Search

Proper timing of gene expression requires that transcription factors (TFs) efficiently locate and bind their target sites within a genome. Theoretical studies have long proposed that one-dimensional sliding along DNA while simultaneously reading its sequence can accelerate TF's location of target sites. Sliding by prokaryotic and eukaryotic TFs were subsequently observed. More recent theoretical investigations have argued that simultaneous reading and sliding is not possible for TFs without their possessing at least two DNA-binding modes. The tumor suppressor p53 has been shown to slide on DNA, and recent experiments have offered structural and single molecule support for a two-mode model for the protein. If the model is applicable to p53, then the requirement that TFs be able to read while sliding implies that noncognate sites will affect p53's mobility on DNA, which will thus be generally sequence-dependent. Here, we confirm this prediction with single-molecule microscopy measurements of p53's local diffusivity on noncognate DNA. We show how a two-mode model accurately predicts the variation in local diffusivity, while a single-mode model does not. We further determine that the best model of sequence-specific binding energy includes terms for "hemi-specific" binding, with one dimer of tetrameric p53 binding specifically to a half-site and the other binding nonspecifically to noncognate DNA. Our work provides evidence that the recognition by p53 of its targets and the timing thereof can depend on its noncognate binding properties and its ability to change between multiple modes of binding, in addition to the much better-studied effects of cognate-site binding.

Cooperative binding of transcription factors (TFs) to promoters and other regulatory regions is essential for precise gene expression. The classical model of cooperativity requires direct interactions between TFs, thus constraining the arrangement of TF sites in regulatory regions. Recent genomic and functional studies, however, demonstrate a great deal of flexibility in such arrangements with variable distances, numbers of sites, and identities of TF sites located in cis-regulatory regions. Such flexibility is inconsistent with cooperativity by direct interactions between TFs. Here, we demonstrate that strong cooperativity among noninteracting TFs can be achieved by their competition with nucleosomes. We find that the mechanism of nucleosome-mediated cooperativity is analogous to cooperativity in another multimolecular complex: hemoglobin. This surprising analogy provides deep insights, with parallels between the heterotropic regulation of hemoglobin (e.g., the Bohr effect) and the roles of nucleosome-positioning sequences and chromatin modifications in gene expression. Nucleosome-mediated cooperativity is consistent with several experimental studies, is equally applicable to repressors and activators, allows substantial flexibility in and modularity of regulatory regions, and provides a rationale for a broad range of genomic and evolutionary observations. Striking parallels between cooperativity in hemoglobin and in transcriptional regulation point to a general mechanism that can be used in various biological systems.

Coordinated regulation of gene expression relies on transcription factors (TFs) binding to specific DNA sites. Our large-scale information-theoretical analysis of > 950 TF-binding motifs demonstrates that prokaryotes and eukaryotes use strikingly different strategies to target TFs to specific genome locations. Although bacterial TFs can recognize a specific DNA site in the genomic background, eukaryotic TFs exhibit widespread, nonfunctional binding and require clustering of sites to achieve specificity. We find support for this mechanism in a range of experimental studies and in our evolutionary analysis of DNA-binding domains. Our systematic characterization of binding motifs provides a quantitative assessment of the differences in transcription regulation in prokaryotes and eukaryotes.

The binding of a transcription factor (TF) to a DNA operator site can initiate or repress the expression of a gene. Computational prediction of sites recognized by a TF has traditionally relied upon knowledge of several cognate sites, rather than an ab initio approach. Here, we examine the possibility of using structure-based energy calculations that require no knowledge of bound sites but rather start with the structure of a protein-DNA complex. We study the PurR Escherichia coli TF, and explore to which extent atomistic models of protein-DNA complexes can be used to distinguish between cognate and noncognate DNA sites. Particular emphasis is placed on systematic evaluation of this approach by comparing its performance with bioinformatic methods, by testing it against random decoys and sites of homologous TFs. We also examine a set of experimental mutations in both DNA and the protein. Using our explicit estimates of energy, we show that the specificity for PurR is dominated by direct protein-DNA interactions, and weakly influenced by bending of DNA.

Strong experimental and theoretical evidence shows that transcription factors (TFs) and other specific DNA-binding proteins find their sites using a two-mode search: alternating between three-dimensional (3D) diffusion through the cell and one-dimensional (1D) sliding along the DNA. We show that, due to the 1D component of the search process, the search time of a TF can depend on the initial position of the TF. We formalize this effect by discriminating between two types of searches: global and local. Using analytical calculations and simulations, we estimate how close a TF and binding site need to be to make a local search likely. We then use our model to interpret the wide range of experimental measurements of this parameter. We also show that local and global searches differ significantly in average search time and the variability of search time. These results lead to a number of biological implications, including suggestions of how prokaryotes achieve rapid gene regulation and the relationship between the search mechanism and noise in gene expression. Lastly, we propose a number of experiments to verify the existence and quantify the extent of spatial effects on the TF search process in prokaryotes.

