Skip to main content
SpringerLink
Log in

Osteogenic Differentiation In Vitro of Human Osteoblasts Is Associated with Only Slight Shift in Their Proteomics Profile

  • Published:
Cell and Tissue Biology Aims and scope Submit manuscript

Abstract

Fracture healing is a complex process in which the periosteum and endosteum become the main sources of osteoblast progenitor cells. However, cellular mechanisms and signaling cascades underlying the early stages of osteoblast progenitors differentiation in adult bone are still not well understood. Therefore, we performed shotgun proteomics analysis of primary culture of isolated human osteoblasts from femur of adult donors in undifferentiated conditions and on the fifth day of osteogenic differentiation in vitro. This is an early timepoint in which we have observed no extracellular matrix mineralization yet. 1612 proteins identified with at least two unique peptides were included in proteomics analysis. Data are available via ProteomeXchange with identifier PXD033697. Despite the fact, that matrix mineralization starts only after induction of osteogenic differentiation, we revealed unexpectedly weak physiological shift associated with a decrease of cells proliferative activity and changes in proteins involved in extracellular matrix secretion and organization. We demonstrated that osteoblasts were positive for markers of later osteogenic differentiation stages during standard cultivation: osteopontin, osteocalcin, BMP-2/4 and RUNX2. Therefore, further differentiation required for matrix mineralization needs minimal physiological changes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.

Similar content being viewed by others

REFERENCES

  1. Bahney, C., Zondervan, R., Allison, P., Theologis, A., Ashley, J., Ahn, J., Miclau, T., Marcucio, R., and Hankenson, K., Cellular biology of fracture healing, J. Orthop. Res., 2019, vol. 37, pp. 35–50.  https://doi.org/10.1002/jor.24170

    Article  Google Scholar 

  2. Blighe, K., Sharmila, R., and Myles, L., EnhancedVolcano: publication-ready volcano plots with enhanced colouring and labeling, 2022. https://bioconductor.org/packages/devel/bioc/vignettes/EnhancedVolcano/inst/doc/EnhancedVolcano.html

  3. Bragdon, B. and Bahney, C., Origin of reparative stem cells in fracture healing, Curr. Osteoporos. Rep., 2018, vol. 16, pp. 490–503.  https://doi.org/10.1007/s11914-018-0458-4

    Article  Google Scholar 

  4. Cleland, T. and Vashishth, D., Bone protein extraction without demineralization utilizing principles from hydroxyapatite chromatography, Anal. Biochem., 2015, vol. 472, pp. 62–66.  https://doi.org/10.1016/j.ab.2014.12.006

    Article  CAS  Google Scholar 

  5. Cleland, T., Voegele, K., and Schweitzer, M., Empirical evaluation of bone extraction protocols, PLoS One, 2012, vol. 7, p. e31443. https://doi.org/10.1371/journal.pone.0031443

    Article  CAS  Google Scholar 

  6. Florencio-Silva, R., Sasso, G., Sasso-Cerri, E., Simões, M., and Cerri, P., Biology of bone tissue: structure, function, and factors that influence bone cells, Biomed. Res. Int., 2015, vol. 2015, p. e421746. https://doi.org/10.1155/2015/421746

    Article  CAS  Google Scholar 

  7. Hastie, T., Tibshirani, R., Narasimhan, B., and Chu, G., Impute: imputation for microarray data. Bioconductor version: release (3.14), 2022.  https://www.bioconductor.org/packages/release/bioc/html/impute.html

  8. Jiang, X., Ye, M., Jiang, X., Liu, G., Feng, S., Cui, L., and Zou, H., Method development of efficient protein extraction in bone tissue for proteome analysis, J. Proteome Res., 2007, vol. 6, pp. 2287–2294. https://doi.org/10.1021/pr070056t

    Article  CAS  Google Scholar 

  9. Lobov, A. and Malashicheva, A., Osteogenic differentiation: a universal cell program of heterogeneous mesenchymal cells or a similar extracellular matrix mineralizing phenotype?, Biol. Commun., 2022, vol. 67, pp. 32–48. https://doi.org/10.21638/spbu03.2022.104

    Article  Google Scholar 

  10. Matthews, B., Novak, S., Sbrana, F., Funnell, J., Cao, Y., Buckels, E., Grcevic, D., and Kalajzic, I., Heterogeneity of murine periosteum progenitors involved in fracture healing, Elife, 2021, vol. 10, p. e58534. https://doi.org/10.7554/eLife.58534

    Article  CAS  Google Scholar 

  11. Perez-Riverol, Y., Bai, J., Bandla, C., García-Seisde-dos, D., Hewapathirana, S., Kamatchinathan, S., Kun-du, D.J., Prakash, A., Frericks-Zipper, A., Eisenacher, M., et al., The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences, Nucleic Acids Res., 2022, vol. 50, pp. D543–D552. https://doi.org/10.1093/nar/gkab1038

    Article  CAS  Google Scholar 

  12. Pitkänen, S., In vitro and in vivo osteogenesis and vasculogenesis in synthetic bone grafts, Doctoral Dissertation, Tampere University, 2020.

