The general affinity of lac repressor for E. coli DNA: implications for gene regulation in procaryotes and eucaryotes

Can molecular dynamics be used to simulate biomolecular recognition?

There are many problems in biochemistry that are difficult to study experimentally. Simulation methods are appealing due to direct availability of atomic coordinates as a function of time. However, direct molecular simulations are challenged by the size of systems and the time scales needed to describe relevant motions. In theory, enhanced sampling algorithms can help to overcome some of the limitations of molecular simulations. Here, we discuss a problem in biochemistry that offers a significant challenge for enhanced sampling methods and that could, therefore, serve as a benchmark for comparing approaches that use machine learning to find suitable collective variables. In particular, we study the transitions LacI undergoes upon moving between being non-specifically and specifically bound to DNA. Many degrees of freedom change during this transition and that the transition does not occur reversibly in simulations if only a subset of these degrees of freedom are biased. We also explain why this problem is so important to biologists and the transformative impact that a simulation of it would have on the understanding of DNA regulation.

Repetitive DNA symmetry elements negatively regulate gene expression in embryonic stem cells

Transcription factor (TF) binding to genomic DNA elements constitutes one of the key mechanisms that regulates gene expression program in cells. Both consensus and nonconsensus DNA sequence elements influence the recognition specificity of TFs. Based on the analysis of experimentally determined c-Myc binding preferences to genomic DNA, here we statistically predict that certain repetitive, nonconsensus DNA symmetry elements can relatively reduce TF-DNA binding preferences. This is in contrast to a different set of repetitive, nonconsensus symmetry elements that can increase the strength of TF-DNA binding. Using c-Myc enhancer reporter system containing consensus motif flanked by nonconsensus sequences in embryonic stem cells, we directly demonstrate that the enrichment in such negatively regulating repetitive symmetry elements is sufficient to reduce the gene expression level compared with native genomic sequences. Negatively regulating repetitive symmetry elements around consensus c-Myc motif and DNA sequences containing consensus c-Myc motif flanked by entirely randomized sequences show similar expression baseline. A possible explanation for this observation is that rather than complete repression, negatively regulating repetitive symmetry elements play a regulatory role in fine-tuning the reduction of gene expression, most probably by binding TFs other than c-Myc.

Biosynthesis of phenylpyruvic acid from l-phenylalanine using chromosomally engineered Escherichia coli

The efficiency of whole-cell biotransformation is often affected by the genetic instability of plasmid-based expression systems, which require selective pressure to maintain the stability of the plasmids. To circumvent this shortcoming, we constructed a chromosome engineering strain for the synthesis of phenylpyruvic acid (PPA) from l-phenylalanine. First, l-amino acid deaminase (pmLAAD) from Proteus myxofaciens was incorporated into Escherichia coli BL21 (DE3) chromosome and the copy numbers of pmLAAD were increased by chemically induced chromosomal evolution (CIChE). Fifty-nine copies of pmLAAD were obtained in E. coli BL8. The PPA titer of E. coli BL8 reached 2.22 g/L at 6 h. Furthermore, the deletion of lacI improved PPA production. In the absence of isopropyl-β-d-thiogalactopyranoside, the resulting strain, E. coli BL8△recA△lacI, produced 2.65 g/L PPA at 6 h and yielded a 19.37% increase in PPA production compared to E. coli BL8△recA. Finally, the engineered E. coli BL8△recA△lacI strain achieved 19.14 g/L PPA at 24 h in a 5-L bioreactor.

Rheostat functional outcomes occur when substitutions are introduced at nonconserved positions that diverge with speciation

