Endocrinol Metab.  2020 Jun;35(2):456-469. 10.3803/EnM.2020.35.2.456.

Transformation of Mature Osteoblasts into Bone Lining Cells and RNA Sequencing-Based Transcriptome Profiling of Mouse Bone during Mechanical Unloading

• Hong AR
• Kim K
• Lee JY
• Yang JY
• Kim JH
• Shin CS
• Kim SW

• KMID: 2503276
• DOI: http://doi.org/10.3803/EnM.2020.35.2.456

Abstract

Background
We investigated RNA sequencing-based transcriptome profiling and the transformation of mature osteoblasts into bone lining cells (BLCs) through a lineage tracing study to better understand the effect of mechanical unloading on bone loss.
Methods
Dmp1-CreERt2(+):Rosa26R mice were injected with 1 mg of 4-hydroxy-tamoxifen three times a week starting at postnatal week 7, and subjected to a combination of botulinum toxin injection with left hindlimb tenotomy starting at postnatal week 8 to 10. The animals were euthanized at postnatal weeks 8, 9, 10, and 12. We quantified the number and thickness of X-gal(+) cells on the periosteum of the right and left femoral bones at each time point.
Results
Two weeks after unloading, a significant decrease in the number and a subtle change in the thickness of X-gal(+) cells were observed in the left hindlimbs compared with the right hindlimbs. At 4 weeks after unloading, the decrease in the thickness was accelerated in the left hindlimbs, although the number of labeled cells was comparable. RNA sequencing analysis showed downregulation of 315 genes in the left hindlimbs at 2 and 4 weeks after unloading. Of these, Xirp2, AMPD1, Mettl11b, NEXN, CYP2E1, Bche, Ppp1r3c, Tceal7, and Gadl1 were upregulated during osteoblastogenic/osteocytic and myogenic differentiation in vitro.
Conclusion
These findings demonstrate that mechanical unloading can accelerate the transformation of mature osteoblasts into BLCs in the early stages of bone loss in vivo. Furthermore, some of the genes involved in this process may have a pleiotropic effect on both bone and muscle.

Keyword

Bone; Osteoporosis; Genes; Gene expression profiling

Figure

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  Fig. 1 Experimental design. For a lineage tracing study, Dmp1-CreERt2:Rosa26R mice were injected with 1 mg of 4-hydroxy-tamoxifen (4-OHTam) three times on postnatal week 7. To determine the fate of mature osteoblasts in vivo, animals were euthanized at postnatal weeks 8, 9, 10, and 12 (2 days, 1, 2, and 4 weeks after the last 4-OHTam treatment). Mechanical unloading was achieved by botulinum toxin and/or achilles tenotomy in the left hindlimb. The right hindlimb served as the control. RNA sequencing-based transcriptome profiling was performed with wild-type (C57BL/6) mice using the same experimental protocol.

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  Fig. 2 (A, B) Changes in bone mass and microarchitecture during mechanical unloading. In vivo measurements of bone mass using dual-energy X-ray absorptiometry. (A) Body weight-adjusted total body bone mineral density (BMD) and (B) hindlimb bone mineral content (BMC). (C-G) Ex vivo measurements of microarchitecture using micro-computed tomography (μCT). (C) The data are representative three-dimensional μCT images of the trabecular bone regions of proximal tibiae from mice euthanized on postnatal week 12 (4 weeks after unloading, left: control hindlimb; right: unloading hindlimb). (D) Bone volume/total volume (BV/TV) (%), (E) trabecular thickness (Tb.Th), (F) trabecular number (Tb.N), (G) trabecular separation (Tb.Sp). Data are expressed as mean±SEM (n=8 to 10 per group). aP<0.05.

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  Fig. 3 Effects of mechanical unloading on the transformation of mature osteoblasts into bone lining cells on the periosteal surface of the femur. 5-Bromo-4-chloro-3-indolyl-β-d-galactopyranoside (X-gal) staining was performed in both hindlimbs on 2 days (postnatal 8 weeks), 1 week (9 weeks), 2 weeks (10 weeks), or 4 weeks (12 weeks) after the last 4-hydroxy-tamoxifen injection, respectively. Unloading was performed on the left hindlimbs, while the right hindlimbs served as controls. (A) Data are representative of the experimental analyses performed on sections. Quantitative analysis of the number (B) and thickness (C) of X-gal(+) cells on the periosteum. Data are expressed as mean±SEM (n=4 to 6 per group). aP<0.05 between controls; bP<0.05 between unloaded hindlimbs; cP<0.05 between unloaded hindlimbs and controls at each time point.

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  Fig. 4 Effects of mechanical unloading on serum levels of N-terminal propeptide of type I procollagen (P1NP). Data are expressed as mean±SEM (n=15 per group). aP<0.05.

