1. Cell Biology

Periosteal skeletal stem cells can migrate into the bone marrow and support hematopoiesis after injury

  1. Tony Marchand  Is a corresponding author
  2. Kemi E Akinnola
  3. Shoichiro Takeishi
  4. Maria Maryanovich
  5. Sandra Pinho
  6. Julien Saint-Vanne
  7. Alexander Birbrair
  8. Thierry Lamy
  9. Karin Tarte
  10. Paul Frenette
  11. Kira Gritsman  Is a corresponding author
  1. Service d’hématologie Clinique, Centre Hospitalier Universitaire de Rennes, France
  2. UMR U1236, INSERM, Université Rennes, EFS Bretagne, Equipe Labellisée Ligue Contre le Cancer, France
  3. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, United States
  4. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, United States
  5. Department of Medical Oncology, Albert Einstein College of Medicine, United States
  6. Department of Pharmacology & Regenerative Medicine, University of Illinois at Chicago, United States
  7. Department of Dermatology, University of Wisconsin-Madison, United States
  8. Laboratoire Suivi Immunologique des Thérapeutiques Innovantes, Centre Hospitalier Universitaire de Rennes, France
https://doi.org/10.7554/eLife.101714.3
Share this article
Cite this article
  1. Tony Marchand
  2. Kemi E Akinnola
  3. Shoichiro Takeishi
  4. Maria Maryanovich
  5. Sandra Pinho
  6. Julien Saint-Vanne
  7. Alexander Birbrair
  8. Thierry Lamy
  9. Karin Tarte
  10. Paul Frenette
  11. Kira Gritsman
(2025)
Periosteal skeletal stem cells can migrate into the bone marrow and support hematopoiesis after injury
eLife 13:RP101714.
https://doi.org/10.7554/eLife.101714.3
  2. Download BibTeX
  3. Download .RIS

eLife Assessment

The study presents valuable insights into the role of periosteal stem cells in bone marrow regeneration. The evidence is convincing. The data broadly support their claims and in line with state-of-art methodology. Future study on their model will help to strengthen their discovery further.

https://doi.org/10.7554/eLife.101714.3.sa0

Abstract

Skeletal stem cells (SSCs) have been isolated from various tissues, including periosteum and bone marrow, where they exhibit key functions in bone biology and hematopoiesis, respectively. The role of periosteal SSCs (P-SSCs) in bone regeneration and healing has been extensively studied, but their ability to contribute to the bone marrow stroma is still under debate. In the present study, we characterized a mouse whole bone transplantation model that mimics the initial bone marrow necrosis and fatty infiltration seen after injury. Using this model and a lineage tracing approach, we observed the migration of P-SSCs into the bone marrow after transplantation. Once in the bone marrow, P-SSCs are phenotypically and functionally reprogrammed into bone marrow mesenchymal stem cells (BM-MSCs) that express high levels of hematopoietic stem cell niche factors such as Cxcl12 and Kitl. In addition, using ex vivo and in vivo approaches, we found that P-SSCs are more resistant to acute stress than BM-MSCs. These results highlight the plasticity of P-SSCs and their potential role in bone marrow regeneration after bone marrow injury.

eLife digest

Bone marrow is the soft tissue inside the bones in our bodies. It is the main production facility for new blood cells and makes billions of blood cells daily. However, like any other tissue or organ, the bone marrow can be damaged, for example, by radiation, chemotherapy drugs, or physical injuries like broken bones.

Bone marrow mesenchymal stromal cells or BM-MSCs are a key component of the bone marrow and are responsible for regulating self-renewal, and for proliferation and differentiation of a group of blood-cell producing stem cells called hematopoietic stem cells or HSCs.

A type of skeletal stem cell, the periosteal skeletal stem cells or P-SSCs, are located in a part of the bone called the periosteum, a thin tissue surrounding long bones. These cells are known to help bones regenerate and heal following a fracture. They are thought to share functional similarities with BM-MSCs. However, it is unclear if P-SSCs also support the recovery of blood cell production after damage to the bone marrow.

To find out more, Marchand, Akkinola et al. used bone tissue derived from genetically engineered mice whose P-SSCs produced a fluorescent tag. Transplanting this bone tissue into otherwise healthy mice mimicked the changes usually seen in the bone marrow after an injury. Microscopy imaging of the transplanted bone at different stages revealed that P-SSCs migrated into the bone marrow after the transplantation injury.

Once in the bone marrow, the P-SSCs developed BM-MSC-like characteristics, producing proteins known to support HSPCs. In other words, P-SSCs effectively transformed into new BM-MSCs, to the extent that the transplanted bone marrow could begin producing blood cells again. Further genetic analysis of P-SSCs and BM-MSCs showed that genes involved in stress resistance were more active in the P-SSCs. This suggests that P-SSCs are better at responding to stress, which may be helpful immediately after an injury.

Marchand, Akkinola et al. have developed a new model to study how the bone marrow repairs itself after it is damaged. These findings may help contribute to a more detailed understanding of the mechanisms behind bone marrow regeneration, as well as treatments to improve recovery following injury.

Introduction

Bone marrow mesenchymal stem cells (BM-MSCs) are rare self-renewing multipotent stromal cells which are capable of multilineage differentiation into osteoblasts, chondrocytes, and adipocytes (Caplan, 1991; Dominici et al., 2006; Frenette et al., 2013). BM-MSCs are mostly localized around the blood vessels and represent an important component of the hematopoietic stem cell (HSC) microenvironment, also referred to as the niche. BM-MSCs closely interact with HSCs and secrete factors, including the C-X-C motif chemokine ligand (CXCL12) and stem cell factor (SCF), that control their self-renewal, differentiation, and proliferation capacities (Kunisaki et al., 2013; Asada et al., 2017; Ding et al., 2012; Acar et al., 2015; Omatsu et al., 2010; Sugiyama et al., 2006). Several studies have used cell surface markers (CD51+, PDGFRα+, Sca-1+) or reporter mice (Lepr-cre, Nestin (Nes)-GFP, Ng2-cre) to describe distinct BM-MSC populations with significant overlap (Kunisaki et al., 2013; Asada et al., 2017; Ding et al., 2012; Méndez-Ferrer et al., 2010; Zhou et al., 2014; Pinho et al., 2013; Morikawa et al., 2009).

Recent studies have suggested that the periosteum, a thin layer of fibrous material that covers the surface of long bones, is a source of skeletal stem cells (SSCs) for bone regeneration (Chan et al., 2015; Duchamp de Lageneste et al., 2018; Debnath et al., 2018; Arnsdorf et al., 2009; Ortinau et al., 2019). These periosteum SSCs (P-SSCs) have been described as sharing some characteristics with BM-MSCs (Chan et al., 2015; Duchamp de Lageneste et al., 2018; Debnath et al., 2018). However, the relationship between these different stromal cell populations is poorly understood and the distinction between MSCs and SSCs remains controversial.

While the bone marrow is classically known as a major source of MSCs, the bone cortex represents a richer source of colony-forming units-fibroblasts (CFU-F) (Pinho et al., 2013; Mizoguchi et al., 2014; Blashki et al., 2016). It has been suggested that bone regeneration is mediated by both endochondral and intramembranous ossification and that the periosteum plays an important role in bone regeneration after injury (Duchamp de Lageneste et al., 2018; Debnath et al., 2018; Utvåg et al., 1996; Wang et al., 2017b; Shapiro, 2008). However, there is little information on the function of P-SSCs, aside from their crucial role in bone healing and remodeling, and whether they contribute to bone marrow regeneration.

In the present study, we developed and characterized a whole bone transplantation model to study bone marrow regeneration, in which an intact adult femur is transplanted subcutaneously into a recipient mouse (Picoli et al., 2023). Shortly after transplantation, bone marrow architecture in the transplanted femur, hereafter referred to as the graft, is severely altered with an expansion of adipocytes that mimics the fatty infiltration classically observed in the bone marrow after chemotherapy or radiation (Zhou et al., 2017). This initial destruction of the bone marrow microenvironment is followed by a progressive regeneration of blood vessels and the BM-MSCs network. The graft is progressively colonized by host-derived HSCs, allowing hematopoiesis to resume. Unexpectedly, we found that P-SSCs can migrate into the bone marrow and acquire BM-MSC niche functions, making them capable of supporting hematopoiesis through the in vivo expression of specific niche genes, such as Cxcl12 and Kitl. In addition, we found that BM-MSCs and P-SSCs display different metabolic profiles, and that P-SSCs exhibit higher resistance to transplantation-induced stress. In conclusion, our study demonstrates the high plasticity of P-SSCs and highlights their potential contribution to bone marrow stroma regeneration after injury.