When amino acids vary during evolution, the outcome can be functionally neutral or biologically-important. We previously found that substituting a subset of nonconserved positions, "rheostat" positions, can have surprising effects on protein function. Since changes at rheostat positions can facilitate functional evolution or cause disease, more examples are needed to understand their unique biophysical characteristics. Here, we explored whether "phylogenetic" patterns of change in multiple sequence alignments (such as positions with subfamily specific conservation) predict the locations of functional rheostat positions. To that end, we experimentally tested eight phylogenetic positions in human liver pyruvate kinase (hLPYK), using 10-15 substitutions per position and biochemical assays that yielded five functional parameters. Five positions were strongly rheostatic and three were non-neutral. To test the corollary that positions with low phylogenetic scores were not rheostat positions, we combined these phylogenetic positions with previously-identified hLPYK rheostat, "toggle" (most substitution abolished function), and "neutral" (all substitutions were like wild-type) positions. Despite representing 428 variants, this set of 33 positions was poorly statistically powered. Thus, we turned to the in vivo phenotypic dataset for E. coli lactose repressor protein (LacI), which comprised 12-13 substitutions at 329 positions and could be used to identify rheostat, toggle, and neutral positions. Combined hLPYK and LacI results show that positions with strong phylogenetic patterns of change are more likely to exhibit rheostat substitution outcomes than neutral or toggle outcomes. Furthermore, phylogenetic patterns were more successful at identifying rheostat positions than were co-evolutionary or eigenvector centrality measures of evolutionary change.

To mock or not: a comprehensive comparison of mock IP and DNA input for ChIP-seq

Chromatin immunoprecipitation (IP) followed by sequencing (ChIP-seq) is the gold standard to detect transcription-factor (TF) binding sites in the genome. Its success depends on appropriate controls removing systematic biases. The predominantly used controls, i.e. DNA input, correct for uneven sonication, but not for nonspecific interactions of the IP antibody. Another type of controls, 'mock' IP, corrects for both of the issues, but is not widely used because it is considered susceptible to technical noise. The tradeoff between the two control types has not been investigated systematically. Therefore, we generated comparable DNA input and mock IP experiments. Because mock IPs contain only nonspecific interactions, the sites predicted from them using DNA input indicate the spurious-site abundance. This abundance is highly correlated with the 'genomic activity' (e.g. chromatin openness). In particular, compared to cell lines, complex samples such as whole organisms have more spurious sites-probably because they contain multiple cell types, resulting in more expressed genes and more open chromatin. Consequently, DNA input and mock IP controls performed similarly for cell lines, whereas for complex samples, mock IP substantially reduced the number of spurious sites. However, DNA input is still informative; thus, we developed a simple framework integrating both controls, improving binding site detection.

Foxh1/Nodal Defines Context-Specific Direct Maternal Wnt/β-Catenin Target Gene Regulation in Early Development

Although Wnt/β-catenin signaling is generally conserved and well understood, the regulatory mechanisms controlling context-specific direct Wnt target gene expression in development and disease are still unclear. The onset of zygotic gene transcription in early embryogenesis represents an ideal, accessible experimental system to investigate context-specific direct Wnt target gene regulation. We combine transcriptomics using RNA-seq with genome-wide β-catenin association using ChIP-seq to identify stage-specific direct Wnt target genes. We propose coherent feedforward regulation involving two distinct classes of direct maternal Wnt target genes, which differ both in expression and persistence of β-catenin association. We discover that genomic β-catenin association overlaps with Foxh1-associated regulatory sequences and demonstrate that direct maternal Wnt target gene expression requires Foxh1 function and Nodal/Tgfβ signaling. Our results support a new paradigm for direct Wnt target gene co-regulation with context-specific mechanisms that will inform future studies of embryonic development and more widely stem cell-mediated homeostasis and human disease.

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Combining RNA-seq and β-catenin ChIP-seq identifies direct Wnt target genes

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Two distinct classes of direct maternal Wnt/β-catenin target genes can be discerned

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We propose coherent feedforward regulation of gene expression of the second class

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Maternal Wnt target gene expression of both classes requires Nodal/Foxh1 signaling

Long-term association of a transcription factor with its chromatin binding site can stabilize gene expression and cell fate commitment

Some kinds of transcription factor proteins are very important in initiating and guiding cell fate differentiation. Overexpression of these factors can force many other kinds of cells to become muscle or nerve. Examples are MyoD for muscle and Ascl1 for nerve. It is not known how long such a factor must remain bound to its binding site for it to have its function; this could be seconds, minutes, hours, or days. We have developed a procedure to determine the required residence time for the Ascl1 nerve factor to have its function. This factor remains closely associated with its chromatin binding site for hours or days. This may be a general characteristic of such factors in nondividing (adult) cells.

