Ultra sensitive biosensor based on impedance spectroscopy at microwave frequencies for cell scale analysis

This paper presents an original approach for biological cell discrimination using impedance spectroscopy analysis at microwave frequencies. The proposed method allows label-free analysis at the cell scale using high frequency electromagnetic waves as a non-invasive probe to analyze the intracellular medium. In the present case, the biosensor design takes advantage of classical planar microwave filter topology, where coupling zones present high sensitivity to tiny dielectric perturbations. With proper design, these specific areas can be used as an electromagnetic (EM) detector. In the present work, biosensor sensitivity allows reaching selective biological sample detection and bio-impedance measurements down to single-cell analysis. As presented in this paper, this concept has been experimentally validated with characterisations conducted on biological cancerous stem cells (cells considered at a low differentiation degree) and U87 glial cells (differentiated cells); both coming from human nervous system. Stem cells are almost similar in shape and size as differentiated cells. They are therefore quite difficult to identify using a microscope, and studies focusing on their differentiation mechanisms are very challenging. Cell chemical labeling would have been suitable if we would have been sure that used label will not induce an unwanted cell differentiation. To the contrary, EM impedance measurements show a significant difference between stem and differentiated cells dielectric permittivity. Therefore, such measurements can be an efficient approach to determine cell differentiation degree in a non-invasive way. As a label-free approach, the high frequency impedance spectroscopy could be very interesting for accurate discrimination of un-differentiated cells. Indeed, stem cells are currently the subject of a large research effort in the biologist community; especially in case of cancers, where cancerous stem cells are suspected to be the origin of most of tumor recurrences. Hence, based on this identification technique, a new diagnostic analysis could be developed for early cancer recurrence prevention.