Cite as: Cold Spring Harb. Protoc.; 2008; doi:10.1101/pdb.prot5028
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Department of Molecular Biology, University of Geneva, CH-1211 Geneva, Switzerland
1Corresponding author (ueli.schibler{at}molbio.unige.ch)
INTRODUCTION
Strict regulation of transcription factor activity is essential to establish and maintain gene expression. Eukaryotic cells control transcription factors at many different levels. Post-translational regulatory mechanisms (e.g., phosphorylation, nuclear translocation, multimerization, regulated degradation, etc.) play particularly important roles because they enable cells to respond to various intra- and extracellular stimuli quickly and without prior protein synthesis. However, extensive post-translational changes can make it difficult to identify differentially regulated transcription factors. Common genomic screening techniques such as DNA microarray analysis are unable to detect any mode of regulation beyond that of mRNA stability. This protocol describes the differential display of DNA-binding proteins (DDDP), which is based on the electrophoretic mobility shift assay (EMSA) and detects DNA-binding transcription factors, independent of the number or nature of regulatory steps required for activation. DDDP is an unbiased screening technique that can be used in any experimental system that uses concentrated protein extracts. A plasmid library containing random DNA sequences is constructed. This library is then used to generate radioactive DNA probes to test protein extracts from different sources in parallel for differentially regulated DNA-binding proteins. Plasmids corresponding to probes that display differential DNA-binding activity can be sequenced, and the binding sequence can be narrowed down in a two-step procedure. The corresponding transcription factors can then be identified by bioinformatic and/or biochemical methods.
RELATED INFORMATION
Reinke et al. (2008) provides more information about the DDDP technique and explains in detail the rationale for using a random DNA library, including the underlying calculations.
MATERIALS
Reagents
Agarose gels
Alternatively, a QiaQuick PCR-purification kit (QIAGEN) can be used.
Cloning vector, pUC19
dATP, dGTP, and dTTP (individual solutions at 5 mM each)
DNA oligonucleotides, synthetic:
P-5'-TCGAGGCGCGCC-3' (AscI-linker)
5'-AAGGGATCCCTT-3' (BamHI-linker)
5'-AATTCGAGCTCGGTACCC-3' (Rand100-A)
5'-ACCATGATTACGCCAAGC-3' (Rand100-B)
5'-ATTGGCGCGCC-[N]50-AAGGGATCCCTT-3' (Random)
dNTP mix (25 mM each of dATP, dTTP, dCTP, and dGTP)
Ethanol (75%)
Klenow fill-in buffer (10X)
Klenow fragment (from DNA polymerase I; 5 U/µL)
Polyacrylamide gel (4%)
Protein extracts
Prepare concentrated protein (preferably nuclear) extracts from different cell/tissue sources as required for comparative studies (e.g., wild-type vs. mutant cell lines, normal vs. cancer cells, cells at different stages of development, tissues harvested from subjects at different time points for circadian studies, etc.).
Reagents for sequencing plasmids
Restriction enzyme incubation buffers (10X)
Restriction enzymes: SalI, AscI and BamHI
Equipment
Beaker (glass) containing 100 mL of boiling H2O
Equipment for running agarose and polyacrylamide gels
Equipment for sequencing plasmids
Filter paper (Whatman)
Gel dryer
Heating block preset to 75°C
Ice
Microcentrifuge
PCR machine
Pipettors and tips
Tubes (microcentrifuge, normal and screw-top)
Vortex mixer
X-ray film and cassettes (or PhosphorImager system)
METHOD
Generation of an Ordered Random DNA Library
See Figure 1 for an outline of the cloning procedure.
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Figure 1. Construction of the random DNA library. Oligonucleotides with 50 random nucleotide positions ([N]50), a 5'-flanking region containing an AscI restriction site (blue), and a palindromic 3'-flanking region containing a BamHI restriction site (red), are self-annealed, rendered double-stranded, and cloned into the AscI site of a bacterial plasmid vector.
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Generation of Radioactive EMSA Probes
See Figure 2 for an outline of the procedure for generating the EMSA probes.
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Figure 2. Generation of EMSA probes from individual clones of the random DNA library. Random DNA inserts are amplified by PCR, digested with AscI and BamHI, and radioactively labeled by the incorporation of [ 32P]dCTP (asterisks).