Results

The whole bone transplant model recapitulates physiological regeneration of the bone marrow

In order to study the mechanisms involved in bone marrow regeneration, we employed a model system based on the subcutaneous transplantation of an intact adult femur into non-conditioned age- and sex-matched recipient mice (Figure 1A). The bone transplantation is followed by a rapid and massive depletion of bone marrow cells in the engrafted femur with a cell viability reaching below 10% at 24 hr after transplantation (Figure 1—figure supplement 1A). Notably, bone marrow necrosis following bone transplantation is associated with the replacement of hematopoietic cells in the graft femur by marrow adipocytes, similar to the effects of chemotherapy or irradiation (Zhou et al., 2017; Yamazaki and Allen, 1991; Figure 1—figure supplement 1B). Following bone transplantation, we observed a progressive increase in bone marrow cellularity over time with no significant difference in cellularity between the graft and host femurs at 5 months following transplantation (Figure 1B). Regeneration of the bone marrow compartment is associated with a reduction in adipogenic infiltration, as revealed by staining with the anti-perilipin antibody at 4-month post-transplantation (Figure 1—figure supplement 1B). Additionally, the absolute number of graft BM-MSCs, defined as CD45−Ter119−CD31−CD51+CD140α+ cells by flow cytometry (Pinho et al., 2013), also increased over time, with no difference between the graft and host femurs at 5 months following transplantation (Figure 1B). We also observed a progressive increase in the number of Lin−Sca1+cKit+CD48−CD150+ phenotypic HSCs in the graft femur over time (Figure 1B). Although the absolute HSC numbers in the graft did not reach HSC numbers as detected in the host femur after 5 months (Figure 1B), no differences were observed in the numbers of hematopoietic progenitors or in the frequencies of hematopoietic cell populations between the host and graft femurs (Figure 1—figure supplement 1C). These data suggest that bone transplantation causes significant bone marrow injury, followed by a recovery process.

Figure 1 with 2 supplements see all
Download asset Open asset
Whole bone transplantation is a good model to study bone marrow regeneration.

(A) Schematic and picture of the bone transplantation procedure. (B) Fold difference quantification of graft femur/host femur cellularity normalized to mean host femur cellularity. Total graft bone marrow cells, bone marrow mesenchymal stem cells (BM-MSCs) and hematopoietic stem cells (HSCs) were analyzed monthly until 5 months after bone transplantation (BT) (n = 3). Ordinary one-way ANOVA with Dunnett multiple comparisons was used to determine statistical significance. (C) Schematic illustration of the non-competitive repopulating assay after bone transplantation. (D) Donor HSC contribution of graft and host recipients at 4 weeks after bone marrow transplantation (n = 10). (E) Quantification of tri-lineage (myeloid, B lymphoid, and T lymphoid cells) engraftment 4-week post-transplantation (n = 10). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. This figure was created with BioRender.com.

Hematopoiesis is a highly regulated and essential process by which all the differentiated blood cells are produced. To investigate whether functional hematopoietic progenitors fully recover in graft femurs, we performed a non-competitive bone marrow transplantation assay, in which we transplanted either graft or host bone marrow cells into lethally irradiated recipients at 5 months after bone transplantation (Figure 1C, Figure 1—figure supplement 2). The survival of lethally irradiated recipients remained equal in both groups, with 100% of recipients surviving throughout the length of the experiment. Chimerism analysis revealed robust engraftment of recipient mice with hematopoietic cells derived from the engrafted femurs, indicating that HSCs and progenitors derived from graft femurs can sustain long-term hematopoiesis upon transplantation (Figure 1D). We also observed no significant differences in donor cell contribution to myeloid or lymphoid lineages between the two groups (Figure 1E). Altogether, these data establish our bone transplantation model as a useful tool to study bone marrow and HSC-niche regeneration.

Graft BM-MSCs are graft-derived and progressively express HSC-niche factors during regeneration

Next, we aimed to determine the origin of the hematopoietic and stromal cell populations in the graft bone marrow. To achieve this, we took advantage of the Rosa26mT/mGand ubiquitin C (UBC) promoter-driven GFP mouse models, in which all cells are labeled by red and green reporters, respectively (Muzumdar et al., 2007; Liu et al., 2020). We transplanted femurs isolated from UBC-GFP mice into Rosa26mT/mG recipients and quantified endothelial cells, BM-MSCs, and hematopoietic cells in the graft (Figure 2A, B). Corroborating the results of Picoli et al., 2023, we observed that at 5 months post-transplantation, over 98% of the graft BM-MSCs originated from the graft femur, while over 99% of the hematopoietic cells in the graft originated from the host mouse (Figure 2C, D). Interestingly, endothelial cells were derived from both the host and the graft, suggesting the contribution of different progenitors. To further assess endothelial regeneration within the context of bone transplantation, we conducted a transplantation experiment in which femurs from Cdh5 (VE-cadherin)-CreER; iTdTomato (Wang et al., 2010) mice were transplanted into WT recipients. Confocal analysis was performed 15 days and 1 month after transplantation (Figure 2—figure supplement 1A, B). This revealed the presence of VE-cadherin-labeled vessels within the periosteum and crossing the cortical bone of the graft. This result demonstrates that endothelial regeneration occurs at an early stage following bone transplantation. Furthermore, when femurs from UBC-GFP mice were transplanted into Cdh5-CreER;iTdTomato mice, contributions of both recipient VE-cadherin-labeled and UBC-GFP vessels were observed 5 months later. This result once again demonstrated the dual contribution of endothelial cells to the grafted femur (Figure 2—figure supplement 1C). Furthermore, we did not detect any cells derived from the graft in the host femurs (data not shown). These results are consistent with data obtained from ossicle-based experiments, where MSC-seeded ossicles are colonized by recipient-derived hematopoietic cells (Méndez-Ferrer et al., 2010; Sacchetti et al., 2007; Friedenstein et al., 1968; Tavassoli and Crosby, 1968; Varas et al., 2000).

Figure 2 with 2 supplements see all
Download asset Open asset
Regenerating bone marrow mesenchymal stem cells (BM-MSCs) are graft-derived and express hematopoietic stem cell (HSC)-niche factors.

(A) Schematic of a UBC-GFP femur transplanted into a mT/mG mouse. (B) Representative FACS plots showing the gating strategy to determine the origin of the different cell fractions in the graft 5 months after transplantation of a UBC-GFP femur into a mT/mG mouse. (C) Representative whole-mount confocal z-stack projections of a UBC-GFP bone transplanted into a mT/mG recipient 5 months after transplantation. Vascularization was stained with anti-CD31 and anti-CD144 antibodies. Scale bar = 100 µm (n = 2 mice). (D) Origin of graft BM-MSCs, endothelial cells (EC) and hematopoietic cells (Hemato) analyzed by flow cytometry 5 months after bone transplantation (n = 2). (E) Schematic of the Nes-GFP femur transplantation into a Nes-GFP mouse recipient. (F) Quantitative RT-PCR analysis of mRNA expression of Cxcl12 and Kitl expression relative to Gapdh in graft Nes-GFP+ BM-MSCs compared to steady-state Nes-GFP+ BM-MSCs at multiple time points after transplantation (n = 2–4 mice per time point). One-way ANOVA with Dunnett multiple comparisons was used to determine statistical significance. Data are represented as the mean ± SEM. Unless otherwise noted, statistical significance was determined using unpaired two-tailed Student’s t-test. *p < 0.05, **p < 0.01, ***p < 0.001,. This figure was created with BioRender.com.

BM-MSCs are a major constituent of the hematopoietic niche, secreting maintenance factors that support HSCs and hematopoietic progenitors (Kunisaki et al., 2013; Asada et al., 2017; Ding et al., 2012; Zhou et al., 2014; Pinho and Frenette, 2019; Greenbaum et al., 2013). To test for HSC-niche supportive activity of graft BM-MSCs, we utilized Nes-GFP reporter mice to isolate BM-MSCs after bone transplantation. Previous work from our group has shown that Nes-GFP marks mouse MSCs with HSC-niche function within the bone marrow (Méndez-Ferrer et al., 2010). Since our previous analysis (Figure 2D) revealed that all of the graft BM-MSCs originate from the graft itself, we transplanted Nes-GFP femurs into Nes-GFP recipient mice and sorted CD45−Ter119−CD31−Nes-GFP+ BM-MSCs from donor and recipient mice for analysis at different time points (Figure 2E). Since we did not detect circulation of BM-MSCs between host and graft bone marrow in our bone transplantation experiments (data not shown), this strategy allowed us to compare host and graft BM-MSCs using equivalent markers. In addition to the previously described increase over time in the absolute number of BM-MSCs in the graft femur (Figure 1B), we observed a progressive increase in the expression of the HSC-niche genes Cxcl12 and Kitl (which encodes Scf), reaching a plateau at 5-month post-transplantation (Figure 2F). Similarly, no differences were observed between host and graft femurs in the expression levels of additional niche factors, including osteopontin (Opn) (Nilsson et al., 2005; Stier et al., 2005), angiopoietin-1 (Angpt1) (Arai et al., 2004), and vascular cell adhesion molecule-1 (Vcam1) (Jacobsen et al., 1996; Papayannopoulou et al., 1998) at 5 months (Figure 2—figure supplement 2A). In this experiment, host and graft BM-MSCs also had similar CFU-F activity at 5 months (Figure 2—figure supplement 2B). Altogether, these results show that by 5 months post-bone transplantation, the niche-supportive and ex vivo clonogenic functions of graft BM-MSCs are restored and are similar to the activity of native host BM-MSCs.

