The mechanical properties of adipose-derived stem cell (ASC) clones correlate with their ability to produce tissue-specific metabolites, a finding that has dramatic implications for cell-based regenerative therapies. Autologous ASCs are an attractive cell source due to their immunogenicity and multipotent characteristics. However, for practical applications ASCs must first be purified from other cell types, a critical step which has proven difficult using surface-marker approaches. Alternative enrichment strategies identifying broad categories of tissue-specific cells are necessary for translational applications. One possibility developed in our lab uses single-cell mechanical properties as predictive biomarkers of ASC clonal differentiation capability. Elastic and viscoelastic properties of undifferentiated ASCs were tested via atomic force microscopy and correlated with lineage-specific metabolite production. Cell sorting simulations based on these "mechanical biomarkers" indicated they were predictive of differentiation capability and could be used to enrich for tissue-specific cells, which if implemented could dramatically improve the quality of regenerated tissues.cell mechanics | mesenchymal stem cell enrichment | viscoelasticity | single-cell characterization | AFM A dipose tissue contains a heterogeneous population of mesenchymal stem cells (MSCs) known as adipose-derived stem cells (ASCs) (1). ASCs are capable of differentiating into a variety of lineage-specific cell types, including adipocytes, osteoblasts, and chondrocytes (1-3). In comparison to MSCs derived from other tissues, ASCs are simple to isolate and available in large quantities (4, 5). Because of the cells' mesodermal origin, ASCs have been used for many soft tissue and orthopaedic applications (6-10). Unfortunately, ASC isolation is confounded by the lack of distinct and universally effective MSC biomarkers. Adipose tissue contains multiple cell types, including mature adipocytes, fibroblasts, smooth muscle cells, and endothelial cells (11), which can contaminate the stromal fraction collected during ASC isolation. While conventional methods such as flow cytometry can isolate stem cells using surface antigen expression (1, 2, 12), resulting cell yields are often less than 1% (13,14). Furthermore, the surface antigens present on ASCs can also be found on other cell types in adipose tissue, complicating the isolation of pure mesenchymal stem cell populations (15-17). Collectively, these limitations suggest a need for alternative biomarkers that allow for ASC enrichment based on lineage potential.Recently, single-cell mechanical properties were found to be akin to gene and protein expressions, capable of distinguishing differences in cellular subpopulations, disease state, and tissue source (18)(19)(20)(21)(22). Cells display varying levels of resistance to deformation (elasticity) and flow (viscosity) in response to an applied force. This behavior depends on the composition and organization of subcellular structures, particularly the cytosk...

These findings suggest that lamin C protein expression is strongly associated with whole-cell mechanical properties and could potentially serve as a biomarker for mechanophenotype.

Adipose-derived stem cells (ASCs) show great promise for tissue engineering applications and cell-based therapies because of their multipotency, relative abundance and immunosuppressive properties. However, ASCs must be isolated from heterogeneous cell populations present in adipose tissue. In this brief report, we provide a concise summary of the history and use of cellular mechanical properties as novel, label-free biomarkers to predict the differentiation potential of ASCs toward adipogenic, osteogenic and chondrogenic lineages. Additionally, we have found that passage number influences the mechanical properties of ASCs along with a discussion of potential environmental factors that could affect these properties. Altogether, this report provides evidence for the reliability of cellular mechanical properties as biomarkers for ASC differentiation potential and outlines how they can be used to sort ASCs with lineage-specific preferences for particular applications.