo repopulating activity of HSCs. 5-FU BMCs transduced with each indicated viral vector were sort-purified, and each of the 5 × 103 transduced cells was transplanted into lethally irradiated recipient mice, and their percentage of engraftment levels of donor-derived cells in peripheral blood (Ly5.1+, GFP+, and/or YFP+) (E) and the lineage distribution of engrafted cells (at 16 weeks after transplantation) (F) were analyzed at each indicated time point after transplantation. The means ± SEM (two experiments, n = 7–8 for each group) are shown. (G–J): Effects of HoxB4 and STAT3-C transduction on the ex vivo expansion culture of BMCs. 5-FU BMCs transduced by each vector were sort-purified and subjected to 14 days of ex vivo culture in the presence of 15% FBS, SCF, IL-3, and IL-6 as described in Materials and Methods and then analyzed for the expansion of undifferentiated cells. (G): Morphology was examined by Wright-Giemsa stain after cytospin to identify the undifferentiated (round nucleus) and differentiated (polymorphic nucleus). (H): Expansions of undifferentiated cells were measured by fold changes of undifferentiated (Lin−Sca-1+) cells compared with the input numbers inoculated into in vitro culture (three experiments). (I): CFC numbers generated from 100 input cells after 14 days of culture are indicated, and the numbers of secondary colonies that were generated from each single primary CFC are indicated (J). The means ± SEM (two experiments, n = 3) are shown. Abbreviations: 5-FU, 5-fluorouracil; BMC, bone marrow cell; CFC, colony-forming cell; GFP, green fluorescent protein; IRES, internal ribosomal entry site; STAT3, signal transducer and activator of transcription 3; YFP, yellow fluorescent protein.

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We first investigated the possibility that two TFs play independent roles in regulating HSC self-renewal. We reasoned that, in this case, the simultaneous upregulation of both the HoxB4 and STAT3 activity in HSCs should exert a cumulative effect on the promotion of HSC self-renewal determined by comparing the effects to those caused by the upregulation of each TF alone.

For this study, we infected 5-FU-treated bone marrow cells with a retrovirus expressing HoxB4 and yellow fluorescent protein (HoxB4/YFP) and with a retrovirus expressing the constitutively activated form of STAT3 (STAT3-C) [15] and green fluorescent protein (STAT3-C/GFP) (Fig. 1B). Cells that were transduced with both (GFP+/YFP+) or transduced with a single TF (GFP+/YFP− or YFP+/GFP−) were then sort purified (Fig. 1C, 1D). We first transplanted each population of purified BMCs into lethally irradiated recipient mice to compare their in vivo repopulating activities to those transduced with two control vectors, MIG (MSCV-IRES-GFP) and MIY (MSCV-IRES-YFP). As shown in Figure 1E, the cells transduced with either HoxB4 or STAT3-C alone exhibited a significantly higher level of engraftment in the recipient mice than the cells with control vector transduction (MIG/MIY) during the observed period, up to 16 weeks post-transplantation. However, the transplantation of the cells transduced with both STAT3-C and HoxB4 resulted in comparable levels of engraftment, with no additive or synergistic effects, similar to those transduced with either HoxB4 or STAT3-C alone. The lack of additive effects by cotransduction of both TFs compared to single transduction was also observed in the mice transplanted with higher dose of transduced cells (Supporting Information Fig. S1A); the only difference observed in the cells transduced with both expression vectors was a moderate skewing of donor-derived cells toward myeloid lineages compared with the control or single-transduced groups (Fig. 1F).

We next examined the effects of coexpressing two TFs on the ex vivo expansion of 5-FU BMCs; each group of purified cells was cultured for 14 days, and their self-renewing expansion levels were compared. As shown, the cells transduced with STAT3-C or HoxB4 exhibited a higher proliferation and maintenance of the undifferentiated state, as defined by the morphology and expansion of cells with the primitive phenotype (Lin−Sca-1+); however, no additional enhancement was observed for the cells double-transduced with both TFs (Fig. 1G, 1H, and Supporting Information Fig. S1B). Similarly, the cells transduced with either STAT3-C or HoxB4 alone exhibited a significant increase in the number of CFCs or the amount of secondary colony formation compared with those transduced with control vectors (MIG/MIY); however, again, no additive enhancing effects were observed for the cells transduced with both TFs compared with the cells transduced with either TF alone (Fig. 1I, 1J, and Supporting Information Fig. S2 for subtypes of CFCs). Together, these results showed that the coexpression of both HoxB4 and STAT3-C does not have any additive effects on the self-renewal or repopulating activities of HSCs, suggesting that the HoxB4 and STAT3 signals are functionally redundant for HSC self-renewal rather than exerting independent effects.

