Polycomb repressive complex 1.1 coordinates homeostatic and emergency myelopoiesis
Abstract
Polycomb repressive complex (PRC) 1 regulates stem cell fate by mediating mono-ubiquitination of histone H2A at lysine 119. While canonical PRC1 is critical for hematopoietic stem and progenitor cell (HSPC) maintenance, the role of non-canonical PRC1 in hematopoiesis remains elusive. PRC1.1, a non-canonical PRC1, consists of PCGF1, RING1B, KDM2B, and BCOR. We recently showed that PRC1.1 insufficiency induced by the loss of PCGF1 or BCOR causes myeloid-biased hematopoiesis and promotes transformation of hematopoietic cells in mice. Here we show that PRC1.1 serves as an epigenetic switch that coordinates homeostatic and emergency hematopoiesis. PRC1.1 maintains balanced output of steady-state hematopoiesis by restricting C/EBPα-dependent precocious myeloid differentiation of HSPCs and the HOXA9- and β-catenin-driven self-renewing network in myeloid progenitors. Upon regeneration, PRC1.1 is transiently inhibited to facilitate formation of granulocyte-macrophage progenitor (GMP) clusters, thereby promoting emergency myelopoiesis. Moreover, constitutive inactivation of PRC1.1 results in unchecked expansion of GMPs and eventual transformation. Collectively, our results define PRC1.1 as a novel critical regulator of emergency myelopoiesis, dysregulation of which leads to myeloid transformation.
Editor's evaluation
The authors present a manuscript aiming to understand the mechanism(s) underlying myeloid bias in HSCs, specifically focused on the role of Pcgf1, and therefore PRC1.1, in the regulation of hematopoiesis. The current study demonstrates that conditional deletion of Pcgf1 in HSCs causes a lineage switch from lymphoid to myeloid fates and that a key mechanism for this lineage switch is regulation of the H2AK119ub1 chromatin mark, leading to de-repression of CEBPalpha, a key transcription factor that promotes myeloid cell fate. This important work is of interest to the community of researchers interested in myeloid differentiation, lineage fate decisions in hematopoietic stem cells, and the molecular mechanisms that contribute to the initiation of myeloid malignancies. The methods are rigorous and the results convincingly support the authors' conclusions.
https://doi.org/10.7554/eLife.83004.sa0Introduction
While lifelong hematopoiesis is considered driven by hematopoietic stem cells (HSCs) (Sawai et al., 2016; Säwen et al., 2018), recent evidence pointed out a major role for multipotent progenitors (MPPs) and lineage-committed progenitors in hematopoiesis (Busch et al., 2015; Sun et al., 2014). Hematopoietic stem and progenitor cells (HSPCs) are highly responsive to various stresses such as infection, inflammation, and myeloablation (Trumpp et al., 2010; Zhao and Baltimore, 2015), which facilitate myelopoiesis by activating HSPCs to undergo precocious myeloid differentiation and transiently amplifying myeloid progenitors that rapidly differentiate into mature myeloid cells (Hérault et al., 2017; Pietras et al., 2016). This reprogramming of HSPCs, termed ‘emergency myelopoiesis,’ serves to immediately replenish mature myeloid cells to control infection and regeneration (Manz and Boettcher, 2014). Recent evidence further suggested that uncontrolled activation of the myeloid regeneration programs results in the development of chronic inflammatory diseases and hematological malignancies (Chiba et al., 2018; Zhao and Baltimore, 2015). Emergency myelopoiesis is driven via activation of key myeloid transcriptional networks at the HSPC and myeloid progenitor cell levels (Rosenbauer and Tenen, 2007). However, the epigenetic regulatory mechanisms governing emergency myelopoiesis remained largely unknown.
Polycomb group (PcG) proteins are the key epigenetic regulators of a variety of biological processes (Piunti and Shilatifard, 2021). They comprise the multiprotein complexes, polycomb repressive complex (PRC) 1 and PRC2, which establish and maintain the transcriptional repression through histone modifications. PRC1 and PRC2 add mono-ubiquitination at lysine 119 of histone H2A (H2AK119ub) and mono-, di-, and tri-methylation at lysine 27 of histone H3 (H3K27me1/me2/me3), respectively, and cooperatively repress transcription (Blackledge et al., 2015; Iwama, 2017). PRC1 complexes are divided into subgroups (PRC1.1 to PRC1.6) according to the subtype of the Polycomb group ring finger (PCGF) subunits (PCGF1-6). PCGF2/MEL18 and PCGF4/BMI1 act as components of canonical PRC1 (PRC1.2 and 1.4, respectively) that are recruited to its target sites in a manner dependent on H3K27me3, whereas the others (PCGF1, 3, 5, and 6) constitute non-canonical PRC1 (PRC1.1, PRC1.3, PRC1.5, and PRC1.6, respectively) that are recruited independently of H3K27me3 (Blackledge et al., 2014; Gao et al., 2012; Wang et al., 2004).
PCGF4/BMI1-containing canonical PRC1 (PRC1.4) has been characterized for its role in maintaining self-renewal capacity and multipotency of HSCs (Sashida and Iwama, 2012). We and others have reported that BMI1 transcriptionally represses the loci for CDKN2A and developmental regulator genes (e.g., B cell regulators) to maintain self-renewal capacity and multipotency of HSPCs (Iwama et al., 2004; Oguro et al., 2010; Park et al., 2003). We also reported that PCGF5-containing PRC1.5 regulates global levels of H2AK119ub, but is dispensable for HSPC function (Si et al., 2016). On the other hand, we and others recently showed that PRC1.1 components, PCGF1, KDM2B, and BCOR, maintain normal hematopoiesis and suppress malignant transformation of hematopoietic cells (Andricovich et al., 2016; Isshiki et al., 2019; Tara et al., 2018). PRC1.1 consists of PCGF1, RING1A/B, KDM2B, and BCOR or BCLRL1. KDM2B binds to non-methylated CpG islands through its DNA-binding domain, thereby recruiting other PRC1.1 components (Farcas et al., 2012; He et al., 2013). PCGF1 was found to restrict the proliferative capacity of myeloid progenitor cells by downregulating Hoxa family genes in in vitro knockdown experiments (Ross et al., 2012). Correspondingly, we demonstrated that Pcgf1 loss induces myeloid-biased hematopoiesis and promotes JAK2V617F-induced myelofibrosis in mice (Shinoda et al., 2022). Bcor loss also showed myeloid-biased hematopoiesis and promoted the initiation and progression of myelodysplastic syndrome in collaboration with Tet2 loss (Tara et al., 2018). However, detailed analysis of the role for PRC1.1 in hematopoiesis, especially in the context of hematopoietic regeneration and emergency myelopoiesis, has not yet been reported.
Here, we analyzed the murine hematopoiesis in the absence of PCGF1 and uncovered critical roles of PCGF1-containing PRC1.1 in homeostatic, emergency, and malignant hematopoiesis.
Results
PCGF1 restricts myeloid commitment of HSPCs
To understand the function of PCGF1 in hematopoiesis, we crossed Pcgf1fl mice, in which exons 2–7 are floxed (Figure 1—figure supplement 1A), with Rosa26::Cre-ERT2 (Rosa26CreERT) mice (Rosa26CreERT;Pcgf1fl/fl). To delete Pcgf1 specifically in hematopoietic cells, we transplanted bone marrow (BM) cells from Rosa26CreERT control and Rosa26CreERT;Pcgf1fl/fl CD45.2 mice into lethally irradiated CD45.1 recipient mice and deleted Pcgf1 by intraperitoneal injection of tamoxifen (Figure 1A and Figure 1—figure supplement 1B). We confirmed the efficient deletion of Pcgf1 in donor-derived hematopoietic cells from the peripheral blood (PB) by genomic PCR (Figure 1—figure supplement 1C). RT-qPCR confirmed the significant reduction of Pcgf1 mRNA lacking exons 2–7 in donor-derived BM Lineage marker–Sca-1+c-Kit+ (LSK) HSPCs (Figure 1—figure supplement 1D). We hereafter refer to the recipient mice reconstituted with Rosa26CreERT control and Rosa26CreERT;Pcgf1fl/fl cells treated with tamoxifen as control and Pcgf1Δ/Δ mice, respectively.