What are the forces that shape the structure of prokaryotic genomes: the order of genes, their proximity, and their orientation? Coregulation and coordinated horizontal gene transfer are believed to promote the proximity of functionally related genes and the formation of operons. However, forces that influence the structure of the genome beyond the level of a single operon remain unknown. Here, we show that the biophysical mechanism by which regulatory proteins search for their sites on DNA can impose constraints on genome structure. Using simulations, we demonstrate that rapid and reliable gene regulation requires that the transcription factor (TF) gene be close to the site on DNA the TF has to bind, thus promoting the colocalization of TF genes and their targets on the genome. We use parameters that have been measured in recent experiments to estimate the relevant length and times scales of this process and demonstrate that the search for a cognate site may be prohibitively slow if a TF has a low copy number and is not colocalized. We also analyze TFs and their sites in a number of bacterial genomes, confirm that they are colocalized significantly more often than expected, and show that this observation cannot be attributed to the pressure for coregulation or formation of selfish gene clusters, thus supporting the role of the biophysical constraint in shaping the structure of prokaryotic genomes. Our results demonstrate how spatial organization can influence timing and noise in gene expression.

Many biological processes involve one-dimensional diffusion over a correlated inhomogeneous energy landscape with a correlation length xi(c). Typical examples are specific protein target location on DNA, nucleosome repositioning, or DNA translocation through a nanopore, in all cases with xi(c) approximately 10 nm. We investigate such transport processes by the mean first passage time (MFPT) formalism, and find diffusion times which exhibit strong sample to sample fluctuations. For a displacement N, the average MFPT is diffusive, while its standard deviation over the ensemble of energy profiles scales as N(3/2) with a large prefactor. Fluctuations are thus dominant for displacements smaller than a characteristic N(c) >> xi(c) : typical values are much less than the mean, and governed by an anomalous diffusion rule. Potential biological consequences of such random walks, composed of rapid scans in the vicinity of favorable energy valleys and occasional jumps to further valleys, is discussed.

Concepts of orthology and paralogy are become increasingly important as whole-genome comparison allows their identification in complete genomes. Functional specificity of proteins is assumed to be conserved among orthologs and is different among paralogs. We used this assumption to identify residues which determine specificity of protein-DNA and protein-ligand recognition. Finding such residues is crucial for understanding mechanisms of molecular recognition and for rational protein and drug design. Assuming conservation of specificity among orthologs and different specificity of paralogs, we identify residues that correlate with this grouping by specificity. The method is taking advantage of complete genomes to find multiple orthologs and paralogs. The central part of this method is a procedure to compute statistical significance of the predictions. The procedure is based on a simple statistical model of protein evolution. When applied to a large family of bacterial transcription factors, our method identified 12 residues that are presumed to determine the protein-DNA and protein-ligand recognition specificity. Structural analysis of the proteins and available experimental results strongly support our predictions. Our results suggest new experiments aimed at rational re-design of specificity in bacterial transcription factors by a minimal number of mutations.

Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (1) protein complexes (splicing machinery, transcription factors, etc.) and (ill dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks. [ABSTRACT FROM AUTHOR]

Summary The cell fate decision between interferon-producing plasmacytoid DC (pDC) and antigen-presenting classical DC (cDC) is controlled by the E protein transcription factor TCF4 (E2-2). We report that TCF4 comprises two transcriptional isoforms, both of which are required for optimal pDC development in vitro. The long Tcf4 isoform is expressed specifically in pDCs, and its deletion in mice impaired pDCs development and led to the expansion of non-canonical CD8 + cDCs. The expression of Tcf4 commenced in progenitors and was further upregulated in pDCs, correlating with stage-specific activity of multiple enhancer elements. A conserved enhancer downstream of Tcf4 was required for its upregulation during pDC differentiation, revealing a positive feedback loop. The expression of Tcf4 and the resulting pDC differentiation were selectively sensitive to the inhibition of enhancer-binding BET protein activity. Thus, lineage-specifying function of E proteins is facilitated by lineage-specific isoform expression and by BET-dependent feedback regulation through distal regulatory elements. [ABSTRACT FROM AUTHOR]

Summary: Stem cells (SC) exhibit a unique capacity for self-renewal in an undifferentiated state. It is unclear whether the self-renewal of pluripotent embryonic SC (ESC) and of tissue-specific adult SC such as hematopoietic SC (HSC) is controlled by common mechanisms. The deletion of transcription factor Zfx impaired the self-renewal but not the differentiation capacity of murine ESC; conversely, Zfx overexpression facilitated ESC self-renewal by opposing differentiation. Furthermore, Zfx deletion abolished the maintenance of adult HSC but did not affect erythromyeloid progenitors or fetal HSC. Zfx-deficient ESC and HSC showed increased apoptosis and SC-specific upregulation of stress-inducible genes. Zfx directly activated common target genes in ESC and HSC, as well as ESC-specific target genes including ESC self-renewal regulators Tbx3 and Tcl1. These studies identify Zfx as a shared transcriptional regulator of ESC and HSC, suggesting a common genetic basis of self-renewal in embryonic and adult SC. [Copyright &y& Elsevier]

The article offers information on identification of a functional genetic variant that alters PRRX1 gene expression in atrial myocytes and provides a link with atrial fibrillation (AF). It mentions the molecular mechanism of transcription factor PRRX1 which is expressed in the pulmonary veins. It also states the role of electrophysiological alterations in atrial myocytes in promoting AF.