Therefore, we next decided to explore the possibility that the signals of STAT3 and HoxB4 are integrated in HSCs for functional organization. We first explored the possibility that the two TFs are functionally integrated in a manner that the STAT3 signal mediates the upregulation of HoxB4 (Fig. 2A). To see whether STAT3 activation regulates HoxB4 expression, we first constructed a transgenic mouse model in which STAT3-C was constitutively expressed under the driving force of CAG promoters, and the bone marrow cells of those mice were examined for their HoxB4 expression levels (Fig. 2B). As shown in Figure 2C, the BMCs of the STAT3-C-transgenic mice did not exhibit any differences in HoxB4 expression compared with their wild-type littermates. To further examine this finding, we transduced 5-FU BMCs with STAT3-C or MIG, and the undifferentiated fraction of the transduced cells (GFP+Lin−Sca-1+) were sort purified for the analysis of their HoxB4 expression (Fig. 2D). As shown in Figure 2E, while the expression level of JunB, a known down-stream target of STAT3 [22], was significantly increased as expected, no significant increase in the expression level of HoxB4 was observed in the STAT3-C transduced undifferentiated cells compared with the equivalent cell population with control vector transduction. Together, these results showed that STAT3 activity does not influence the transcriptional regulation of HoxB4, and therefore, it is less likely that the STAT3 activation signal is conveyed into the transcriptional regulation of HoxB4 in hematopoietic progenitors.

image

Figure 2. Effects of STAT3 activation on HoxB4 expression levels. (A): Hypothetical models for the functional integration of HoxB4 and STAT3 such that STAT3 signal is conveyed into HoxB4. (B): Schematic illustration of transgenic mice constitutively expressing STAT3-C. (C): Effects of STAT3 activation on HoxB4 expression levels. Transgenic mice expressing STAT3-C were established, and the lineage (−) population of their BMCs were analyzed for HoxB4 transcript levels, along with expression of the transgene (STAT3-C). The representative RT-PCR profile is shown. (D): In vitro study model for the effects of STAT3-C on HoxB4 expression. MIG- or STAT3-C-transduced cells were sorted for Lin−Sca-1+ cells and subjected to quantitative RT-PCR analysis. (E): Representative RQ-PCR plots and their quantitative measurements of the transcript levels relative to β-actin. The means ± SEM for expression folds of each transcript in STAT3-C-transduced cells relative to the levels in control (MIG) group (two experiments, n = 6) are shown. Abbreviations: GFP, green fluorescent protein; STAT3, signal transducer and activator of transcription 3.

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Therefore, we next explored the possibility that the HoxB4 signal is conveyed into the activation of STAT3 signals and that, in such case, the self-renewal-enhancing effects of HoxB4 are dependent on STAT3 activity in HSCs (Fig. 3A). To investigate the possibility, we examined the effects of the coexpression of dominant negative STAT3 (dnSTAT3), which was shown to inhibit STAT3 and repopulating activities of HSCs (Supporting Information Fig. S3) together with HoxB4 in HSCs. Thus, 5-FU BMCs double-transduced with HoxB4 and the dominant negative form of STAT3 (dnSTAT3) [14] (GFP+/YFP+) were again sort-purified and transplanted into irradiated recipient mice to examine their effects on the in vivo repopulating activity. As shown in Figure 3B, 3C, the enhancing effects of HoxB4 on the bone marrow repopulation by 5-FU BMCs were nearly lost without the associated changes in the lineage distribution of the donor-derived cells when the BMCs were transduced together with dnSTAT3, indicating that the enhancing effects of HoxB4 on HSC repopulation are dependent on intact STAT3 activity.

