Romain Perrier

Bioelectronic organ-based sensor for microfluidic real-time analysis of the demand in insulin

On-line and real-time analysis of micro-organ activity permits to use the endogenous analytical power of cellular signal transduction algorithms as biosensors. We have developed here such a sensor using only a few pancreatic endocrine islets and the avoidance of transgenes or chemical probes reduces bias and procures general usage. Nutrient and hormone-induced changes in islet ion fluxes through channels provide the first integrative read-out of micro-organ activity. Using extracellular electrodes we captured this read-out non-invasively as slow potentials which reflect glucose concentration-dependent (3-15 mM) micro-organ activation and coupling. Custom-made PDMS-based microfluidics with platinum black micro-electrode arrays required only some tens of islets and functioned at flow rates of 1-10 µl/min which are compatible with microdialysis. We developed hardware solutions for on-line real-time analysis on a reconfigurable Field-Programmable Gate Array (FPGA) that offered resource-efficient architecture and storage of intermediary processing stages. Moreover, real-time adaptive and reconfigurable algorithms accounted for signal disparities and noise distribution. Based on islet slow potentials, this integrated set-up allowed within less than 40 μs the discrimination and precise automatic ranking of small increases (2 mM steps) of glucose concentrations in real time and within the physiological glucose range. This approach shall permit further development in continuous monitoring of the demand for insulin in type 1 diabetes as well as monitoring of organs-on-chip or maturation of stem-cell derived islets.

Simultaneous monitoring of single cell and of micro-organ activity by PEDOT:PSS covered multi-electrode arrays

Continuous and long-term monitoring of cellular and micro-organ activity is required for new insights into physiology and novel technologies such as Organs-on-Chip. Moreover, recent advances in stem cell technology and especially in the field of diabetes call for non-invasive approaches in quality testing of the large quantities of surrogate pancreatic islets to be generated. Electrical activity of such a micro-organ results in single cell action potentials (APs) of high frequency and in low frequency changes in local field potentials (slow potentials or SPs), reflecting coupled cell activity and overall organ physiology. Each of them is indicative of different physiological stages in islet activation. Action potentials in islets are of small amplitude and very difficult to detect. The use of PEDOT:PSS to coat metal electrodes is expected to reduce noise and results in a frequency-dependent change in impedance, as shown here. Whereas detection of high-frequency APs improves, low frequency SPs are less well detected which is, however, an acceptable trade off in view of the strong amplitude of SPs. Using a dedicated software, recorded APs and SPs can be automatically diagnosed and analyzed. Concomitant capture of the two signals will considerably increase the diagnostic power of monitoring islets and islet surrogates in fundamental research as well as drug screening or the use of islets as biosensors.

Multimed: An Integrated, Multi-Application Platform for the Real-Time Recording and Sub-Millisecond Processing of Biosignals

Enhanced understanding and control of electrophysiology mechanisms are increasingly being hailed as key knowledge in the fields of modern biology and medicine. As more and more excitable cell mechanics are being investigated and exploited, the need for flexible electrophysiology setups becomes apparent. With that aim, we designed Multimed, which is a versatile hardware platform for the real-time recording and processing of biosignals. Digital processing in Multimed is an arrangement of generic processing units from a custom library. These can freely be rearranged to match the needs of the application. Embedded onto a Field Programmable Gate Array (FPGA), these modules utilize full-hardware signal processing to lower processing latency. It achieves constant latency, and sub-millisecond processing and decision-making on 64 channels. The FPGA core processing unit makes Multimed suitable as either a reconfigurable electrophysiology system or a prototyping platform for VLSI implantable medical devices. It is specifically designed for open- and closed-loop experiments and provides consistent feedback rules, well within biological microseconds timeframes. This paper presents the specifications and architecture of the Multimed system, then details the biosignal processing algorithms and their digital implementation. Finally, three applications utilizing Multimed in neuroscience and diabetes research are described. They demonstrate the system’s configurability, its multi-channel, real-time processing, and its feedback control capabilities.