P-SSCs but not BM-MSCs expand early after bone transplantation

SSCs are multipotent cells of the skeletal lineage that are important for bone development, repair, and homeostasis (Bianco and Gehron Robey, 2000; Matsushita et al., 2020). SSCs have been identified in the periosteum (P-SSCs), compact bone, and bone marrow (Méndez-Ferrer et al., 2010; Zhou et al., 2014; Duchamp de Lageneste et al., 2018; Jeffery et al., 2022). Similar to BM-MSCs, P-SSCs have been shown to have CFU-F activity and the ability to differentiate into osteoblasts, chondrocytes, and adipocytes (Chan et al., 2015; Debnath et al., 2018; Mirmalek-Sani et al., 2006). Due to the severe necrosis and depletion of the marrow cavity content that we observed following bone transplantation (Figure 1B, Figure 1—figure supplement 1A), we hypothesized that cells derived from the compact bone and/or the periosteum could potentially contribute to stromal marrow regeneration. We first analyzed the cellularity of graft bone marrow, compact bone, and periosteum at different early time points following transplantation. While the number of live cells within the bone marrow and compact bone were drastically reduced in the first 24 hr post-transplantation, we unexpectedly observed a significant but transient increase in live periosteal cells (Figure 3A, Figure 3—figure supplement 1A). Moreover, while most of the bone marrow cells were depleted shortly after transplantation, cell viability was not affected in the periosteum within this time frame (Figure 3A, Figure 3—figure supplement 1B). To quantify P-SSCs and BM-MSCs by flow cytometry, we used the combination of CD51 and CD200, as these markers have been well-validated in both tissues (Chan et al., 2015; Debnath et al., 2018; Gulati et al., 2018). Within the CD45−Ter119−CD31− fraction of live periosteal cells, we confirmed that CD51+CD200+ P-SSCs had the highest CFU-F activity and were also capable of trilineage differentiation (Figure 3—figure supplement 1C–E). Flow cytometric analysis confirmed an expansion of P-SSCs starting at day 3 post-transplantation and peaking at day 8 (Figure 3B, Figure 3—figure supplement 1F). These results were confirmed by confocal microscopy analysis of Nes-GFP graft femurs transplanted into WT mice and stained for Periostin, a matricellular protein highly expressed by periosteal cells (Duchamp de Lageneste et al., 2018; González-González and Alonso, 2018; Horiuchi et al., 1999; Merle and Garnero, 2012; Oshima et al., 2002). We detected an expansion of Nes-GFP+ skeletal progenitors (Tournaire et al., 2020) within the periosteum with a peak at day 8 (Figure 3C), similar to the expansion kinetics that we detected by flow cytometry. Interestingly, by day 15, we could detect Nes-GFP+ cells outside of the periosteum layer stained by an anti-periostin antibody and in the compact bone (Figure 3C).

Figure 3 with 1 supplement see all
Download asset Open asset
P-SSCs remain viable and expand after bone transplantation, in contrast to bone marrow mesenchymal stem cells (BM-MSCs).

(A) Flow cytometric quantification of fold difference of total graft bone marrow and periosteum cellularity to total steady-state cellularity. Different time points early after transplantation were analyzed (n = 2–8). One-way ANOVA with Dunnett multiple comparisons was used to determine statistical significance. (B) Absolute number of CD45−Ter119−CD31−CD51+CD200+ P-SSCs at steady state and 1-, 8-, and 15-day post-transplantation (n = 3–4 mice per time point). One-way ANOVA with Dunnett multiple comparisons was used to determine statistical significance. (C) Representative whole-mount confocal z-stack projections of Nes-GFP+ bone graft at steady state, 3-, 8-, and 15-day post-transplantation. Three independent experiments yielded similar results. Arrowheads point at Nes-GFP+ cells within the bone and bone marrow. Scale bar = 100 µm. (D) Total bone marrow cellularity and BM-MSC absolute number 5 months after transplantation of bones with or without intact periosteum (n = 3–4 mice per group). Data are represented as the mean ± SEM. Unless otherwise noted, statistical significance was determined using unpaired two-tailed Student’s t-test. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

To evaluate the potential role of the periosteum in overall bone marrow regeneration, we compared the regenerative capacity of transplanted femurs with intact periosteum to that of femurs in which the periosteum was mechanically removed (Figure 3D). At 5 months after transplantation, total cellularity and BM-MSC number were significantly reduced in femurs lacking the periosteum, highlighting a potentially critical role for the periosteum and P-SSCs during bone marrow regeneration.

P-SSCs are more resistant to stress than BM-MSCs

Due to the ability of P-SSCs to survive bone transplantation, as opposed to BM-MSCs, we explored the intrinsic differences between BM-MSCs and P-SSCs. Using RNA sequencing, we analyzed the transcriptional differences between CD51+CD200+ P-SSCs and BM-MSCs at steady state. Gene set enrichment analysis (GSEA) revealed that P-SSCs were positively enriched for gene sets associated with stemness and negatively enriched for gene sets associated with proliferation (Figure 4A). These results are in line with qPCR analysis showing that P-SSCs express high levels of the cell cycle inhibitor genes Cdkn1a and Cdkn1c, and low levels of the cell cycle progression gene Cdk4 at steady state (Figure 4B). Additionally, flow cytometric analysis revealed that, compared to BM-MSCs, P-SSCs are less metabolically active, as shown by decreased glucose uptake as assessed by 2-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose (2-NDBG) (Figure 4C). This led us to hypothesize that P-SSCs are more resistant to stress than BM-MSCs.

Figure 4 with 2 supplements see all
Download asset Open asset
Periosteal skeletal stem cells (SSCs) have a metabolic profile conferring a resistance to stress.

(A) Gene set enrichment analysis (GSEA) plots comparing P-SSCs versus bone marrow mesenchymal stem cells (BM-MSCs) at steady state (n = 3 per group). (B) Quantitative RT-PCR analysis of mRNA expression of Cdkn1a, Cdkn1c, Cdk4 relative to Actb in sorted CD45−Ter119−CD31−CD51+CD200+ BM-MSCs and P-SSCs (n = 3–6 per group). (C) Flow cytometric analysis of glucose uptake at steady state in CD45−Ter119−CD31−CD51+CD200+ BM-MSCs and P-SSCs (n = 5 per group). (D) Quantification of cellular reactive oxygen species (ROS) at steady state in CD45−Ter119−CD31−CD51+CD200+ BM-MSCs and P-SSCs (n = 8 per group). (E) Quantitative RT-PCR analysis of mRNA expression of Sod1, Gls, and Gpx1 relative to Actb in sorted CD45−Ter119−CD31−CD51+CD200+ BM-MSCs and P-SSCs (n = 3–7 per group). (F) Schematic illustration of the protocol for the in vitro apoptosis assay. BM-MSCs and P-SSCs were isolated and digested before plating in a 10-cm dish. At near confluence, cells underwent CD45 lineage depletion and plated into multi-well plates. At near confluence, medium was switched from 20% to 0% fetal bovine serum (FBS). Cells were analyzed at the time of medium switch and 12 hr. (G) Percentage of apoptotic BM-MSCs and P-SSCs cultured under 5% O2 at baseline and 12 hr after being in 0% FBS serum conditions (n = 11–12 per group). Two-way ANOVA with Tukey’s multiple comparisons test was used to determine statistical significance. Data are represented as the mean ± SEM. Unless otherwise noted, statistical significance was determined using unpaired two-tailed Student’s t-test. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. This figure was created with BioRender.com.

These observations led us to also use RNA sequencing to compare steady-state P-SSCs to P-SSCs at 3 days after bone transplantation. We chose the 72 hr time point to capture the time when P-SSCs are expanding but have not yet hit the peak of expansion at around day 8. We found that while steady-state P-SSCs and day 3 graft P-SSCs are quite distinct from steady-state BM-MSCs, there is a clear variance starting to occur between the two P-SSC populations (Figure 4—figure supplement 1A). As early as 3 days post bone transplantation, we observed a downregulation of extracellular matrix (ECM) factors such as fibromodulin (Fmod) and nidogen 1 (Nid1) in the graft P-SCCs (Figure 4—figure supplement 1B). Additionally, GSEA comparing steady-state P-SSCs with graft P-SSCs, revealed an upregulation of cell cycle and DNA replication signatures and downregulation of ECM–receptor interaction and glutathione metabolism (Figure 4—figure supplement 1C), indicating that a change in the P-SSCs phenotype occurs early after bone transplantation.

Low levels of reactive oxygen species (ROS) and high expression of antioxidant enzymes are mechanisms that help stem cells to avoid stress-induced cell death (Ito and Suda, 2014; Suda et al., 2011). Thus, we measured ROS levels by staining cells with the superoxide indicator dihydroethidium (DHE). At steady state, flow cytometric analysis revealed that P-SSCs had lower levels of cellular ROS than BM-MSCs (Figure 4D). Under physiological conditions, cells can maintain low ROS levels by expressing antioxidant enzymes. Indeed, qPCR analysis revealed higher expression of three major ROS-detoxifying enzymes genes: superoxide dismutase (Sod1), glutaminase (Gls) and glutathione peroxidase (Gpx1), in sorted CD51+CD200+ P-SSCs than in CD51+CD200+ BM-MSCs (Figure 4E). Altogether, these results suggest that P-SSCs are more stress-resistant than BM-MSCs, which may leave P-SSCs poised to proliferate in response to transplantation.