image

Figure 3. The HoxB4 effects on hematopoietic stem cell (HSC) are conveyed into STAT3 signals. (A): Hypothetical models and experimental designs for the functional integration of HoxB4 and STAT3 in which the HoxB4 signal is conveyed into STAT3 signal. (B, C): Effects of simultaneous transduction of HoxB4 and dnSTAT3 on the in vivo repopulating activity of HSCs. 5-FU BMCs transduced with each indicated viral vector were sort-purified, and each of the 5 × 104 transduced cells was transplanted into lethally irradiated recipient mice. Their percentage of engraftment levels of donor-derived cells in peripheral blood (Ly5.1+, GFP+, and/or YFP+) (B) and the lineage distribution of engrafted cells (at 16 weeks after transplantation) (C) were analyzed at each indicated time point after transplantation. The means ± SEM from two experiments (n = 7–8 for each group) are shown. *, p < .05. (D–G): Effects of coexpressing HoxB4 and dnSTAT3 on the in vitro expansion culture of BMCs. (D): 5-FU BMCs transduced by each vector were sort-purified and subjected to 14 days of ex vivo culture in the presence of 10% FBS, SCF, FL, and TPO with half-medium changes during the culture period. The cultured cells were analyzed by morphology (Wright-Giemsa stain) for undifferentiated (round nucleus) and differentiated (polymorphic nucleus) cells as well as by cell phenotype (Lin−Sca-1+). (E): The expansions of undifferentiated cells during the culture were measured by fold changes of undifferentiated (Lin−Sca-1+) cells compared with the input numbers inoculated into in vitro culture (three experiments, n = 3). CFC numbers that were generated from 1,000 input cells after 14 days of culture are indicated (F), and numbers of secondary colonies generated from each single primary CFC are indicated (G). The means ± SEM (three experiments) are shown. (H): Effects of HoxB4 overexpression on the Tyr705 phosphorylation of STAT3. Lin(−) BMCs were transduced with control vector, or HoxB4 and Lin(−)YFP(+) cells were resorted. The transduced and purified BMCs were cultured in the serum free media for 24 hours in the absence of cytokines and then stimulated with IL-6 (10 ng/ml) for 30 minutes and subjected to Western blot analysis with antibodies against total form STAT3 or phospho-STAT3 (Y705). In parallel, GPE-86 cells transduced with HoxB4 were similarly isolated, starved, stimulated with IL-6, and then subjected to Western blot analysis. Abbreviations: 5-FU, 5-fluorouracil; BMC, bone marrow cell; GFP, green fluorescent protein; STAT3, signal transducer and activator of transcription 3.

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Similarly, when we examined this phenomenon after 14 days of in vitro culture, we found that the cells that were double-transduced with HoxB4 and dnSTAT3 (GFP+YFP+) exhibited a profound loss of the undifferentiated hematopoietic cell population (Lin−Sca-1+) compared with the cells transduced with HoxB4 alone (YFP+GFP−), even under the cytokine conditions that maintain the self-renewal of primitive hematopoietic population [13, 23] (Fig. 3D, 3E). Moreover, the cells double-transduced with HoxB4 and dnSTAT3 exhibited lower numbers of primary CFCs and secondary CFCs than the cells transduced with HoxB4 alone after 14 days of ex vivo culture, albeit to a lesser extent than the effects observed for in the in vivo repopulating activity (Fig. 3F, 3G). These results showed that the enhancing effects of HoxB4 on the in vivo repopulating activity of HSCs are dependent on intact STAT3 activity, suggesting that the effects of HoxB4 on the self-renewal of HSCs are conveyed into the STAT3 signal.

To further examine this functional integration between STAT3 and HoxB4, we next investigated whether the upregulation of HoxB4 could induce the upregulation of STAT3 activity. As shown in Figure 3H, the overexpression of HoxB4 in Lin(−) BMCs resulted in the rapid phosphorylation of the Tyr705 residue of STAT3 independent of IL-6 stimulation. Moreover, the phosphorylation of STAT3 caused by the overexpression of HoxB4 was also observed in nonhematopoietic fibroblasts (GPE-86) that were not responsive to IL-6 stimulation, indicating that HoxB4 activates STAT3 in a ligand-independent manner. Taken together, these results showed that the upregulation of HoxB4 leads to STAT3 activation and that the enhancement of HSC self-renewal by HoxB4 is dependent on the down-stream activation of STAT3 signals, revealing their molecular integration toward HSC self-renewal.

