Abstract
Autosomal dominant PDGFRβ gain-of-function mutations in mice and humans cause a spectrum of wasting and overgrowth disorders afflicting the skeleton and other connective tissues, but the cellular origin of these disorders remains unknown. We demonstrate that skeletal stem cells (SSCs) isolated from mice with a gain-of-function D849V point mutation in PDGFRβ exhibit SSC colony formation defects that parallel the wasting or overgrowth phenotypes of the mice. Single-cell RNA transcriptomics with the SSC colonies demonstrates alterations in osteoblast and chondrocyte precursors caused by PDGFRβD849V. Mutant SSC colonies undergo poor osteogenesis in vitro and mice with PDGFRβD849V exhibit osteopenia. Increased expression of Sox9 and other chondrogenic markers occurs in SSC colonies from mice with PDGFRβD849V. Increased STAT5 phosphorylation and overexpression of Igf1 and Socs2 in PDGFRβD849V SSCs suggests that overgrowth in mice involves PDGFRβD849V activating the STAT5-IGF1 axis locally in the skeleton. Our study establishes that PDGFRβD849V causes osteopenic skeletal phenotypes that are associated with intrinsic changes in SSCs, promoting chondrogenesis over osteogenesis.
Introduction
Two platelet-derived growth factor (PDGF) receptors (PDGFRs) have been identified in mammals, PDGFRα and PDGFRβ, which bind to five PDGF ligands. PDGFRs play crucial and distinct roles in embryo development by regulating the proliferation, migration, survival, and differentiation of mesenchymal cells that populate all tissues and organs (Hoch and Soriano 2003; Andrae et al. 2008; Klinkhammer et al. 2018). It has recently been discovered that humans with gain-of-function mutations in PDGFRB exhibit a spectrum of phenotypes affecting the skeleton and other connective tissues in an autosomal-dominant fashion (Guerit et al. 2021). These mutations result in constitutive PDGFRβ signaling, causing Penttinen syndrome (MIM 601812) or Kosaki overgrowth syndrome (MIM 616592). Both disorders progressively affect the skeleton beginning in childhood. Other activating variants of PDGFRB are associated with a milder phenotype, infantile myofibromas (MIM 228550), which does not affect the skeleton. Penttinen syndrome, with PDGFRB mutations V665A or N666S (mutated in the first kinase domain), is characterized as a premature aging condition with osteoporosis, scoliosis, lipoatrophy, dermal atrophy, aneurysms, and acro-osteolysis (Johnston et al. 2015; Bredrup et al. 2019). Kosaki overgrowth syndrome, with PDGFRB mutations P584R or W566R (mutated in the juxtamembrane domain), is featured by tall stature, elongated long bones, enlarged hands and feet, distintive facial features, scoliosis, hyperelastic skin, aneurysms, myofibromas, and neurodegeneration (Takenouchi et al. 2015; Minatogawa et al. 2017). The pathological mechanisms of the human disorders are still unknown.
We previously demonstrated that mice with a gain-of-function D849V mutation in Pdgfrb (mutated in the second kinase domain, corresponding to the human D850 residue) died between 2-3 weeks of age after developing a postnatal wasting phenotype (Olson and Soriano 2011; He et al. 2017). Surprisingly, these phenotypes were modulated by signal transducer and activator of transcription 1 (STAT1). Mice with PdgfrbD849V mutation but lacking Stat1 (Pdgfrb+/D849VStat1-/-mice) survived until 8-9 weeks while becoming overweight with widespread connective tissue overgrowth (not obesity), thick calvarias, abnormally curved spine, and enlarged rib cage (He et al. 2017). Although the murine model clearly identified Stat1 as a gene modulating the phenotype spectrum driven by PdgfrbD849V, many questions remain about the target cell types and signaling pathways underlying such striking phenotypes. Moreover, the role of PDGFRβ in the skeleton is not well understood, as PDGFRβ seems to be redundant for skeletal development based on the normal skeletal phenotypes of global and osteoblast-specific knockouts in mice (Soriano 1994; Bohm et al. 2019).
Ligand binding to wild type PDGFRβ induces receptor dimerization, which activates the receptor’s kinase activity and results in autophosphorylation of intracellular tyrosine residues that activate downstream signaling pathways (Lemmon and Schlessinger 2010). Gain-of-function PDGFRβ mutations disrupt the inactive conformation of the receptor, leading to constitutive kinase activity and autophosphorylation. PDGFRs utilize a variety of signaling pathways to mediate their effects on cell behavior, including PI3K, MAPK, PLCγ, and STAT1/3/5 (Heldin and Westermark 1999; Tallquist and Kazlauskas 2004; Demoulin and Essaghir 2014). PDGFRβ is particularly important for pericyte development and function, but it is also expressed on fibroblasts, osteoblasts, and stem/progenitor cells with potential to differentiate into multiple mesenchymal cell types (Andrae et al. 2008).
Skeletal stem cells (SSCs) residing in bone and bone marrow are responsible for postnatal bone development, tissue homeostasis, and repair (Bianco and Robey 2015). A single SSC at the apex of skeletal lineages can give rise to chondrocytes, osteoblasts, adipocytes and fibroblasts. Recent findings with in vivo lineage tracing and single-cell transplantation have increased the rigor of SSC biology and improved our understanding of SSC heterogeneity (Ambrosi et al. 2019; Serowoky et al. 2020). Perisinusoidal vasculature in bone marrow (BM) is surrounded by SSCs expressing PDGFRβ, PDGFRα, CD146, Nestin, LepR and Cxcl12, while arterial vasculature is associated with SSCs expressing PDGFRβ, PDGFRα, Sca1 and LepR (Sacchetti et al. 2007; Morikawa et al. 2009; Mendez-Ferrer et al. 2010; Zhou et al. 2014). The resting zone of the growth plate harbors SSCs expressing Grem1, Col2a1, PthrP and Itgav (CD45-/TER119-/Tie2-/Thy-/6C3-/CD105-/CD200-/Itgav+) (Chan et al. 2015; Worthley et al. 2015; Mizuhashi et al. 2018; Newton et al. 2019). The periosteum and cranial sutures contain SSCs expressing PDGFRβ, Gli1, Axin2, Ctsk, and αSMA (Yang et al. 2013; Zhao et al. 2015; Shi et al. 2017; Debnath et al. 2018; Ortinau et al. 2019). PDGFRβ is broadly expressed in SSCs, but its role has not been examined. We speculated that PDGFRβ signaling could be functional in SSCs, and hypothesized that elevated PdgfrbD849V mutant signaling in SSCs could alter stem cell functions to generate skeletal disorders.
