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Biotechnology Progress, Vol.27, No.3, 891-895, 2011
Skeletal Myotube Integration with Planar Microelectrode Arrays In Vitro for Spatially Selective Recording and Stimulation: A Comparison of Neuronal and Myotube Extracellular Action Potentials
Microelectrode array (MEA) technology holds tremendous potential in the fields of biodetection, lab-on-a-chip applications, and tissue engineering by facilitating noninvasive electrical interaction with cells in vitro. To date, significant efforts at integrating the cellular component with this detection technology have worked exclusively with neurons or cardiac myocytes. We investigate the feasibility of using MEAs to record from skeletal myotubes derived from primary myoblasts as a way of introducing a third electrogenic cell type and expanding the potential end applications for MEA-based biosensors. We find that the extracellular action potentials (EAPs) produced by spontaneously contractile myotubes have similar amplitudes to neuronal EAPs. It is possible to classify myotube EAPs by biological signal source using a shape-based spike sorting process similar to that used to analyze neural spike trains. Successful spike-sorting is indicated by a low within-unit variability of myotube EAPs. Additionally, myotube activity can cause simultaneous activation of multiple electrodes, in a similar fashion to the activation of electrodes by networks of neurons. The existence of multiple electrode activation patterns indicates the presence of several large, independent myotubes. The ability to identify these patterns suggests that MEAs may provide an electrophysiological basis for examining the process by which myotube independence is maintained despite rapid myoblast fusion during differentiation. Finally, it is possible to use the underlying electrodes to selectively stimulate individual myotubes without stimulating others nearby. Potential uses of skeletal myotubes grown on MEA substrates include lab-on-a-chip applications, tissue engineering, co-cultures with motor neurons, and neural interfaces. (C) 2011 American Institute of Chemical Engineers Biotechnol. Prog., 27: 891-895, 2011