To further explore the significance of the molecular interplay between the STAT3 and HoxB4 signals, we investigated whether this functional convergence can be observed in the genome-wide transcriptional architectures induced by HoxB4 and STAT3 in hematopoietic progenitor cells. For this, we compared the transcriptional changes induced by the two genes by measuring global gene expression levels in the transduced, undifferentiated hematopoietic cells (GFP+ or YFP+, Lin−) using expression microarray (Fig. 4A). When examined by significance analysis of microarray at a cutoff of a 1.5-fold change, 149 and 159 upregulated genes in the HoxB4 and STAT3-C transduced cells, respectively, were identified. In addition, 171 and 87 genes were under-expressed in HoxB4 and STAT3-C transduced cells, respectively, compared to control group (Fig. 4B, 4C) (Supporting Information Tables S1–S6). A significant overlap was observed between the genes differentially upregulated by HoxB4 and STAT3-C (29 genes, p = 3.46 × 10−36; Fisher's exact text), where the p value represents the probability of observing the number of overlapping genes between the two independent gene sets (Supporting Information Table S1). Similarly, a significant overlap was found between the differentially downregulated genes in the HoxB4 and STAT3-C transduced hematopoietic progenitor cells (26 genes, p = 4.88 × 10−37 in Fisher's exact test) (Supporting Information Table S2). The significant overlap between the two gene expression profiles of Lin(−) cells transduced with either HoxB4 or STAT3 suggested a functional convergence of these TFs, generating a similar transcription profiles in undifferentiated hematopoietic cells.

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Figure 4. Parallel analysis of transcriptomes induced by transduction of HoxB-4 or STAT3-C. (A): Schematic illustration of the experiment. 5-Fluorouracil (5-FU)-treated bone marrow cells (BMCs) were transduced with MIG, STAT3-C (GFP), or HoxB4 (YFP). After transduction, Lin(−) populations of transduced cells were resorted for gene expression analysis. Eighteen profiles corresponding to seven HoxB4-, six STAT3-C-, and five MIG-transduced cell profiles were analyzed. To identify differentially expressed genes, significant analysis of microarray in R packages was used, with a cutoff of a 1.5-fold change. (B): The results of differential gene expression changes induced by HoxB4 or STAT3-C compared with the control (MIG) group. Shown are the numbers of gene sets differentially expressed in the HoxB-4 or STAT3-C-transduced cells and numbers of overlapping target genes, where the significance of overlap between two gene sets was calculated using Fisher's exact test. The p-value in Fisher's exact test represents the probability of observing the number of overlapping genes between two independent gene sets. (C): Validation of the gene expression changes by quantitative RT-PCR. Representative genes showing common upregulation or downregulation in the HoxB4 and STAT3-C-transduced cells (listed in Supporting Information Tables S1, S2) were analyzed for expression levels by quantitative RT-PCR. Shown are the fold changes of each gene in HoxB4 or STAT3-transduced Lin(−) cells in comparison to the control (MIG) transduced cells obtained from three experiments. Abbreviations: GFP, green fluorescent protein; STAT3, signal transducer and activator of transcription 3; YFP, yellow fluorescent protein.

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To further extend the analysis by the gene set-level functional coherence, we next performed a GSEA (PMID: 16199517) to identify potential TFs whose target genes are enriched in the genes upregulated after the activation of HoxB4 and STAT3. We curated a list of experimentally validated targets of TFs by ChIP-chip or ChIP-seq from a public database of ChEA (PMID: 20709693). Table 1 lists the TFs that were identified as having targets that are substantially (unadjusted p < .1) enriched toward the differential gene expression patterns induced by the upregulation of HoxB4 or STAT3 activation, thereby recapitulating their transcriptional profiles.

Table 1. Gene set enrichment analysis of the HoxB-4 and STAT3-C-transduced target genes
 NameGene nameSizeESNESNOM p-val
  1. Transcription factors whose targets are enriched toward genes upregulated by HoxB4 and STAT3-C were identified based on the experimentally validated chromatin-immunoprecipitation (ChIP)-chip and ChIP-seq database. Two pluripotent genes common to HoxB4 and STAT3-C groups are shown in bold.

  2. Abbreviations: ES, enrichment score; NES, normalized enrichment score; NOM p-val, nominal p value.

HOXB4POU5F1–18555785POU domain, class 5, transcription factor 14510.32461.53320
CREB1–15753290cAMP responsive element binding protein 14240.30711.44030
NOTCH1–17114293Notch homolog 1, translocation-associated (Drosophila)960.39681.5777.003871
STAT3–1855785Signal transducer and activator of transcription 34750.27971.3298.007455
NANOG-18555785Nanog homeobox4460.28191.3386.009825
TP53–16413492Tumor protein 532380.2951.3266.031616
WT1–19549856Wilms tumor protein1620.31321.3378.035842
ETS2–20176728Protein C-ets-21730.31.2936.05694
PPARG-19300518Peroxisome proliferator-activated receptor gamma2100.2811.2452.072104
STAT3CNANOG-18700969Nanog homeobox2150.26461.2997.037475
PPARG-19300518Peroxisome proliferator-activated receptor gamma2100.24651.2105.067864
POU5F1–16153702POU domain, class 5, transcription factor 14170.22741.1934.07024
NR4A2–19515692Nuclear receptor subfamily 4, group A, member 21740.26341.2533.075926
STAT3–1855785Signal transducer and activator of transcription 34750.21941.1642.077778