Pcgf1Δ/Δ mice exhibited mild anemia and leukopenia, which was mainly attributed to the reduction in B cell numbers (Figure 1B, Figure 1—figure supplement 2A and B). Myeloid cell numbers in PB were relatively maintained and their proportion increased over time in Pcgf1Δ/Δ mice (Figure 1B and Figure 1—figure supplement 2B). While BM cellularity was comparable between control and Pcgf1Δ/Δ mice, Mac1+ mature myeloid cells were increased at the expense of B cells in Pcgf1Δ/Δ BM and spleen (Figure 1C and Figure 1—figure supplement 2C–E). Monocytes but not neutrophils or F4/80+ macrophages significantly increased in Pcgf1Δ/Δ BM while both neutrophils and monocytes significantly increased in Pcgf1Δ/Δ spleen (Figure 1—figure supplement 2C and D). These findings indicate that Pcgf1Δ/Δ HSPCs generate more mature myeloid cells than the control without showing evident differentiation block. Among the committed progenitor cells, the numbers of granulocyte-macrophage progenitors (GMPs) were significantly increased in Pcgf1Δ/Δ BM, whereas those of megakaryocyte-erythroid progenitors (MEPs), pre- and pro-B cells, all-lymphoid progenitors (ALPs) and B-cell-biased lymphoid progenitors (BLPs) were decreased (Figure 1C, Figure 1—figure supplement 2C, and Figure 1—figure supplement 3B). Of interest, Pcgf1Δ/Δ mice showed reduction in the numbers of HSCs and all subsets of MPPs in BM (Figure 1C and Figure 1—figure supplement 3A). The reduction in the HSPC pool size was accompanied by decreased cells in cycling phases in Pcgf1Δ/Δ HSPCs (CD34– and CD34+ LSK cells) (Figure 1D). Despite the reduction in phenotypic HSPCs, limiting dilution assays with competitive BM transplantation revealed that the numbers of HSPCs that established long-term repopulation of myeloid and T cells (B cells were excluded due to the low contribution of Pcgf1Δ/Δ HSPCs to B cells, see below) were comparable between control and Pcgf1Δ/Δ BM (Figure 1E). Extramedullary hematopoiesis was evident in the Pcgf1Δ/Δ spleen, as judged by markedly increased numbers of LSK HSPCs, GMPs, and mature myeloid cells including monocytes and neutrophils (Figure 1—figure supplement 2C, D, and F and Figure 1—figure supplement 3C). Differentiation of thymocytes in the Pcgf1Δ/Δ thymus was largely normal (Figure 1—figure supplement 2C).
To further evaluate the role of PCGF1 in hematopoiesis, we transplanted BM cells with the same number of CD45.1 wild-type (WT) competitor cells (Figure 1F). In this competitive setting, only a mild decrease was detected in the overall chimerism of CD45.2+ Pcgf1Δ/Δ cells in PB (Figure 1G). In contrast, the chimerism of Pcgf1Δ/Δ cells in myeloid cells (Mac-1+ and/or Gr1+) was markedly increased while that in B cell lineage (B220+) was decreased (Figure 1G). In BM, Pcgf1Δ/Δ cells outcompeted the competitor cells in the myeloid lineage compartments from the common myeloid progenitor (CMP) stage (Figure 1H). Since Pcgf1Δ/Δ cell showed reductions in the numbers of HSCs and MPPs in a non-competitive setting (Figure 1C), we examined the absolute numbers of test and competitor cells in this competitive repopulation. Of interest, the competitive Pcgf1Δ/Δ recipients also exhibit similar changes in BM hematopoietic cell numbers. Both CD45.2+ Pcgf1Δ/Δ and CD45.1+ WT cells were depleted in HSPC fractions in Pcgf1Δ/Δ recipients, while the total numbers of myeloid progenitors and mature myeloid cells were maintained or rather increased (Figure 1I). These findings suggest that Pcgf1Δ/Δ hematopoietic cells suppress expansion of both Pcgf1Δ/Δ and co-existing WT HSPCs through non-autonomous mechanisms. It is possible that accumulating Pcgf1Δ/Δ mature myeloid cells produce inflammatory cytokines that are suppressive to HSPCs. The underlying mechanism is an intriguing issue to be analyzed. To evaluate the impact of PCGF1 loss on long-term hematopoiesis, we harvested BM cells from primary recipient mice 4 mo after tamoxifen injection and transplanted them into secondary recipients. Pcgf1Δ/Δ cells reproduced the myeloid-biased hematopoiesis in secondary recipients (Figure 1J).
We next evaluated the capacity of Pcgf1Δ/Δ HSCs to differentiate to myeloid and lymphoid cells in culture. Pcgf1Δ/Δ HSCs displayed slower population doubling under HSPC-expanding culture conditions (Figure 1—figure supplement 4A), which is in good agreement with fewer cycling Pcgf1Δ/Δ HSPCs (Figure 1D). Nevertheless, Pcgf1Δ/Δ HSCs showed better population doubling than control cells under myeloid culture conditions (Figure 1—figure supplement 4A). On the other hand, limiting dilution assays using a co-culture system with TSt-4 stromal cells (Masuda et al., 2005) revealed that the capacity of Pcgf1Δ/Δ HSCs to produce B and T cells was declined by two- and fivefold, respectively, compared to the control (Figure 1—figure supplement 4B). The discrepancy in T cell production between in vitro and in vivo may be due to the compensatory expansion of T cells in the thymus. These results indicate that PCGF1 loss enhances myelopoiesis at the expense of lymphopoiesis. These phenotypes were similar to those of mice expressing a carboxyl-terminal truncated BCOR that cannot interact with PCGF1 (Tara et al., 2018).
PCGF1 inhibits precocious myeloid commitment of HSPCs through repression of C/EBPα, which is critical for balanced output of HSPCs
To clarify the molecular mechanisms underlying myeloid-biased differentiation of Pcgf1Δ/Δ HSPCs, we performed RNA sequence (RNA-seq) analysis of HSPCs from mice 4 wk after the tamoxifen injection. Principal component analysis (PCA) showed shifts of the transcriptomic profiles of Pcgf1Δ/Δ MPP2 and MPP3 toward pre-GMs (Figure 2A). Gene set enrichment analysis (GSEA) revealed upregulation of genes involved in myeloid cell development (Brown et al., 2006), CEBP targets (Gery et al., 2005), and genes upregulated upon C/EBPα overexpression (Loke et al., 2018) in Pcgf1Δ/Δ HSPCs compared to controls (Figure 2B and Supplementary file 1). C/EBP family are master transcription factors for myeloid differentiation (Avellino and Delwel, 2017; Rosenbauer and Tenen, 2007). RT-PCR analysis demonstrated a significant upregulation of Cepba in HSPCs, but not in GMPs (Figure 2C). C/EBPα drives myelopoiesis and antagonizes lymphoid differentiation (Fukuchi et al., 2006; Rosenbauer and Tenen, 2007; Xie et al., 2004). Disruption of Cebpa blocks the transition from CMPs to GMPs (Zhang et al., 1997). So, we evaluated the contribution of de-repressed Cebpa in Pcgf1Δ/Δ HSPCs. First, we overexpressed Cebpa in WT LSK cells and cultured them on TSt-4 stromal cells. Only twofold upregulation of Cebpa was sufficient to enhance myeloid differentiation and suppress B cell differentiation of HSPCs (Figure 2D). Conversely, we next tested whether myeloid skewing of Pcgf1Δ/Δ HSPCs could be canceled by reducing Cebpa expression. We seeded HSPCs from Rosa26CreERT, Rosa26CreERT;Pcgf1fl/fl, and Rosa26CreERT;Pcgf1fl/flCebpafl/+ mice on TSt-4 stromal cells and recombined Pcgf1fl and Cebpafl alleles by supplementation of 4-hydroxytamoxifen (4-OHT) (Figure 2—figure supplement 1A). Of note, the reduction in the levels of Cebpa expression by introducing a Cebpafl/+ allele in Pcgf1Δ/Δ LSK cells was sufficient to restore balanced production of myeloid and B cells by Pcgf1Δ/Δ HSPCs (Figure 2E). These results demonstrate that de-repression of Cebpa largely accounts for at least the myeloid-biased differentiation of Pcgf1Δ/Δ HSPCs.