Results
PDGFRβD849V alters skeletal growth in mice
To explore the PDGFRβD849V skeleton, we generated a cohort of mice and measured their weights and bone lengths. As Stat1 is an important modifier of PDGFRβD849V phenotypes (He et al. 2017), four offspring genotypes were established with the Sox2Cre driver for germline activation of PdgfrbD849V and/or deletion of Stat1-floxed alleles by crossing Pdgfrb+/D849VStat1flox/flox and Stat1+/-Sox2Cre+/- mice. The resulting four genotypes are: Stat1+/- (hereafter designated as S+/-), Stat1-/- (S-/-), Pdgfrb+/D849VStat1+/- (KS+/-), and Pdgfrb+/D849VStat1-/- (KS-/-). The Pdgfrb allele expressing D849V is designated K because the mutation is in the kinase domain. We used two genetic controls, S+/- and S-/-, that do not show growth or survival defects (Meraz et al. 1996; He et al. 2017). KS+/- mice died by 3 weeks of age with features of autoinflammation and wasting. KS-/- mice, however, were rescued in survival at 3 weeks and died around 8-9 weeks, consistent with previous findings (He et al. 2017). Thus, body weights were collected from live mice at 2-9 weeks of age, and bone length data were collected from tibias at 3 or 6-8 weeks of age. In the resulting growth curve, KS+/- and KS-/- mice were clearly distinguishable by their obvious wasting and overgrowth phenotypes, respectively (Figure 1A). 3-week-old KS+/- tibias were shorter than KS-/- and control tibias (Figure 1B), and by 6-8 weeks the KS-/- tibias were significantly longer than controls (Figure 1C). We also examined osteoclasts by tartrate-resistant acid phosphate (TRAP) staining in each genotype to test whether altered bone resorbing cells could be coupled with the skeleton growth defects. TRAP stain was stronger in both mutants at 3 weeks old (Supplementary Figure 1), which indicates increased osteoclastogenesis in both KS+/- and KS-/- mice and does not correlate with the wasting or overgrowth phenotypes. We conclude that changes in osteoclast activity do not explain the skeleton growth phenotypes. Instead, skeletal lineages expressing PDGFRβ are likely to be responsible for the skeletal growth defects. Therefore, we next investigated the effects of PDGFRβD849V on SSCs.
PDGFRβD849V regulates SSC numbers and colony formation
To determine whether SSCs were altered in PDGFRβD849V-expressing mice, we performed SSC quantification and colony formation assays. SSCs were immunophenotyped from limb bones with enzymatic digestion and flow cytometry using two well-established SSC markers, PDGFRα and Sca1/Ly6a (PαS) (Morikawa et al. 2009; Houlihan et al. 2012) (Supplementary Figure 2). The percentage of PαS cells in the stromal fraction (excluding hematopoietic and endothelial cells) was calculated at 3 and 6 weeks of age. The PαS percentage was similar between all genotypes at 3 weeks old (Figure 2A), but it was significantly increased in cells isolated from KS-/- bones at 6 weeks old (Figure 2B). To characterize stem cell function, we sorted out PαS cells from 3-week-old and 6 to 9-week-old bones and performed colony formation assays. Western blotting confirmed constitutive activation of PDGFRβ and knockout of STAT1 in SSC-derived colonies (Figure 2C). At 3 weeks there was a decrease in the number of colonies generated by KS+/- SSCs compared to equal numbers of S+/- or S-/- colonies, while the number of colonies was increased in KS-/- SSCs (Figure 2D and 2E). The colonies were classified into groups based on size (small (=<5 um), medium (5<x<36), large (=>36)) to examine the expansion capacity of control and mutant SSCs. KS+/- SSCs generated decreased colony numbers of all three sizes, and KS-/- increased medium size colonies (Figure 2E). 6 to 9-week-old KS-/- SSCs also increased the number of colonies formed compared to controls (Figure 2F-2G). These results show that mice with PDGFRβD849V exhibit changes in the number of SSCs and colony forming unit activity in parallel to the wasting and overgrowth phenotypes displayed in vivo, consistent with the idea of intrinsic defects in mutant SSCs mediating skeletal phenotypes.
Single-cell RNA sequencing indicates multi-lineage potential of cultured SSCs
PαS cell-derived colonies can differentiate into osteoblasts or adipocytes when treated with differentiation cocktails (Morikawa et al. 2009). However, we noted that the colonies were only partially differentiated (Supplementary Figure 3), suggesting cellular heterogeneity within each SSC-derived colony. As an approach to evaluate cellular heterogeneity of SSCs and obtain detailed information on single-cell differentiation potential, we performed single-cell transcriptomics. To escape the autoinflammatory condition in KS+/- mice, which would strongly influence gene expression, we utilized SSC colonies that had been cultured for 14 days without differentiation cocktails instead of freshly isolated cells. Thus, single-cell suspensions of colonies from the four genotypes were subjected to single-cell RNA (scRNA) sequencing using 10X Genomics Chronium platform. We integrated scRNA sequencing data from eight samples, representing the four genotypes in duplicate, to generate general clusters using the Seurat package (Butler et al. 2018; Stuart et al. 2019). Each cluster was grouped based on signature genes that were differentially expressed between clusters (Figure 3A). A heatmap of signature gene marker expression is shown in Figure 3B (full list in Supplementary Table 1). These markers, combined with current literature and gene ontology, were used to define the cell type represented by each cluster (Figure 3C and 3D, Supplementary Table 2). Clusters of biological duplicates were distributed similarly within each genotype (Supplementary Figure 4A). As shown by uniform manifold approximation and projection (UMAP) plot (Figure 3A), we found 10 clusters containing either SSCs, intermediate skeletal stem and progenitor cells (SSPCs), chondrocyte precursors, osteoblast precursors, or adipocyte precursors. All 10 clusters were conserved across the four genotypes (Supplementary Figure 4B).
