278961 Quantitative Profiling of Active Transcription Factors in Parallel

Wednesday, October 31, 2012: 10:18 AM
Somerset East (Westin )
Betul Bilgin1, Li Liu2, Christina Chan3,4 and S. Patrick Walton1, (1)Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI, (2)Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, (3)Chemical Engineering and Materials Science and Materials Science, Michigan State University, East Lansing, MI, (4)Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI

Transcription factors (TFs) are cell regulatory proteins facilitating proper cell function by controlling gene expression in response to intracellular and extracellular stimuli. TFs mediate cellular responses through binding to specific sites of chromosomal DNA. TF activation can occur from many stimuli, and, conversely, a single stimulus can activate many TFs. Thus, measurement of the activity of a single TF provides only a limited picture of the instantaneous state of cell function. However, given the ~1850 different human TFs, parallel quantification of the levels of active TFs even under basal conditions remains technically challenging.

Several methods currently exist to measure the levels of active TFs in parallel. These include electrophoretic mobility-shift assays (EMSA), reporter gene assays, or protein binding microarrays. However, these techniques are limited in scale, accuracy, and sensitivity. Using magnetic bead separation, we have developed a new, scalable, flexible, sensitive, and complementary method for screening of multiple TFs in parallel. In this proof-of-principle work, we successfully analyzed NF-kB and Ap1 levels quantitatively in parallel with ~5-10 fold improved sensitivity over existing approaches. We have also quantified differences in the levels of NF-kB and Ap1 from cells following TNF-alpha stimulation relative to control cells. In this presentation, current results will be described along with further directions, including expansion to larger sets of TFs and analysis of complex biological processes.

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