We next attempted to rescue the myeloid-biased differentiation of Pcgf1Δ/Δ HSPCs by exogenous Pcgf1 or a canonical PRC1 gene Bmi1/Pcgf4. We transduced Rosa26CreERT;Pcgf1fl/fl HSPCs to induce Pcgf1 or Bmi1 expression, transplanted them into lethally irradiated mice, and deleted endogenous Pcgf1 (Figure 2—figure supplement 1B). The myeloid skew in Pcgf1Δ/Δ PB leukocytes was completely prevented by ectopic expression of Pcgf1 but not of Bmi1 (Figure 2—figure supplement 1B), highlighting distinct roles of non-canonical PRC1.1 and canonical PRC1 in hematopoietic differentiation.
We also noticed that the E2F targets (Ishida et al., 2001) were downregulated in Pcgf1Δ/Δ HSPCs (Figure 2B), which may underlie the disturbed cell cycle progression and delayed proliferation observed in Pcgf1Δ/Δ HSPCs (Figure 1D and Figure 1—figure supplement 4A). C/EBPα represses E2F-mediated transcription (D’Alo’ et al., 2003; Slomiany et al., 2000), inhibits HSC cell cycle entry (Ye et al., 2013; Zhang et al., 2004), and promotes precocious IL-1β-driven emergency myelopoiesis (Higa et al., 2021). Thus, upregulated Cebpa upon PCGF1 loss may inhibit cell cycle and promote myeloid commitment of HSPCs.
Deletion of Pcgf1 affects levels of H2AK119ub1
To understand how PCGF1 loss affects H2AK119ub1 status in HSPCs, we performed chromatin immunoprecipitation followed by sequencing (ChIP-seq) analysis using control and Pcgf1Δ/Δ HSPCs. Since none of the anti-PCGF1 antibodies were suitable for ChIP analysis, we used 3×Flag-PCGF1-expressing BM LK cells obtained by retrovirally transducing LSK cells and transplanting them to lethally irradiated mice. We defined ‘PRC1 targets’ and ‘PRC2 targets’ as genes with H2AK119ub1 and H3K27me3 enrichment greater than twofold over the input signals in control LSK cells at promoter regions (transcription start site [TSS] ± 2.0 kb), respectively (Supplementary file 2). GSEA revealed that both PRC1 and PRC2 targets were upregulated in Pcgf1Δ/Δ HSPCs and GMPs (Figure 2B). K-means clustering divided PRC1 targets into two clusters depending on the levels of H2AK119ub1 and H3K27me3. Cluster 1 genes (1835 RefSeq ID genes) were marked with high levels of H2AK119ub1 and H3K27me3 at promoter regions, while cluster 2 genes (2691 RefSeq ID genes) showed moderate levels of H2AK119ub1 and H3K27me3 (Figure 3A). PCGF1 showed stronger binding to the promoters of cluster 2 genes than cluster 1 genes (Figure 3A). Interestingly, only cluster 2 genes showed moderate but significant reductions in H2AK119ub1 and H3K27me3 levels in Pcgf1Δ/Δ HSPCs (Figure 3B). The loss of PCGF1 was also significantly associated with de-repression of PRC1 target genes in clusters 1 and 2 (Figure 3B). These results suggest that cluster 2 genes are the major targets of PCGF1-containing PRC1.1 and Cebpa was included in cluster 2 genes. Bivalent genes, which are enriched for developmental regulator genes marked with both active and repressive histone marks (H3K4me3 and H3K27me3, respectively, mostly with H2AK119ub1), are classical targets of canonical PRC1 and PRC2 (Bernstein et al., 2006; Ku et al., 2008) and are implicated in multipotency of HSPCs (Oguro et al., 2010). Of note, bivalent genes defined by our previous ChIP-seq data of HSPCs (Aoyama et al., 2018; Supplementary file 2) were more enriched in cluster 1 genes than cluster 2 genes (Figure 3C).
We then defined ‘PCGF1 targets’ whose H2AK119ub1 levels were decreased by Pcgf1 deletion greater than twofold at promoter regions in HSPCs (997 RefSeq ID genes; Supplementary file 2). We found that Cebpa and Cebpe were included in PCGF1 targets, showed reductions in H2AK119ub1 levels (Figure 3D and E), and were de-repressed in expression in Pcgf1Δ/Δ LSK cells (Figure 2C and Figure 2—figure supplement 1C). ChIP-qPCR confirmed a significant reduction in H2AK119ub1 levels at the promoter region of Cebpa in Pcgf1Δ/Δ HSPCs (Figure 3F). These results indicate that the deletion of Pcgf1 compromises PRC1.1 function and causes precocious activation of key myeloid regulator genes in HSPCs.
To clarify whether the Pcgf1 deletion has any impact on the chromatin accessibility in HSPCs, we performed an assay for transposase accessible chromatin with high-throughput sequencing (ATAC-seq) analysis using CD135–LSK HSPCs, which include HSCs and MPP1-3 but not lymphoid-primed MPP4. ATAC-seq profiles open chromatin regions enriched for transcriptional regulatory regions, such as promoters and enhancers. ATAC peaks were significantly enriched at the promoter regions of PCGF1 target genes, but not of PCGF1 non-target genes, in Pcgf1Δ/Δ HSPCs compared to the corresponding controls (Figure 3G), further validating de-repression of PCGF1 targets upon the deletion of Pcgf1. Motif analysis of ATAC peaks in the proximal promoter regions (TSS ± 2 kb) revealed that the CTCF motif, which has been reported to be associated with differentiation of HSCs (Buenrostro et al., 2018; Takayama et al., 2021), was highly enriched in Pcgf1Δ/Δ HSPCs (Figure 3H). Interestingly, the other top-ranked motifs were related to stress response transcription factors, such as Bach family (Bach1 and 2), CNC family (Nrf2 and NF-E2), AP1 family, and Atf3 (Figure 3H and Supplementary file 3). In contrast, the binding motifs for transcription factors essential for T and B cell commitment, including HEB and E2A (de Pooter and Kee, 2010), were negatively enriched in Pcgf1Δ/Δ HSPCs (Figure 3H). Together with the significant upregulation of Cebpa and Cebpe in Pcgf1Δ/ΔHSPCs (Figure 2C and Figure 2—figure supplement 1C), these results further support the notion that PRC1.1 deficiency caused precocious activation of myeloid differentiation program at the expense of lymphoid differentiation program in HSPCs.
PCGF1 inhibition facilitates emergency myelopoiesis
Myeloid-biased hematopoiesis in Pcgf1-deficient mice reminded us of the myeloproliferative reactions caused by emergencies such as regeneration (Manz and Boettcher, 2014). Individual GMPs scatter throughout the BM in the steady state, while expanding GMPs evolve into GMP clusters during regeneration, which, in turn, differentiate into granulocytes. Inducible activation of β-catenin and Irf8 controls the formation and differentiation of GMP clusters, respectively (Hérault et al., 2017). Immunofluorescence analyses of BM sections readily detected GMP clusters in steady-state Pcgf1Δ/Δ BM (Figure 4A), which was reminiscent of those observed during regeneration after 5-fluorouracil (5-FU) treatment (Figure 4—figure supplement 1A). To address whether PCGF1 also regulates myelopoiesis at the GMP level during regeneration, we challenged control and Pcgf1Δ/Δ mice with a single dose of 5-FU (Figure 4B). Consistent with the previous report (Hérault et al., 2017), control mice showed transient expansion of BM HSPCs and GMPs around day 14 and subsequent burst of circulating PB myeloid cells around day 21. In sharp contrast, Pcgf1Δ/Δ mice displayed sustained GMP expansion until day 28 without efficient production of PB myeloid cells, leading to the accumulation of excess GMPs (Figure 4C).