Overall, the target genes of nine and five TFs showed a coordinated upregulation in the HoxB4 and STAT3-activated expression profiles, respectively. Notable overlap was observed for four TFs (POU5F1/Oct-4, Nanog, STAT3, and PPARG), again supporting the similarity between the two transcription profiles and their transcriptional architectures. Surprisingly, among these common TFs, two of the genes that are essential for the maintenance of pluripotent stem cells, Oct-4 and Nanog [24, 25], were included, suggesting that the transcription programs commonly induced by HoxB4 or STAT3 mimic the programs induced by pluripotency genes. Taken together, a substantial overlap between the HoxB4 and STAT3-activated groups of differentially expressed genes, as well as among the TFs whose targets are coordinately upregulated (including pluripotent stem cell factors, such as Oct4 and Nanog), suggests that these stemness-related TFs play an equivalent function by generating conserved gene expression profiles, thus representing a functional convergence of the diverse spectrums of stemness-regulating TFs.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

During the decades, large efforts have been made to define the factors that can regulate the stemness and/or self-renewal properties of HSCs, and multiple TFs similarly involved in the self-renewal of HSCs have been identified [3, 4, 8]. While the significance of multiple entries of TFs for regulation of HSC self-renewal remains to be determined, a recent transcriptome study pointed the importance of the molecular interaction by multiple TFs targeting the “super-enhancer” to determine the stem cell state [26]. Moreover, studies to decipher global architecture of transcriptomes in hematopoietic cells indicated modules of highly coexpressed genes with interconnection of cis-elements of TFs in undifferentiated hematopoietic cells [9, 10], providing insight on the importance of molecular interplay and functional integration of multiple TFs to maintain the stem cell state of HSCs. In our study, to gain insight on such molecular integration of TFs in HSCs, we chose the model of HoxB4 and STAT3-mediated regulation of HSCs, since activation of either TF in HSCs caused a similar functional outcome, that is, enhancement of the HSC self-renewal and repopulating activities, but remaining subject to the normal physiological feedback mechanisms.

We first speculated that the two TFs should play each independent role to promote HSCs self-renewal. However, unexpectedly, when both TFs were simultaneously upregulated, no additive effects were observed, precluding the possibility for independent function of the two. Instead, we found that the upregulation of HoxB4 led to increased phosphorylation of STAT3 in the Tyr705 residue and that the enhancing effects of HoxB4 were dependent on intact STAT3 activity, with the enhancing effects of HoxB4 on the in vivo repopulating activity of HSCs being almost totally abrogated by inhibition of STAT3.

Interestingly, unlike in vivo repopulating activity, CFCs were less affected by inhibition of STAT3 in HoxB4 expressing cells. Since it was shown that dnSTAT3 expression exerts more profound effects on the primitive hematopoietic cell population than on the down-stream CFC population [13, 14], it is possible that certain distinction exists in the spectrum of functional target gene activated by STAT3 and HoxB4. Together, while the down-stream of HoxB4 has been sought in the previous studies using models of immortalized cell lines or embryonic stem cell-derived hematopoietic cells [27-29], our findings show that STAT3 plays a key role to mediate the enhancing effects of HoxB4 on the repopulating activity of HSCs serving as a functional integration point of these two TFs in the regulation of the repopulating activity of HSCs.

