AVS 49th International Symposium
    Biomaterials Thursday Sessions
       Session BI-ThA

Paper BI-ThA10
Integration of Cells and Silicon Devices via Surface Microengineering

Thursday, November 7, 2002, 5:00 pm, Room C-201

Session: Cell Patterning to Engineer Function
Presenter: J. Hickman, Clemson University
Authors: J. Hickman, Clemson University
M. Das, Clemson University
P. Molnar, Clemson University
Correspondent: Click to Email
The long-term research goal of our group is to learn how to handle and prepare biological cells as components for microdevices and engineered tissues, and then to demonstrate the practicality of this approach by manipulating them to build hybrid systems and engineer functional tissues. The idea is to integrate microsystems fabrication technology and surface modifications with cellular components, with the aim of initiating and maintaining self-assembly and growth into biologically, mechanically and electronically interactive functional multi-component systems. The ability to control the surface composition of an in vitro system, as well as controlling other variables, such as growth media and cell preparation, all play important roles in creating a defined system for hybrid device fabrication. We are using self-assembled monolayers (SAMs) to control the intrinsic and geometric properties of surfaces in contact with these cellular systems. We have used the geometric control of the surface composition afforded us by SAMs to create in vitro circuits of rat hippocampal neurons. We have also demonstrated functional control of these systems by recording the electrophysiological signals on the patterned SAMs in response to stimuli and demonstrated geometric control of synaptic development. We have used geometric only cues to define axonal/dendrite polarity in developing hippocampal neurons which is a key step in creating engineered neuronal networks. Summed together these all represent a growing set of tools for building hybrid cellular systems. We are using this ability to integrate biological systems with silicon-based systems to create cell-based sensors for high throughput drug discovery and functional genomic assays as well as for hybrid neuronal/silicon systems to study biological computation. We are also using what we learn for a more fundamental understanding of cellular development and neuronal regeneration.