GMPs can be divided into steady-state GMPs (ssGMP) and self-renewing GMPs (srGMP), the latter of which transiently increase during regeneration (Hérault et al., 2017). We performed RNA-seq analysis of GMPs isolated from 5-FU-treated WT mice at various time points (Figure 4—figure supplement 1B and C), and defined differentially expressed genes (DEGs) on day 8 after 5-FU treatment since srGMPs reportedly most expand on that day (Figure 4—figure supplement 1B and C, Supplementary file 4; Hérault et al., 2017). Of note, a significant portion of upregulated DEGs in day 8 5-FU-treated GMPs were also upregulated in Pcgf1Δ/Δ GMPs (Figure 4D and Supplementary file 4). These overlapping genes included Hoxa9, a PRC1.1 target (Figure 4—figure supplement 1D; Ross et al., 2012; Shinoda et al., 2022; Tara et al., 2018), which is highly expressed in srGMPs (Hérault et al., 2017). RT-qPCR confirmed significantly higher expression of Hoxa9 in Pcgf1Δ/Δ GMPs than control GMPs (Figure 4E). Correspondingly, 5-FU treatment transiently decreased H2AK119ub1 levels at Hoxa9 locus around day 10 (Figure 4F). ChIP-seq analysis also revealed significant reductions in H2AK119ub1 levels at promoters of upregulated DEGs in day 8 5-FU-treated GMPs in Pcgf1Δ/Δ GMPs (Figure 4G). These results suggest that transient inhibition of PRC1.1 de-represses genes critical to expand srGMP during myeloid regeneration, although the expression of PRC1.1 genes remained largely unchanged during regeneration (Figure 4—figure supplement 1E).
To better understand the role of PRC1.1 in myeloid progenitors, we performed single-cell RNA-seq (scRNA-seq) of Lin–Sca-1–c-Kit+ myeloid progenitors from control and Pcgf1Δ/Δ mice at steady state. We used data from 6171 control and 6198 Pcgf1Δ/Δ single cells and identified 10 major clusters based on dimension reduction by UMAP (Figure 4H). Functional annotation of respective UMAP clusters using previously reported myeloid progenitor cell gene expression profiles (Nestorowa et al., 2016) assigned clusters 0, 2, and 4 to GMPs (Figure 4H). PCA subdivided GMPs into two major groups (Figure 4I). These two groups exhibited distinct expression profiles of Hoxa9, Irf8, Csf1r, and Il6ra, key genes differentially expressed between ssGMPs (Hoxa9lo, Irf8hi, Csf1rhi, Il6rahi) and srGMPs (Hoxa9hi, Irf8lo, Csf1rlo, Il6ralo) (Hérault et al., 2017), and we classified clusters 2 and 4 as ssGMPs and cluster 0 as srGMPs (Figure 4J). Gene Ontology and pathway enrichment analyses using DEGs (cluster 2 or 4 versus cluster 0) revealed that clusters 2 and 4 represented more mature myeloid cell populations than cluster 0 (Figure 4K). As expected, Pcgf1Δ/Δ myeloid progenitors had a greater proportion of total GMPs including srGMPs than controls (Figure 4L). Of note, the frequency of srGMPs was also increased in Pcgf1Δ/Δ myeloid progenitors (Figure 4L). These results indicate that PRC1.1 restricts expansion of self-renewing GMPs and suggest that transient PRC1.1 inhibition allows for temporal amplification of GMPs and their subsequent differentiation to mature myeloid cells.
PCGF1 restricts GMP self-renewal network
To further investigate the mechanism by which PCGF1 regulates GMPs, we took advantage of in vitro culture experiments. Remarkably, Pcgf1Δ/Δ GMPs displayed better proliferation than control GMPs under myeloid-expanding culture conditions (Figure 5A). Moreover, while comparable numbers of cells expressing immunophenotypic GMP markers (CD34+FcγR+c-Kit+Sca-1-Lineage-) (immunophenotypic GMPs) were produced by control and Pcgf1Δ/Δ HSCs on day 7 of culture, control HSCs showed a rapid decline in immunophenotypic GMP production afterward but Pcgf1Δ/Δ HSCs persistently produced immunophenotypic GMPs until day 23 (Figure 5B). Of interest, differentiation of the expanded Pcgf1Δ/Δ GMPs was largely blocked, as indicated by reduced Mac1+ differentiated myeloid cells/GMP ratios until day 19 (Figure 5—figure supplement 1A), suggesting that Pcgf1Δ/Δ GMPs underwent enhanced self-renewal rather than differentiation. However, Pcgf1Δ/Δ GMPs did not lose its differentiation potential to mature myeloid cells and did not show evident differentiation block, with more Mac1+ cells ultimately generated from HSC cultures than control GMPs (Figure 5—figure supplement 1A). This was also consistent that the number of mature myeloid cells expressing myeloid differentiation markers increased in Pcgf1Δ/Δ BM and spleen (Figure 1—figure supplement 2C and D). Furthermore, Pcgf1Δ/Δ HSPCs showed remarkably sustained colony formation activity upon serial replating with myeloid cytokines, which is in line with the elevated self-renewing activity of Pcgf1Δ/Δ GMPs (Figure 5C).
srGMPs have increased levels of nuclear β-catenin, which is known to confer aberrant self-renewal features to leukemic GMPs (Wang et al., 2010) and directly suppresses Irf8 expression (Hérault et al., 2017). The proportion of nuclear β-catenin was significantly increased in Pcgf1Δ/Δ GMPs at later time points of culture when GMPs in control culture shrunk but GMPs in Pcgf1Δ/Δ culture kept expanding (Figure 5B and D). Pcgf1Δ/Δ GMPs in culture possessed a transcriptional profile typical to srGMPs; upregulation of Hoxa9 and downregulation of Irf8, Csf1r, and Il6ra (Figure 5E). GSEA revealed activation of the Wnt/β-catenin pathway (Shooshtarizadeh et al., 2019) and downregulation of the Irf8 targets (Kubosaki et al., 2010) in Pcgf1Δ/Δ GMPs (Figure 5F). We hypothesized that Hoxa9, a direct target of PCGF1, could have a role in the GMP self-renewal network. Overexpression of Hoxa9 in HSPCs significantly enhanced their growth and induced persistent production of GMPs for a long period (Figure 5G and Figure 5—figure supplement 1B). Most Hoxa9-overexpressing GMPs had nuclear β-catenin (Figure 5H). These results indicate that HoxaA9 can reinforce activation of β-catenin, thus placing Hoxa9 as a component of the GMP self-renewal network and PCGF1-PRC1.1 as a negative regulator of this network (Figure 5I). The promoter region of the Ctnnb1 gene contains at least one predicted sequence for Hoxa9 binding (CTTATAAATCG) (data not shown). We performed qPCR analysis using Hoxa9 overexpression samples at day 12 of culture, in which nuclear localization of β-catenin was observed (Figure 5H). Ctnnb1 gene expression was slightly but significantly upregulated in Hoxa9 overexpression samples compared to mock control (Figure 5—figure supplement 1C). These results raise the possibility that Hoxa9 is a direct transcriptional activator of the Ctnnb1 gene, but this warrants further analysis.
