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Novel immortalization approach defers senescence of cultured canine adipose-derived mesenchymal stromal cells

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Abstract

In the last decades, the scientific community spared no effort to elucidate the therapeutic potential of mesenchymal stromal cells (MSCs). Unfortunately, in vitro cellular senescence occurring along with a loss of proliferative capacity is a major drawback in view of future therapeutic applications of these cells in the field of regenerative medicine. Even though insight into the mechanisms of replicative senescence in human medicine has evolved dramatically, knowledge about replicative senescence of canine MSCs is still scarce. Thus, we developed a high-content analysis workflow to simultaneously investigate three important characteristics of senescence in canine adipose-derived MSCs (cAD-MSCs): morphological changes, activation of the cell cycle arrest machinery, and increased activity of the senescence-associated β-galactosidase. We took advantage of this tool to demonstrate that passaging of cAD-MSCs results in the appearance of a senescence phenotype and proliferation arrest. This was partially prevented upon immortalization of these cells using a newly designed PiggyBac™ Transposon System, which allows for the expression of the human polycomb ring finger proto-oncogene BMI1 and the human telomerase reverse transcriptase under the same promotor. Our results indicate that cAD-MSCs immortalized with this new vector maintain their proliferation capacity and differentiation potential for a longer time than untreated cAD-MSCs. This study not only offers a workflow to investigate replicative senescence in eukaryotic cells with a high-content analysis approach but also paves the way for a rapid and effective generation of immortalized MSC lines. This promotes a better understanding of these cells in view of future applications in regenerative medicine.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

The image analysis pipelines are available in the following GitHub repository: https://github.com/StojiljkovicVetAna/HCA-to-investigate-senescence.

The Shiny App to navigate the single-cell data generated for this study is available at: https://anastojiljkovic.shinyapps.io/shiny_morpho/.

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Acknowledgements

We gratefully acknowledge the kind support of the staff from the Small Animal Clinic, Vetsuisse Faculty Bern and the assistance of Helga Mogel in the lab. We also thank Philippe Plattet and Marianne Wyss for providing us with plasmids and helping with cloning. We thank Meike Mevissen, Angélique Ducray, Volker Enzmann and Simone Forterre for helpful discussions. This study was performed with the support of the interfaculty Microscopy Imaging Center (MIC) of the University of Bern.

Funding

This work was funded by the Division of Veterinary Anatomy, University of Bern, Switzerland.

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Authors and Affiliations

  1. Division of Veterinary Anatomy, Vetsuisse Faculty, University of Bern, Bern, Switzerland

    Ana Stojiljković, Véronique Gaschen, Michael H. Stoffel & Jasmin Bluteau

  2. Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland

    Ana Stojiljković

  3. Division of Small Animal Surgery and Orthopaedics, Vetsuisse Faculty, University of Bern, Bern, Switzerland

    Franck Forterre & Ulrich Rytz

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  1. Ana Stojiljković
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Contributions

AS designed the high-content analysis approach, wrote the manuscript and created the figures with the support of JB and MHS. AS designed and created the Shiny App for the navigation of the single-cell data. AS performed all the experiments with the help of VG for cell culture and molecular biology. FF and UR organized the collection of the tissue samples.

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Correspondence to Ana Stojiljković.

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Stojiljković, A., Gaschen, V., Forterre, F. et al. Novel immortalization approach defers senescence of cultured canine adipose-derived mesenchymal stromal cells. GeroScience 44, 1301–1323 (2022). https://doi.org/10.1007/s11357-021-00488-x

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