Statistic estimation of cell compressibility based on acoustophoretic separation data

Abstract

AbstractWe present a new experimental method that measures the compressibility of phenotype-specific cell populations. This is done by performing statistical analysis of the cell counts from the outlets of an acoustophoresis chip as a function of the increasing actuator voltage (i.e. acoustic energy density) during acoustophoretic separation. The theoretical separation performance curve, henceforth, Side-Stream Recovery ($$\mathrm {SSR}$$ SSR ), vs the piezo-actuator voltage (V) is derived by moment analysis of a one-dimensional model of acoustophoresis separation, accounting for distributions of the cell or microparticle properties and the system parameters (hydrodynamics, radiation force, drag enhancement, and acoustic streaming). The acoustophoretic device is calibrated with polymer microbeads of known properties by fitting the experimental $$\mathrm {SSR}$$ SSR with the theoretical $$\mathrm {SSR}$$ SSR , in which the acoustic energy density is considered proportional to the squared voltage, i.e. $$E_\mathrm {ac}^{}=\alpha \,V^2_{}$$ E ac = α V 2 . The fitting parameter $$\alpha$$ α for the calibration procedure is the device effectivity, reflecting the efficiency in performing acoustophoretic microparticle displacement. Once calibrated, the compressibility of unknown cells is estimated by fitting experimental $$\mathrm {SSR}$$ SSR cell data points with the theoretical $$\mathrm {SSR}$$ SSR curve. In this procedure, the microparticle compressibility is the fitting parameter. The method is applied to estimate the compressibility of a variety of cell populations showing its utility in terms of rapid analysis and need for minute sample amounts.