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. 2019 Apr 12;15:79–94. doi: 10.1016/j.isci.2019.04.015

Glucose Restriction Promotes Osteocyte Specification by Activating a PGC-1α-Dependent Transcriptional Program

Cristina Sánchez-de-Diego 1, Natalia Artigas 1, Carolina Pimenta-Lopes 1, José Antonio Valer 1, Benjamin Torrejon 2, Pau Gama-Pérez 1, Josep A Villena 3, Pablo M Garcia-Roves 1, José Luis Rosa 1, Francesc Ventura 1,4,∗
PMCID: PMC6488568  PMID: 31039455

Summary

Osteocytes, the most abundant of bone cells, differentiate while they remain buried within the bone matrix. This encasement limits their access to nutrients and likely affects their differentiation, a process that remains poorly defined. Here, we show that restriction in glucose supply promotes the osteocyte transcriptional program while also being associated with increased mitochondrial DNA levels. Glucose deprivation triggered the activation of the AMPK/PGC-1 pathway. AMPK and SIRT1 activators or PGC-1α overexpression are sufficient to enhance osteocyte gene expression in IDG-SW3 cells, murine primary osteoblasts, osteocytes, and organotypic/ex vivo bone cultures. Conversely, osteoblasts and osteocytes deficient in Ppargc1a and b were refractory to the effects of glucose restriction. Finally, conditional ablation of both genes in osteoblasts and osteocytes generate osteopenia and reduce osteocytic gene expression in mice. Altogether, we uncovered a role for PGC-1 in the regulation of osteocyte gene expression.

Subject Areas: Molecular Mechanism of Behavior, Molecular Physiology, Specialized Functions of Cells

Graphical Abstract

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Highlights

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    Glucose restriction promotes osteocytic gene expression and mitochondrial function

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    Glucose restriction triggers activation of the AMPK/PGC-1 pathway

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    Effects of glucose restriction on osteocyte gene expression depend on Ppargc1a/b

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    Deletion of Ppargc1a/b in osteoblasts and osteocytes leads to osteopenia

Molecular Mechanism of Behavior; Molecular Physiology; Specialized Functions of Cells

Introduction

Of the major cell types in bone, osteocytes make up over 90% to 95% of total bone cells in the adult skeleton. No longer considered passive placeholders in bone, osteocytes have recently emerged as major orchestrators of bone remodeling, physical mechanosensors, hematopoietic niche cells, and endocrine regulators of whole-body metabolism (Dallas et al., 2013, Sato et al., 2013, Karsenty and Olson, 2016). Lower osteocyte function has been directly linked to mechanical bone fragility, osteopenia associated with aging or diabetes, chronic kidney disease, and atherosclerosis (Dallas et al., 2013, Lai et al., 2015, Napoli et al., 2017).

Osteocytes derive from osteoblasts through an active and dynamic process involving their embedding in mineralized osteoid matrices. During osteocytogenesis dramatic morphological changes occur, including an important restructuring of the cytoskeleton and acquisition of a unique gene expression profile (Bonewald, 2011). As osteocytogenesis progresses, we see the downregulation of some osteoblastic genes and the progressive expression of osteocyte-specific genes such as Dmp1, Fgf23, and Sost (Woo et al., 2011). Yet the genetic and molecular mechanisms that govern the differentiation and maturation of osteocytes are far from clear.

One of the driving forces of osteoblast-osteocyte transition is likely to be their encasement within a mineralized bone matrix. This restricts their access to oxygen and nutrients and can induce modifications in their metabolic profile (Riddle and Clemens, 2017). The lacuno-canalicular system connects osteocytes between these matrices and allows those near the surface to interact with osteoblasts and bone-lining cells (Buenzli and Sims, 2015). However, the mechanisms of diffusion between the bone surface and the osteocytes are challenged to maintain an adequate supply and exchange of nutrients and metabolic products (Piekarski and Munro, 1977, Petrov and Pollack, 2003, Wang, 2018). Therefore we can infer that osteoblasts, as they differentiate into osteocytes, must adapt to a nutrient-restricted environment. For instance, osteocytes are enriched in proteins involved in hypoxic response, and hypoxic conditions promote the expression of osteocytic genes (Hirao et al., 2007, Guo et al., 2010, Dallas et al., 2013).

It has been shown that osteocytes maintain oxidative status utilizing mainly aerobic mitochondrial pathways (Frikha-Benayed et al., 2016). In contrast, osteoprogenitors and osteoblasts represent by far the most glucose-avid cells in bone with relatively sparse uptake in osteocytes (Dirckx et al., 2018). Glucose is not only used by osteoblasts but also its uptake synergizes with Runx2 to determine bone formation and homeostasis throughout life (Wei et al., 2015). Recent studies have further revealed the importance of aerobic glycolysis for the anabolic effects of parathyroid hormone (PTH) and Wnts (Esen et al., 2013, Esen et al., 2015, Regan et al., 2014). These studies pointed out that modulation of AMPK and/or mTORC1/2 is the mechanism involved in the functional link between glucose metabolism and bone formation.

