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BME Seminar Series: Eric M. Darling

Tuesday, April 15, 2014
8:30 a.m.
Goergen Hall 101 (Sloan Auditorium)

Single-cell Mechanical Properties as a Biomarker of Differentiation in Adult Stem Cells

Assistant Professor, Dept. of Molecular Pharmacology, Physiology, & Biotechnology, Center for Biomedical Engineering, Brown University

Abstract:

Cellular mechanical biomarkers can be defined as a set of elastic and viscoelastic parameters that describe the deformation behavior of a cell under load. Recent work by our lab and others has shown that these mechanical characteristics are closely associated with biological phenotype. A primary example of this is a malignant cancer cell, which is more compliant than healthy cells of the same type. Conversely, osteoarthritic chondrocytes exhibit a less compliant phenotype compared to normal to compensate for changes in the cartilage tissue. Our group recently showed that the mechanical biomarkers of undifferentiated, adipose-derived stem/progenitor cells (ASCs) predicted the differentiation capabilities of the cells for the osteogenic, adipogenic, and chondrogenic lineages. Results showed that elastic and viscoelastic moduli positively correlated with osteogenic potential, i.e., stiffer ASC clones produced more calcified matrix upon differentiation than softer clones, and negatively correlated with adipogenic potential. Apparent viscosity positively correlated with chondrogenic potential, indicating the importance of assessing time/frequency responses when characterizing cells. These findings provide support for identifying, and possibly enriching for, lineage-specific, stem/progenitor subpopulations based on their mechanical properties. This could benefit cell-based therapeutics, since mechanical biomarkers indicated not only the differentiation potential of ASC clones but their synthetic potential as well. Continuing work in our lab is investigating the feasibility of using these properties as biomarkers, including whether they are distinct from other cells residing in fat and how similar characterizations can be done in an efficient, high-throughput fashion.