  13. Raouf, A., Ganss, B., McMahon, C., Vary, C., Roughley, P.J., and Seth, A. Lumican is a major proteoglycan component of the bone matrix, Matrix Biol., 2002, vol. 21, p. 361–367. https://doi.org/10.1016/s0945-053x(02)00027-6

    Article  CAS  Google Scholar 

  14. Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., Smyth, G.K., Limma powers differential expression analyses for RNA-sequencing and microarray studies, Nucleic Acids Res., 2015, vol. 43, p. e47. https://doi.org/10.1093/nar/gkv007

    Article  CAS  Google Scholar 

  15. Rohart, F., Gautier, B., Singh, A., and Cao, K., mixOmics: an R package for ‘omics feature selection and multiple data integration, PLoS Comput. Biol., 2017, vol. 13, p. e1005752. https://doi.org/10.1371/journal.pcbi.1005752

    Article  CAS  Google Scholar 

  16. Rutkovskiy, A., Stensløkken, K., and Vaage, I., Osteoblast differentiation at a glance, Med. Sci. Monit. Basic Res., 2016, vol. 22, pp. 95–106. https://doi.org/10.12659/MSMBR.901142

    Article  Google Scholar 

  17. Wickham, H., ggplot2, Cham: Springer Int. Publ., 2016.

  18. Yan L., ggvenn: Draw Venn Diagram by “ggplot2”, 2021. https://cran.r-project.org/web/packages/ggvenn/

Download references

ACKNOWLEDGMENTS

Shotgun proteomics were performed in the research center «Molecular and cell technologies» of St. Petersburg State University Research Park.

Funding

The work was supported by the Russian Science Foundation (RSF), research grant no. 18-14-00152.

Author information

Authors and Affiliations

  1. Laboratory of Regenerative Biomedicine, Institute of Cytology of the Russian Academy of Sciences, 194064, St. Petersburg, Russia

    I. A. Khvorova, D. A. Kostina, E. A. Fefilova, E. S. Gromova, A. B. Malashicheva & A. A. Lobov

  2. Resource Centre for Molecular and Cell Technologies, St. Petersburg State University, 199034, St. Petersburg, Russia

    B. R. Zainullina

  3. Vreden National Medical Research Center of Traumatology and Orthopedics, 195427, St. Petersburg, Russia

    R. M. Tikhilov, S. A. Bozhkova, A. P. Sereda & V. V. Karelkin

Authors
  1. I. A. Khvorova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D. A. Kostina
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. B. R. Zainullina
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. E. A. Fefilova
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. E. S. Gromova
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. R. M. Tikhilov
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. S. A. Bozhkova
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. A. P. Sereda
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. V. V. Karelkin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. A. B. Malashicheva
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. A. A. Lobov
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization, A.A.L.; methodology, I.A.K., A.A.L., A.B.M.; software, I.A.K., A.A.L.; validation, A.A.L., D.S.K., A.B.M.; formal analysis: I.A.K.; investigation, I.A.K., D.S.K., B.R.Z., E.S.G., R.M.T., S.A.B., A.P.S., V.V.K.; resources, A.A.L., A.B.M.; data curation, I.A.K., D.S.K.; writing—original draft preparation, I.A.K.; review and editing, A.A.L. and A.B.M.; visualization, E.S.G., I.A.K.; supervision, A.A.L., A.B.M.; project administration, A.B.M.; funding acquisition, A.A.L., A.B.M. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to A. A. Lobov.

Ethics declarations

Conflict of interest. The authors declare no conflicts of interest.

Statement of compliance with standards of research involving humans as subjects. All procedures performed in the study involving human beings complied with the ethical standards of the institutional and/or national research ethics committee and the 1964 Helsinki Declaration and its subsequent changes or comparable ethical standards. An informed written consent was obtained from each of the participants enrolled in the study.

Additional information

Abbreviations: DAVID—database for Aanotation, visualization and integrated discovery, DMEM—Dulbecco’s modified Eagle medium; ECM—extracellular matrix, FBS—fetal bovine serum, FDR—false discovery rate; GO BP—gene ontology biological process, MSC—mesenchymal stem cells, PBS—phosphate-buffered saline, PCA—principal component analysis, sPLS-DA—sparse partial least squares discriminant analysis, VEGF— vascular endothelial growth factors.

Supplementary Information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khvorova, I.A., Kostina, D.A., Zainullina, B.R. et al. Osteogenic Differentiation In Vitro of Human Osteoblasts Is Associated with Only Slight Shift in Their Proteomics Profile. Cell Tiss. Biol. 16, 540–546 (2022). https://doi.org/10.1134/S1990519X22060025

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1990519X22060025

Keywords:

Search

Navigation