Daisy D Canepa1,2, Elisa A Casanova1, Eirini Arvaniti3, Vinko Tosevski4, Sonja Märsmann1, Benjamin Eggerschwiler1,2, Sascha Halvachizadeh1, Johanna Buschmann5, André A Barth5, Jan A Plock5, Manfred Claassen3, Hans-Christoph Pape1, Paolo Cinelli6. 1. Department of Trauma, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland. 2. Life Science Zurich Graduate School, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland. 3. Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Otto-Stern-Weg 3, 8093, Zurich, Switzerland. 4. Mass Cytometry Facility, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland. 5. Department of Plastic and Hand Surgery, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland. 6. Department of Trauma, University Hospital Zurich, Rämistrasse 100, 8091, Zurich, Switzerland. paolo.cinelli@usz.ch.
Abstract
BACKGROUND: The impressive progress in the field of stem cell research in the past decades has provided the ground for the development of cell-based therapy. Mesenchymal stromal cells obtained from adipose tissue (AD-MSCs) represent a viable source for the development of cell-based therapies. However, the heterogeneity and variable differentiation ability of AD-MSCs depend on the cellular composition and represent a strong limitation for their use in therapeutic applications. In order to fully understand the cellular composition of MSC preparations, it would be essential to analyze AD-MSCs at single-cell level. METHOD: Recent advances in single-cell technologies have opened the way for high-dimensional, high-throughput, and high-resolution measurements of biological systems. We made use of the cytometry by time-of-flight (CyTOF) technology to explore the cellular composition of 17 human AD-MSCs, interrogating 31 markers at single-cell level. Subcellular composition of the AD-MSCs was investigated in their naïve state as well as during osteogenic commitment, via unsupervised dimensionality reduction as well as supervised representation learning approaches. RESULT: This study showed a high heterogeneity and variability in the subcellular composition of AD-MSCs upon isolation and prolonged culture. Algorithm-guided identification of emerging subpopulations during osteogenic differentiation of AD-MSCs allowed the identification of an ALP+/CD73+ subpopulation of cells with enhanced osteogenic differentiation potential. We could demonstrate in vitro that the sorted ALP+/CD73+ subpopulation exhibited enhanced osteogenic potential and is moreover fundamental for osteogenic lineage commitment. We finally showed that this subpopulation was present in freshly isolated human adipose-derived stromal vascular fractions (SVFs) and that could ultimately be used for cell therapies. CONCLUSION: The data obtained reveal, at single-cell level, the heterogeneity of AD-MSCs from several donors and highlight how cellular composition impacts the osteogenic differentiation capacity. The marker combination (ALP/CD73) can not only be used to assess the differentiation potential of undifferentiated AD-MSC preparations, but also could be employed to prospectively enrich AD-MSCs from the stromal vascular fraction of human adipose tissue for therapeutic applications.
BACKGROUND: The impressive progress in the field of stem cell research in the past decades has provided the ground for the development of cell-based therapy. Mesenchymal stromal cells obtained from adipose tissue (AD-MSCs) represent a viable source for the development of cell-based therapies. However, the heterogeneity and variable differentiation ability of AD-MSCs depend on the cellular composition and represent a strong limitation for their use in therapeutic applications. In order to fully understand the cellular composition of MSC preparations, it would be essential to analyze AD-MSCs at single-cell level. METHOD: Recent advances in single-cell technologies have opened the way for high-dimensional, high-throughput, and high-resolution measurements of biological systems. We made use of the cytometry by time-of-flight (CyTOF) technology to explore the cellular composition of 17 human AD-MSCs, interrogating 31 markers at single-cell level. Subcellular composition of the AD-MSCs was investigated in their naïve state as well as during osteogenic commitment, via unsupervised dimensionality reduction as well as supervised representation learning approaches. RESULT: This study showed a high heterogeneity and variability in the subcellular composition of AD-MSCs upon isolation and prolonged culture. Algorithm-guided identification of emerging subpopulations during osteogenic differentiation of AD-MSCs allowed the identification of an ALP+/CD73+ subpopulation of cells with enhanced osteogenic differentiation potential. We could demonstrate in vitro that the sorted ALP+/CD73+ subpopulation exhibited enhanced osteogenic potential and is moreover fundamental for osteogenic lineage commitment. We finally showed that this subpopulation was present in freshly isolated human adipose-derived stromal vascular fractions (SVFs) and that could ultimately be used for cell therapies. CONCLUSION: The data obtained reveal, at single-cell level, the heterogeneity of AD-MSCs from several donors and highlight how cellular composition impacts the osteogenic differentiation capacity. The marker combination (ALP/CD73) can not only be used to assess the differentiation potential of undifferentiated AD-MSC preparations, but also could be employed to prospectively enrich AD-MSCs from the stromal vascular fraction of human adipose tissue for therapeutic applications.
Authors: James B Mitchell; Kevin McIntosh; Sanjin Zvonic; Sara Garrett; Z Elizabeth Floyd; Amy Kloster; Yuan Di Halvorsen; Robert W Storms; Brian Goh; Gail Kilroy; Xiying Wu; Jeffrey M Gimble Journal: Stem Cells Date: 2005-12-01 Impact factor: 6.277
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Authors: S A Kuznetsov; P H Krebsbach; K Satomura; J Kerr; M Riminucci; D Benayahu; P G Robey Journal: J Bone Miner Res Date: 1997-09 Impact factor: 6.741
Authors: Chen Xi Li; Nilesh P Talele; Stellar Boo; Anne Koehler; Ericka Knee-Walden; Jenna L Balestrini; Pam Speight; Andras Kapus; Boris Hinz Journal: Nat Mater Date: 2016-10-31 Impact factor: 43.841
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Authors: Eli R Zunder; Rachel Finck; Gregory K Behbehani; El-Ad D Amir; Smita Krishnaswamy; Veronica D Gonzalez; Cynthia G Lorang; Zach Bjornson; Matthew H Spitzer; Bernd Bodenmiller; Wendy J Fantl; Dana Pe'er; Garry P Nolan Journal: Nat Protoc Date: 2015-01-22 Impact factor: 13.491