AMPK acts as a cellular energy sensor and has a critical role in adaptive metabolic reprogramming. Several studies demonstrate that AMPK deletion of AMPKα1, β1, or β2 subunits in mice results in reduced trabecular bone without modifying the numbers of osteoclasts and osteoblasts (Quinn et al., 2010). Once active, AMPK activity leads to higher glucose uptake, autophagy, and mitochondrial biogenesis (Hardie, 2018). Some of these functions are mediated by the proliferator-activated receptor γ co-activator-1 (PGC-1). PGC-1s are transcriptional co-activators that respond to a number of environmental cues and coordinate mitochondrial biogenesis and tissue-specific programs of gene regulation (Villena, 2015). Therefore considering that metabolic rewiring is likely to be crucial for bone cell specification, we hypothesize that low glucose concentration can induce metabolic and genetic reprogramming, which promotes osteocytogenesis.

Results

Glucose Restriction Promotes Osteocyte Differentiation

We investigated the effects of different glucose concentrations, the major source of energy in culture media, on bone cell specification. We differentiated the pre-osteocytic IDG-SW3 cell line and mouse primary osteoblasts in the presence of 1, 5, or 25 mM glucose. Selected glucose concentrations did not affect cell viability or proliferation of IDG-SW3 cells (Figures S1A–S1C). Alkaline phosphatase and alizarin red staining showed the ability of IDG-SW3 cells to differentiate into mature osteoblasts and revealed a decrease in the formation of calcium deposits (alizarin red) when cultured in 25 mM glucose (Figure 1A). Confluent IDG-SW3 cells differentiated into an early stage of osteocyte specification after 14 days in culture at 37°C (Woo et al., 2011). These cells also carry a Dmp1-GFP reporter (expression of GFP under the control of the osteocyte-specific Dmp1 promoter) that facilitates the follow-up of the osteoblast-to-osteocyte transition. Our data showed a negative correlation between osteocytic Dmp1-GFP expression and glucose supply. Low glucose supply enhanced the expression of Dmp1-GFP, as analyzed by either fluorescence microscopy or fluorescence-activated cell sorting (Figures 1A and 1B). To further characterize the induced phenotype, we quantified mRNAs associated with osteoblasts and osteocytes. Gene expression profiling during the osteoblast-to-osteocyte transition in IDG-SW3 cells indicated that mRNA levels of osteoblastic genes (Alpl, Col1a1, Bglap, or Atf4) peaked at the seventh day and decreased thereafter, whereas expression of the osteocytic markers Dmp1 increased at day 14 (Figure 1C). A high-glucose regime reduced the levels of osteoblast genes, such as Bglap, Osx, or Dkk1. More importantly, glucose restriction (1 mM glucose) significantly increased the expression of the osteocyte markers Dmp1 and Fgf23 compared with normoglycemia or hyperglycemia (5 and 25 mM glucose, respectively) (Figure 1C). The effects of distinct glucose concentrations in the osteocytic transcriptional program were independent of changes in the osmotic pressure (Figure S1D). We also investigated the gene expression profile of osteocytes and bone organotypic cultures maintained for 4 and 5 days respectively, with different glucose regimes. As with IDG-SW3 cells, low-glucose media increased the expression of some osteocytic genes (Dkk1, Dmp1, Fgf23, or Sost) in osteocytes and bone organotypic cultures (Figures 1D and S1E). Altogether, these data demonstrated that glucose restriction favors osteocytic gene expression.

Figure 1.

Figure 1

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Effect of Glucose Supply in Osteocyte Differentiation

(A) Representative images of alkaline phosphatase staining (ALP), alizarin red staining, and visualization of Dmp1-GFP expression in IDG-SW3 differentiated for 14 days in the presence of 1, 5, or 25 mM glucose. Cell nuclei were stained with DAPI (blue).

(B) Flow cytometry analysis of Dmp1-GFP expression in IDG-SW3 undifferentiated and differentiated cells for 14 days in the presence of 1, 5, or 25 mM glucose.

(C) mRNA expression profile of osteoblast and osteocyte gene markers during IDG-SW3 differentiation (at 3, 7, and 14 days) in the presence of 1, 5, and 25 mM glucose.

(D) Quantification of mRNA expression levels in primary osteocytes cultured for 4 days in the presence of 1, 5, or 25 mM glucose. mRNA levels were measured by qRT-PCR and normalized to Tbp expression.

Results are plotted as expression relative to undifferentiated IDG-SW3 or osteocytes cultured in 5 mM glucose (mean ± SEM of five to seven independent experiments). *p < 0.05 and **p < 0.01 using one-way ANOVA. See also Figure S1.