The location of the periosteum on the exterior of the bone, exposing P-SSCs to a higher oxygen tension than BM-MSCs, may be a contributing factor to the observed differences in resilience between P-SSCs and BM-MSCs. Therefore, to determine whether the anatomic location of BM-MSCs and P-SSCs is the primary determinant of their differential stress response, we performed an ex vivo culture experiment designed to subject BM-MSCs and P-SSCs to equivalent levels of stress while in the same environment. After short-term ex vivo expansion of total bone marrow and periosteal cells, we performed a lineage depletion of CD45+ hematopoietic cells in both fractions. Purified P-SSCs and BM-MSCs were then maintained for 12 hr in serum-free culture media to stress the cells and mimic the nutrient deprivation that occurs immediately following bone transplantation (Figure 4F). Flow cytometric analysis of activated caspase-3/7 revealed that after 12 hr in serum-free media, BM-MSCs exhibited a significantly higher level of apoptosis compared to P-SSCs (Figure 4G, Figure 4—figure supplement 2). These results suggest that P-SSCs are more intrinsically resilient than BM-MSCs, even when they are subjected to similar stress conditions in an equivalent environment.

P-SSCs as a source of functional BM-MSCs during regeneration

As we observed that bone transplantation was followed by a depletion of bone marrow cellularity with an early expansion of P-SSCs, and that transplantation of bones without periosteum negatively impacts graft regeneration (Figure 3D), we hypothesized that proliferating P-SSCs migrate into the bone marrow and contribute to stromal regeneration. To test this hypothesis, we removed the periosteum from WT femurs and wrapped these femurs with the periosteum isolated from UBC-GFP mice (Figure 5A, B). We then transplanted these bones into WT host mice and observed GFP+ cells within the compact bone at 5 months after transplantation (Figure 5C), consistent with the well-described role of the periosteum in bone remodeling (Duchamp de Lageneste et al., 2018; Debnath et al., 2018; Julien et al., 2020). Consistent with our hypothesis, we also observed GFP+ cells enwrapping endomucin-stained sinusoids and forming a network, similar to the perivascular nature of BM-MSCs (Sugiyama et al., 2006; Méndez-Ferrer et al., 2010; Figure 5C).

Figure 5 with 1 supplement see all
Download asset Open asset
Periosteal skeletal stem cells (SSCs) migrate into the bone marrow and support stromal regeneration after bone transplantation.

(A) Schematic of the transplantation of a WT bone enwrapped with periosteum from a UBC-GFP mouse donor into a WT recipient mouse. (B) Pictures illustrating the transplantation of a WT bone enwrapped with periosteum from a UBC-GFP mouse donor into a WT recipient mouse. (C) Representative whole-mount confocal z-stack projections of wild-type bone graft enwrapped with periosteum from a UBC-GFP mouse donor into a WT recipient mouse 5 months after transplantation. Three independent experiments yielded similar results. Right panel: arrows pointing to GFP+ periosteum located perivascularly. Scale bar = 50 µm (left panel) and 20 µm (right panel). (D) Quantification of Cxcl12 and Kitl mRNA levels relative to Gapdh in sorted control CD45−Ter119−CD31−Nestin-GFP+ bone marrow mesenchymal stem cells (BM-MSCs), CD45−Ter119−CD31−CD51+CD200+ P-SSCs, and CD45−Ter119−CD31−CD51+CD200+GFP+ periosteum-derived graft BM-MSCs (n = 3–4 per group). One-way ANOVA with Tukey’s multiple comparisons was used to determine statistical significance. Data are represented as the mean ± SEM. Unless otherwise noted, statistical significance was determined using unpaired two-tailed Student’s t-test. **p < 0.01. This figure was created with BioRender.com.

Flow cytometric analysis of the graft at 5-month post-transplantation confirmed the presence of periosteum-derived GFP+ MSCs within the bone marrow cavity (Figure 5—figure supplement 1A). Importantly, while P-SSCs do not express Cxcl12 or Kitl at steady state, periosteum-derived GFP+ BM-MSCs expressed these niche cytokines at a similar level to control sorted Nes-GFP+BM-MSCs (Figure 5D). We also quantified the expression of the niche factors Angpt1 and Opn. Similarly, we found that Angpt1 expression in the graft GFP+ BM-MSCs reached the level of control BM-MSCs, while Opn expression was higher in GFP+ BM-MSCs than in control Nes-GFP+ BM-MSCs at 5 months after transplantation (Figure 5—figure supplement 1B). However, Opn has been shown to be upregulated in settings of inflammation, injury, and migration (Denhardt et al., 2003; Wang et al., 2017a; Zou et al., 2013). Therefore, the moderate increase in Opn expression level in graft BM-MSCs compared to steady-state BM-MSCs could be due to a residual inflammatory effect of bone transplantation. These results show that P-SSCs can both migrate into the bone marrow cavity and upregulate HSC maintenance genes to support hematopoiesis.

To confirm these results, we took advantage of a previously described transgenic mouse model in which an inducible Cre is placed under the promoter of the Periostin gene (PostnMCM), hereafter referred to as PostnCre-ER (Kanisicak et al., 2016). Postn encodes the secreted matricellular protein Periostin, and is highly expressed by periosteal cells and upregulated during bone healing and formation (Duchamp de Lageneste et al., 2018). While Postn is expressed by multiple cell types, including but not limited to osteoblasts and fibroblasts (Horiuchi et al., 1999; Oshima et al., 2002; Oka et al., 2007), its high expression in P-SSCs compared with BM-MSCs (Figure 6—figure supplement 1A) makes it a useful marker to distinguish endogenous BM-MSCs from periosteum-derived BM-MSCs after bone transplantation. We crossed the PostnCre-ER line with Rosa26LSL-tdTomato reporter (Tomato) mice to be able to lineage trace P-SSCs. We transplanted femurs from PostnCre-ER;tdTomato mice into WT CD45.2 recipient mice, and then injected the host mice with tamoxifen shortly after transplantation to induce Cre recombination and Tomato expression in periosteal cells (Figure 6A). At early time points following bone transplantation, we see Tomato+ cells confined to the periosteum and located perivascularly. At 21 days after transplantation, we observe Tomato+ cells migrating into the bone marrow (Figure 6B). By 5 months after transplantation, we observe robust Tomato+ labeling in the bone marrow located around the vasculature by confocal imaging (Figure 6—figure supplement 1B), consistent with our prior observations (Figure 5C). Additionally, flow cytometric analysis revealed that an average of 85.4% (range: 65.0–94.5%) of the BM-MSCs within the engrafted bone marrow were Tomato+, indicating a periosteal origin (Figure 6C, Figure 6—figure supplement 1C).

Figure 6 with 3 supplements see all
Download asset Open asset
Periosteum-derived graft bone marrow mesenchymal stem cells (BM-MSCs) adopt characteristics of baseline BM-MSCs, including the expression of hematopoietic stem cell (HSC)-niche factors.

(A) Schematic illustration of the transplantation of a PostnCre-ER;tdTomato femur into a WT recipient mouse. (B) Representative whole-mount confocal z-stack projections of transplanted PostnCre-ER;tdTomato femurs into a WT recipient 8-, 15-, and 21 days after transplantation. Two to three independent experiments yielded similar results. Scale bar = 100 µm. (C) Percentage of graft periosteum-derived BM-MSCs labeled Tomato+ 5 months after transplantation of a bone from a PostnCre-ER;tdTomato mouse into a WT recipient (n = 5). (D) Heatmap expression level of selected genes defined by previous studies for HSC-niche cells and extracellular matrix genes (n = 3–4). (E) Volcano plot of P-SSCs compared to graft BM-MSCs showing higher expression of HSC-niche-associated genes in graft BM-MSCs. Data are represented as the mean ± SEM. Unless otherwise noted, statistical significance was determined using unpaired two-tailed Student’s t-test. ****p < 0.0001. This figure was created with BioRender.com.

We then wanted to assess our Postn mouse model using irradiation as a more physiologically relevant model of bone marrow injury, and to compare the effects of localized irradiation to femur transplantation on P-SSC plasticity. Single hindlimbs of PostnCre-ER;tdTomato mice were irradiated in order to compare the effects of irradiation within the same mouse (Figure 6—figure supplement 2A). While a clear difference in the architecture of bone marrow vasculature was observed between the non-irradiated and irradiated limbs, no difference in P-SSCs expansion or migration into the bone marrow was detected, contrasting with the findings in our femur transplant model (Figure 6—figure supplement 2B). This observation suggests that bone transplantation results in a more severe injury to the bone marrow compared to localized irradiation, thereby enabling the assessment of BM-MSCs’ recovery after more severe injury. However, it is also conceivable that stronger irradiation or a longer observation period would be necessary to observe a similar phenotype.

To examine changes in periosteum-derived BM-MSCs at the gene expression level, we performed bulk RNA sequencing on sorted CD51+CD200+Tomato+ BM-MSCs from graft PostnCre-ER;tdTomato femurs at 5 months after transplantation and on sorted steady-state CD51+CD200+ BM-MSCs and P-SSCs. Venn diagram and principal component analysis revealed that periosteum-derived graft BM-MSCs display a gene expression profile distinct from that of both steady-state BM-MSCs and steady-state P-SSCs (Figure 6—figure supplement 3A, B). Consistent with our previous tracing experiment using UBC-GFP periosteum (Figure 5D), we observed an upregulation of HSC-niche-associated maintenance genes in the 5-month-old graft BM-MSCs compared to P-SSCs at steady state (Figure 6D, E). We also observed the downregulation of Postn and other extracellular matrix-related genes, such as fibronectin (Fn1) and fibromodulin (Fmod), in periosteum-derived graft BM-MSCs compared with P-SSCs at steady state (Figure 6D, E). Taken together, our results indicate that P-SSCs can be reprogrammed and adapt a niche-supportive phenotype akin to native BM-MSCs after migrating into the bone marrow following acute stress and subsequent regeneration.