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32P]dCTP Differential Display
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Figure 3. Four typical gels from a DDDP screen. Each autoradiograph displays groups of EMSAs performed on six nuclear extracts harvested from mouse livers at 4-h intervals over a 24-h period with six random DNA probes each (labeled 1-24). Prominent differences in DNA-binding activities were identified with probes 8, 11, 12, and 18 (asterisks). |
Narrowing Down Binding Sites
To facilitate further sequence analysis, this two-step procedure can be used to narrow down the exact position of a binding site within a random probe from 100 bp to 10-30 bp. It is usually sufficient to use only one protein extract for these procedures. Only use other extracts for side-by-side comparisons if in doubt as to the identity of the band showing differential binding activity
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Figure 4. Strategy to identify an unknown binding site in random DNA probes. (A) Two 50-bp random DNA sequences derived from a random DNA insert are amplified separately by PCR and used as competitor DNA in EMSA experiments against the original probe. Six oligonucleotides (arrows) are then designed for the competing fragment. (B) The oligonucleotides are then used in competition experiments individually or in combination with each other, annealed or filled in, as shown. |
TROUBLESHOOTING
Problem: Many clones of the random DNA library contain inserts that are too small and contain less than 100 bp of random DNA.
[Step 9.ii]
Solution: The Random DNA oligonucleotide might not have self-annealed correctly. Avoid warming the annealed oligonucleotide before adding the Klenow fragment.
Problem: Most of the bands on the EMSA gel show only a black smear or show no protein binding at all.
[Step 27]
Solution: The EMSA reactions contain either too much or too little nonspecific competitor. Make a titration series with three to five random probes to determine the ideal amount of competitor DNA.
DISCUSSION
Various methods exist to identify differential transcription factor activity in an unbiased way. Genomic screening methods like DNA microarray analysis or serial analysis of gene expression are powerful techniques to detect differences in steady-state mRNA levels (Velculescu et al. 1995; De Haro and Panda 2006). However, many transcription factors are regulated extensively at the post-transcriptional and/or post-translational levels. Proteomic methods can, in principle, be used to screen for transcription factor regulation at the protein level. However, these methods are generally ineffective at detecting transcription factors because of the low levels at which these proteins are expressed (Reddy et al. 2006). DDDP complements these methods by using an activity assay to select specifically for transcriptionally competent DNA-binding proteins.
A key feature of DDDP is the use of a random DNA library, which enables the screening of a maximum number of potential DNA-binding sites within a minimum length of DNA sequence. The question arises: What is the chance of finding functional binding sites in synthetic DNA sequences that have not been evolutionarily tuned for efficient transcription factor binding? Transcription factors have, in general, a very high affinity for their binding sites. We have shown previously that a single mismatch in a transcription factor recognition site reduces its binding affinity by, at most, one order of magnitude (Fonjallaz et al. 1996). Therefore, most factors should also bind to such imperfect binding sites. Consequently, this reduces greatly the number of binding sites that have to be present in the library. As outlined in greater detail (Reinke et al. 2008), if one allows for at most one mismatch in the binding site, a binding site for a typical eukaryotic transcription factor can still be found (with a probability of more than 99%) in as few as 11,000 bps of random DNA sequence (Fig. 5 ).
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Figure 5. Frequency of imperfect transcription factor binding sites in a random DNA library. Consensus binding sites for REV-ERB and PAR bZIP proteins show the probability for each nucleotide position in random DNA. The calculations determine the number of base pairs (n) that must be tested in random DNA to obtain with a probability (p) of more than 99% a binding site with a complexity equal to that of a REV-ERB or PAR bZIP binding site if a single mismatch is allowed. The total frequency (Ftotal) of such binding sites is a function of the frequency of a perfect match (Fpm) plus the frequency of all sequences with one mismatch (Fmm).
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REFERENCES
De Haro, L. and Panda, S. 2006. Systems biology of circadian rhythms: An outlook. J. Biol. Rhythms 21: 507–518.
Fonjallaz, P., Ossipow, V., Wanner, G., and Schibler, U. 1996. The two PAR leucine zipper proteins, TEF and DBP, display similar circadian and tissue-specific expression, but have different target promoter preferences. EMBO J. 15: 351–362.[Medline]
Kadonaga, J.T. and Tjian, R. 1986. Affinity purification of sequence-specific DNA binding proteins. Proc. Natl. Acad. Sci. 83: 5889–5893.
Reddy, A.B., Karp, N.A., Maywood, E.S., Sage, E.A., Deery, M., ONeill, J.S., Wong, G.K., Chesham, J., Odell, M., Lilley, K.S., et al. 2006. Circadian orchestration of the hepatic proteome. Curr. Biol. 16: 1107–1115.[Medline]
Reinke, H., Saini, C., Fleury-Olela, F., Dibner, C., Benjamin, I.J., and Schibler, U. 2008. Differential display of DNA-binding proteins reveals heat-shock factor 1 as a circadian transcription factor. Genes & Dev. 22: 331–345.
Velculescu, V.E., Zhang, L., Vogelstein, B., and Kinzler, K.W. 1995. Serial analysis of gene expression. Science 270: 484–487.
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