Glucose Supply Modifies Osteoblast and Osteocyte Metabolism

We then aimed to characterize bone cell metabolism by different glucose concentrations. IDG-SW3 cells differentiated in low-glucose conditions had decreased intracellular ATP levels compared with normoglycemia or hyperglycemia, which suggests a compromised energy supply (Figure 2A). We assayed lactate released by IDG-SW3 cells during the initial steps of differentiation (24 h) and after complete differentiation (14 days). As expected, either at 24 h or after differentiation, IDG-SW3 cells cultured in low-glucose medium showed a reduction in lactate production, whereas a high-glucose regime raised lactate production values (Figure 2B). For a further characterization of metabolic reprogramming, we also analyzed glucose uptake capacity after differentiation for 14 days in 1, 5, and 25 mM glucose. Glucose uptake was tested at 10 μM glucose for all conditions. Low glucose exposure significantly increased the uptake capacity for glucose, whereas glucose-enriched media decreased it (Figure 2C). We also investigated the bone cell metabolism in primary osteoblasts cultured for 10 days with different glucose concentrations. Mature primary osteoblasts cultured in 1 mM glucose were still able to maintain ATP levels and, as IDG-SW3 cells, osteoblasts increased their glucose uptake capacity in low-glucose conditions (Figures S2A and S2B). Lactate production was also increased when cultured in 25 mM glucose (Figure S2C). Therefore mature osteoblasts in culture can maintain energetic balance and anaerobic glycolysis even at 1 mM glucose. These data suggested a sparing effect in glucose-restricted conditions, maximizing uptake and reducing lactate release, and vice versa under hyperglycemic conditions.

Figure 2.

Figure 2

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Metabolic Profile Induced by Glucose Supply

(A) ATP levels in IDG-SW3 after 14 days of differentiation in the presence of 1, 5, or 25 mM glucose.

(B) Quantification of lactate release in predifferentiated IDG-SW3 cultured in 1, 5, or 25 mM glucose media for 24 h, and in IDG-SW3 differentiated for 14 days in the presence of 1, 5, or 25 mM glucose.

(C) Determination of the maximal uptake capacity for glucose in IDG-SW3 cells differentiated for 14 days in the presence of 1, 5, or 25 mM glucose.

(D) Determination of routine oxygen consumption, leak respiration (uncoupled), electron transfer capacity (ETS), and coupled respiration of IDG-SW3 differentiated for 14 days in the presence of 1, 5, or 25 mM glucose. A total of 700,000 IDG-SW3 cells were incubated in the respirometry chamber with 1, 5, or 25 mM glucose in α-MEM without FBS during the analysis. All results were expressed relative to protein content. Results are plotted as mean ± SEM of four to eight independent experiments.

(E) Flow cytometry analysis of IDG-SW3 cells differentiated for 14 days in the presence of 1, 5, or 25 mM glucose and labeled with MitoTracker Deep Red.

*p < 0.05, **p < 0.01, and ***p < 0.001 using one-way ANOVA. See also Figure S2.

We then measured mitochondrial respiration in intact, differentiated IDG-SW3 cells using the different glucose supplies. These different glucose concentrations were also maintained during the assay as major energy substrate. We determined routine O2 consumption, leak state (uncoupled respiration after addition of oligomycin into the assay), electron transfer capacity (determination of electron transfer system [ETS] after carbonylcyanide-4- (trifluoromethoxy)-phenyl-hydrazone (FCCP)), and coupled respiration. Differences in respiratory parameters were not significant between groups, and we only observed a slightly increased routine respiration in cells cultured with 25 mM glucose (Figure 2D). Interestingly, IDG-SW3 cells were able to maintain O2 consumption under glucose restriction conditions. Moreover, total mitochondrial potential was unmodified by the different glucose regimes when analyzed by flow cytometry using a mitochondrial potential-dependent dye (Figure 2E). It is known that routine respiration is controlled by ATP turnover and substrate availability (Brand and Nicholls, 2011). Therefore these data suggested that cells adapt to meet energy demands by increasing glucose uptake and through the diversion of glucose to mitochondrial respiration.

Glucose Restriction Increases the Mitochondrial DNA and Changes Mitochondrial Morphology

To identify further the changes in energy metabolism induced by glucose supply, we quantified the expression of genes involved in glycolysis and mitochondrial function. GLUT1 (Slc2a1) is the most expressed glucose transporter in IDG-SW3 cells during osteocyte specification (Figure S3A). In addition, different glucose concentrations did not induce a significant change in expression between GLUT family members (Figures S3B and 3A). IDG-SW3 cells and osteoblasts differentiated under low-glucose conditions had higher expression of the glycolytic genes Pfkfb3 and Hk2, whereas the expression of Cox4i1 and the genes involved in mitochondrial fusion/fission Mtf2 and Opa1 did not show significant differences between distinct glucose regimes (Figures 3A and S3C). As mitochondria are remarkable dynamic organelles that respond to changes in energy demands, we wondered whether glucose concentration would modify mitochondrial content and function. Reduced glucose supply increased the ratio of mitochondrial DNA (mtDNA) to nuclear DNA (Figures 3B and S3D). This increase in mtDNA was consistent with an increase in the protein levels of members of the different oxidative phosphorylation (OXPHOS) complexes (Figures 3C and S3E).