Constitutive PCGF1 loss promotes malignant transformation
In leukemia, GMP clusters are constantly produced owing to persistent activation of the myeloid self-renewal network and a lack of termination cytokines that normally restore HSC quiescence (Hérault et al., 2017). A significant portion of Pcgf1Δ/Δ mice, which exhibit constant production of GMP clusters, developed lethal myeloproliferative neoplasms (MPN) with severe anemia and massive accumulation of mature myeloid cells in PB, BM, and spleen (Figure 6A–E). Morphological analysis of BM and spleen sections revealed accumulation of mature myeloid cells but no obvious differentiation block like acute myeloid leukemia (AML) was observed (Figure 6F). Indeed, AML was not observed in long-term observation of Pcgf1Δ/Δ mice. It is assumed that the epigenetic status that allows GMP self-renewal was enforced over time in the absence of Pcgf1, leading to enhanced production of mature myeloid cells that mimic MPN. A part of Pcgf1Δ/Δ mice also developed lethal T-cell acute lymphoblastic leukemia (T-ALL) (Figure 6A and G) like Bcor mutant mice (Tara et al., 2018). These results indicate that constitutive activation of the GMP self-renewal network in Pcgf1Δ/Δ mice serves to promote malignant transformation. Taken together, these results highlight the importance of PRC1.1-dependent suppression of the myeloid self-renewing network to prevent malignant transformation.
Discussion
In this study, we demonstrated that PCGF1 contributes to balanced hematopoiesis by restricting precocious myeloid commitment of HSPCs and expansion of myeloid progenitors while its inhibition promotes emergency myelopoiesis and myeloid transformation. These findings present a sharp contrast with PCGF4/BMI1 essential for self-renewal of HSCs (Iwama et al., 2004; Oguro et al., 2006; Park et al., 2003) and underscore distinct functions between canonical PRC1 and non-canonical PRC1.1 in hematopoiesis (Figure 6H).
PcG and trithorax group proteins mark developmental regulator gene promoters with bivalent histone domains to keep them poised for activation in ES cells (Bernstein et al., 2006). We previously reported that canonical PRC1 reinforces bivalent domains at the B cell regulator genes, Ebf1 and Pax5, to maintain B cell lineage commitment poised for activation in HSPCs (Oguro et al., 2010). In contrast, PCGF1 appeared to target non-bivalent PRC1 target genes marked with moderate levels of H2AK119ub1 and H3K27me3. Among these, PCGF1 targets myeloid regulator genes, such as Cebpa, thereby negatively regulating myeloid commitment. Our findings indicate that canonical and non-canonical PRC1 restrict the lymphoid and myeloid commitment of HSPCs, respectively, by targeting different transcriptional programs of differentiation, thereby fine-tuning the balance of HSPC commitment (Figure 6H). Although there might be considerable functional redundancy between canonical and non-canonical PRC1 complexes, our results uncovered a unique function of PRC1.1 in the lineage commitment of HSPCs. The reduction in the levels of Cebpa expression by introducing a Cebpafl/+ allele in Pcgf1Δ/Δ LSK cells was sufficient to restore balanced production of myeloid and B cells by Pcgf1Δ/Δ HSPCs in culture (Figure 2E). However, we could not confirm these data in mice probably due to inefficient deletion of Cebpa using a Cre-ERT system (data not shown). The real impact of de-repressed Cebpa in myeloid-biased differentiation of Pcgf1Δ/Δ HSPCs requires further validation in vivo.
Myeloid-biased output from HSPCs is one of the hallmarks of emergency hematopoiesis (Trumpp et al., 2010; Zhao and Baltimore, 2015). In mouse models of regeneration, myeloid-biased MPP2 and MPP3 are transiently overproduced, suggesting that HSCs produce functionally distinct lineage-biased MPPs to adapt blood production to hematopoietic demands (Pietras et al., 2015). In the present study, we found that Pcgf1-deficient hematopoiesis recapitulates sustained emergency myelopoiesis, although the production of circulating myeloid cells was not enhanced. Expanding GMPs, GMP clusters during regeneration, which, in turn, differentiate into granulocytes (Hérault et al., 2017). Of note, PCGF1 loss induced constitutive GMP cluster formation at steady state and sustained GMP expansion in mice after myeloablation and in culture. Correspondingly, Pcgf1-deficient mice had a greater number of self-renewing GMPs than control mice. This unique phenotype may implicate the importance of transient but not constitutive PCGF1 repression for proper myeloid regeneration. β-catenin and Irf8 constitute an inducible self-renewal progenitor network controlling GMP cluster formation, with β-catenin directly suppressing Irf8 expression while restoration of Irf8 expression terminating the self-renewal network and inducing GMP differentiation (Hérault et al., 2017; Figure 5I). Hoxa9, which is upregulated in srGMPs, is one of the PRC1.1 targets in myeloid progenitors (Figure 4—figure supplement 1D; Ross et al., 2012; Shinoda et al., 2022; Tara et al., 2018). We demonstrated that Hoxa9 expression activates β-catenin and promotes GMP self-renewal, identifying Hoxa9 as a component of the GMP self-renewal network. Of note, PRC1.1 is transiently inhibited to de-repress such GMP self-renewal network genes. This transient nature of PRC1.1 inhibition allows for srGMP expansion and GMP cluster formation followed by proper differentiation of expanded GMPs. As expression levels of PRC1.1 components remained unchanged during hematopoietic regeneration, non-canonical PRC1.1 activity could be modulated by post-translational modifications in response to extracellular stimuli like canonical PRC1 (Banerjee Mustafi et al., 2017; Liu et al., 2012; Nacerddine et al., 2012; Voncken et al., 2005). How extrinsic signals modulate PRC1.1 functions to regulate myelopoiesis remains an important question.
The molecular machineries that drive emergency myelopoiesis are often hijacked by transformed cells (Hérault et al., 2017). A significant portion of Pcgf1-deficient mice eventually developed lethal MPN after a sustained myeloproliferative state. These findings indicate that PRC1.1 functions as a critical negative regulator of myeloid transformation. Among the components of PRC1.1, BCOR and BCLRL1, but not PCGF1 are targeted by somatic gene mutations in various hematological malignancies, including myelodysplastic syndrome (MDS), chronic myelomonocytic leukemia (CMML), and acute myeloid leukemia (AML) (Isshiki and Iwama, 2018). We reported that mice expressing a carboxyl-terminal truncated BCOR, which cannot interact with PCGF1, showed myeloid-biased hematopoiesis like Pcgf1-deficient mice. Importantly, HSPCs in these mice showed a growth advantage in the myeloid compartment, which was further enhanced by the concurrent deletion of Tet2, leading to the development of lethal MDS (Tara et al., 2018). De-repression of myeloid regulator genes, such as Cebp family and Hoxa cluster genes, were also detected in Bcor mutant progenitor cells (Tara et al., 2018). These findings also support the idea that PRC1.1 restricts myeloid transformation by transcriptionally repressing aberrant activation of myeloid regeneration programs.
Collectively, our findings highlight a critical role of PRC1.1 in coordinating steady-state and emergency hematopoiesis and preventing malignant transformation. They also suggest that transient inhibition of PRC1.1 would be a novel approach to temporarily induce emergency myelopoiesis and enhance myeloid cell supply while avoiding the potential risk for malignant transformation.
Materials and methods
Mice
Wild-type mice (C57BL/6) and Rosa::Cre-ERT2 mice were purchased from the Japan SLC and TaconicArtemis GmbH, respectively. Pcgf1fl and Cebpafl mice were kindly provided by Haruhiko Koseki and Daniel G. Tenen, respectively, and previously reported (Almeida et al., 2017; Zhang et al., 2004). All experiments using mice were performed in accordance with our institutional guidelines for the use of laboratory animals and approved by the Review Board for Animal Experiments of Chiba University (approval ID: 30-56) and the University of Tokyo (approval ID: PA18-03).
Bone marrow transplantation
Request a detailed protocolTo generate hematopoietic cell-specific Pcgf1 KO mice, we transplanted total BM cells (5 × 106) from Rosa26CreERT and Rosa26CreERT;Pcgf1fl/fl mice into lethally irradiated (9.5 Gy) CD45.1 recipient mice. For competitive bone marrow transplantation assay, we transplanted total BM cells (2 × 106) from CD45.2 donor mice with CD45.1+ competitor total BM cells (2 × 106) into lethally irradiated (9.5 Gy) CD45.1 recipient mice. To induce Cre activity, transplanted mice were injected with 100 μL of tamoxifen (Sigma-Aldrich) dissolved in corn oil (Sigma-Aldrich) at a concentration of 10 mg/mL intraperitoneally once a day for five consecutive days 4 wk after transplantation.