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  Fig. 5 Scatter plot of log2 fold change (FC) and Venn diagram for differentially expressed gene (DEG) analysis. RNA sequencing-based analysis of differentially expressed mRNA after mechanical unloading at postnatal weeks 10 and 12 mice. DEGs were defined using the following criteria: |log2(FC)|>log2(1.2) and |avg(log2(FC))|>log2(1.5) at postnatal weeks 8 and 12; and each log2(FC)>log2(1.5) at postnatal week 10. Scatter plot of DEG analysis at postnatal weeks 10 (A) and 12 (B). Red dots: upregulated (Up) DEGs, blue dots: downregulated (Dn) DEGs, and gray dots: non-DEGs. (C) Venn diagram for DEG analysis. Each number indicates the number of upregulated and downregulated genes at postnatal weeks 10 and 12 (n=3/group in postnatal weeks 8 and 12; n=2/group in postnatal week 10).

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  Fig. 6 Gene set analysis for 315 genes downregulated at both postnatal weeks 10 and 12 using the Database for Annotation, Visualization and Integrated Discovery (DAVID) web-based tool. P values were calculated using the Fisher exact test. Significantly enriched gene sets were determined by a Benjamini-Hochberg adjusted P value (q value) below 0.05.

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  Fig. 7 Protein-protein interaction network analysis of differentially expressed genes (DEGs) in subnetwork 1. The STRING database was used to analyze the protein-protein interaction network based on the proteins corresponding to selected DEGs.

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  Fig. 8 mRNA expression levels of nine genes downregulated at both postnatal weeks 10 and 12 on (A) osteoblastogenic, (B) myogenic, and (C) osteocytic differentiation using quantitative real-time polymerase chain reaction. aP<0.05 between un-differentiated and differentiated cell lines.

Reference

1. Lanyon LE, Hampson WG, Goodship AE, Shah JS. Bone deformation recorded in vivo from strain gauges attached to the human tibial shaft. Acta Orthop Scand. 1975; 46:256–68.

2. Usui T, Maki K, Toki Y, Shibasaki Y, Takanobu H, Takanishi A, et al. Measurement of mechanical strain on mandibular surface with mastication robot: influence of muscle loading direction and magnitude. Orthod Craniofac Res. 2003; 6(Suppl 1):163–7. 179–82.

3. Hong AR, Kim SW. Effects of resistance exercise on bone health. Endocrinol Metab (Seoul). 2018; 33:435–44.

4. Globus RK, Bikle DD, Morey-Holton E. The temporal response of bone to unloading. Endocrinology. 1986; 118:733–42.

5. Vandamme K, Holy X, Bensidhoum M, Deschepper M, Logeart-Avramoglou D, Naert I, et al. Impaired osteoblastogenesis potential of progenitor cells in skeletal unloading is associated with alterations in angiogenic and energy metabolism profile. Biomed Mater Eng. 2012; 22:219–26.

6. Inoue M, Tanaka H, Moriwake T, Oka M, Sekiguchi C, Seino Y. Altered biochemical markers of bone turnover in humans during 120 days of bed rest. Bone. 2000; 26:281–6.

7. Vico L, Collet P, Guignandon A, Lafage-Proust MH, Thomas T, Rehaillia M, et al. Effects of long-term microgravity exposure on cancellous and cortical weight-bearing bones of cosmonauts. Lancet. 2000; 355:1607–11.

8. LeBlanc A, Marsh C, Evans H, Johnson P, Schneider V, Jhingran S. Bone and muscle atrophy with suspension of the rat. J Appl Physiol (1985). 1985; 58:1669–75.

9. Fitts RH, Metzger JM, Riley DA, Unsworth BR. Models of disuse: a comparison of hindlimb suspension and immobilization. J Appl Physiol (1985). 1986; 60:1946–53.

10. Judex S, Garman R, Squire M, Busa B, Donahue LR, Rubin C. Genetically linked site-specificity of disuse osteoporosis. J Bone Miner Res. 2004; 19:607–13.

11. Doherty TJ. The influence of aging and sex on skeletal muscle mass and strength. Curr Opin Clin Nutr Metab Care. 2001; 4:503–8.

12. Palmer IJ, Runnels ED, Bemben MG, Bemben DA. Muscle-bone interactions across age in men. J Sports Sci Med. 2006; 5:43–51.

13. Raisz LG, Seeman E. Causes of age-related bone loss and bone fragility: an alternative view. J Bone Miner Res. 2001; 16:1948–52.

14. Raisz LG, Rodan GA. Pathogenesis of osteoporosis. Endocrinol Metab Clin North Am. 2003; 32:15–24.

15. Kim SW, Pajevic PD, Selig M, Barry KJ, Yang JY, Shin CS, et al. Intermittent parathyroid hormone administration converts quiescent lining cells to active osteoblasts. J Bone Miner Res. 2012; 27:2075–84.

16. Jang MG, Lee JY, Yang JY, Park H, Kim JH, Kim JE, et al. Intermittent PTH treatment can delay the transformation of mature osteoblasts into lining cells on the periosteal surfaces. J Bone Miner Metab. 2016; 34:532–9.

17. Kim SW, Lu Y, Williams EA, Lai F, Lee JY, Enishi T, et al. Sclerostin antibody administration converts bone lining cells into active osteoblasts. J Bone Miner Res. 2017; 32:892–901.