Discussion

Bone marrow regeneration is a critical process that enables the recovery of hematopoiesis after injury such as irradiation or chemotherapy. Bone marrow mesenchymal stromal cells represent a key component of the bone marrow microenvironment. These stromal cells play a crucial role in regulating the self-renewal, differentiation, and proliferative properties of HSCs. The periosteum, a thin membrane that is highly vascularized and innervated, is located on the outside of the bone. This membrane contains numerous skeletal stromal cells, which play a pivotal role in maintaining the bone tissue and facilitating post-fracture healing. While the bone marrow microenvironment at steady state has been extensively studied, the mechanisms of bone marrow regeneration and stromal recovery remain poorly understood. Furthermore, data related to the functions of P-SSC beyond their established role in bone maintenance and fracture healing remain scarce. The objective of this study was to develop and characterize a model of whole bone transplantation in order to study bone marrow regeneration in mice. In this model, severe injury to hematopoietic and stromal cells within the bone marrow is induced, allowing for the investigation of the regeneration process of both cell populations. We found that the total graft bone marrow cellularity and BM-MSC cellularity demonstrate a gradual increase over time, ultimately reaching levels comparable to steady-state levels by 5-month post-transplantation. The 5-month time point was subsequently employed for further analyses. Prior research has emphasized the significance of stromal integrity for the recovery of HSCs following irradiation or chemotherapy (Banfi et al., 2001; Lucas et al., 2013; Hérodin and Drouet, 2005). The findings of our study indicate that, while initially impacted by the stress associated with transplantation, BM-MSCs ultimately demonstrate their capacity to regenerate and sustain hematopoiesis within the engrafted femur. Furthermore, our findings indicate that hematopoietic progenitors derived from the graft femur are capable of engraftment in secondary recipient mice, thereby facilitating multi-lineage reconstitution. This model system recapitulates a recovering bone marrow microenvironment. Furthermore, it allows for genetic in vivo analysis of bone marrow regeneration. Consequently, bone transplantation can be employed as a valuable tool in future studies for investigating bone marrow regeneration.

The origin of endothelial progenitors in the bone marrow is not well defined. A recent study showed that during bone marrow regeneration after chemotherapy, sinusoidal and arteriolar vessels are derived from distinct progenitors (Xu et al., 2018). Intriguingly, in the present study, we observed that endothelial cells within the graft originate from both the graft and host, which supports the hypothesis that different progenitors contribute to the bone marrow vascular network. Therefore, it is likely that endothelial regeneration in the graft, and vascular anastomoses between the host and graft femur are also important for the hematopoietic regeneration process. Further studies are needed to clarify the respective contributions of graft- and host-derived endothelial progenitors and the relative contributions of these different progenitor populations to regeneration of the vascular network and to hematopoietic regeneration.

Our results also highlight the high resilience and plasticity of P-SSCs and reveal their potential contribution to the bone marrow stromal network and bone marrow regeneration. At steady state, P-SSC do not express HSC maintenance genes, such as Kitl and Cxcl12, and the potential capacity of P-SSC to support HSCs has not been previously addressed. Unexpectedly, our results show that in our model, P-SSCs can migrate to the bone marrow and adopt a phenotype similar to that of BM-MSCs. Therefore, it is possible that P-SSCs can be harvested and manipulated as a source of BM-MSCs. Interestingly, we did not observe a similar migration and plasticity of P-SSCs in the context of localized femur irradiation. This observation suggests that femur transplantation introduces a greater stress on the bone marrow than irradiation, and that this increased level of stress is required to induce P-SSC plasticity and migration into the bone marrow.

In accordance with our findings, a recent study employing Gli1 to trace P-SSC demonstrated the localized expression of Kitl and Cxcl12 by P-SSCs at the fracture site (Jeffery et al., 2022). However, this model was not designed to specifically address the role of P-SSC in bone marrow regeneration. Furthermore, niche-specific genes were only expressed by cells adjacent to the fracture callus. Although we did not find a baseline difference in Gli1 expression between BM-MSCs and P-SSCs in our RNA sequencing analysis, this may be due to the differences in surface markers and reporters used to identify P-SSCs and BM-MSCs. In the same study, authors did not find expression of reporters in the periosteum using the PostnCre-ER mice. It is likely that this discrepancy is attributable to differences in generation of the Postn-Cre mice used. Indeed, previous studies have demonstrated that, compared to steady state, the Postn gene is upregulated following the activation of P-SSC, which is clearly evident in the context of whole bone transplantation (Duchamp de Lageneste et al., 2018). The results of our flow cytometry and imaging analyses demonstrate that P-SSC is specifically labeled at early time points following the transplantation of grafts from PostnCre-ER mice. Therefore, we show a novel application for the use of the inducible PostnCre-ER mice to differentiate between BM-MSCs and P-SSCs in vivo. Accordingly, Duchamp de Lageneste et al. demonstrated that periostin contributes to the highly regenerative nature of P-SSCs compared to BM-MSCs (Duchamp de Lageneste et al., 2018). While previous studies have used Prx1 and Ctsk-Cre models, these models do not adequately allow the distinction between P-SSCs and BM-MSCs, likely due to their common embryonic origin (Duchamp de Lageneste et al., 2018; Debnath et al., 2018; Bianco and Gehron Robey, 2000). Periostin is a well-studied protein that has been shown to interact with extracellular matrix proteins and plays a key role in tissue regeneration and cancer progression, promoting proliferation, invasion, and anti-apoptotic signaling (González-González and Alonso, 2018; Bao et al., 2004; Butcher et al., 2007; Conway et al., 2014). Therefore, it is possible that periostin contributes to P-SSC proliferation and migration into the bone marrow, which would be an interesting area for future investigation.

Additionally, our findings illustrate the differential stress response between BM-MSCs and P-SSCs. While BM-MSCs are renowned for their resilience to stress, our findings illustrate that P-SSCs exhibit an even greater resistance to stress, which is attributed, at least in part, to their distinctive metabolic profile (Morikawa et al., 2009; Haas et al., 1969). Given that differences in apoptosis were observed between BM-MSCs and P-SSCs, even when they were cultured ex vivo under identical stress culture conditions with identical oxygen tension, it can be concluded that the observed differences between P-SSCs and BM-MSCs are due to intrinsic cellular properties rather than their anatomical location. Nevertheless, additional studies are required to elucidate the underlying mechanism responsible for the observed relative stress resistance of P-SSCs.

In conclusion, we have used a whole bone transplantation model to study bone marrow regeneration in vivo in response to acute injury using genetic tools. Our study has shown that through their high level of resilience and plasticity, P-SSCs can facilitate BM-MSC regeneration. Our data suggest that P-SSCs are able to contribute to hematopoietic cell recovery under stress conditions.

Materials and methods

Mice

Mice were maintained under specific pathogen-free conditions in a barrier facility in microisolator cages. This study complied with all ethical regulations involving experiments with mice, and the Institutional Animal Care and Use Committee of Albert Einstein College of Medicine approved all experimental procedures, based on protocol #00001101. C57BL/6J mice (stock #000664), B6.129-Postntm2.1(cre/Esr1*)Jmol/J (Kanisicak et al., 2016) mice (stock #029645), Gt(ROSA)26Sortm4(ACTB-tdTomato,-EGFP)Luo/J (Rosa26mT/mG) mice (stock #007576), and C57BL/6-Tg(UBC-GFP)30Scha/J (stock #004353) mice were ordered from Jackson Laboratory and then bred in our facilities. Nestin-GFP (Méndez-Ferrer et al., 2010) mice were kindly provided by G. Enikolopov and then bred in our facilities. Cdh5 (VE-cadherin)-CreER; iTdTomato (Wang et al., 2010) mice were kindly provided by R. H. Adams (Max Planck Institute for Molecular Biomedicine, Germany) and then bred in our facilities. Unless otherwise specified, 6- to 12-week-old mice were used for the experiments. For all analytical and therapeutic experiments, sex-matched animals from the same age group were randomly assigned to experimental groups.

Bone transplantation procedure

Request a detailed protocol

Donor mice were anesthetized with isoflurane and euthanized by cervical dislocation. Femurs were isolated and preserved in an ice-cold phosphate-buffered saline (PBS) solution with 1% fetal bovine serum (FBS). Recipient mice were anesthetized with a ketamine/xylazine intraperitoneal injection (10 µl/g). Donor femurs were subcutaneously implanted in the back of the recipient mice, and the skin was sutured with a non-absorbable polyamide 5/0 silk. Mice were allowed to recover under a heat lamp until awake and monitored daily for up to a week post-surgery.

In vivo treatment

Request a detailed protocol

For lineage tracing experiments using femurs from Postntm2.1(cre/Esr1*)Jmol/J donor mice, tamoxifen (1 mg/mouse) was administered intraperitoneally to recipient mice twice daily for 10 consecutive days starting at day 2 post-transplantation.