Figure 3.

Figure 3

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Modification of Glycolytic Gene Expression and Mitochondrial Function Induced by Glucose Supply

(A) mRNA expression levels of glycolytic and mitochondrial genes in IDG-SW3 differentiated for 14 days in the presence of 1, 5, or 25 mM glucose. mRNA expression levels were measured by qRT-PCR and normalized to Tbp expression. Results were plotted as expression relative to undifferentiated IDG-SW3 (mean ± SEM of six independent experiments).

(B) Quantification of mtDNA (tRNA-Glu) in IDG-SW3 differentiated for 14 days in the presence of 1, 5, or 25 mM glucose. mtDNA copy number was measured by qPCR and normalized relative to nuclear DNA (Dmp1 and Fgf23). Results are plotted as mean ± SEM of six independent experiments.

(C) Immunoblot analysis of the expression of Glut1 and mitochondrial complexes in IDG-SW3 differentiated for 14 days in the presence of 1, 5, or 25 mM glucose.

(D) Visualization of mitochondria in IDG-SW3 differentiated for 14 days in the presence of 1, 5, or 25 mM glucose. Dmp1-GFP was visualized, and mitochondria were stained with MitoTracker Deep Red.

*p < 0.05, **p < 0.01, and ***p < 0.001 using one-way ANOVA. See also Figure S3.

Emerging evidence showed that mitochondria continuously adjust their shape, size, and network organization through fusion or fission events, to regulate their function (Galloway et al., 2012). Confocal images showed dramatic differences in mitochondrial structure and network among the three conditions. IDG-SW3 cells and primary osteoblasts differentiated in 1 mM glucose media arranged their mitochondria in elongated tubules, with higher branching, forming reticular networks (Figures 3D and S3F). In contrast, hyperglycemic conditions increased mitochondrial fragmentation with the formation of ring-like structures in differentiated IDG-SW3 and osteoblasts (Figures 3D and S3F). It has been demonstrated that elongated mitochondria are more resistant to mitophagy and more efficient at producing ATP through enhanced cristae density and ATP synthase dimerization (Gomes et al., 2011). In addition, it is known that ring-like and fragmented mitochondria structures arise from cellular stresses (Yu et al., 2006). Therefore these data suggest that during osteocyte differentiation, glucose restriction stimulates glycolytic pathways and increases mtDNA and efficiency in an effort to maintain ATP levels.

Glucose Restriction Effects on Osteocyte Gene Expression Depend on AMPK

Nutrient starvation signals through activation of AMPK and mTORC1 energy sensors (Carroll and Dunlop, 2017). Thus we determined the activation state of signaling pathways likely to be involved in the metabolic and genetic reprogramming of osteocytes. We analyzed early activation of these pathways during the first hours of differentiation and after complete differentiation, in IDG-SW3 and primary osteoblasts. In response to glucose restriction, AMPK and its substrate acetyl-CoA carboxylase (ACC) became phosphorylated (Figures 4A, 4B, S4A, and S4B). Similarly, the stress kinase p38-MAPK was also activated either at 24 h or after 14 days.

Figure 4.

Figure 4

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Signaling Pathways Involved in Metabolic and Genetic Reprogramming of Osteocytes

(A and B) Immunoblots from IDG-SW3 cells cultured in 1, 5, and 25 mM glucose media for 6, 12, and 24 h (A) or after 14 days of differentiation in 1, 5, and 25 mM glucose media (B).

(C) mRNA expression of osteoblastic and osteocytic genes in IDG-SW3 differentiated for 14 days in 5 mM glucose and treated with 0.05 mM AICAR (activator of AMPK), 0.5 μM SRT2104 (activator of SIRT1), 1 μM sirtinol (inhibitor of SIRT1), and 2.5 μM Mdivi (inhibitor of mitochondrial fission). mRNA levels were measured by qRT-PCR and normalized to Tbp expression. Results were plotted as expression relative to untreated IDG-SW3 (mean ± SEM of five independent experiments).

(D) mRNA expression of osteoblastic and osteocytic genes in organotypic cultures from mouse femur. Organotypic cultures were maintained in 5 mM glucose media and treated with 0.05 mM AICAR, 0.5μM SRT2104, and 1 μM sirtinol for 5 days. mRNA levels were measured by qRT-PCR and normalized to Tbp expression.

Results were expressed as gene expression relative to untreated organotypic cultures (mean ± SEM of five independent experiments). *p < 0.05, **p < 0.01, and ***p < 0.001 using Student's t test. See also Figure S4.

