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A microfluidic chip integrating amperometric enzyme sensors for the detection of glucose, glutamate and glutamine in cell-culture fermentation processes has been developed. The enzymes glucose oxidase, glutamate oxidase and glutaminase were immobilized by means of cross-linking with glutaraldehyde on platinum thin-film electrodes integrated within a microfluidic channel. The biosensor chip was coupled to a flow-injection analysis system for electrochemical characterization of the sensors. The sensors have been characterized in terms of sensitivity, linear working range and detection limit. The sensitivity evaluated from the respective peak areas was 1.47, 3.68 and 0.28 μAs/mM for the glucose, glutamate and glutamine sensor, respectively. The calibration curves were linear up to a concentration of 20 mM glucose and glutamine and up to 10 mM for glutamate. The lower detection limit amounted to be 0.05 mM for the glucose and glutamate sensor, respectively, and 0.1 mM for the glutamine sensor. Experiments in cell-culture medium have demonstrated a good correlation between the glutamate, glutamine and glucose concentrations measured with the chip-based biosensors in a differential-mode and the commercially available instrumentation. The obtained results demonstrate the feasibility of the realized microfluidic biosensor chip for monitoring of bioprocesses.
The chemical imaging sensor is a device to visualize the spatial distribution of chemical species based on the principle of LAPS (light-addressable potentiometric sensor), which is a field-effect chemical sensor based on semiconductor. In this study, the chemical imaging sensor has been applied to investigate the ion profile of laminar flows in a microfluidic channel. The chemical images (pH maps) were collected in a Y-shaped microfluidic channel while injecting HCl and NaCl solutions into two branches. From the chemical images, it was clearly observed that the injected solutions formed laminar flows in the channel. In addition, ion diffusion across the laminar flows was observed, and the diffusion coefficient could be derived by fitting the pH profiles to the Fick's equation.