Bone marrow transplantation

Request a detailed protocol

Non-competitive repopulation assays were performed using CD45.1 and CD45.2 mice. Recipient mice were lethally irradiated (12 Gy, two split doses) in a Cesium Mark 1 irradiator (JL Shepherd & Associates). A total of 1 × 106 CD45.2+ bone marrow nuclear cells from either the graft or host femurs were obtained at 5 months after transplantation and injected retro-orbitally into irradiated CD45.1+ mice. Mice were bled retro-orbitally every 4 weeks after bone marrow transplantation, and peripheral blood was analyzed for engraftment and repopulation up to 16 weeks.

Preparation of single-cell suspensions

Request a detailed protocol

To isolate P-SSCs, muscle tissue was carefully removed using scissors and intact bones were submerged for 30 min in ice-cold PBS with 1% FBS. The periosteum was carefully removed with a surgical blade, and mechanical dissociation was performed using scissors. Enzymatic dissociation was performed by incubating the periosteum fragments for 45 min at 37°C in digestion buffer (Hank’s balanced salt solution (Gibco) containing 1 mg ml−1 collagenase type IV (Gibco) and 2 mg ml−1 dispase (Gibco)) on a rotator. Bone marrow cells were obtained by flushing and dissociating using a 1-ml syringe with PBS via a 21-gauge needle. For analysis of stromal and endothelial cell populations, intact bone marrow plugs were flushed into digestion buffer using 21- or 25-gauge needles and incubated at 37°C for 30 min with manual mixing every 10 min. After bone marrow and periosteum isolation, the remaining compact bone was crushed, mechanically dissociated using scissors as previously described (Gulati et al., 2018) and digested in the digestion buffer, rotating for 45 min at 37°C. Enzymatic digestion was stopped by adding ice-cold PEB buffer (PBS with 0.5% BSA and 2 mM EDTA).

Flow cytometry and cell sorting

Request a detailed protocol

For FACS analysis and sorting, red blood cells were lysed (distilled H2O containing 155 mM ammonium chloride, 10 mM potassium bicarbonate, and 0.5 M EDTA) and washed in ice-cold PEB (PBS containing 0.5% BSA and 2 mM EDTA) before staining with antibodies in PEB for 20 min on ice. Dead cells and debris were excluded by FSC (forward scatter), SSC (side scatter), and DAPI (4′,6-diamino-2-phenylindole; Sigma). FACS analyses were carried out using BD LSRII flow cytometry (BD Biosciences) and cell sorting experiments were performed using a MoFlo Astrios (Beckman Coulter). Data were analyzed with FlowJo 10.4.0 (LCC) and FACS Diva 6.1 software (BD Biosciences). Antibodies used for FACS can be found in Supplementary file 1. For metabolic assays, cells were first stained with cell surface markers prior to labeling with metabolic dyes. For cellular ROS quantification, cells were incubated with DHE (5 µM; Molecular Probes) for 20 min at 37°C in PBS. Glucose uptake quantification was performed by incubating the cells in DMEM without glucose (Gibco) containing Glutamax (1:100; Gibco) and 2-NBDG (17 µmol ml–1; Cayman Chemical Company) for 30 min at 37°C.

CFU-F assays

Request a detailed protocol

For CFU-F and stromal cell culture, CD45−Ter119−CD31−CD51+CD200+ stromal cells isolated from bone marrow and periosteum were sorted and plated at a clonal density (1000 cell/well) in α-MEM (Gibco) containing 20% FBS (HyClone), 10% MesenCult Stimulatory supplement (StemCell Technologies), and 1% penicillin–streptomycin. Half of the medium was changed at day 7. Cells were cultured for 12–14 days, at the end of which the colonies were scored.

Osteogenic, adipogenic, and chondrogenic differentiation assays

Request a detailed protocol

Trilineage differentiation assays toward the osteogenic, adipogenic, and chondrogenic lineages were performed as previously described (Pinho et al., 2013), with minor modifications. Briefly, cells were treated with StemXVivo Osteogenic, Adipogenic, or Chondrogenic mouse differentiation media, according to the manufacturer’s instructions (R&D Systems). All cultures were maintained with 5% CO2 in a water-jacketed incubator at 37°C. Osteogenic differentiation was revealed by Alizarin Red S staining. Adipocytes were identified by the typical production of lipid droplets and Bodipy (Invitrogen) staining. Chondrocytes were revealed by Alcian Blue staining.

Ex vivo culture nutrient deprivation assay

Request a detailed protocol

Whole bone marrow from one femur and whole periosteum from two femurs were isolated and digested as previously described and plated in α-MEM (Gibco) containing 20% FBS (HyClone), 1% penicillin–streptomycin, 1% L-glutamine, and βFGF. The medium was changed every 3–4 days. Once a plate reached near confluence, CD45 lineage depletion was performed on both bone marrow and periosteum fractions. Cells were then counted and plated in 12- or 24-well plates at approximately 5000 cells/cm2. Once the plates reached near confluence, media was switched to α-MEM without FBS, 1% L-glutamine, and βFGF. Twelve hours after the medium was switched to 0% FBS medium, the cells were trypsinized, spun down, and stained for cell surface markers. After 4–5 days, flow cytometric apoptosis quantification was performed using the CellEvent Caspase 3/7 kit (Thermo Fisher) following the manufacturer’s recommendations.

Immunofluorescence imaging of bone sections

Request a detailed protocol

To stain blood vessels, anti-CD31 and anti-CD144 antibodies were injected intravenously into mice (10 μg, 20 μl of 0.5 μg μl−1) and mice were sacrificed for analysis at 10 min after injection. For frozen sections of long bones, femurs and tibias were fixed in 4% paraformaldehyde (PFA) overnight at 4°C. For cryopreservation, the bones were incubated sequentially in 10%, 20%, and 30% sucrose/PBS at 4°C for 1 hr each and embedded and flash frozen in SCEM embedding medium (SECTION-LAB). Frozen sections were prepared at 20 μm thickness with a cryostat (CM3050, Leica) using the Kawamoto’s tape transfer method (Kawamoto and Shimizu, 2000). For immunofluorescence staining, sections were rinsed with PBS, post-fixed with 4% cold PFA for 10 min, followed by blocking with 20% donkey serum (DS; Sigma) in 0.5% Triton X-100/PBS for 3 hr at room temperature (20–25°C). For perilipin staining, sections were incubated for 1 hr at room temperature in saturation buffer (PBS-DS 10%). The rabbit polyclonal anti-perilipin antibody (clone: D1D8; Cat: 9349; Cell Signaling Technology) was used at 1:100 dilution in 2% DS 0.1% Triton X-100/PBS overnight at 4°C. Periostin staining was performed using whole-mount femur imaging. The bone marrow was exposed by shaving the bone using a cryostat (CM3050, Leica). Shaved femurs were fixed 30 min at 4°C in PBS/PFA 4%. Samples were then incubated in the saturation buffer (PBS-DS 10%) during 1 hr at room temperature. Polyclonal goat anti-periostin antibody (Cat: AF2955; R&D) and monoclonal rat anti-endomucin antibodies (clone: V.7C7; Cat: sc-65495; Santa Cruz) were used at a 1:100 dilution overnight at 4°C in PBS-DS 2%. When necessary, primary antibody staining was followed by three washes with 2% DS 0.1% Triton X-100/PBS and a 30-min incubation with Alexa Fluor 568 or Alexa Fluor 488-conjugated secondary antibodies (Invitrogen) and 0.2% DAPI (Sigma).

Image acquisition

Request a detailed protocol

All images were acquired at room temperature using a Zeiss Axio examiner D1 microscope (Zeiss) with a confocal scanner unit (Yokogawa) and reconstructed in three dimensions with Slide Book software (Intelligent Imaging Innovations). Image analysis was performed using both Slide Book software (Intelligent Imaging Innovations) and the Fiji build of ImageJ (NIH).

Single limb irradiation

Request a detailed protocol

Mice were anesthetized using isoflurane chamber and kept anesthetized throughout the procedure. Mice were irradiated using the Small Animal Radiation Research Platform, SARRP (XStrahl, Surrey, UK). Whole body lead shielding protected the mice except for one hindlimb which was protruding out from under the shield and irradiated to 20 Gy for 319 s in a single fraction. Mice were left under the heat lamp until they recovered.

RNA isolation and quantitative real-time PCR

Request a detailed protocol

mRNA was purified using the Dynabeads mRNA DIRECT Micro Kit (Life technologies – Invitrogen) by directly sorting stromal cells into lysis buffer, and reverse transcription was performed using RNA to cDNA EcoDry Premix (Clontech – Takara Bio) following the manufacturer’s instructions. The SYBR green (Roche) method was used for quantitative PCR using the QuantStudio 6 Flex system (Applied Biosystems, Thermo Fisher). All mRNA expression levels were calculated relative to Gapdh or Actb. Supplementary file 2 lists the primer sequences used.

RNA sequencing and analysis

Request a detailed protocol

Total RNA from 1000 to 3000 sorted steady BM-MSCs, steady-state P-SSCs, graft P-SSCs, and graft BM-MSCs was extracted using the RNAeasy Plus Micro kit (QIAGEN) and assessed for integrity and purity using an Agilent Bioanalyzer. When applicable, RNA from two mice was combined; however, each replicate contained RNA from distinct mice. RNA-seq data generated from Illumina Novaseq6000 were processed using the following pipeline. Briefly, clean reads were mapped to the mouse genome (GRCm38) using Spliced Transcripts Alignment to a Reference (STAR 2.6.1d). Gene expression levels were calculated and differentially expressed genes were identified using DESeq2 and enriched using clusterProfiler. All RNA sequencing data are available under the SuperSeries dataset GSE222272 in GEO omnibus.