Some lineage-determining transcription factors are overwhelmingly important in directing embryonic cells to a particular differentiation pathway, such as Ascl1 for nerve. They also have an exceptionally strong ability to force cells to change from an unrelated pathway to one preferred by their action. Transcription factors are believed to have a very short residence time of only a few seconds on their specific DNA or chromatin-binding sites. We have developed a procedure in which DNA containing one copy of the binding site for the neural-inducing factor Ascl1 is injected directly into a Xenopus oocyte nucleus which has been preloaded with a limiting amount of the Ascl1 transcription factor protein. This is followed by a further injection of DNA as a competitor, either in a plasmid or in chromosomal DNA, containing the same binding site but with a different reporter. Importantly, expression of the reporter provides a measure of the function of the transcription factor in addition to its residence time. The same long residence time and resistance to competition are seen with the estrogen receptor and its DNA response elements. We find that in this nondividing oocyte, the nerve-inducing factor Ascl1 can remain bound to a specific chromatin site for hours or days and thereby help to stabilize gene expression. This stability of transcription factor binding to chromatin is a necessary part of its action because removal of this factor causes discontinuation of its effect on gene expression. Stable transcription factor binding may be a characteristic of nondividing cells.

Transcription Factors and DNA Play Hide and Seek

Transcription factors (TFs) bind to specific DNA motifs to regulate the expression of target genes. To reach their binding sites, TFs diffuse in 3D and perform local motions such as 1D sliding, hopping, or intersegmental transfer. TF-DNA interactions depend on multiple parameters, such as the chromatin environment, TF partitioning into distinct subcellular regions, and cooperativity with other DNA-binding proteins. In this review, how current understanding of the search process has initially been shaped by prokaryotic studies is discussed, as well as what is known about the parameters regulating TF search efficiency in the context of the complex eukaryotic chromatin landscape.

The strengths and limitations of using biolayer interferometry to monitor equilibrium titrations of biomolecules

Every method used to quantify biomolecular interactions has its own strengths and limitations. To quantify protein-DNA binding affinities, nitrocellulose filter binding assays with 32 P-labeled DNA quantify Kd values from 10-12 to 10-8 M but have several technical limitations. Here, we considered the suitability of biolayer interferometry (BLI), which monitors association and dissociation of a soluble macromolecule to an immobilized species; the ratio koff /kon determines Kd . However, for lactose repressor protein (LacI) and an engineered repressor protein ("LLhF") binding immobilized DNA, complicated kinetic curves precluded this analysis. Thus, we determined whether the amplitude of the BLI signal at equilibrium related linearly to the fraction of protein bound to DNA. A key question was the effective concentration of immobilized DNA. Equilibrium titration experiments with DNA concentrations below Kd (equilibrium binding regime) must be analyzed differently than those with DNA near or above Kd (stoichiometric binding regime). For ForteBio streptavidin tips, the most frequent effective DNA concentration was ~2 × 10-9 M. Although variation occurred among different lots of sensor tips, binding events with Kd ≥ 10-8 M should reliably be in the equilibrium binding regime. We also observed effects from multi-valent interactions: Tetrameric LacI bound two immobilized DNAs whereas dimeric LLhF did not. We next used BLI to quantify the amount of inducer sugars required to allosterically diminish protein-DNA binding and to assess the affinity of fructose-1-kinase for the DNA-LLhF complex. Overall, when experimental design corresponded with appropriate data interpretation, BLI was convenient and reliable for monitoring equilibrium titrations and thereby quantifying a variety of binding interactions.

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome.

Mechanistic insight into the regulation of transcriptional modules remains scarce. Here, the authors identify statistically independent gene sets by applying independent component analysis to a high-quality E. coli RNA-seq data compendium and find that most gene sets represent the effects of specific transcriptional regulators.

Enhancement of LacI binding in vivo

Transcription factors (TFs) bind to specific sequences in DNA to regulate transcription. Despite extensive measurements of TFs’ dissociation constant (K_d) in vitro, their apparent K_din vivo are usually unknown. LacI, a bacterial TF, is often used to artificially recruit proteins onto eukaryotic genomes. As LacI binds tightly to its recognition site (LacO) in vitro with a K_d about 10 picomolar (pM), it is often assumed that LacI also has high affinity to LacO in vivo. In this work, we measured LacI binding in living yeast cells using a fluorescent repressor operator system and found an apparent K_d of ∼0.6 μM, four orders of magnitude higher than that in vitro. By genetically altering (i) GFP-LacI structure, (ii) GFP-LacI stability, (iii) chromosome accessibility and (iv) LacO sequence, we reduced the apparent K_d to <10 nM. It turns out that the GFP tagging location and the fusion protein stability have a large effect on LacI binding, but surprisingly, chromosome accessibility only plays a mild role. These findings contribute to our quantitative understanding of the features that affect the apparent K_d of TF in cells. They also provide guidance for future design of more specific chromosomal recruitment through high-affinity TFs.