The significance of the molecular integration of the two TFs remains unclear. However, taking into account that multiple extracellular signals, such as TPO/c-mpl [30] or Wnt/Frz [31], cause the upregulation of HoxB4 and that multiple extracellular signals, such as SCF/c-kit, IL-6/gp-130, or G-CSF, cause the activation of STAT3 signals [11, 12], it is reasonable to speculate that diverse extracellular signals regulating HSC self-renewal converge onto a limited number of TFs, such as HoxB4 and STAT3. In this sense, it is possible that HoxB4 and STAT3 serve as tissue-specific TFs that can convey the diverse signals from distinct microenvironments into a common molecular signature for the stem cell state of HSCs. Of note, such possibility for convergence into common transcription profile was further supported by the significant overlap of the target genes in the parallel comparisons of genes differentially induced by HoxB4 and STAT3. Moreover, the GSEA analysis further supported this possibility by revealing a significant overlap in the TFs that can induce an analogous transcription profile as those induced by HoxB4 or STAT3, indicating that the molecular milieu that can induce the transcription profiles are also shared between the two TFs.

Surprisingly, Oct-4 and Nanog, two TFs known as key molecules for the stemness of pluripotent stem cells [24, 25], were among the common candidate TFs with targets that were enriched in the STAT3 or HoxB4-induced transcription profiles, indicating that the gene expression programs induced by HoxB4 or STAT3 in HSCs recapitulate, if not identical, the expression changes induced by Oct-4 or Nanog induction. This result raises the possibilities that (a) HoxB4 or STAT3 is tissue-specific stem cell-related TF, analogous to the pluripotent genes, and (b) that stemness-related genes are, therefore, functionally equivalent in activating a genetic program that is conserved among various types of stem cells. Consistent to this view, limitations in the in vivo self-renewal have been observed for HSCs that had been derived from either hematopoietic-committed pluripotent stem cells or from the direct conversion of somatic cells [32-35].

Of note, our observations provide an insight into the molecular-level convergence toward the functional stem cell state; different microenvironmental signals converge into a signal involving a limited number of tissue-specific TFs, which in turn induce a conserved transcription profiles shared by pluripotency-related genes (schematically illustrated in Fig. 5). However, further studies are necessary to gain insights into the key molecular signatures for stem cell state as well as their dynamic changes in response to various stimuli regulating maintenance of stemness under the physiological and pathological conditions.

image

Figure 5. Hypothetical model for molecular convergence of self-renewing genes toward conserved transcription profiles for stem cell state. Each variety of physiological conditions triggers diverse entries of extracellular ligands that are converged into limited numbers of tissue-specific TFs (convergence of ligands toward TFs). The signals from tissue-specific TFs are conveyed into even narrower spectrums of TFs through the functional integration of different TFs (convergence at the levels of tissue-specific TFs). The gene expression profiles induced by each TF can recapitulate the transcription profile of pluripotent stem cell factors, leading to conserved gene expression programs common to the stem cell state (convergence into transcription profile). Abbreviations: STAT3, signal transducer and activator of transcription 3; TF, transcription factor.

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Nevertheless, our study shows that the signals from STAT3 and HoxB4 are converged toward a common gene expression program in HSCs that is conserved among distantly related stem cell-related factors. Our results provide insight into the molecular integration of divergence and functional convergence toward a conserved signature of stem cell states.

Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

The Self-renewal of hematopoietic stem cells (HSCs) is regulated by multiple families of transcription factors (TFs) that are functionally integrated to exert common biological outcomes. In this study, using the model of HoxB4 and STAT3, we showed that HoxB4 signal is converged into STAT3 activity and that the two TFs induce conserved patterns of gene expression changes that are also shared by pluripotent genes. These findings provide insight on the molecular convergence of multiple TFs that play equivalent roles for regulation of stem cell self-renewal.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

This research was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (No. 2011-0019352), and a grant by the Korea Health technology R&D Project, Ministry of Health and Welfare, Republic of Korea (A120262). S.-H.H. is currently affiliated with the Beckton Dickinson Korea, Ltd., Seoul, Korea.

Author Contributions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

S.H.H., S.J.Y., T.M.K,. H.S.L., B.B.P., G.Y.L., and J.S.S.: performed research, collected data, and prepared manuscript figures; S.W.N.: performed research, collected data, and interpreted data; Z.Y.R.: performed research and established transgenic mice; I.H.O.: designed research, analyzed and interpreted data, and wrote the manuscript. S.H.H. and S.J.Y. contributed equally to this article.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Acknowledgments
  9. Author Contributions
  10. Disclosure of Potential Conflicts of Interest
  11. References
  12. Supporting Information

Additional Supporting Information may be found in the online version of this article.

FilenameFormatSizeDescription
stem1631-sup-0001-suppfig1.pdf168KSupporting Information Figure 1
stem1631-sup-0002-supptbl1.docx36KSupporting Information Table 1

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