dc.description.abstract | The progression of science and medicine is often predicated by advancements in technology. Particularly, automation has played a large role in many of these technological advancements, allowing for progress to occur at a more rapid pace. For example, high impact technological driving forces, such as gene sequencing, microarray technology, and high-throughput screening, have led to a genomic revolution that has fueled not only the mapping of the human genome, but also drug discovery, epigenetics, biomarker discovery, systems biology and basic science research as a whole. As popularity in approaching scientific issues from a systems biology perspective continues to grow, the need for new tools capable of rapidly producing data has become evident. The development of technology platforms for complex biological studies will be twofold. The first, a platform for assessing the metabolic state of a population of cells under highly controllable environmental parameters, could provide significant insight regarding the underlying biological phenomenon, leading to potential advancement in both clinical and academic systems biology research. This platform is comprised of the Vanderbilt Institute for Integrative Biosystems Research and Education Multitrap Nanophysiometer paired with a solid phase extraction desalter, and an Ion Mobility-Mass Spectrometer. Naïve and cocaine-experienced T cell metabolism of cocaine is used for an inaugural biological test system to confirm the capability of the platform, highlight its potential for metabolite discovery applications, and to explore immunological memory of T cell drug exposure. The second technology framework developed will be for the generation and receiving of oscillatory chemical signals and will consist of parallel Rotary Planar Peristaltic Micropumps for the generation of sinusoidal concentrations of chemical signals, a microfluidic mixer for the combination the oscillatory signals, the Continuous Flow Photometer for the collection of light as a reaction product, and data analysis techniques for describing the frequency domain of the raw data. This framework stands to provide unique information regarding nonlinear reaction dynamics and is transferrable to more complex biochemical signaling pathways. | |