Locus-specific genotyping of Pcgf1, Cebpa, and Rosa::Cre-ERT
Request a detailed protocolTo detect Pcgf1fl, Pcgf1Δ, Cebpafl, CebpaΔ, and Rosa::Cre-ERT PCR reactions were performed using the specific oligonucleotides. The oligonucleotide sequences used are shown in Supplementary file 5.
5-FU challenge
Request a detailed protocol8–12-week-old wild-type mice or control and Pcgf1Δ/Δ were injected with 300 μL PBS or 150 mg/kg (3.75 mg per 25 g body weight mouse) 5-FU (Kyowa KIRIN) dissolved in 300 μL PBS intraperitoneally once.
Flow cytometry analyses and antibodies
Request a detailed protocolThe monoclonal antibodies recognizing the following antigens were used in flow cytometry and cell sorting: CD45.1 (A20), CD45.2 (104), Gr-1 (RB6-8C5), CD11b/Mac-1 (M1/70), Ter-119 (TER-119), B220 (RA3-6B2), CD127/IL-7R (SB/119), CD4 (GK1.5), CD8a (53–6.7), CD117/c-Kit (2B8), Sca-1 (D7), CD34 (RAM34), CD150 (TC15-12F12.2), CD48 (HM48-1), CD135 (A2F10), CD16/32/FcγRII-III (93), CD41 (eBioMWReg30), CD105 (MJ7/18), Ly6D (49-H4), Ly6G (HK1.4), Ly6G (1A8), F4/80 (BM8), lineage mixture (Gr-1, Mac-1, Ter-119, CD127/IL-7R, B220, CD4, CD8α), and lineage mixture for CLP (Gr-1, Mac-1, Ter-119, B220, CD4, CD8α). Monoclonal antibodies were purchased from BioLegend, Tonbo Biosciences, Thermo Fisher Scientific, or BD Biosciences. Dead cells were eliminated by staining with 0.5 μg/mL propidium iodide (Sigma-Aldrich). All flow cytometric analyses and cell sorting were performed on FACSAria IIIu, FACSCanto II, and FACSCelesta (BD Biosciences). Cell surface protein expression used to define hematopoietic cell types were as follows:
HSC: CD150+CD48-CD135-CD34-c-Kit+Sca-1+Lineage-
MPP1: CD150+CD48-CD135-CD34+c-Kit+Sca-1+Lineage-
MPP2: CD150+CD48+CD135-CD34+c-Kit+Sca-1+Lineage-
MPP3: CD150-CD48+CD135-CD34+c-Kit+Sca-1+Lineage-
MPP4: CD150-CD48+CD135+CD34+c-Kit+Sca-1+Lineage-
CMP: CD34+FcγR-c-Kit+Sca-1-Lineage-
GMP: CD34+FcγR+c-Kit+Sca-1-Lineage-
MEP: CD34-FcγR-c-Kit+Sca-1-Lineage-
pre-GM: CD150-CD105-FcγR-CD41-c-Kit+Sca-1-Lineage-
CLP: c-KitlowSca-1lowCD135+IL7R+Lineage (for CLP)-
ALP: Ly6D-cKitlowSca-1lowCD135+IL7R+Lineage-
BLP: Ly6D+cKitlowSca-1lowCD135+IL7R+Lineage-
LSK: c-Kit+Sca-1+Lineage-
LK: c-Kit+Lineage-
Pro-B: B220+CD43+IgM-
Pre-B: B220+CD43-IgM-
Quantitative RT-PCR
Request a detailed protocolTotal RNA was extracted using a RNeasy Micro Plus Kit (QIAGEN) or TRIZOL LS solution (MOR) and reverse transcribed by the SuperScript IV First-Strand Synthesis System (Invitrogen) or the ReverTra Ace α- (TOYOBO) with an oligo-dT primer. Real-time quantitative PCR was performed with a StepOnePlus Real-Time PCR System (Life Technologies) using FastStart Universal Probe Master (Roche) and the indicated combinations of the Universal Probe Library (Roche), or TB Green Premix Ex Taq II (TaKaRa Bio). All data are presented as relative expression levels normalized to Hprt expression. The primer sequences used are shown in Supplementary file 5 (Murakami et al., 2021; Sonntag et al., 2018).
Limiting dilution assay
Request a detailed protocolFor in vivo limiting dilution assay, we transplanted limiting numbers of total BM cells (1 × 104, 4 × 104, 8 × 104, and 2 × 105) isolated from primary recipients (control and Pcgf1Δ/Δ mice 1 mo after tamoxifen injections) with CD45.1+ competitor total BM cells (2 × 105) into lethally irradiated CD45.1 recipient mice. PB analyses were performed at 16 wk after transplantation.
For in vitro limiting dilution assay, we sorted HSCs from control and Pcgf1Δ/Δ mice 1 mo after tamoxifen injections and cultured limiting numbers of the cells (1, 5, 25, and 125) with TSt-4 (B cells) or TSt-4/DLL1 stromal cells (T cells) in RPMI (Thermo Fisher Scientific) supplemented with 10% BSA (093001; STEMCELL Technologies), 50 μM 2-ME (Sigma-Aldrich), 100 μM MEM Non-Essential Amino Acids solution (Gibco), 100 μM sodium pyruvate (Gibco), and 2 ng/mL recombinant mouse IL-7 (577802; BioLegend) for 28 d. The generation of CD19+ B cells or Thy1.2+ T cells in each well was detected by flow cytometry.
Cell cycle assay
Request a detailed protocolBM cells were stained with antibodies against cell-surface markers. After washing, cells were fixed and permeabilized with a BD Phosflow Lyse/Fix Buffer and a BD Phosflow Perm Buffer II (BD Biosciences) according to the manufacturer’s instructions. Cells were stained with FITC-Ki67 antibody (#11-5698-82; Thermo Fisher Scientific) at room temperature for 30 min and then with 1 μg/mL 7-AAD (Sigma-Aldrich). Flow cytometric analyses were performed on FACSAria IIIu (BD Biosciences).
Cell culture
Request a detailed protocolFor growth assays, sorted CD34-CD150+LSK HSCs were cultured in S-Clone SF-O3 (Sanko Junyaku) supplemented with 0.1% BSA (093001; STEMCELL Technologies), 50 μM 2-ME (Sigma-Aldrich) and 1% penicillin/streptomycin/glutamine (Gibco). 20 ng/mL of recombinant mouse SCF (579706; BioLegend) and recombinant human TPO (763706; BioLegend) for HSC culture conditions and 10 ng/mL of SCF, TPO, recombinant mouse IL-3 (575506; BioLegend), and recombinant murine GM-CSF (315-03; PeproTech) for myeloid culture condition-1 were added to cultures. In the case of myeloid culture condition-2, sorted CD150+CD48-CD135-CD34-LSK HSCs, LSK cells, and GMPs were cultured in IMDM (Gibco) supplemented with 5% FBS, 50 μM 2-ME (Sigma-Aldrich), 1% penicillin/streptomycin/glutamine (Gibco), 1 mM sodium pyruvate (Gibco), and 0.1 mM MEM Non-Essential Amino Acids solution (Gibco). 25 ng/mL of SCF, TPO, recombinant human Flt3L (300-19; PeproTech) and recombinant murine IL-11 (220-11; PeproTech) and 10 ng/mL of IL-3 and GM-CSF were added to cultures.
For replating assays, LSK cells were plated in methylcellulose medium (Methocult M3234; STEMCELL Technologies) containing 20 ng/mL of SCF, TPO, IL-3, and GM-CSF.