Effects of AMPK on mitochondrial biogenesis rely on PGC-1 (PGC1-α and β) expression and activation (Hardie, 2018). The PGC-1 family of transcriptional co-activators plays a major role in integrating physiological signals into the expression of nuclear-encoded mitochondrial genes (Villena, 2015). Posttranslational modifications that activate PGC-1 members include phosphorylation by AMPK and p38 and deacetylation by SIRT1 (Fan et al., 2004, Gerhart-Hines et al., 2007, Jager et al., 2007). Therefore to further characterize the role of AMPK/SIRT/PGC1α/β pathways in osteocyte reprogramming and differentiation, we treated IDG-SW3 cells and bone organotypic cultures with different chemical modulators of these pathways. The activation of AMPK by AICAR during differentiation increased the expression of Runx2 and Osx in IDG-SW3 cells and the expression of Dmp1, Fgf23, and Sost osteocyte genes in both IDG-SW3 and bone organotypic cultures (Figures 4C and 4D). Similarly, the activation of SIRT1 by SRT2104 treatment induced the expression of late osteocyte markers in both experimental models. On the other hand, the inhibition of SIRT1 by sirtinol reduced the levels of Osx and Fgf23 in IDG-SW3 cultures. These results suggested that the activation of AMPK/SIRT1 enhances osteocytic differentiation.

We also evaluated whether induction of mitochondrial fusion and elongation was sufficient for enhancement of osteocytic gene expression. DRP1 is a dynamin-related GTPase that mediates mitochondrial fission (Galloway et al., 2012). Inhibition of DRP1 by Mdivi-1 increases the number of elongated mitochondria and their reticular network (Cassidy-Stone et al., 2008). Inhibition of mitochondrial fission by Mdivi-1 during osteocytic differentiation reduced the expression of Osx and Dmp1 but only induced the expression of Sost (Figure 4C). These results suggest that mitochondrial reorganization is not sufficient to enhance osteocytogenesis.

PGC-1 Mediates Enhanced Osteocytic Gene Expression in Response to Reduced Glucose Supply

Next, we determined the expression of Ppargc1a and b genes during the osteoblast to osteocyte transition in IDG-SW3 cells and primary osteoblasts. Proliferative IDG-SW3 cells expressed higher levels of Ppargc1a compared with Ppargc1b. Moreover, differentiated cells shifted further toward a major expression of Ppargc1a over Ppargc1b (Figure 5A). Similarly, the ratio of expression between Ppargc1a and Ppargc1b in primary osteoblasts and calvarial mRNA was about 3-fold (data not shown). mRNA levels of PGC-1α or SIRT1 did not change among the three culture conditions in IDG-SW3 (Figure 5B). On the contrary, in primary osteoblasts, glucose restriction induced Ppargc1a and b mRNA expression (Figure S4C). Ppargc1a and b play redundant roles by regulating gene expression programs through their interaction with a variety of transcription factors such as NRF2, ERRα, PPARs, or MEF2. In silico analysis of regulatory motifs present in the promoters of the osteocyte genes Dmp1, Fgf23, and Sost revealed conserved potential binding sites for PGC-1 co-activated factors. We confirmed the recruitment of PGC-1 to these regulatory regions by chromatin immunoprecipitation with an anti-PGC-1α antibody. Ectopic expression of PGC-1α and its activation with AICAR increased PGC-1α occupancy of Fgf23 and Sost promoters in IDG-SW3 cells (Figure 5C). We also determined whether higher PGC-1α activity could induce expression of these genes. Overexpression of ectopic PGC-1α in IDG-SW3 and primary osteoblasts led to higher mRNA levels of osteoblastic (Col1a1, Bglap, Osx) and osteocytic (Dkk1, Fgf23, and Sost) genes (Figure 6A). We also analyzed gene expression in primary osteoblasts and osteocytes deficient in PGC-1α and PGC-1β. Deletion of Ppargc1a and b did not affect cell proliferation or viability, although it reduced morphological reorganization and hampered the increase in mtDNA induced by glucose restriction (Figure S5). Deletion of Ppargc1a and Ppargc1b in primary osteoblasts or osteocytes decreased the levels of Runx2 and Osx irrespective of the glucose regime (Figures 6B and 6C). Furthermore, deletion of Ppargc1a and b genes abolished the induction of the Dmp1, Fgf23, and Sost mRNAs upon glucose restriction. Altogether, these results proved that PGC-1 co-activators act as regulators of osteocyte gene expression.

Figure 5.

Figure 5

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PGC1-α Binds to Osteocytic Promoters

(A) mRNA expression levels of the different isoforms of PGC-1 in IDG-SW3 differentiated for 14 days in 5 mM glucose media. mRNA expression was quantified by qRT-PCR and normalized to Tbp expression. Results are plotted as 2−ΔΔCt (mean ± SEM of six independent experiments).

(B) mRNA expression levels of Ppargc1a, Ppargc1b, and Sirt1 during IDG-SW3 differentiation in 5 mM glucose media. mRNA levels were quantified by qRT-PCR, normalized by Tbp and plotted as expression relative to undifferentiated IDG-SW3 (mean ± SEM of six independent experiments).