Homolog comparisons further reconcile in vitro and in vivo correlations of protein activities by revealing over-looked physiological factors

To bridge biological and biochemical disciplines, the relationship between in vitro protein biochemical function and in vivo activity must be established. Such studies can (a) help determine whether properties measured in simple, dilute solutions extrapolate to the complex in vivo conditions and (b) illuminate cryptic biological factors that are new avenues for study. We have explored the in vivo-in vitro relationship for chimeras built from LacI/GalR transcription regulators. In prior studies of individual chimeras, amino acid changes that altered in vitro DNA binding affinity exhibited correlated changes in in vivo transcription repression. However, discrepancies arose when the two datasets were compared to each other: Although their DNA binding domains were identical and their in vitro binding affinities spanned the same range, their in vivo repression ranges differed by >50-fold. Here, we determined that the presence of endogenous ligand for one chimera further exacerbated the offset, but that different abilities to simultaneously bind and "loop" two DNA operators resolves the discrepancy. Indeed, results suggest that the lac operon can be looped by even weakly interacting repressor dimers. For looping-competent repressors, we measured in vitro binding to the secondary operator. Surprisingly, this was largely insensitive to amino acid changes in the repressor protein, which reflects altered specificity; this supports the emerging view that the locations of specificity determining positions can be unique to each protein homolog. In aggregate, this work illustrates how a comparative approach can enrich understanding of the in vivo-in vitro relationship and suggest unexpected avenues for future study.

Dissociation rate compensation mechanism for budding yeast pioneer transcription factors

Nucleosomes restrict the occupancy of most transcription factors (TF) by reducing binding and accelerating dissociation, while a small group of TFs have high affinities to nucleosome-embedded sites and facilitate nucleosome displacement. To understand this process mechanistically, we investigated two Saccharomyces cerevisiae TFs, Reb1 and Cbf1. We show that these factors bind to their sites within nucleosomes with similar binding affinities as to naked DNA, trapping a partially unwrapped nucleosome without histone eviction. Both the binding and dissociation rates of Reb1 and Cbf1 are significantly slower at the nucleosomal sites relative to those for naked DNA, demonstrating that the high affinities are achieved by increasing the dwell time on nucleosomes in order to compensate for reduced binding. Reb1 also shows slow migration rate in the yeast nuclei. These properties are similar to those of human pioneer factors (PFs), suggesting that the mechanism of nucleosome targeting is conserved from yeast to humans.

Genome-wide analysis of canonical Wnt target gene regulation in Xenopus tropicalis challenges β-catenin paradigm

Wnt/β‐catenin signaling is an important cell‐to‐cell signaling mechanism that controls gene expression during embryonic development and is critically implicated in human diseases. Developmental, cellular, and transcriptional responses to Wnt signaling are remarkably context‐specific in different biological processes. While nuclear localization of β‐catenin is the key to activation of the Wnt/β‐catenin pathway and target gene expression, the molecular mechanisms of how the same Wnt/β‐catenin signaling pathway induces specific responses remain undetermined. Recent advances in high‐throughput sequencing technologies and the availability of genome information for Xenopus tropicalis have enabled us to uncover a genome‐wide view of Wnt/β‐catenin signaling in early vertebrate embryos, which challenges previous concepts about molecular mechanisms of Wnt target gene regulation. In this review, we summarize our experimental approaches, introduce the technologies we employed and focus on recent findings about Wnt target gene regulation from Xenopus research. We will also discuss potential functions of widespread β‐catenin binding in the genome that we discovered in this species.