As a percentage of all cells, SSCs and SSPCs were more abundant than the committed precursors (Figure 3E). The most abundant cluster was cluster 0 (26.6%, SSPCs with Pdgfrahigh), followed by cluster 1 (21.9%, SSPCs with Sca1/Ly6ahigh) and cluster 2 (11.1%, SSCs with Pdgfrahigh and Sca1/Ly6ahigh). Cluster 2 was considered the origin of all populations due to high expression of Pdgfra and Sca1/Ly6a. The mesoderm marker Prrx1 was most highly expressed in cluster 2 and was broadly expressed in other clusters, as expected for SSCs and their progeny (Supplementary Figure 4C). Pdgfrb was moderately expressed in most clusters including SSCs (cluster 2), but was downregulated in chondrocyte precursors (clusters 6, 8 and 9) (Figure 3C). The SSC and SSPC clusters broadly expressed several previously identified stem cell markers including Prg4, Cxcl12, Ctsk, Cd164, Cd51/Itgav and Grem1, but others were barely detected including Nes, Cd146/Mcam, Lepr, and Gli1 (Supplementary Figure 4C).
The remaining clusters, 3 through 9, were considered precursors rather than differentiated cells, because the colonies were cultured with maintenance medium to support clonal expansion without differentiation. Representative markers for each precursor cluster are summarized in Supplementary Figure 4D. Of note, cluster 3 represents osteogenic precursors expressing Mmp13, Alpl and Sp7. Cluster 4 represents adipocyte precursors expressing Lpl, Fabp4, Hp and Adipoq. Cluster 5 represents osteoblastic precursors highly expressing Col1a1 and Col1a2 and moderately expressing Acta2, Tagln and Myl9. Clusters 6 and 8 represent actively proliferating chondrocyte precursors highly expressing cell cycle genes (Cdk1, Mki67 and Pcna) and early chondrogenic markers (Col2a1, Pdpn and Grem1). Since we regressed out cell cycle genes (S and G2/M phase genes) during dimensional reduction of scRNA data, many S phase cells were distributed throughout all the clusters (Supplementary Figure 4E). However, clusters 6 and 8 remained prominent for cell cycle, chromosome and mitosis gene signatures (Supplementary Table 2). Cluster 7 represents chondrogenic precursors with expression of Sema3c and Prelp. Cluster 9 represents chondrocyte precursors with expression of Acan, Ucma, Col9a1, Sox9 and Col2a1.
Given the initial seeding of PαS SSCs (cluster 2) and subsequent emergence of precursors with chondrogenic (clusters 6-9), osteogenic (clusters 3 and 5) and adipogenic (cluster 4) properties, we hypothesize that precursors were generated through intermediate SSPCs (clusters 0 and 1). Pseudotime projection analysis with Slingshot was performed to identify possible branching events representing cell lineages (Street et al. 2018). This suggested two major lineage trajectories from cluster 2 as the top of the hierarchy: one trajectory leads through Sca1/Ly6ahigh SSPCs (cluster 1) to chondrogenic precursors, and the other leads through Pdgfrahigh SSPCs to osteogenic/adipogenic precursors (Figure 3F). The lineage scheme from SSCs to SSPCs to precursors is summarized in Figure 3G.
PDGFRβD849V impairs osteogenesis
To identify changes in clusters and gene expression due to PDGFRβD849V, we split the scRNA data into controls (S+/- and S-/-) and mutants (KS+/- and KS-/-). Pdgfrb mRNA was moderately decreased in KS+/- and KS-/- genotypes, as shown previously in dermal fibroblasts (He et al. 2017), and Stat1 mRNA was absent from S-/- and KS-/- (Supplementary Figure 5A). We quantified the abundance of each cluster as a percentage of all cells represented by control or mutant genotypes (Figure 4A). Clusters that were increased or decreased in mutant colonies compared to controls were color-coded in the lineage map summaries (Figure 4B). PDGFRβD849V colonies particularly decreased osteogenic clusters (cluster 3 and 5). To identify specific gene expression changes, we further analyzed scRNA data with the Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis (Huang da et al. 2009) (Supplementary Table 3 and 4). We found that PDGFRβD849V colonies downregulated osteogenesis-related genes including Col1a1, Col1a2, Mmp13, Ptx3, Serpine1 and Serpinf1 (Figure 4C). Their expression levels were decreased in almost all clusters, suggesting a broad impact across skeletal lineages (Figure 4D).
To examine PDGFRβ-mediated osteogenic defects in vitro, we isolated primary SSPCs from 3-week-old long bones (see Methods) and cultured them for osteoblast differentiation with a standard cocktail of inducers. KS+/- and KS-/- SSPCs showed reduced alkaline phosphatase staining, which indicates defective osteoblast differentiation (Figure 4E), and reduced alizarin red staining, which indicates defective mineralization (Figure 4F).
