Binding of the antigen receptor on T cells initiates a rapid series of signaling events leading to an immune response. To fully understand T cell mediated immunity, underlying regulatory properties of the receptor network must be understood. Monitoring dynamic protein signaling events allows for network analysis. Unfortunately, dynamic data acquisition is often extremely time-consuming and expensive with conventional methods; the number of proteins monitored at the same time on the same sample is limited. Furthermore, with conventional, multi-well plate assays it is difficult to achieve adequate resolution at sub-minute timescales. Microfluidics is a capable alternative, providing uniformity in sample handling to reduce error between experiments and precision in timing, an important factor in monitoring phosphorylation events that occur within minutes of stimulation. We used a two-module microfluidic platform for simultaneous multi-time point stimulation and lysis of T cells to investigate early signaling events with a resolution down to 20 seconds using only small amounts of cells and reagents. The device did not elicit adverse cellular stress in Jurkat cells. The activation of 6 important proteins in the signaling cascade upon stimulation with a soluble form of α-CD3 in the device was quantified and compared under a variety of conditions. First, in comparison to manual pipetting, the microdevice exhibits significantly less error between experiments. Secondly, a comparison between Jurkat cells and primary T cells shows similar dynamic trends across the 6 proteins. Finally, we have used the device to compare properties of long-term vs, short-term cultured primary T cells. As expected, older cells present a much weakened response to antigenic cues, as measured with TCR response markers. This modular microdevice provides a flexible format for investigating cell signaling properties through the use of soluble cue stimuli.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/31674 |
| Date | 19 November 2008 |
| Creators | Rivet, Catherine Aurelie |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Thesis |
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