Dynamic equilibrium on DNA defines transcriptional regulation of a multidrug binding transcriptional repressor, LmrR

LmrR is a multidrug binding transcriptional repressor that controls the expression of a major multidrug transporter, LmrCD, in Lactococcus lactis. Promiscuous compound ligations reduce the affinity of LmrR for the lmrCD operator by several fold to release the transcriptional repression; however, the affinity reduction is orders of magnitude smaller than that of typical transcriptional repressors. Here, we found that the transcriptional regulation of LmrR is achieved through an equilibrium between the operator-bound and non-specific DNA-adsorption states in vivo. The effective dissociation constant of LmrR for the lmrCD operator under the equilibrium is close to the endogenous concentration of LmrR, which allows a substantial reduction of LmrR occupancy upon compound ligations. Therefore, LmrR represents a dynamic type of transcriptional regulation of prokaryotic multidrug resistance systems, where the small affinity reduction induced by compounds is coupled to the functional relocalization of the repressor on the genomic DNA via nonspecific DNA adsorption.

Conformational Dynamics and the Binding of Specific and Nonspecific DNA by the Autoinhibited Transcription Factor Ets-1

The affinity of the Ets-1 transcription factor for DNA is autoinhibited by an intrinsically disordered serine-rich region (SRR) and a helical inhibitory module (IM) appended to its winged helix-turn-helix ETS domain. Using NMR spectroscopy, we investigated how Ets-1 recognizes specific versus nonspecific DNA, with a focus on the roles of protein dynamics and autoinhibition in these processes. Upon binding either DNA, the two marginally stable N-terminal helices of the IM predominantly unfold, but still sample partially ordered conformations. Also, on the basis of amide chemical shift perturbation mapping, Ets-1 associates with both specific and nonspecific DNA through the same canonical ETS domain interface. These interactions are structurally independent of the SRR, and thus autoinhibition does not impart DNA-binding specificity. However, relative to the pronounced NMR spectroscopic changes in Ets-1 resulting from specific DNA binding, the spectra of the nonspecific DNA complexes showed conformational exchange broadening and lacked several diagnostic amide and indole signals attributable to hydrogen bonding interactions seen in reported X-ray crystallographic structures of this transcription factor with its cognate DNA sequences. Such differences are highlighted by the chemical shift and relaxation properties of several interfacial lysine and arginine side chains. Collectively, these data support a general model in which Ets-1 interacts with nonspecific DNA via dynamic electrostatic interactions, whereas hydrogen bonding drives the formation of well-ordered complexes with specific DNA.

TrmBL2 from Pyrococcus furiosus Interacts Both with Double-Stranded and Single-Stranded DNA

In many hyperthermophilic archaea the DNA binding protein TrmBL2 or one of its homologues is abundantly expressed. TrmBL2 is thought to play a significant role in modulating the chromatin architecture in combination with the archaeal histone proteins and Alba. However, its precise physiological role is poorly understood. It has been previously shown that upon binding TrmBL2 covers double-stranded DNA, which leads to the formation of a thick and fibrous filament. Here we investigated the filament formation process as well as the stabilization of DNA by TrmBL2 from Pyroccocus furiosus in detail. We used magnetic tweezers that allow to monitor changes of the DNA mechanical properties upon TrmBL2 binding on the single-molecule level. Extended filaments formed in a cooperative manner and were considerably stiffer than bare double-stranded DNA. Unlike Alba, TrmBL2 did not form DNA cross-bridges. The protein was found to bind double- and single-stranded DNA with similar affinities. In mechanical disruption experiments of DNA hairpins this led to stabilization of both, the double- (before disruption) and the single-stranded (after disruption) DNA forms. Combined, these findings suggest that the biological function of TrmBL2 is not limited to modulating genome architecture and acting as a global repressor but that the protein acts additionally as a stabilizer of DNA secondary structure.

Making sense of transcription networks

When transcription regulatory networks are compared among distantly related eukaryotes, a number of striking similarities are observed: a larger-than-expected number of genes, extensive overlapping connections, and an apparently high degree of functional redundancy. It is often assumed that the complexity of these networks represents optimized solutions, precisely sculpted by natural selection; their common features are often asserted to be adaptive. Here, we discuss support for an alternative hypothesis: the common structural features of transcription networks arise from evolutionary trajectories of "least resistance"--that is, the relative ease with which certain types of network structures are formed during their evolution.