Next, to examine bone mass and mineralization in mice, we used micro-computed tomography (microCT) to examine 3-week-old tibias from the four original genotypes. KS+/- bones displayed osteoporosis-like pores in the cortical bone of the diaphysis (Figure 5A) and reduced trabecular bone formation in the proximal tibial metaphysis (Figure 5B). KS-/- bones had no pores and partially normalized bone mass and mineralization in both cortical and trabecular regions (Figure 5A and 5B). However, 5 to 8-week-old KS-/- bones displayed less bone mass and mineralization in the cortical bone of the diaphysis (Figure 5C) and the proximal tibial metaphysis (Figure 5D) compared to age-matched control bones. To corroborate PDGFRβD849V-mediated bone formation defects, we performed calcein double staining to quantify mineral appositional growth rate (MAR). Histomorphometric analysis of cortical bone at 3 weeks showed decreased bone growth in KS+/-, which was normalized in KS-/- (Figure 5E). Interestingly, 6-week-old KS-/- cortical bone showed increased MAR compared to controls (Figure 5F), but the calcein labelling was thicker and more diffuse than controls, which is consistent with incomplete or delayed mineralization. In summary, as suggested by transcriptomics, we find that PDGFRβD849V impairs osteogenic differentiation in cells derived from KS+/- and KS-/- mice, and leads to osteopenia that becomes severe early in KS+/- mice (by 3 weeks) and later in KS-/- mice (by 6 weeks).
PDGFRβD849V and STAT1 augment chondrogenic fate of SSCs
The growth and survival phenotypes (Figure 1A), and the time required to develop osteopenic phenotypes (Figure 5) are very different between KS+/- and KS-/- mice. This indicates a strong modifier effect of Stat1, at least in part due to Stat1-mediated autoinflammation downstream of PDGFRβD849V (He et al. 2017). To identify changes in cell clusters and gene expression contributed by Stat1, we split the scRNA data into four groups representing the original genotypes S+/-, S-/-, KS+/- and KS-/- (Supplementary Fig. 5A and 5B, Supplementary Table 6). We found that KS+/- decreased SSCs (cluster 2), but prominently increased chondrogenic SSPCs (cluster 1), proliferating chondrocytes (cluster 6 and 8) and Acanhigh-chondrogenic precursors (cluster 9) compared to two controls (Figure 6A, Supplementary Figure 5B and 5C). In comparison, KS-/- moderately increased the chondrogenic SSPCs (cluster 1) and proliferating chondrogenic precursors (cluster 8), but less than KS+/-. We further analyzed differentially expressed genes specific to the KS+/- genotype (Supplementary Figure 5B and 5D). Among 34 genes specifically upregulated in KS+/- versus the other three genotypes, cartilage development genes were highly enriched, including Sox9, Col2a1, H19 and Acan (Figure 6B, Supplementary Table 3 and 4). Increased Sox9, Col2a1 and H19 expression was not limited to cluster 9, but also showed increased expression in other clusters (Figure 6C, Supplementary Figure 5E). Col2a1 and H19 are known downstream targets of Sox9, which is a master transcription factor for chondrocyte proliferation and differentiation (Akiyama et al. 2002) and directly regulates collagen 2 production (Bell et al. 1997). Sox9 also indirectly promotes collagen 2 expression via a long non-coding RNA H19 and its micro-RNA, miR675 (Dudek et al. 2010). This suggests that increased Sox9 in KS+/-SSCs promotes chondrogenic proliferation and commitment. To evaluate chondrogenesis in vivo, we analyzed Safranin-O-stained tibias at 3 weeks old. Although KS+/- tibias were smaller in size, the proportional area of KS+/- cartilage was larger than the three other genotypes (Figure 6D). KS-/- also mildly increased cartilage area. We evaluated Sox9 expression in vivo in femurs from 3-week-old mice. Sox9-positive cell numbers were increased in both KS+/- and KS-/- genotypes, each with a distinct distribution in the distal femur. KS+/- showed ectopic expansion of Sox9-positive cells near the growth plate (Figure 6E). KS-/- also increased Sox9-positive chondrocytes in the proliferating and prehypertrophic zones within the growth plate (Figure 6E), consistent with the expansion of proliferating chondrogenic precursors (clusters 1 and 8) (Supplementary Figure 5D). To evaluate KS+/- chondrogenesis in autoinflammation-free conditions, we performed pellet culture with primary SSPCs from 3-week-old long bones of the four genotypes. We found that KS+/- SSPCs dramatically increased pellet size compared to the others after 21 days in culture (Figure 6F). Interestingly, while many KS+/- cells appeared to have matured into chondrocytes in matrices that were strongly positive for toluidine blue and safranin-O, cells in the pellet core appeared to remain undifferentiated (Figure 6F). KS+/- cells often generated irregular donut shaped pellets, unlike spherical pellets formed by control cells. KS-/- cells generated chondrocyte pellets similar to controls. Together, these findings suggest that PDGFRβD849V and STAT1 enhance chondrogenic fate within the SSC lineage.
Low interferon signature in SSCs
Since KS+/- mice showed wasting due to PDGFRβ-STAT1-mediated auto-inflammation, and KS+/- intrinsically overexpress interferon-stimulated genes (ISGs) in dermal fibroblasts (He et al. 2017) and SSPCs (Supplementary Figure 6A), we examined whether KS+/- SSCs also exhibit an ISG signature. A few ISGs, including Ifi27, Bst2, Isg15, Ifit1, Psmb8, Mx1, and Stat1, were upregulated in KS+/- SSCs throughout all clusters (Supplementary Figure 6B-6D). However, expression was very low for most ISGs and was detected in few cells of the SSC colonies regardless of genotype. It has been shown that other types of stem cells are intrinsically protected from interferon responses (Burke et al. 1978; Eggenberger et al. 2019), and this may be true as well for SSCs.