Retroviral vector and virus production
Request a detailed protocolFull-length Pcgf1 and Bmi1 cDNA tagged with a 3×Flag at the N-terminus was subcloned into the retroviral vector pGCDNsam-IRES-EGFP. Full-length Hoxa9 cDNA was subcloned into the retroviral vector pMYs-IRES-mCherry. A recombinant retrovirus was generated by a 293gpg packaging cell line. The virus in supernatants of 293gpg cells was concentrated by centrifugation at 6000 × g for 16 hr.
Immunofluorescence imaging of bone marrow and spleen sections
Request a detailed protocolIsolated mouse femurs were immediately placed in ice-cold 2% paraformaldehyde solution (PFA/PBS) and fixed under gentle agitation for 16 hr. The samples were then incubated in 15 and 30% sucrose for cryoprotection overnight. Samples were embedded in O.C.T. (Sakura) and frozen in cooled hexane. The 7 μm frozen sections were generated with a cryostat (Cryostar NX70, Thermo Scientific) using Kawamoto’s tape method (Kawamoto, 2003). Sections on slide glasses were blocked with staining buffer (10% normal donkey serum in TBS) and an Avidin/Biotin Blocking Kit (VECTOR), then stained with biotinylated anti-lineage antibody cocktail and anti-c-Kit antibody (#AF 1356; R&D Systems), or anti-FcγR-Alexa Fluor 647 (#101314; BioLegend) in staining buffer overnight at 4℃. For secondary staining, sections were incubated with streptavidin-Alexa Fluor 488 (#S11223; Invitrogen) and donkey anti-goat Alexa Fluor 555 (#A21432; Invitrogen) antibody for 3 hr at room temperature. Finally, sections were incubated with 1 μg/mL DAPI/TBS for 10 min and mounted with ProLong Glass Antifade Mountant (Thermo Scientific). Images of sections were captured on a confocal microscope (Dragonfly, Andor, or A1Rsi, Nikon) and processed using Fiji. ImageJ was used for image quantification.
Immunofluorescence imaging of purified GMPs
Request a detailed protocolGMPs were sorted directly onto glass slides using BD AriaIIIu. The cells were washed three times with PBS for 5 min between each staining step. Cells were fixed with 4% PFA for 15 min, permeabilized with 0.1% Triton X-100 for 10 min, and then blocked with 3% BSA for 1 hr at room temperature. The cells were then incubated with rabbit anti-mouse β-catenin (#9582S; Cell Signaling) primary antibody at 4°C overnight. The cells were then stained with anti-rabbit AF488A (#20015; Biotium) secondary antibody for 2 hr at room temperature. After staining with 1 μg/mL DAPI/PBS for 5 min, the cells were mounted with ProLong Glass Antifade Mountant (Thermo Fisher). DragonFly (Andor, ×40 objective) was used for image acquisition.
Bulk RNA-seq and data processing
Request a detailed protocolTotal RNAs were extracted from 1000 to 5000 cells using an RNeasy Plus Micro Kit (QIAGEN) and cDNAs were synthesized using a SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Clontech) according to the manufacturer’s instructions. The ds-cDNAs were fragmented using S220 or M220 Focused-ultrasonicator (Covaris), then cDNA libraries were generated using a NEBNext Ultra DNA Library Prep Kit (New England BioLabs) according to the manufacturer’s instructions. Sequencing was performed using HiSeq1500 or HiSeq2500 (Illumina) with a single-read sequencing length of 60 bp. TopHat2 (version 2.0.13; with default parameters) was used to map the reads to the reference genome (UCSC/mm10) with annotation data from iGenomes (Illumina). Levels of gene expression were quantified using Cuffdiff (Cufflinks version 2.2.1; with default parameters). Significant expression differences were detected edgeR (version 3.14; with default parameters), with raw counts generated from String Tie. The super-computing resource was provided by the Human Genome Center, the Institute of Medical Science, the University of Tokyo (http://sc.hgc.jp/shirokane.html). The enrichment analyses were performed using g:Profiler tool.
Single-cell RNA-seq and data processing
Request a detailed protocolControl (1.2 × 104) and Pcgf1Δ/Δ (1.2 × 104) LK cells were collected for single-cell RNA-seq. mRNA were isolated and libraries were prepared according to Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 (10X Genomics). Raw data files (Base call files) were demultiplexed into fastq files using Cell Ranger with mkfastq command. Then, ‘cellranger count’ command was used for feature counts, barcode counts with reference ‘refdata-gex-mm10-2020-A.’ Filtered_feature_bc_matrix included 6565 control LK cells and 7651 Pcgf1Δ/Δ LK cells. We subsampled 6565 cells from 7651 Pcgf1Δ/Δ LK cells to adjust cell numbers between Pcgf1Δ/Δ and control LK. Subsequent analyses were performed using Seurat 4.1.0. Quality filtering for each feature and cell was conducted based on these criteria (min.cells = 3 & min.features = 200 & nFeature_RNA >200 & nFeature_RNA <10000 & percent.mt <5). After quality filtering, 6171 control LKs and 6198 KO LKs were used for further analysis. Feature counts are log-normalized with the function of ‘NormalizeData.’ 2000 highly variable features are selected for PCA. PC 1–10 components are used for UMAP and graph-based clustering with the functions of FindNeighbors(object, reduction = "pca", dims = 1:15) and FindClusters(object, resolution = 0.28). Cluster 0, 2, and 4 cells are extracted and reanalyzed with PCA. DEGs are selected with the function of ‘FindMarkers(object, min.pct=0.25)’.
Chromatin immunoprecipitation (ChIP) assays and ChIP-sequencing
Request a detailed protocolChIP assays for histone modifications were performed as described previously (Aoyama et al., 2018) using an anti-H2AK119ub1 (#8240S; Cell Signaling Technology) and an anti-H3K27me3 (#07-449; Millipore). BM LSK cells were fixed with 1% FA at 37°C for 2 min, lysed in ChIP buffer (10 mM Tris-HCl pH 8.0, 200 mM NaCl, 1 mM CaCl2, 0.5% NP-40 substitute and cOmplete proteases inhibitor cocktail) and sonicated for 5 s ×3 times by a Bioruptor (UCD-300; Cosmo Bio). Then, cells were digested with Micrococcal Nuclease at 37°C for 40 min (New England BioLabs) and added 10 mM EDTA to stop the reaction. After the addition of an equal volume of RIPA buffer (50 mM Tris-HCl pH 8.0, 150 mM NaCl, 2 mM EDTA pH 8.0, 1% NP-40 substitute, 0.5% sodium deoxycholate, 0.1% SDS and cOmplete proteases inhibitor cocktail), cells were sonicated again for 5 s × 10 times by a Bioruptor. After centrifugation, supernatants were immunoprecipitated at 4°C overnight with Dynabeads Sheep Anti-Rabbit IgG (Invitrogen) conjugated with each antibody. Immunoprecipitates were washed with ChIP wash buffer (10 mM Tris-HCl pH 8.0, 500 mM NaCl, 1 mM CaCl2, 0.5% NP-40 substitute, and cOmplete proteases inhibitor cocktail) four times and TE buffer (10 mM Tris-HCl pH 8.0 and 1 mM EDTA pH 8.0) twice. Bound chromatins and 30 μL of input DNA were suspended in 95 μL and 65 μL elution buffer (50 mM Tris-HCl pH 8.0, 10 mM EDTA pH 8.0, 1% SDS, and 250 mM NaCl), respectively. After the addition of 5 μL of 5 M NaCl, the solutions were incubated at 65°C for 4 hr, treated with 25 μg/mL RNase A (Sigma-Aldrich) at 37°C for 30 min and 0.1 mg/mL proteinase K (Roche) at 50°C for 1 hr and were purified with a MinElute PCR Purification Kit (QIAGEN).
In 3×Flag-Pcgf1ChIP assay, BM LK cells were fixed with 1% FA at 25°C for 10 min, lysed in RIPA buffer, and sonicated for 11 s ×15 times by a homogenizer (NR-50M; Micro-tec Co.). After centrifugation, supernatants were immunoprecipitated at 4°C overnight with Dynabeads Sheep Anti-Mouse IgG (Invitrogen) conjugated with an anti-FLAG antibody (Sigma-Aldrich). Then, the samples were treated in the same way as ChIP assays for histone modifications.
