Molecular basis for modulation of the p53 target selectivity by KLF4

The tumour suppressor p53 controls transcription of various genes involved in apoptosis, cell-cycle arrest, DNA repair and metabolism. However, its DNA-recognition specificity is not nearly sufficient to explain binding to specific locations in vivo. Here, we present evidence that KLF4 increases the DNA-binding affinity of p53 through the formation of a loosely arranged ternary complex on DNA. This effect depends on the distance between the response elements of KLF4 and p53. Using nuclear magnetic resonance and fluorescence techniques, we found that the amino-terminal domain of p53 interacts with the KLF4 zinc fingers and mapped the interaction site. The strength of this interaction was increased by phosphorylation of the p53 N-terminus, particularly on residues associated with regulation of cell-cycle arrest genes. Taken together, the cooperative binding of KLF4 and p53 to DNA exemplifies a regulatory mechanism that contributes to p53 target selectivity

Conservation of DNA-binding specificity and oligomerisation properties within the p53 family

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Transcription factors activate their target genes by binding to specific response elements. Many transcription factor families evolved from a common ancestor by gene duplication and subsequent divergent evolution. Members of the p53 family, which play key roles in cell-cycle control and development, share conserved DNA binding and oligomerisation domains but exhibit distinct functions. In this study, the molecular basis of the functional divergence of related transcription factors was investigated. Results We characterised the DNA-binding specificity and oligomerisation properties of human p53, p63 and p73, as well as p53 from other organisms using novel biophysical approaches. All p53 family members bound DNA cooperatively as tetramers with high affinity. Despite structural differences in the oligomerisation domain, the dissociation constants of the tetramers was in the low nanomolar range for all family members, indicating that the strength of tetramerisation was evolutionarily conserved. However, small differences in the oligomerisation properties were observed, which may play a regulatory role. Intriguingly, the DNA-binding specificity of p53 family members was highly conserved even for evolutionarily distant species. Additionally, DNA recognition was only weakly affected by CpG methylation. Prediction of p53/p63/p73 binding sites in the genome showed almost complete overlap between the different homologs. Conclusion Diversity of biological function of p53 family members is not reflected in differences in sequence-specific DNA binding. Hence, additional specificity factors must exist, which allowed the acquisition of novel functions during evolution while preserving original roles.Published versio

Accurate prediction of gene expression by integration of DNA sequence statistics with detailed modeling of transcription regulation

Gene regulation involves a hierarchy of events that extend from specific protein-DNA interactions to the combinatorial assembly of nucleoprotein complexes. The effects of DNA sequence on these processes have typically been studied based either on its quantitative connection with single-domain binding free energies or on empirical rules that combine different DNA motifs to predict gene expression trends on a genomic scale. The middle-point approach that quantitatively bridges these two extremes, however, remains largely unexplored. Here, we provide an integrated approach to accurately predict gene expression from statistical sequence information in combination with detailed biophysical modeling of transcription regulation by multidomain binding on multiple DNA sites. For the regulation of the prototypical lac operon, this approach predicts within 0.3-fold accuracy transcriptional activity over a 10,000-fold range from DNA sequence statistics for different intracellular conditions.Comment: 15 pages, 5 figure