PDGFRβD849V activates STAT5 and increases Igf1 expression
Although both KS+/- and KS-/- mutants showed defective mineralization, only KS-/- showed overgrowth in vivo. From scRNA data, we found that Igf1 and Socs2 were highly upregulated in KS-/- SSC colonies and were upregulated to a lesser amount in KS+/- colonies, compared to controls (Figure 7A). Increased Igf1 and Socs2 mRNAs were detected in most KS+/- and KS-/- clusters, from SSCs to precursors (Figure 7B). Igf1 and Socs2 are direct transcriptional targets of STAT5. The STAT5-IGF1 axis is critical for the biological effects of growth hormone receptor signaling (Udy et al. 1997; Chia et al. 2006), and SOCS2 is involved in negative feedback on STAT5 (Greenhalgh et al. 2002). It is known that PDGFRβ can phosphorylate STAT5 (Valgeirsdottir et al. 1998), although the biological significance is unclear. Interestingly, Stat5a mRNA was overexpressed by KS+/- colonies and Stat5b was overexpressed by KS-/- colonies (Figure 7C). However, the role of STAT5 in signaling and gene activation is mainly regulated by phosphorylation. Both KS+/- and KS-/- SSC colonies exhibited constitutive STAT5 phosphorylation (Figure 7D), and STAT5 was constitutively phosphorylated in SSPCs from both mutants (Figure 7E). The antibodies used for these Western blots detect both STAT5 proteins and therefore cannot discern whether there is differential activation of the two isoforms in KS+/- and KS-/- colonies. Based on these results, we suggest that STAT5-IGF1 axis could be a key signaling pathway for PDGFRβ-mediated overgrowth. Serum IGF1 levels were very low in 3-week-old KS+/- mice, which were moribund. Serum IGF1 was unchanged between controls and KS-/- mice, which were on the cusp of overgrowth (Figure 7F). However, IGF1 levels were elevated in culture medium of KS+/- and KS-/- SSPCs (Figure 7G). Therefore, PDGFRβ mutant skeletal lineages may promote skeletal overgrowth by increasing IGF1 levels locally, rather than systemically. We suggest that both KS+/- and KS-/- mice have potential for overgrowth due to increased signaling through the STAT5-IGF1 axis. But KS+/- mice do not exhibit the overgrow phenotype because of growth-suppressive (and lethal) effects of Stat1-mediated autoinflammation.
Discussion
The depletion of SSCs by conditional diphtheria toxin expression in mice shows the importance of SSCs in skeleton growth (Worthley et al. 2015; Mizuhashi et al. 2018), but signaling pathways and genes regulating SSC functions are still largely unknown. In this study, we found that increased PDGFRβ signaling alters SSC abundance and lineage differentiation in parallel to phenotypes affecting the skeleton. Our results suggest that constitutive PDGFRβ signaling in SSCs precedes alterations in osteogenic and chondrogenic differentiation. These cell-autonomous and skeletal lineage-autonomous defects, combined with systemic effects of constitutive PDGFRβ signaling (including interferonopathy-like autoinflammation), lead to osteopenia and skeletal phenotypes that are reminiscent of humans with PDGFRB mutations.
Our work demonstrates the utility of using scRNA sequencing to uncover pathways and genes in cultured stem cells to provide new molecular understanding of diseases. Colony formation assays have long been used to assay for the enrichment of cells with stem cell properties, but it has been challenging to identify molecular targets or cellular pathways due to the rarity of SSCs. In our case, it was important to isolate SSCs and culture them because the KS+/- mutants exhibit severe autoinflammation in vivo. With scRNA transcriptomics of cultured SSCs, we overcame these limitations and identified sub-populations of SSC and precursor cells with alterations that are linked to phenotypes in KS+/- and KS-/- mutant mice.
We found that wasting KS+/- mutants and overgrown KS-/- mutants both exhibit impaired osteogenesis in vivo. Both mutant SSC colonies decreased osteogenesis-related genes such as Col1a1, Col1a2, and Serpinf1 and both mutant SSPCs showed reduced osteogenic differentiation and mineralization capacities. Similar to mice, humans show osteogenesis imperfecta caused by loss of function mutations in COL1A1 or COL1A2 (MIM 166200) or SERPINF1 (MIM 172860) with decreased mineralization and brittle bones (Byers and Pyott 2012). However, differentially expressed genes between KS+/- and KS-/- mutants suggest that Stat1-depedent mechanisms are also involved. We highlighted increased Sox9 expression in KS+/- mice and SSC colonies as an intrinsic source of osteogenesis defects because Sox9 overexpression in mice leads to impaired osteogenesis and dwarfism (Akiyama et al. 2004; Zhou et al. 2006). KS+/- osteogenesis defects in vivo are likely compounded by autoinflammation (Redlich and Smolen 2012). The kidneys are critical for maintaining healthy bones by regulating phosphorous and calcium levels in the blood. A PDGFRβ gain-of function mutation controlled by Foxd1Cretg has been shown to cause mesangioproliferative glomerulonephritis and renal fibrosis with progressive anemia in mice (Buhl et al. 2020). However, as these phenotypes begin to appear at 6 weeks of age, renal dysfunction is unlikely to initiate skeletal phenotypes in our mice, but it may contribute to later progression in KS-/-.
Our study suggests that PdgfrbD849V signaling through STAT1 promotes Sox9 expression and chondrocyte proliferation. We found that KS+/- SSPCs formed irregularly shaped chondrocyte pellets. The non-spherical morphology may occur because of excessive cartilage matrix. For example, bone marrow stromal cells obtained from familial osteochondritis dissecans (FOCD) patients (ACAN loss-of-function mutant) produce enlarged and irregularly shaped chondrocyte pellets with highly upregulated cartilage matrix proteins including collagen 11 and proteoglycans (Xu et al. 2016). We found that Acan, Col2a1, and Col11a1 were all upregulated in KS+/- SSC colonies. We do not know how PdgfrbD849V-STAT1 regulates Sox9. But STAT3, a related transcription factor, has been shown to directly regulate Sox9 in chondrogenesis (Hall et al. 2017), and STAT1 can heterodimerize with STAT3.
