Functional fingerprinting of human mesenchymal stem cells using high-throughput RNAi screening
Mesenchymal stem cells (MSCs) are promising candidates for cellular therapies ranging from tissue repair in regenerative medicine to immunomodulation in graft versus host disease after allogeneic transplantation or in autoimmune diseases. Nonetheless, progress has been hampered by their enormous phe...
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| Main Authors: | , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
17 May 2015
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| In: |
Genome medicine
Year: 2015, Volume: 7 |
| ISSN: | 1756-994X |
| DOI: | 10.1186/s13073-015-0170-2 |
| Online Access: | Verlag, kostenfrei, Volltext: http://dx.doi.org/10.1186/s13073-015-0170-2 Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s13073-015-0170-2 
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| Author Notes: | Gerrit Erdmann, Michael Suchanek, Patrick Horn, Fabian Graf, Christian Volz, Thomas Horn, Xian Zhang, Wolfgang Wagner, Anthony D. Ho and Michael Boutros |
| Summary: | Mesenchymal stem cells (MSCs) are promising candidates for cellular therapies ranging from tissue repair in regenerative medicine to immunomodulation in graft versus host disease after allogeneic transplantation or in autoimmune diseases. Nonetheless, progress has been hampered by their enormous phenotypic as well as functional heterogeneity and the lack of uniform standards and guidelines for quality control. In this study, we describe a method to perform cellular phenotyping by high-throughput RNA interference in primary human bone marrow MSCs. We have shown that despite heterogeneity of MSC populations, robust functional assays can be established that are suitable for high-throughput and high-content screening. We profiled primary human MSCs against human fibroblasts. Network analysis showed a kinome fingerprint that differs from human primary fibroblasts as well as fibroblast cell lines. In conclusion, this study shows that high-throughput screening in primary human MSCs can be reliably used for kinome fingerprinting. |
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| Item Description: | Gesehen am 01.02.2018 |
| Physical Description: | Online Resource |
| ISSN: | 1756-994X |
| DOI: | 10.1186/s13073-015-0170-2 |