A mathematical method for extracting cell secretion rate from affinity biosensors continuously monitoring cell activity

Our laboratory has previously developed miniature aptasensors that may be integrated at the site of a small group of cells for continuous detection of cell secreted molecules such as inflammatory cytokine interferon gamma (IFN-c). In a system such as this, the signal measured at the sensor surfaces is a complex function of transport, reaction, as well as of cellular activity. Herein, we report on the development of a mathematical framework for extracting cell production rates from binding curves generated with affinity biosensors. This framework consisted of a diffusion-reaction model coupled to a root finding algorithm for determining cell production rates values causing convergence of a predetermined criterion. To experimentally validate model predictions, we deployed a microfluidic device with an integrated biosensor for measuring the IFN-c release from CD4 T cells. We found close agreement between secretion rate observed theoretically and those observed experimentally. After taking into account the differences in sensor geometry and reaction kinetics, the method for cell secretion rate determination described in this paper may be broadly applied to any biosensor continuously measuring cellular activity.