SSCs with PdgfrbD849V increase functional SSC numbers and growth signaling gene expression (ie., Igf1 and Socs2). STAT5 may be an important mediator of overgrowth because Igf1 is a direct transcriptional target of STAT5, which is directly activated by PDGFRβ (Valgeirsdottir et al. 1998; Chia et al. 2006). STAT5 activation is constitutive in mutant SSCs and SSPCs, but only KS-/- induces overgrowth. As discussed above, there are additional effectors in KS+/- to counterbalance potential overgrowth, such as STAT1-dependent autoinflammation and Sox9 expression. Furthermore, KS+/- SSCs upregulated the expression of IGF binding proteins (IGFBP3, 6 and 7) (Supplementary Table 3 and 4), potentially blocking IGF1 signals. Increased IGF1 in KS-/- mice seems to occur locally in SSCs and SSPCs rather than systemically because increased IGF1 was detected in mutant SSPC conditioned medium but not in mutant mouse circulation. We do not know if IGF1 causes overgrowth through autocrine signaling or by signaling between cell types. Tissue-specific genetic studies will be needed to investigate the involvement of a PDGFRβ-STAT5-IGF1 axis and to identify IGF1-responsive cells.
Although the D849V mutation in our study is not the same as mutations seen in Penttinen syndrome and Kosaki overgrowth syndrome, we believe our findings here are closely related to the human conditions. Osteopenia, often associated with bone fractures, is a common feature in both human diseases. For example, two Kosaki overgrowth syndrome patients developed fractured tibias and compression fractures in the spine, causing deformation of their bones (Minatogawa et al. 2017; Foster et al. 2020). Further, a Penttinen Syndrome patient exhibited osteoporosis with multiple fractures (Johnston et al. 2015). Similarly, we found osteopenia in PdgfrbD849V mice regardless of their phenotype on the wasting-overgrowth spectrum. A better understanding of the pathogenic mechanisms of different activating PDGFRβ mutations will be obtained through future genetic models that reproduce the specific human PDGFRB mutations seen in Penttinen and Kosaki syndromes. The current work puts forth SSCs as a conceptual tool for considering pathological changes in the PDGFRβ mutant skeleton as resulting from altered stem cell functions.
Materials and Methods
Animal models
Mouse strains PdgfrbD849V (#018435), Sox2Cretg (#008454) and Stat1flox (#012901) are available at the Jackson Laboratory. All procedures performed on mice were approved by the Institutional Animal Care and Use Committee of the Oklahoma Medical Research Foundation. Mice were maintained on a mixed C57BL/6;129 genetic background with a standard mouse chow diet (5053 Purina). Mutant KS+/- and KS-/- mice were compared with age and sex-matched littermate control S+/- and S-/- mice.
Fluorescence-activated cell sorting (FACS) and CFU-F of skeletal stem cells
PDGFRα and Sca1 double positive SSCs (PαS cells) were isolated by the method of Houlihan et al. (Houlihan et al. 2012) with some modifications. FACS buffer was made of 1x HBSS (Gibco), 2% FBS, 1x penicillin/streptomycin (Gibco), 1 mM ethylenediaminetetraacetic acid (EDTA, VWR) in autoclaved H2O. Limbs of control and mutant mice at 3, 6 and 9 weeks old were dissected and soaked in 70% EtOH for 2 mins, followed by careful removal of adherent muscles. Bone marrow (BM) was flushed 2-3 times with sterile PBS using a 26G x 1/2 needle and 1 ml syringe (BD). BM-free bones were cut into small pieces with sterile scissors until bones became paste (usually 3 mins for 3 weeks old and 5 mins for 6-9 weeks old). The bone paste from each mouse was transferred to a 15 ml conical tube and enzymatically digested with 15 ml 0.2% type II collagenase (Worthington) in DMEM (Corning) for 1 hour with agitation at 37 °C. Digested bone paste was filtered through 70 μm cell strainer and collected in a 50 ml conical tube on ice. Bone paste remaining on the filter was collected with 2.5 ml FACS buffer, gently tapped in a mortar with a pestle and filtered into the same 50 ml conical tube on ice. This was repeated until the total volume of filtrate reached 50 ml. After centrifugation at 280 x g for 10 min at 4 °C, 1 ml ice-cold sterile H2O was used to remove red blood cells for 6 sec. Then 1 ml 4% FBS in PBS and 13 ml FACS buffer were added, followed by filtering with 70 μm cell strainer into a new 15 ml tube. After centrifugation for 5 min, re-suspended cells were incubated with fluorophore-conjugated antibodies (Supplementary Table 8) on ice for 20 min in dark. PαS cells were sorted using MoFlo XDP Cell Sorter (Beckman Coulter) or FACSAria III (BD) by negative gating with Zombie GreenTM(live/dead cell dye), CD31, CD45 and TER119 and positive gating with PDGFRα and Sca1 (Supplementary Figure 2). For colony formation assays, 2,000 PαS cells were cultured in a 6-well plate with 20% FBS (mesenchymal stem cell-qualified, Gibco), 25 units/mL penicillin/streptomycin and 2 mM L-glutamine in alpha MEM (Gibco) for 2 weeks under hypoxia (5% oxygen) at 37 °C. Colonies were fixed with 4% PFA for 5 min and stained with 0.5% crystal violet for quantification.