Statistical analysis

Request a detailed protocol

All data are presented as the mean ± SEM. N represents the number of mice in each experiment, as detailed in the figure legends. No statistical method was used to predetermine sample sizes; sample sizes were determined by previous experience with similar models of hematopoiesis, as shown in previous experiments performed in our laboratory.  Statistical significance was determined by an unpaired, two-tailed Student’s t-test to compare two groups or a one-way ANOVA with multiple group comparisons. Statistical analyses were performed, and data presented using GraphPad Prism 8 (GraphPad Software), FACS Diva 6.1 software BD Biosciences, FlowJo 10.4.0 (LLC), Slide Book Software 6.0 (Intelligent Imaging Innovations), and QuantStudio 6 Real-Time PCR Software (Applied Biosystem, Thermo Fisher). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain, strain background (M. musculus)B6.129S-Postntm2.1(cre/Esr1*)Jmol/JKanisicak et al., 2016Strain #:029645
RRID:IMSR_JAX:029645
Strain, strain background (M. musculus)Nestin-GFPMéndez-Ferrer et al., 2010Strain #:033927
RRID:IMSR_JAX:033927
Strain, strain background (M. musculus)Gt(ROSA)26Sortm4(ACTB-tdTomato,-EGFP)Luo/J (RosamT/mG)Muzumdar et al., 2007Strain #:007576
RRID:IMSR_JAX:007576
Strain, strain background (M. musculus)C57BL/6-Tg(UBC-GFP)30Scha/JLiu et al., 2020Strain #:004353
RRID:IMSR_JAX:004353
Strain, strain background (M. musculus)Cdh5-CreER; iTdTomatoH. Adams (Max Planck Institute for Molecular Biomedicine, Germany)
Strain, strain background (M. musculus)C57BL/6The Jackson Laboratory/ Bred in labStrain #:000664
RRID:IMSR_JAX:000664
Antibodyanti-streptavidin FITC/ APC-Cy7InvitrogenRRID:AB_10053373 (FITC), AB_10054651 (APC-Cy7)FC (1:100)
Antibodyanti-CD45 APC-eFluor 780/Pacific BlueInvitrogen (APC-eFluor 780), Biolegend (Pacific Blue)APC- eFluor 780 (RRID:AB_1548781), Pacific Blue (RRID:AB_493535)Clone: 30-F11
FC (1:100)
Antibodyanti-CD11b AF647BiolegendRRID:AB_389327Clone: M1/70
FC (1:100)
Antibodyanti-CD4 PE-Cy7InvitrogenRRID:AB_469576Clone: GK1.5
FC (1:100)
Antibodyanti-CD8a PE-Cy7InvitrogenRRID:AB_469584Clone: 53-6.7
FC (1:100)
Antibodyanti-B220 PerCP-Cy5.5InvitrogenRRID:AB_1107006Clone: RA3-6B2
FC (1:100)
Antibodyanti-CD45.1 PEBiolegendRRID:AB_389327Clone: A20
FC (1:100)
Antibodyanti-CD45.2 FITCBiolegendRRID:AB_313442Clone: 104
FC (1:100)
Antibodyanti-CD144 AF647BiolegendRRID:AB_10568319Clone: BV13
FC (1:100)
IF (1:10)
Antibodyanti-Gr-1 APC-eFluor 780InvitrogenRRID:AB_2534437Clone: RB6-8C5
FC (1:100)
Antibodyanti-Ter119 Pacific Blue/ APC-eFlour 780Biolegend (Pacific Blue), Invitrogen (APC- eFluor 780)RRID:AB_1548786 (APC- eFluor 780), AB_225116 (Pacific Blue)Clone: Ter-119
FC (1:100)
Antibodyanti-CD31 PE-Cy7/AF647BiolegendRRID:AB_830756 (PE-Cy7), AB_493410 (AF647)Clone: 390
FC (1:100)
IF (1:10)
Antibodyanti-CD51 biotin/ PEBiolegend (biotin), Invitrogen (PE)RRID:AB_313072 (biotin), AB_465704 (PE)Clone: RMV-7
FC (1:100)
Antibodyanti-CD200 APCBiolegendRRID:AB_10900447Clone: OX-90
FC (1:100)
AntibodyAnti-perilipin rabbit polyclonalCell Signalling TechnologyCatalog #: 9349Clone D1D8
IF (1:100)
AntibodyAnti-periostin goat polyclonalR&DCatalog #: AF2955IF (1:100)
AntibodyAnti-endomucin rat monocloncalSanta CruzCatalog #: sc-65495Clone: V.7C7
(1:100)
Chemical compoundCollagenase Type IVGibcoCatalog #: 17104019
Chemical compoundDispase IIGibcoCatalog #: 17105041
Chemical compoundGlutamaxGibcoCatalog #: 35050061(1:100)
Chemical compound10% MesenCult Stimulatory SupplementStemCell TechnologiesCatalog #: 05402
Chemical compound2-NDBGCayman Chemical CompanyCatalog #: 11046
Chemical compoundSCEM embedding mediaSection-labKawamoto and Shimizu, 2000
Chemical CompoundStemXVivo Osteogenic/Adipogenic Base mediaR&D SystemsCatalog #: CCM007
Chemical CompoundStemXVivo Chondrogenic Base MediaR&D SystemsCatalog #: CCM005
Chemical CompoundStemXVivo Osteogenic SupplementR&D SystemsCatalog #: CCM009
Chemical CompoundStemXVivo Chondrogenic SupplementR&D SystemsCatalog #: CCM006
Chemical CompoundStemXVivo Adipogenic SupplementR&D SystemsCatalog #: CCM011
Commercial assay, kitBodipy 493/503InvitrogenCatalog #: D3922
Commercial assay, kitRNA to cDNA EcoDry PremixClontech – Takara BioCatalog #: 639543
Commercial assay, kitCellEvent Caspase 3/7 GreenThermo FisherCatalog #: C10423
Commercial assay, kitRNAeasy Plus Micro KitQIAGENCatalog #: 74034
Commercial assay, kitDynabeads mRNA DIRECT Micro KitInvitrogenInvitrogen 61021
Sequence-based reagentCxcl12_FThis paperPCR primer5′-CGCCAAGGTCGTCGCCG-3′
Sequence-based reagentCxcl12_RThis paperPCR primer5′-TTGGCTCTGGCGATGTGGC-3′
Sequence-based reagentKitl_FThis paperPCR primer5′-CCCTGAAGACTCGGGCCTA-3′
Sequence-based reagentKitl_RThis paperPCR primer5′-CAATTACAAGCGAAATGAGAGCC-3′
Sequence-based reagentOpn_FThis paperPCR primer5′-AGCAAGAAACTCTTCCAAGCAA-3′
Sequence-based reagentOpn_RThis paperPCR primer5′-GTGAGATTCGTCAGATTCATCCG-3′
Sequence-based reagentAngpt1_FThis paperPCR primer5′-CTCGTCAGACATTCATCATCCAG-3′
Sequence-based reagentAngpt1_RThis paperPCR primer5′-CACCTTCTTTAGTGCAAAGGCT-3′
Sequence-based reagentVcam1_FThis paperPCR primer5′-GACCTGTTCCAGCGAGGGTCTA-3′
Sequence-based reagentVcam1_RThis paperPCR primer5′-CTTCCATCCTCATAGCAATTAAGGTG-3′
Sequence-based reagentCdkn1a_FThis paperPCR primer5′-CCTGGTGATGTCCGACCTG-3′
Sequence-based reagentCdkn1a_RThis paperPCR primer5′-CCATGAGCGCATCGCAATC-3′
Sequence-based reagentCdkn1c_FThis paperPCR primer5′-CGAGGAGCAGGACGAGAATC-3′
Sequence-based reagentCdkn1c_RThis paperPCR primer5′-GAAGAAGTCGTTCGCATTGGC-3′
Sequence-based reagentCdk4_FThis paperPCR primer5′-ATGGCTGCCACTCGATATGAA 3′
Sequence-based reagentCdk4_RThis paperPCR primer5′-TCCTCCATTAGGAACTCTCACAC-3′
Sequence-based reagentSod1_FThis paperPCR primer5′-TGGTGGTCCATGAGAAACAA-3′
Sequence-based reagentSod1_RThis paperPCR primer5′-GTTTACTGCGCAATCCCAAT-3′
Sequence-based reagentGls_FThis paperPCR primer5′-TTCGCCCTCGGAGATCCTAC-3′
Sequence-based reagentGls_RThis paperPCR primer5′-CCAAGCTAGGTAACAGACCCT-3′
Sequence-based reagentGpx1_FThis paperPCR primer5′-AGTCCACCGTGTATGCCTTCT-3′
Sequence-based reagentGpx1_RThis paperPCR primer5′-GAGACGCGACATTCTCAATGA-3′
Sequence-based reagentPostn_FThis paperPCR primer5′-CCTGCCCTTATATGCTCTGCT-3′
Sequence-based reagentPostn_RThis paperPCR primer5′-AAACATGGTCAATAGGCATCACT-3′
Sequence-based reagentGapdh_FThis paperPCR primer5′-TGTGTCCGTCGTGGATCTGA-3′
Sequence-based reagentGapdh_RThis paperPCR primer5′-CCTGCTTCACCACCTTCTTGA-3′
Sequence-based reagentActb_FThis paperPCR primer5′-GCTTCTTTGCAGCTCCTTCGT-3′
Sequence-based reagentActb_RThis paperPCR primer5′-ATCGTCATCCATGCCGAACT-3′
OtherDAPISigmaProd #: D9542

Data availability

All RNA sequencing data are available under the SuperSeries dataset GSE222272 in GEO omnibus.