In ChIP-qPCR assay, quantitative real-time PCR was performed with a StepOnePlus Thermal Cycler (Thermo Fisher Scientific) using SYBR Premix Ex Taq II or TB Green Premix Ex Taq II (Takara Bio). The primer sequences used are shown in Supplementary file 5.
ChIP-seq libraries were prepared using a ThruPLEX DNA-seq Kit (Clontech) according to the manufacturer’s instructions. Bowtie2 (version 2.2.6; with default parameters) was used to map the reads to the reference genome (UCSC/mm10). The RPM (reads per million mapped reads) values of the sequenced reads were calculated every 1000 bp bin with a shifting size of 100 bp using bedtools. In order to visualize with Integrative Genomics Viewer (IGV) (http://www.broadinstitute.org/igv), the RPM values of the immunoprecipitated samples were normalized by subtracting the RPM values of the input samples in each bin and converted to a bigwig file using wigToBigWig tool. The super-computing resource was provided by the Human Genome Center, the Institute of Medical Science, the University of Tokyo (http://sc.hgc.jp/shirokane.html).
Assay for transposase accessible chromatin with high-throughput (ATAC)-sequencing
Request a detailed protocolBM CD135-LSK cells (1.6–3.0 × 104) and GMPs (3.0 × 104) were lysed in cold lysis buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.1% IGEPAL CA-630) on ice for 10 min. After centrifugation, nuclei pellets were resuspended with 50 μL of transposase reaction mix (25 μL Tagment DNA buffer (illumine), 2.5 μL Tagment DNA enzyme (illumine) and 22.5 μL water), incubated at 37°C for 35 min and were purified with a MinElute PCR Purification Kit (QIAGEN). After the optimization of PCR cycle number using SYBER Green I Nucleic Acid gel Stain (Takara Bio), transposed fragments were amplified using NEBNext High Fidelity 2×PCR Master mix and index primers, and were purified with a MinElute PCR Purification Kit (QIAGEN). Library DNA was sized selected (240–360 bps) with BluePippin (Sage Science). Sequencing was performed using HiSeq1500 or HiSeq2500 (Illumina) with a single-read sequencing length of 60 bp. Bowtie2 (version 2.2.6; with default parameters) was used to map reads to the reference genome (UCSC/mm10) with annotation data from iGenomes (Illumina). Reads mapped to mitochondria were removed. To ensure even processing, reads were randomly downsampled from each sample to adjust to the smallest read number of samples. MACS (version 2.1.1; with default parameters) was used to call peaks in downsampled reads. The catalogue of all peaks called in any samples was produced by merging all called peaks that overlapped by at least one base pair using bedtools. The MACS bdgcmp function was used to compute the fold enrichment over the background for all populations, and the bedtools map function was used to count fragments in the catalogue in each population. Fragment counts at each site in the catalogue were quantile normalized between samples using the PreprocessCore package in R (3.3.2). We used the Homer package with command annotatePeaks.pl using default parameters to annotate regions with promoter and distal labels and the nearest gene, and with command findMotifsGenome.pl using default parameters to identify enriched motifs, and the catalogue of all called peaks as a background.
Quantification and statistical analysis
Request a detailed protocolStatistical tests were performed using Prism version 9 (GraphPad). The significance of difference was measured by the Student’s t-test or one-way ANOVA. Data are shown as the mean ± SEM. Significance was taken at values of *p<0.05, **p<0.01, and ***p<0.001.
Appendix 1
Data availability
RNA sequence, ChIP sequence and ATAC sequence data were deposited in the DDBJ (accession numbers DRA008518 and DRA013523).
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DDBJID DRA013523. Polycomb repressive complex 1.1 orchestrates homeostatic and emergency hematopoiesis and restricts transformation by acting as a rheostat of myelopoiesis.
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DDBJID DRA008518. Non-canonical PRC1 orchestrates homeostatic and emergency hematopoiesis and restricts transformation by acting as a rheostat of myeloid differentiation.
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Article and author information
Author details
Funding
Japan Society for the Promotion of Science (19H05653)
- Atsushi Iwama
Japan Society for the Promotion of Science (20K08728)
- Yaeko Nakajima-Takagi
Japan Society for the Promotion of Science (19H05746)
- Atsushi Iwama
Japan Agency for Medical Research and Development (21zf0127003h0001)
- Atsushi Iwama
Japan Agency for Medical Research and Development (JP223fa627001)
- Atsushi Iwama
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Acknowledgements
We thank Dr. Daniel G Tenen for providing us with Cebpa mutant mice. The super-computing resource was provided by The Human Genome Center, The Institute of Medical Science, The University of Tokyo. This work was supported in part by Grants-in-Aid for Scientific Research (#19H05653, #20K08728) and Scientific Research on Innovative Area 'Replication of Non-Genomic Codes' (#19H05746) from Japanese Society for the Promotion of Science, and Moonshot (#21zf0127003h0001) and UTOPIA (JP223fa627001) projects from the Japan Agency for Medical Research and Development.
Ethics
All experiments using mice were performed in accordance with our institutional guidelines for the use of laboratory animals and approved by the Review Board for Animal Experiments of Chiba University (approval ID: 30-56) and the University of Tokyo (approval ID: PA18-03).
Copyright
© 2023, Nakajima-Takagi et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Stem Cells and Regenerative Medicine
Adult mammals, unlike some lower organisms, lack the ability to regenerate damaged hearts through cardiomyocytes (CMs) dedifferentiation into cells with regenerative capacity. Developing conditions to induce such naturally unavailable cells with potential to proliferate and differentiate into CMs, that is, regenerative cardiac cells (RCCs), in mammals will provide new insights and tools for heart regeneration research. In this study, we demonstrate that a two-compound combination, CHIR99021 and A-485 (2C), effectively induces RCCs from human embryonic stem cell-derived TNNT2+ CMs in vitro, as evidenced by lineage tracing experiments. Functional analysis shows that these RCCs express a broad spectrum of cardiogenesis genes and have the potential to differentiate into functional CMs, endothelial cells, and smooth muscle cells. Importantly, similar results were observed in neonatal rat CMs both in vitro and in vivo. Remarkably, administering 2C in adult mouse hearts significantly enhances survival and improves heart function post-myocardial infarction. Mechanistically, CHIR99021 is crucial for the transcriptional and epigenetic activation of genes essential for RCC development, while A-485 primarily suppresses H3K27Ac and particularly H3K9Ac in CMs. Their synergistic effect enhances these modifications on RCC genes, facilitating the transition from CMs to RCCs. Therefore, our findings demonstrate the feasibility and reveal the mechanisms of pharmacological induction of RCCs from endogenous CMs, which could offer a promising regenerative strategy to repair injured hearts.
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- Stem Cells and Regenerative Medicine
Bone regeneration is mediated by skeletal stem/progenitor cells (SSPCs) that are mainly recruited from the periosteum after bone injury. The composition of the periosteum and the steps of SSPC activation and differentiation remain poorly understood. Here, we generated a single-nucleus atlas of the periosteum at steady state and of the fracture site during the early stages of bone repair (https://fracture-repair-atlas.cells.ucsc.edu). We identified periosteal SSPCs expressing stemness markers (Pi16 and Ly6a/SCA1) and responding to fracture by adopting an injury-induced fibrogenic cell (IIFC) fate, prior to undergoing osteogenesis or chondrogenesis. We identified distinct gene cores associated with IIFCs and their engagement into osteogenesis and chondrogenesis involving Notch, Wnt, and the circadian clock signaling, respectively. Finally, we show that IIFCs are the main source of paracrine signals in the fracture environment, suggesting a crucial paracrine role of this transient IIFC population during fracture healing. Overall, our study provides a complete temporal topography of the early stages of fracture healing and the dynamic response of periosteal SSPCs to injury, redefining our knowledge of bone regeneration.