Structured model networks
The ability to structure cellular model networks by introducing lesions or spatially constricting network formation allows insight into fundamental mechanisms of cellular interaction. In this context, we work with several cell model systems including cancer cell lines, cardiomyocytes, as well as neuronal networks.
Signal propagation in cardiomyocyte models
One of our model systems for the investigation of structured cell networks is the HL-1 cell line. This cell line originates from murine heart muscle cells. If grown at a sufficiently high density, these cells generate spontaneous action potentials that spread through the cell layer. The propagation of these signals can be monitored by measuring the extracellular potential or via so-called calcium imaging.
In our experiments, we investigate e.g. the influence of thermal lesions on the signal propagation. By sequentially introducing lesions at different positions in the network, we are able to isolate subpopulations of ca. 100 cells from the network. We can then monitor the activity of these subpopulations independently.
Furthermore, we investigate the signal propagation in networks that inherit certain geometries from their substrate. To this end, we use our stereolithographic 3D printers to fabricate appropriate substrates. These substrates comprise individual compartments that are connected via channels. This allows us to control the size and connectivity of different populations in the network.
Axotomy in neuronal model systems
Apart from lesions in cardiomyocyte model systems, we are interested in regeneration mechanisms in neuronal systems. In cooperation with the Helmholtz Nanoelectronic Facility of the Forschungszentrum Jülich (HNF), we fabricate special microwire arrays that allow us to introduce lesions to cell networks with a resolution in the low micrometer regime.
In order to structure these networks, we use microchannels that are also fabricated via modern microtechnological means at the HNF. These channels allow the localization and orientation of axonal connections in neuronal networks. In the future, we intend to combine these approaches to create a chip-based model system for the regeneration after an axotomy.