This work presents a fully automated method for detecting the contact between a microcapillary tip and a cell membrane based on a statistical process control (SPC) algorithm known as the double-sided cumulative sum (or "cusum"). By analyzing current measurements obtained through a microcapillary electrode, the proposed goal of this system is to determine when tip-to-membrane (tip-membrane) contact occurs using thin adhered cells (e.g., less than 10 mu m) for the purposes of fully automated robotic-assisted, single cell electroporation (SCE)-a powerful method of gene transfection. This SPC algorithm is robust against uncontrollable system parameters such as system noise common in electrode-based systems, nonstationary processes, and variations in the physical parameters of cells. The proposed algorithm was successfully demonstrated on adhered mammal cells as small as 4 mu m in thickness and using tip-placement velocities from 1 to 8 mu m/s. In addition, a novel method of experimentation is described correlating optical measurements between tip-membrane proximity and changes in i(cct) during the tip-placement sequence. Note to Practitioners-SCE by microcapillary is an efficient method to insert molecules into single cells for human health research. Before SCE can occur, placement of a microcapillary tip on a cell membrane is required. The same electrical infrastructure used for SCE is also used to detect tip-membrane contact by sensing changes in current through an electrode in the microcapillary. An abrupt decrease in current occurs during tip-membrane contact and throughout membrane indentation. By measuring this current there is no need for additional proximity sensors. In previous works, the objective was to indent the membrane sufficiently beyond the initial contact decreasing the current to a predetermined threshold-indicating the conditions required for SCE to occur. However, thin, adhered cells pose a challenge tip-membrane contact to the glass substrate is small. This limits the amount of cell indentation possible before damage to the cell and microcapillary tip occurs. In addition, the inherent noise of electrode-based systems and physical variations in thin cells, reduce the repeatability for specifying a predetermined threshold during tip-placement sequence. This work describes a system to achieve fully automated, tip-membrane contact detection of thin cells using the double-sided cumulative sum as a precursor to SCE. Little, if any, parameter modification is required for general-purpose use and this real-time, recursive algorithm can be implemented on microcontroller-based systems. This method could be extended to other electrode-based applications that are not facilitated by a microcapillary (e. g., lab-on-a-chip, microfluidic, or MEMS applications), where cell contact detection is required in the presence of a low signal-to-noise ratio.