(C) Chromatin immunoprecipitation of IDG-SW3 cells infected with control GFP or PGC-1α expression vectors and differentiated in 5 mM glucose media for 5 days in the presence or absence of 0.5 mM AICAR.

Results were normalized to input chromatin and plotted relative to untreated IDG-SW3 cells infected with control GFP vector (mean ± SEM of four independent experiments). *p < 0.05, **p < 0.01, and ***p < 0.001 using Student's t test. See also Figure S4.

Figure 6.

Figure 6

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Role of PGC-1 in Osteocyte Differentiation

(A) mRNA expression levels of IDG-SW3 cells (left) and primary osteoblasts (right) infected with GFP or PGC-1α expression vectors and differentiated in 5 mM glucose media for 5 days. mRNA expression levels were measured by qRT-PCR and normalized to Tbp expression. Results were plotted as expression relative to cells infected with GFP vector (mean ± SEM of six to eight independent experiments).

(B and C) mRNA expression levels of osteocytic and osteoblastic genes in primary osteoblasts (B) and primary osteocytes (C) wild-type and knockout for PGC-1α/β. Osteoblasts and osteocytes were isolated from calvarias obtained from Ppargc1a/bfl/fl mice and infected with pMSCV-Puro or pMSCV-puro-Cre-ERT2 vectors. Infected cells were cultured for five days in 1, 5, or 25 mM glucose media. mRNA expression levels were measured by qRT-PCR and normalized to Tbp.

Results are plotted as expression relative to control infection (mean ± SEM of six independent experiments). *p < 0.05, **p < 0.01, and ***p < 0.001 using Student's t test. See also Figures S5 and S6.

Rearrangement of the cytoskeletal organization is a hallmark of osteocytes. In consequence, we examined the arrangement of actin cytoskeleton in IDG-SW3 cells cultured in different glucose concentrations as well as in osteoblasts and osteocytes either wild-type or deficient in Ppargc1a/b. We did not find significant differences in any of the conditions (Figure S6).

We further explored the role of Ppargc1a/b in bone formation and homeostasis in mice. Transgenic mice for Cre under the control of the 2.3-Col1a1 promoter (Dacquin et al., 2002) allowed deletion of Ppargc1a and b in osteoblasts and osteocytes (hereafter Ppargc1a f/f; Ppargc1b f/f; Col1a1-Cre; knockout [KO]) (Figures S7A and S7B). Ppargc1a/b deletion did not affect either body weight or femur length. As expected, Ppargc1a and Ppargc1b mRNA levels in calvaria from KO mice were significantly reduced in both male and female mice (Figures S7C and S7D). We visualized bone formation in male and female mice in distal femurs by micro-computed tomography scanning and histological analysis. In 8 week-old mice, deletion of Ppargc1a and Ppargc1b led to a decrease in both trabecular and cortical bone architecture. KO male mice presented lower cortical bone volume (BV) associated with reduced cortical thickness, whereas bone perimeter around the midshaft was not affected (Figure 7A). In addition, distal femurs in males also presented less trabecular bone volume (BV/TV) resulting from a significantly lower trabecular number (Tb.N) and trabecular thickness (Tb.Th) (Figure 7A). Trabecular analysis of distal femurs in KO females also showed a significant reduction in BV/TV, Tb.N, and Tb.Th. However, reduction in cortical bone parameters were lower in magnitude and did not reach significant differences (Figure 7B). To clarify the underlying reason for the osteopenic phenotype of the KO mice, we analyzed the expression of osteoblast and osteocyte genes from calvaria. KO male and female mice displayed a reduced expression of osteocyte genes, including Dmp1, Fgf23, and Sost, and increased levels of osteoblastic genes such as Bglap, Runx2, or Osx (Figure 7C). Reduced osteocyte gene expression occurs without significant changes in either the density of osteocytes per bone area or the number of empty lacunae in cortical bone (Figures S8 and S9). Mice deficient for Ppargc1α/β showed reduced Rankl/Opg ratio of expression in calvaria (Figure S10). Similar results were obtained in osteocytes deficient in Ppargc1α/β. These data suggest that although Ppargc1α/β affects the expression of Rankl and Opg in osteocytes, osteopenia in young Ppargc1α/β-deficient mice does not arise for increased osteoclastogenesis induced directly by an increased Rankl/Opg ratio. In conclusion, our data demonstrate the relevant role of PGC-1 in co-activation of the osteoblast and osteocyte transcriptional programs.

Figure 7.

Figure 7

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Bone phenotype of Ppargc1α/β Conditional Knockout Mice

(A and B) Micro-computed tomographic analysis and representative images of femurs obtained from male (A) and female (B) Ppargc1a/bf/f;Col1a1-Cre and control (Ppargc1a/bf/f) mice. Results were plotted as mean ± SEM of 8–11 independent animals.