Single-cell RNA sequencing and annotation
Single-cell suspensions of PαS colonies were harvested from CFU-F assays after culturing for 2 weeks as explained above. Trypsinized cells were filtered through a 40 μm cell strainer. 4 batches were generated in duplicate with 1 male and 1 female of each genotype. A total of 8 samples (maximum 20,000 cells per each sample) were loaded for the 10X Genomics Chromium platform, barcoded, and sequenced on the Illumina NovaSeq SP flowcell platform at a depth of 400 million reads per sample. See Supplementary Table 5 for actual cell numbers sequenced and analyzed. Using the 10X Genomics Cellranger software (version 3), sequences were demultiplexed to extract cellular barcodes, cDNA inserts and unique molecular identifiers (UMIs) and the cDNA sequences were aligned to the murine mm10 genome reference to count UMIs. Quality control, data integration, clustering and gene expression analysis were performed with Seurat package V3 for R (Butler et al. 2018; Stuart et al. 2019). Cells with > 8,000 genes, < 1,500 genes, or > 8% of genes mapping to mitochondrial genes were removed as poor quality or doublets. Eight samples were individually normalized by using the log transformation method in Seurat. Data integration of 8 samples to remove batch effect was done with canonical component analysis (CCA) with the top 2,000 variable genes identified by FindVariableFeatures function in Seurat (Butler et al. 2018). Cells were categorized into S, G1 or G2/M phase by scoring cell cycle-associated gene expression (Kowalczyk et al. 2015). Principal component analysis (PCA) was performed by regressing out cell cycle, mitochondrial and ribosomal gene expression. The top 100 PCs were selected to perform dimensional reduction using uniform manifold approximation and projection (UMAP). We determined a cluster resolution of 0.4 (total 12 Clusters) using Clustree R package (graphic-based cluster resolution analyzer) (Zappia and Oshlack 2018). Among the 12 clusters, 10 were selected for analysis, because 2 of the clusters only included about 10 cells per each. A heatmap was generated with the top 10 genes (Supplementary Table 1) in each cluster determined by FindAllMarkers function in Seurat. For gene signature analysis, differentially expressed genes (DEGs) of each cluster were determined by FindMarkers function in Seurat with 0.25 log-scale fold-change threshold between two groups (ie., genotypes). DEGs were further analyzed with the Database for Annotation, Visualization and Integrated Discovery (DAVID) to determine gene ontology and pathway identification (Huang da et al. 2009). Cell types of clusters were defined with a signature gene list, gene ontology and literature as SSCs, SSPCs, chondrocyte precursors, osteoblast precursors and adipocyte precursors. Trajectory analysis was performed using Slingshot (Street et al. 2018). SingleCellExperiment objects (transformed from Seurat objects) and UMAP information were utilized as input for trajectory predictions. We selected cluster 2 (SSCs) as the top of the hierarchy. Sub-grouping and trajectory analysis with chondrogenic lineages (clusters 1, 2, 6, 7, 8 and 9) were additionally performed to determine an additional branch (clusters 8>6>9). To identify PDGFRβ GOF-specific genes and clusters, we split the integrated data into 2 groups (controls S+/- and S-/- versus mutants KS+/- and KS-/-) or 4 groups (individually S+/-, S-/-, KS+/- and KS-/-). DEGs between 2 or 4 groups were identified with by FindMarkers function in Seurat.
Primary skeletal stem and progenitor cell (SSPC) culture and tri-lineage differentiation
Compact bone was used to isolate primary skeletal stem and progenitor cells (Zhu et al. 2010). BM-free bones were collected as described above and were cut into small pieces (1-3 mm3) with sterile scissors. The bone chips were transferred into a 1.6 ml microcentrifuge tube and enzymatically digested with 1.5 ml of 1 mg/ml type II collagenase (Worthington) in alpha MEM (Corning) plus 10% FBS (mesenchymal stem cell-qualified, Gibco) for 1.5 hours with agitation in a 37 °C incubator. The bone chips were washed with 1 ml of alpha MEM, seeded into a 6-well plate, and maintained with alpha MEM plus 10% FBS (mesenchymal stem cell-qualified, Gibco), 25 units/mL penicillin/streptomycin and 2 mM L-glutamine at 37 °C. 0.25 %. Passages 4 to 6 were used for tri-lineage differentiation assays. For osteogenesis, 2 x 105 cells were seeded in a 24-well plate. On the following day, they were treated with alpha MEM supplemented with 10% FBS (mesenchymal stem cell-qualified), 10-7 M dexamethasone, 10 mM β-glycerol-phosphate and 50 mM ascorbate-2-phosphate. Medium was changed 3 times per week for 2 weeks (early osteoblast differentiation) and 4 weeks (mineralization). After 2 weeks, some samples were subjected to alkaline phosphatase (ALP) staining with ALP buffer (100mM Tris-HCl, 100mM NaCl, 5mM MgCl2, 0.05% Tween-20 in deionized water (adjusted at pH 9.5)) plus 0.02% 5-bromo-4-chloro-3-indolyl phosphate (BCIP) and 0.03% nitro blue tetrazolium (NBT). After 4 weeks, some samples were stained with 40 mM alizarin red. For chondrogenesis, 1 x 106 cells were pelleted in a 15 ml conical tube at 280 x g for 6 min at 4 °C and cultured for 3 weeks with the MesenCultTM-ACF chondrogenic differentiation kit (Stemcell Tech). Pellets were fixed with 4% PFA for 1 hour, embedded in paraffin, sectioned at 8 μm and stained with 0.05% toluidine blue or 1% safranin-O. For SSC colony osteogenesis, colonies cultured for 2 weeks under hypoxia were further treated with the osteogenesis inducers as explained above for additional 2 weeks under normoxia and stained with alkaline phosphatase (Fast green as a counterstain). For SSC colony adipogenesis, 2-week-cultured colonies were treated with alpha MEM supplemented with 10% FBS (mesenchymal stem cell-qualified), 10-6 M dexamethasone, 250 μM IBMX, 10 μg/ml insulin and 5 nM rosiglitazone for 2 days. Colonies were maintained with alpha MEM plus 10% FBS (mesenchymal stem cell-qualified) and 10 ng/ml insulin for additional 8 days by changing 3 times in a week. Adipocytes were quantified with Oil-O-Red stain (Fast green as a counterstain).