18. Boppart MD, Kimmel DB, Yee JA, Cullen DM. Time course of osteoblast appearance after in vivo mechanical loading. Bone. 1998; 23:409–15.

19. Dallas SL, Prideaux M, Bonewald LF. The osteocyte: an endocrine cell... and more. Endocr Rev. 2013; 34:658–90.

20. Pedersen BK. Muscle as a secretory organ. Compr Physiol. 2013; 3:1337–62.

21. Brotto M, Bonewald L. Bone and muscle: interactions beyond mechanical. Bone. 2015; 80:109–14.

22. Kramer I, Baertschi S, Halleux C, Keller H, Kneissel M. Mef2c deletion in osteocytes results in increased bone mass. J Bone Miner Res. 2012; 27:360–73.

23. Huang J, Hsu YH, Mo C, Abreu E, Kiel DP, Bonewald LF, et al. METTL21C is a potential pleiotropic gene for osteoporosis and sarcopenia acting through the modulation of the NF-κB signaling pathway. J Bone Miner Res. 2014; 29:1531–40.

24. Soriano P. Generalized lacZ expression with the ROSA26 Cre reporter strain. Nat Genet. 1999; 21:70–1.

25. Chung UI, Lanske B, Lee K, Li E, Kronenberg H. The parathyroid hormone/parathyroid hormone-related peptide receptor coordinates endochondral bone development by directly controlling chondrocyte differentiation. Proc Natl Acad Sci U S A. 1998; 95:13030–5.

26. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014; 30:2114–20.

27. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013; 29:15–21.

28. Liao Y, Smyth GK, Shi W. FeatureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014; 30:923–30.

29. Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 2003; 4:P3.

30. Doncheva NT, Morris JH, Gorodkin J, Jensen LJ. Cytoscape StringApp: network analysis and visualization of proteomics data. J Proteome Res. 2019; 18:623–32.

31. Wang J, Zhong J, Chen G, Li M, Wu FX, Pan Y. ClusterViz: a Cytoscape app for cluster analysis of biological network. IEEE/ACM Trans Comput Biol Bioinform. 2015; 12:815–22.

32. Bindea G, Galon J, Mlecnik B. CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data. Bioinformatics. 2013; 29:661–3.

33. Bindea G, Mlecnik B, Hackl H, Charoentong P, Tosolini M, Kirilovsky A, et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics. 2009; 25:1091–3.

34. Powell WF Jr, Barry KJ, Tulum I, Kobayashi T, Harris SE, Bringhurst FR, et al. Targeted ablation of the PTH/PTHrP receptor in osteocytes impairs bone structure and homeostatic calcemic responses. J Endocrinol. 2011; 209:21–32.

35. Maes C, Kobayashi T, Selig MK, Torrekens S, Roth SI, Mackem S, et al. Osteoblast precursors, but not mature osteoblasts, move into developing and fractured bones along with invading blood vessels. Dev Cell. 2010; 19:329–44.

36. Wein MN, Spatz J, Nishimori S, Doench J, Root D, Babij P, et al. HDAC5 controls MEF2C-driven sclerostin expression in osteocytes. J Bone Miner Res. 2015; 30:400–11.

37. Ayturk UM, Jacobsen CM, Christodoulou DC, Gorham J, Seidman JG, Seidman CE, et al. An RNA-seq protocol to identify mRNA expression changes in mouse diaphyseal bone: applications in mice with bone property altering Lrp5 mutations. J Bone Miner Res. 2013; 28:2081–93.

38. McCalmon SA, Desjardins DM, Ahmad S, Davidoff KS, Snyder CM, Sato K, et al. Modulation of angiotensin II-mediated cardiac remodeling by the MEF2A target gene Xirp2. Circ Res. 2010; 106:952–60.

39. Wang H, Li Z, Wang J, Sun K, Cui Q, Song L, et al. Mutations in NEXN, a Z-disc gene, are associated with hypertrophic cardiomyopathy. Am J Hum Genet. 2010; 87:687–93.

40. Armoni M, Harel C, Ramdas M, Karnieli E. CYP2E1 impairs GLUT4 gene expression and function: NRF2 as a possible mediator. Horm Metab Res. 2014; 46:477–83.

41. Lee SK, Moon JW, Lee YW, Lee JO, Kim SJ, Kim N, et al. The effect of high glucose levels on the hypermethylation of protein phosphatase 1 regulatory subunit 3C (PPP1R3C) gene in colorectal cancer. J Genet. 2015; 94:75–85.

42. Cheng J, Morisaki H, Toyama K, Sugimoto N, Shintani T, Tandelilin A, et al. AMPD1: a novel therapeutic target for reversing insulin resistance. BMC Endocr Disord. 2014; 14:96.

43. Shi X, Garry DJ. Myogenic regulatory factors transactivate the Tceal7 gene and modulate muscle differentiation. Biochem J. 2010; 428:213–21.

44. En-Nosse M, Hartmann S, Trinkaus K, Alt V, Stigler B, Heiss C, et al. Expression of non-neuronal cholinergic system in osteoblast-like cells and its involvement in osteogenesis. Cell Tissue Res. 2009; 338:203–15.