(C) mRNA expression levels of osteocytic and osteoblastic genes in calvaria obtained from PGC1α/β conditional knockout (Ppargc1a/bf/f;Col1a1-Cre) and control mice.

Results are plotted as mean ± SEM of eight independent animals. mRNA expression levels were measured by qRT-PCR and normalized to Tbp expression. *p < 0.05, **p < 0.01, and ***p < 0.001 using Student's t test. B.Ar, bone area; B.Pm, bone perimeter; Ct.Th, cortical thickness; Tb.N, trabecular number; Tb.Sp, trabecular spacing; Tb.Th, trabecular thickness; See also Figures S7–S10.

Discussion

In this study, we identified that a reduced supply of glucose facilitates the expression of osteocytic genes in osteoblast/osteocyte precursors. These effects took place in parallel with an increased mtDNA. Glucose reduction triggers the activation of the AMPK/PGC-1 pathway whereas AMPK and SIRT1 activators were sufficient to increase osteocyte gene expression. Osteoblasts and osteocytes deficient in Ppargc1a and b were refractory for glucose restriction effects, whereas mice deficient in both genes were osteopenic. Our data strongly support modulation of the metabolic state as a strategy for the differentiation of bone cells.

In recent years, several studies have demonstrated that metabolism of osteoblast lineage cells is programmed to optimize energy production to fulfill functional demands throughout their life cycle (Riddle and Clemens, 2017). Early stage of osteoblast specification relies on glycolysis to generate ATP, initiate collagen synthesis, and stabilize RUNX2 expression (Wei et al., 2015, Guntur et al., 2018). Accordingly, molecular signals that determine osteoblast specification, such as Wnt, PTH, or Hypoxia-inducible factor 1 (HIF-1), also promote aerobic glycolysis in osteoblast progenitors (Esen et al., 2013, Esen et al., 2015, Regan et al., 2014, Dirckx et al., 2018). However, in the adult human skeleton, about 42 billion osteocytes are entrapped in their own mineralized matrix while being connected by cytoplasmic projections with a total length of 175,000 km. These resident osteocytes leave space for just 24 mL extracellular fluid (Buenzli and Sims, 2015). Therefore osteocyte transition and network formation processes are likely to demand high levels of energy in a nutrient-restricted environment. Our data demonstrate that a shift of the metabolic machinery toward a higher mitochondrial function occurs during the transition of osteoblasts into osteocytes under conditions of glucose restriction. Mitochondria optimize their morphology to cope with reduced caloric supply. Correspondingly, osteocytes in vivo have been shown to have numerous mitochondria and to maintain normal oxidative status through mitochondrial pathways (Frikha-Benayed et al., 2016). Osteocytes contribute little to glucose consumption in murine bones compared with osteoprogenitors and osteoblasts (Dirckx et al., 2018). Furthermore, it has been recently shown that bone accumulates a significant fraction of postprandial fatty acids and that suppression of fatty acid oxidation in mature osteoblasts and osteocytes impairs bone accrual (Kim et al., 2017). This link between metabolic reprogramming and cellular specification was already well established for other models of cell specification. For example, higher mitochondrial biogenesis and function is related to the final stage of neurogenesis, astrocytogenesis, hepatic differentiation, and erythropoiesis (Agostini et al., 2016, Xing et al., 2017). On the other hand, we also found that hyperglycemic conditions modify mitochondrial organization and impair osteoblast and osteocyte gene expression. Hyperglycemic microenvironments have been associated with a reduction in osteocyte number and function (Rinker et al., 2014), whereas bone turnover and remodeling have been found to be compromised in patients with diabetes (Kalaitzoglou et al., 2016).

Consistent with its role as regulator of energy homeostasis, we found an inverse correlation between AMPK activity and glucose supply. These results are in agreement with recent evidence showing that AMPK became activated by phosphorylation at Thr172, by sensing not only low cellular energy but also low glucose supply (Lin and Hardie, 2017, Zhang et al., 2017). Activation of AMPK with AMP analogs in normoglycemia was sufficient to induce osteocyte gene expression in IDG-SW3 cells and organotypic bone cultures. Indeed, studies using whole-body and osteoblast-specific genetic abrogation of AMPK activity showed lower cortical and trabecular bone density and enhanced bone turnover (Jeyabalan et al., 2012, Kanazawa et al., 2018). It has been shown that AMPK activation decreases Rankl and increases Sost expression in osteocytes to delicately coordinate bone turnover (Jeyabalan et al., 2012). Our data also demonstrated that activation of SIRT1 by SRT2104 led to increased osteocyte gene expression program in IDG-SW3 cells and organotypic bone cultures. An increase in bone mineral density was observed in mice fed on a diet supplemented with SRT2104 and shown to be Sirt1 dependent (Mercken et al., 2014). The beneficial role of SIRT1 in bone formation and remodeling were further confirmed in whole-body and osteoblast-specific Sirt1-deficient mice, which displayed low bone mass phenotype (Cohen-Kfir et al., 2011). Moreover, SIRT1 activation gave protection against osteoporosis in both mice and humans (Ornstrup et al., 2014).

