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J Biomol Tech. 2007 February; 18(1): 31–32.
PMCID: PMC2292066

P92-M The ABI 3730 DNA Analyzer is an Efficient System for Simultaneous, Bi-Directional Analysis of Dual-Labeled Probes Used to Study Protein-DNA Interactions

Abstract

DNA footprinting is a powerful tool to study regions of DNA where proteins bind. Traditionally, target DNA fragments are labeled with 32P, incubated with the protein of interest, then subjected to chemical nuclease attack. The DNA probe is then purified and nicked fragments analyzed on sequencing gels to reveal regions of DNA protected by the protein from attack.

The traditional method is a time-consuming and difficult protocol requiring specialized skill. Proteins with low dissociation constants require an additional preparatory separation before analysis, which reduces the yield of bound probe. The isotope is labile, involves safety considerations, and requires a separate labeling and purification step. The finished gels must be dried down and exposed. This adds time to the overall process, varies according to the potency of the isotope, and decreases resolution. Normalization and alignment of free and bound probes is difficult. The one-dimensional nature of the single label necessitates separate analysis of each DNA strand, and the analytical gel limits the length of the analytical window.

We have developed a novel method of DNA footprinting that utilizes the multi-dimensional nature of fluorophores to label both strands of the DNA target, which permits differential analysis of both strands simultaneously. Labeled primers are commercially available for use as PCR primers, permitting simultaneous labeling and amplification of the DNA probe. The use of the chemical nuclease 1,10-phenathroline-copper facilitates in-gel attack of free and bound probe, which increases the yield of bound probe and reduces perturbation of the three-dimensional conformation of the complex. Samples can be analyzed rapidly by standard automated sequencing instrumentation with baseline, base pair resolution. Software data manipulation reduces normalization issues. The result is high-quality data acquisition in a matter of hours instead of days.


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