Enzyme-linked immunosorbent assay (ELISA)
IGF1 levels were measured in serum and SSPC culture supernatant using ELISA (Sigma-Aldrich, RAB-0229) according to the manufacturer’s protocol. Blood was collected from four genotypes at 3 weeks old, incubated at room temperature for 30 min, and centrifuged at 1,000 rpm for 10 min at 4 °C. Clear supernatant was stored at −20 °C until used. SSPCs (passages 4-5) isolated from four genotypes at 3 weeks old were cultured in a 24-well plate until confluent. After washing three times with sterile PBS, 500 μl serum-free fresh alpha MEM was replaced and cultured for 72 hrs. Cell culture supernatant was filtered through a 20 μm cell-strainer and stored at −20 °C until used. Both serum and cell culture supernatant were diluted to 1:100 for ELISA.
Western blotting
For PαS SSC colonies, cells were starved in medium containing 0.2% FBS (mesenchymal stem cell-qualified) for 24 hours. For SSPCs, cells were starved in medium containing 0.1% FBS (mesenchymal stem cell-qualified) for 24 hours and treated with 10 ng/ml PDGF-BB (R&D systems) for 10-15 min. Cells were then lysed in RIPA buffer (50mM Tris pH 7.4, 1% NP-40, 0.25% sodium deoxycholate, 150 mM NaCl, 0.1% sodium dodecyl sulfate) with 1 mM NaF, Na3VO4, PMSF, and 1x protease inhibitor cocktail (Complete, Roche). Pierce BCA assay was utilized to determine protein concentration. Aliquots of 5-10 μg of protein were separated by SDS-PAGE, transferred to nitrocellulose membranes, blocked with 5% BSA, and incubated with primary antibodies (Supplementary Table 8) overnight at 4 °C. Membranes were probed with horseradish peroxidase (HRP)-conjugated secondary antibodies at 1:5000 (Jackson ImmunoResearch) in 5% milk. Pierce ECL Western blotting substrate (ThermoFisher) and autoradiography film (Santa Cruz) were utilized to develop blots.
RNA isolation and qRT-PCR
Total RNA was isolated from cultured primary skeletal stem and progenitor cells enriched from compact bones using Trizol (ThermoFisher). cDNA reverse transcription was performed with Superscript III RT (Invitrogen) and random primers. Quantitative PCR was performed using a Bio-Rad iCycler with iQ TM SYBR green master mix and designated primers (Supplementary Table 7).
Tissue and histology
Tissue was fixed overnight in 10% neutral buffered formalin (NBF, Sigma-Aldrich) or 4% paraformaldehyde (PFA, Electron Microscopy). Bones were decalcified in 0.5 M EDTA solution (pH 7.4) for 2 weeks at room temperature. For cartilage staining, fixed tissues were embedded in paraffin and sectioned at 6 μm thickness followed by Hematoxylin and Eosin (H&E) or Safranin O staining (Fast green and Hematoxylin as counter stain). For tartrate-resistant acid phosphate (TRAP) staining, fixed tissues were decalcified in 0.5 M EDTA solution at 4 °C, dehydrated in 20% sucrose in PBS and cryosectioned at 8-10 μm thickness followed by Naphthol AS-BI phosphoric acid and diazotized Fast Garnet GBC stains (Fast green as counter stain) (Sigma Aldrich, 387A). For immunostaining, PFA-fixed tissues were cryosectioned at 8-12 μm. Slides were stained with primary and secondary antibodies (Supplementary Table 8) and DAPI (Sigma) as a nuclear stain. Imaging was performed with a Nikon Eclipse 80i microscope with a digital camera.
Bone formation rate and microcomputed tomography
To measure the mineral appositional growth rate (MAR) of bone formation, double calcein stain was performed. calcein (10 mg/kg, Sigma) in 0.9% NaCl and 2% NaHCO3 was intraperitoneally injected in 3- or 6-week-old mice with a 4-day interval. Mice were harvested 2 days after the second injection. Paraffin sectioning was performed as per the method of Porter et al. (Porter et al. 2017): femurs were harvested with adherent muscles and fixed with formalin for 2 days, then cleared with 10% KOH for 96 hours. The tissues were embedded in paraffin and sectioned at 6 μm thickness, pre-soaking the paraffin blocks in 1% KOH just before sectioning. For microCT, tibias were harvested and stored in 70% EtOH at 4 °C, then analyzed to measure bone volume (BV, mm3), total volume (TV, mm3), mean/density (mg HA/ccm), trabecular numbers (1/mm), trabecular thickness (mm), and trabecular separation (mm) with a VivaCT 40 microCT (Scanco Medical) at an X-ray tube volatage of 70 kVp and an X-ray current 114 μA for 2- to 3-week-old bones or 55 kVp and 85 μA for older bones.
Image quantification and statistics analysis
The size of CFU-F and chondrocyte pellets, and the distance between double calcein stain, were quantified with ImageJ software (National Institute of Health). The Set Scale function was used to convert units from pixels to mm or μm with known scale of images. Regions of interest (ROIs) were selected using the polygon selection tool to measure the area of CFU-F and pellet images. The straight tool was utilized to measure the distance between double calcein stain. Statistical calculations were performed by using GraphPad Prism 9 with one-way or two-way ANOVA. Data were represented with mean ± standard error of the mean (SEM).
Author contributions
H.R.K designed experiments and analyzed data. H.R.K., J.P.W., and J.K. performed experiments. H.R.K. and L.E.O. wrote the manuscript. H.R.K., J.P.W., and L.E.O. edited the manuscript. All authors read and approved the final manuscript.
Acknowledgements
We thank Jacquelyn C. Herron, Shouan Zhu, Mary Beth Humphrey, Timothy M. Griffin, and members of the Olson lab for their assistance and helpful discussion. We also thank the Microscopy Core and Mouse Phenotyping Core Facilities (associated with P30-GM114731) of the Oklahoma Medical Research Foundation Centers of Biomedical Research Excellence. H.R.K. was supported by F32-HL142222 from National Institutes of Health (NIH)/National Heart, Lung, and Blood Institute (NHLBI). This work was supported by US National Institutes of Health (NIH) grant R01-AR073828 (L.E.O.) and grants from the Oklahoma Center for Adult Stem Cell Research – a program of TSET (L.E.O).