Figure 4. Sequence logos for p53 consensus created from two datasets. The height of the letter indicates the frequency or binding preference at that nucleotide position in the RE. A) Traditional position weight matrix with p53 RE sequences from Table S2. B) Sequence logo developed from the binding data (Figure 3B) using a modified approach of Veprintsev and Fersht [30]. Binding values were put into a binding position weight matrix (BPWM) and the letter height represents experimentally determined binding preference. C) Binding values for bona fide p53 RE sequences (as in Figure 6 and Table S1) plotted against traditional PWM model prediction (4C) and binding based model prediction (4D). The correlation between PWM calculation and measured binding improved from r2 = 0.40 with the traditional PWM model (Figure 4C) to r2 = 0.64 with binding-based model (4D). doi:10.1371/journal.pgen.1000462.g004 EOMES displayed binding strength that was ,30% of p21 binding, a level that is similar to PUMA and GADD45 (Figures 2 and 6). With the exception of REs upstream of DCC and SEI1, we observed that the predicted weak alleles showed significantly reduced binding. SNPs that altered the conserved core sequence (ADARB1, EOMES, RRM1 and TLR8) showed dramatic reductions in binding. This approach to functional evaluation of TF binding site SNPs would be useful for rapid screening of candidate SNPs in TF binding sites identified through bioinfor- matics or whole genome association studies. Assessing the Binding Spectrum Phenotype of Wild Type vs. Mutant p53 Proteins The p53 protein is a master regulator of the cell cycle, DNA repair and apoptosis. p53 activation state is dependent on tissue type and activating stimulus [2] and may impact binding, but few experiments have explored this idea. Using a panel of p53 target REs to assess binding phenotype, we examined nuclear extracts containing activated p53 from different human cell types Sequence Variation and p53 DNA Binding (Figure 6A). To compare the p53 binding spectra for these functional p53 molecules, we added equal quantities of p53 protein based on western blotting (Figure 6B insert) and normalized binding values from each cell type by setting p21LWT equal to 1. Both DOXO-induced and wt p53 binding spectra are shown in Figure 6A; with binding levels for most REs showing little difference (see also Figure S7A). While the profiles are remarkably similar, given that p53 is derived from two different cell types and two types of stimulus, some probes display differences in binding. The very strong ConA RE (perfect consensus) and the 14-3-3s RE showed somewhat increased binding with DOXO treatment relative to wt p53, while GADD45, PCNA and MDM2 REs displayed reduced binding. Given the difference between these cell preparations, it is unclear if the binding differences observed are biologically meaningful. While treatment-specific, posttranslational modifications, such as acetylation at lysine 317, phosphorylation at serine 33 or cofactor interactions, have been hypothesized to mediate p53-mediated gene expression and/or binding [1,2,32,33], this may not be the case for some established tumor cell lines [34]. In general for both DOXO-activated and wt p53, we observed that p53 REs from cell cycle arrest genes (p21LT, 1.22; 14-3-3s, 1.26) and DNA repair genes (p53R2, 1.02; PCNA, 0.33; GADD45, 0.44) showed greater relative binding than REs from apoptotic response genes (PUMA, 0.42; NOXA, 0.12; AIP1, 0.23; BAX-B, 0.07). Importantly, these wild type patterns recapitulate in vivo transactivation experiments using a reporter assay in SaOS2 cells expressing p53. Figure 6A (inset) shows the strong correlation between p53 binding and transactivation capability of p53 REs measured in mammalian cells for several known p53 target gene REs (R2 = 0.97, p = 4.39E-05). Mutations in p53 that lead directly to tumor growth are often described as having a loss- or gain-of-function, as well as dominant-negative phenotype [35,36]. The basis for these descriptive names is presumed to be structural changes in the protein that lead to functional effects and influence consequent tumor phenotype. As shown in Figure 6B, p53 mutants carrying DNA binding domain changes, R175H and S121F (previously characterized in SaOS2 cells [22]), displayed dramatically attenuated binding compared to wild type p53 (Figure 6A, 6B). However, not all target REs are affected to the same extent. The classical tumor suppressor R175H p53 mutant (grey stippled bar) appears to abolish binding entirely as expected and several other loss-of-function, DNA-binding domain mutants (G245S, C277W, G279E) tested also showed total loss of binding (data not shown). Notably, the change-of-spectrum S121F mutant (open bar) displays significantly reduced binding for most REs compared to wt p53 (mean reduction = 51%) but S121F retains strong binding for several REs, particularly those found upstream of the NOXA, BAX-B, RGC and CycG genes (noted by # symbol). This alteration in binding profile could translate to differences in transactivation and eventual phenotypic consequences [22,37]. Discussion Understanding variation in complex biological responses, such as those mediated by the p53 tumor suppressor, requires integrating bioinformatics with experimental approaches that reveal fundamental molecular events and their phenotypic consequences at the cellular level. The relationship between the degree of DNA binding and target gene transactivation has been the subject of many studies and there is considerable interest in how human genetic variation in TF binding sites may impact gene expression and disease susceptibility [5,9,10,11,38,39,40,41,42]. PLoS Genetics | www.plosgenetics.org 6 May 2009 | Volume 5 | Issue 5 | e1000462