(306g) Dynamic Viscoelasticity As a Rapid Single-Cell Biomarker | AIChE

(306g) Dynamic Viscoelasticity As a Rapid Single-Cell Biomarker

Authors 

Marr, D. W. M. - Presenter, Colorado School of Mines
Roth, K. B. - Presenter, Colorado School of Mines
Kasukurti, A. - Presenter, Colorado School of Mines
Sawetzki, T., Colorado School of Mines
Eggleton, C., University of Maryland Baltimore County
Desai, S. A., National Institute of Allergy and Infectious Disease



Probing the mechanics of living cells has been successfully identified as a label-free biophysical property marking variations in the health condition of individual cells in a broad range of different biological systems.  The exploitation of this promising biomarker in population-based studies, however, has been limited by the low measurement throughput of available methods. Besides the technical challenges of a cell-mechanics based cytometry, a fundamental hurdle is the signal response time of biological samples to external loading. Where the fluorescence signatures of common cell cytometers are virtually instantaneous, the cell stress relaxation occurs on the order of ~0.1 seconds, therefore greatly limiting the potential speed of current elastic property measurements.

 To circumvent these limitations, we introduce a novel optical-based technique probing the cell response to dynamic optical force fields modulated at high frequencies, thus providing deeper insights into cell mechanics than common cell stretching approaches. Individual cell in microfluidic environment are repeatedly deformed by the anisotropic distribution of laser light, generating linear optical traps aligned with the streamlines of the flowing carrier liquid. Studying the viscous contribution to the cell relaxation mechanism provides an additional criterion that allows an extended classification of cellular systems at timescales where pure elasticity-based methods fail. As a well-explored model system, we investigate the viscoelastic properties of malaria-infected and uninfected red blood cells, demonstrating the destruction-free detectability of both populations at timescales at the order of 10 ms, far beyond the typical stress relaxation times of classic approaches. With our current configuration we realized throughputs of more than 20 cells/s and a total of ~750 cells/min, so far mainly limited by the rapidness of our data-intensive video-based detection.