We identified a key role of PGC-1, downstream of AMPK, in the coordination of mitochondrial biogenesis and osteocyte specification in cultured cells and murine models. Lessons from other tissues indicate that PGC-1α and PGC-1β have a redundant transcriptional role because noticeable phenotypes were only observed when the expression of both co-activators was abolished (Villena, 2015). Our data show that PGC-1α/β also have a fundamental role in osteoblast and osteocyte function and bone homeostasis. Ppargc1a was expressed in osteoblasts and osteocytes in preference to Ppargc1b. Moreover, osteoblast-to-osteocyte transition further increased this tendency. Interestingly, PGC-1β is the main member of the PGC-1 family expressed in osteoclasts and is specifically required for osteoclast function (Wei et al., 2010, Zhang et al., 2018). The functional and therapeutic implications of such cell-type-specific co-activator preferences await further research. For instance, the action of different activators of PGC-1α in osteoblasts prevents bone loss in type 2 diabetes models without improving diabetes in a PGC-1α-dependent manner (Khan et al., 2015).

PGC-1 co-activates specific transcription factors, including NRF1, NRF2, PPARs, ERα, ERRα, and MEF2C (Villena, 2015). Co-activation of ERα could account for the milder osteopenic phenotypes that we obtained in female mice because osteocyte-specific deletion of ERα has been shown to affect bone mineral density only in male mice (Lee et al., 2003, Windahl et al., 2013). Co-activation of diverse transcription factors by PGC-1 has been shown to deeply affect developmental transcriptional programs such as erythropoiesis, chondrogenesis, and differentiation of hepatocytes, cardiomyocytes, and brown adipocytes (Wanet et al., 2017, Cui et al., 2014). Our data show that this would also be the case for osteocytogenesis. For instance, PGC-1α binds to the Fgf23 or Sost gene promoters, whereas overexpression and loss-of-function experiments produce effects on the expression of Dmp1, Dkk1, Fgf23, Sost, or Osx genes. We found numerous conserved binding sites for known transcription factors in the promoter and enhancer regions of Fgf23, Sost, Dmp1, or Osx genes that could mediate their regulation by PGC1-α. For instance, it is known that ERα, NRF2, PPARs, ERRα, and MEF2C positively regulate osteocyte gene expression (Kramer et al., 2012, Stechschulte et al., 2016). Therefore PGC-1s are able to co-activate a number of transcription factors with universal and osteocyte-specific functions. Altogether, we have uncovered a central role of PGC-1-mediated transcriptional program required for osteoblast and osteocyte function.

Limitations of Study

Our results demonstrate that glucose restriction promotes osteocytic gene expression through PGC-1-mediated transcriptional co-activation. However, at present, the transcription factors directly involved in this co-activation in specific gene promoters are still unknown and require further investigation. In addition, Ppargc1a/b is deleted in both osteoblasts and osteocytes in our mouse model. Therefore we are unable to distinguish the relative contribution in bone homeostasis in vivo of PGC-1 expressed in osteoblasts and osteocytes.

Methods

All methods can be found in the accompanying Transparent Methods supplemental file.

Acknowledgments

We thank Dr. L. Bonewald for IDG-SW3 cells. We also thank E. Adanero, E. Castaño, B. Barroso, and L. Gómez-Segura for technical assistance. Cristina Sánchez de Diego and Carolina Pimenta Lopes are the recipients of F.P.U. fellowships from the Spanish Ministry of Education. N.A. and Pau Gama are recipients of a fellowship from the University of Barcelona. This research was supported by grants from the M.E.C. (BFU2014-56313-P and BFU2017-8 2421-P) and Fondo Europeo de Desarrollo Regional (FEDER).

Author Contributions

Conceived and designed the experiments: C.S.-d.-D., N.A., C.P.-L., B.T., P.M.G.-R., J.L.R., and F.V. Performed the experiments: C.S.-d.-D., N.A., C.P.-L., J.A. Valer, B.T., P.G.-P., P.M.G.-R., J.L.R., and F.V. Analyzed the data: C.S.-d.-D., N.A., C.P.-L., P.M.G.-R., J.L.R., and F.V. Contributed materials J.A. Villena. Wrote the paper: C.S.-d.-D., F.V.

Declaration of Interests

The authors declare no conflicts of interest.

Published: May 31, 2019

Footnotes

Supplemental Information can be found online at https://doi.org/10.1016/j.isci.2019.04.015.

Supplemental Information

Document S1. Transparent Methods and Figures S1–S10
mmc1.pdf (4.5MB, pdf)

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Associated Data

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Supplementary Materials

Document S1. Transparent Methods and Figures S1–S10
mmc1.pdf (4.5MB, pdf)

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