The following data sets were generated
    1. Marchand T
    2. Akinnola M
    (2023) NCBI Gene Expression Omnibus
    ID GSE222272. Periosteal skeletal stem cells can migrate into the bone marrow and support hematopoiesis after injury.
    https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE222272

References

    1. Friedenstein AJ
    2. Petrakova KV
    3. Kurolesova AI
    4. Frolova GP
    (1968)
    Heterotopic of bone marrow: Analysis of precursor cells for osteogenic and hematopoietic tissues
    Transplantation 6:230–247.
    1. Varas F
    2. Grande T
    3. Ramírez A
    4. Bueren JA
    (2000)
    Implantation of bone marrow beneath the kidney capsule results in transfer not only of functional stroma but also of hematopoietic repopulating cells
    Blood 96:2307–2309.
    1. Yamazaki K
    2. Allen TD
    (1991)
    Ultrastructural and morphometric alterations in bone marrow stromal tissue after 7 Gy irradiation
    Blood Cells 17:527–549.

Article and author information

Author details

  1. Tony Marchand

    1. Service d’hématologie Clinique, Centre Hospitalier Universitaire de Rennes, Rennes, France
    2. UMR U1236, INSERM, Université Rennes, EFS Bretagne, Equipe Labellisée Ligue Contre le Cancer, Rennes, France
    3. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    4. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing
    Contributed equally with
    Kemi E Akinnola
    For correspondence
    tony.marchand@chu-rennes.fr
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4932-2169

  2. Kemi E Akinnola

    1. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    2. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing
    Contributed equally with
    Tony Marchand
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0746-6762

  3. Shoichiro Takeishi

    1. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    2. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    Contribution
    Formal analysis, Investigation, Methodology, Writing – original draft
    Competing interests
    No competing interests declared

  4. Maria Maryanovich

    1. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    2. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    Contribution
    Conceptualization, Formal analysis, Investigation, Visualization, Writing – original draft
    Competing interests
    No competing interests declared

  5. Sandra Pinho

    1. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    2. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    3. Department of Medical Oncology, Albert Einstein College of Medicine, Bronx, United States
    4. Department of Pharmacology & Regenerative Medicine, University of Illinois at Chicago, Chicago, United States
    Contribution
    Formal analysis, Investigation, Visualization, Writing – original draft
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5241-7364

  6. Julien Saint-Vanne

    UMR U1236, INSERM, Université Rennes, EFS Bretagne, Equipe Labellisée Ligue Contre le Cancer, Rennes, France
    Contribution
    Software, Formal analysis, Validation, Visualization, Writing – original draft
    Competing interests
    No competing interests declared

  7. Alexander Birbrair

    1. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    2. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    3. Department of Dermatology, University of Wisconsin-Madison, Madison, United States
    Contribution
    Conceptualization, Methodology
    Competing interests
    No competing interests declared

  8. Thierry Lamy

    1. Service d’hématologie Clinique, Centre Hospitalier Universitaire de Rennes, Rennes, France
    2. UMR U1236, INSERM, Université Rennes, EFS Bretagne, Equipe Labellisée Ligue Contre le Cancer, Rennes, France
    Contribution
    Investigation, Visualization
    Competing interests
    No competing interests declared

  9. Karin Tarte

    1. UMR U1236, INSERM, Université Rennes, EFS Bretagne, Equipe Labellisée Ligue Contre le Cancer, Rennes, France
    2. Laboratoire Suivi Immunologique des Thérapeutiques Innovantes, Centre Hospitalier Universitaire de Rennes, Rennes, France
    Contribution
    Conceptualization, Supervision, Writing – original draft
    Competing interests
    No competing interests declared

  10. Paul Frenette (deceased)

    1. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    2. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    3. Department of Medical Oncology, Albert Einstein College of Medicine, Bronx, United States
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Visualization
    Competing interests
    No competing interests declared

  11. Kira Gritsman

    1. Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    2. Department of Cell Biology, Albert Einstein College of Medicine, Michael F. Price Center, Bronx, United States
    3. Department of Medical Oncology, Albert Einstein College of Medicine, Bronx, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Visualization, Writing – original draft, Project administration, Writing – review and editing
    For correspondence
    kira.gritsman@einsteinmed.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1367-1167

Funding

National Institute of Diabetes and Digestive and Kidney Diseases (5R01DK056638)

  • Paul Frenette
  • Kira Gritsman

National Institute of Diabetes and Digestive and Kidney Diseases (R01DK056638-23S1)

  • Kemi E Akinnola

National Institute of Diabetes and Digestive and Kidney Diseases (R56DK130895)

  • Kira Gritsman

National Institute of Diabetes and Digestive and Kidney Diseases (R01DK130895)

  • Kira Gritsman

National Heart, Lung, and Blood Institute (R01HL162584)

  • Sandra Pinho

National Institute of General Medical Sciences (T32GM007288-50)

  • Kemi E Akinnola

New York State Stem Cell Science (IIRP C029570A)

  • Paul Frenette

Fondation ARC pour la Recherche sur le Cancer

  • Tony Marchand

Association pour le Développement de l'Hématologie Oncologie

  • Tony Marchand

Société Française d'Hématologie

  • Tony Marchand

Centre Hospitalier Universitaire de Rennes

  • Tony Marchand

Philip Foundation

  • Tony Marchand

Japan Society for the Promotion of Science

  • Shoichiro Takeishi

Uehara Memorial Foundation

  • Shoichiro Takeishi

New York State Stem Cell Science

  • Shoichiro Takeishi

EMBO European Commission FP7 (EMBOCOFUND2012)

  • Maria Maryanovich

New York Stem Cell Foundation

  • Maria Maryanovich

American Society of Hematology

  • Maria Maryanovich

Norn Group

  • Sandra Pinho

NCI (P30CA013330)

  • Kira Gritsman

EMBO European Commission FP7 (Marie Curie Actions)

  • Maria Maryanovich

The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.

Acknowledgements

We would like to thank Colette Prophete and Daqian Sun for technical assistance and Lydia Tesfa and the Einstein Flow Cytometry Core Facility for expert cell sort assistance. We thank Charles Brottier and Robert Dubin of the Albert Einstein College of Medicine Computational Biology core facility for their help with analysis of RNA sequencing data. This work was supported by the National Institutes of Health (NIH) Grant 5R01DK056638 (to PSF and KG), administrative supplement R01DK056638-23S1 (to KEA), R01DK112976 (to PSF), R56DK130895 (to KG), R01DK130895 (to KG), R01HL162584 (to SP), the NIH training Grant T32GM007288-50 (to KEA), and NYSTEM IIRP C029570A (to PSF). TM was supported by the Fondation ARC pour la Recherche sur le Cancer, the Association pour le Développement de l’Hématologie Oncologie, the Société Française d’Hématologie, the Centre Hospitalier Universitaire de Rennes, and the Philip Foundation. ST was supported by the Japan Society for the Promotion of Science (JSPS) Postdoctoral Fellowship for Research Abroad, the Uehara Memorial Foundation Research Fellowship, and the NYSTEM Empire State Institutional Program in Stem Cell Research. M.M. was supported by the EMBO European Commission FP7 (Marie Curie Actions; EMBOCOFUND2012, GA-2012-600394, ALTF 447-2014), by the New York Stem Cell Foundation (NYSCF) Druckenmiller fellowship, and by the American Society of Hematology (ASH) Research Restart Award. SP was also supported by a Longevity Impetus Grant from Norn Group. This work was also supported by the Albert Einstein Cancer Center core support grant P30CA013330. Experimental figure illustrations were created using BioRender. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Ethics

This study complied with all ethical regulations involving experiments with mice, and the Institutional Animal Care and Use Committee of Albert Einstein College of Medicine approved all experimental procedures, based on IACUC protocol #00001101.

Version history

  1. Preprint posted:
  2. Sent for peer review:
  3. Reviewed Preprint version 1:
  4. Reviewed Preprint version 2:
  5. Version of Record published:

Cite all versions

You can cite all versions using the DOI https://doi.org/10.7554/eLife.101714. This DOI represents all versions, and will always resolve to the latest one.

Copyright

© 2024, Marchand, Akinnola 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.

Metrics

  • 394
    views
  • 36
    downloads
  • 0
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Tony Marchand
  2. Kemi E Akinnola
  3. Shoichiro Takeishi
  4. Maria Maryanovich
  5. Sandra Pinho
  6. Julien Saint-Vanne
  7. Alexander Birbrair
  8. Thierry Lamy
  9. Karin Tarte
  10. Paul Frenette
  11. Kira Gritsman
(2025)
Periosteal skeletal stem cells can migrate into the bone marrow and support hematopoiesis after injury
eLife 13:RP101714.
https://doi.org/10.7554/eLife.101714.3

Share this article

https://doi.org/10.7554/eLife.101714

Categories and tags

Research organism