Hill function-based models of transcriptional switches: impact of specific, nonspecific, functional and nonfunctional binding

We explore minimalist models of transcription in which we take into account that a cis-regulatory sequence is embedded in, and interacts with, a complex genome. The classical Hill equation is the simplest way to represent a transcriptional response. However, it may overlook the fact that a transcription factor (TF) establishes specific and nonspecific nonfunctional interactions with chromatin. Classical papers have shown that nonfunctional binding (not leading to transcription) may influence gene expression. We examine how the presence of additional binding sites for a TF, besides those on the gene(s) of interest, affect the shape and parameters of the transcriptional response. We consider two conditions: at equilibrium and at steady-state. In many cases the TF level is determined by the position of the cell within a spatial or temporal gradient. We show that such gradients can be adjusted by evolutionary selection to compensate for the alteration of the gene transcription response by the presence of nonfunctional binding sites. Finally, we analyse how the transcriptional response is affected by a decrease in TF concentration, as in cases of haploinsufficiency. We show that the nonlinearity of the transcriptional response as a function of [TF] exacerbates the effect of a decrease in the latter, at least for weakly expressed TFs. Although decades of work on TFs have led to the impression that almost everything is known about the control of gene expression, we show that even the simplest models of transcription control have not delivered all their secrets yet.

Nuclear physics (of the cell, not the atom)

The nucleus is physically distinct from the cytoplasm in ways that suggest new ideas and approaches for interrogating the operation of this organelle. Chemical bond formation and breakage underlie the lives of cells, but as this special issue of Molecular Biology of the Cell attests, the nonchemical aspects of cell nuclei present a new frontier to biologists and biophysicists.

Mouse regulatory DNA landscapes reveal global principles of cis-regulatory evolution

To study the evolutionary dynamics of regulatory DNA, we mapped >1.3 million deoxyribonuclease I-hypersensitive sites (DHSs) in 45 mouse cell and tissue types, and systematically compared these with human DHS maps from orthologous compartments. We found that the mouse and human genomes have undergone extensive cis-regulatory rewiring that combines branch-specific evolutionary innovation and loss with widespread repurposing of conserved DHSs to alternative cell fates, and that this process is mediated by turnover of transcription factor (TF) recognition elements. Despite pervasive evolutionary remodeling of the location and content of individual cis-regulatory regions, within orthologous mouse and human cell types the global fraction of regulatory DNA bases encoding recognition sites for each TF has been strictly conserved. Our findings provide new insights into the evolutionary forces shaping mammalian regulatory DNA landscapes.

Transcription factors: specific DNA binding and specific gene regulation

Specific recognition of cis-regulatory regions is essential for correct gene regulation in response to developmental and environmental signals. Such DNA sequences are recognized by transcription factors (TFs) that recruit the transcriptional machinery. Achievement of specific sequence recognition is not a trivial problem; many TFs recognize similar consensus DNA-binding sites and a genome can harbor thousands of consensus or near-consensus sequences, both functional and nonfunctional. Although genomic technologies have provided large-scale snapshots of TF binding, a full understanding of the mechanistic and quantitative details of specific recognition in the context of gene regulation is lacking. Here, we explore the various ways in which TFs recognizing similar consensus sites distinguish their own targets from a large number of other sequences to ensure specific cellular responses.

The nuclear physique

This volume brings together a number of perspectives on how certain physical phenomena contribute to the functional design and operation of the nucleus. This collection could not be more timely, resonating with an increasing awareness of the opportunities that lie at the interface of cell biology and the physical sciences. For example, this was a major theme in the 2012 and 2013 annual meetings of the American Society for Cell Biology, and one that the Society aims to emphasize even further going forward. In addition, the emerging canonical relevance of the physical sciences to cell biology has in recent summers made a most conspicuous appearance in the curriculum (lectures and intense labs) of the famed Physiology Course at the Marine Biological Laboratory in Woods Hole. So, much credit is due to Ronald Hancock and Kwang Jeon, the coeditors of this volume, and all the authors for creating a work that is so au courant.

Cooperativity and rapid evolution of cobound transcription factors in closely related mammals

To mechanistically characterize the microevolutionary processes active in altering transcription factor (TF) binding among closely related mammals, we compared the genome-wide binding of three tissue-specific TFs that control liver gene expression in six rodents. Despite an overall fast turnover of TF binding locations between species, we identified thousands of TF regions of highly constrained TF binding intensity. Although individual mutations in bound sequence motifs can influence TF binding, most binding differences occur in the absence of nearby sequence variations. Instead, combinatorial binding was found to be significant for genetic and evolutionary stability; cobound TFs tend to disappear in concert and were sensitive to genetic knockout of partner TFs. The large, qualitative differences in genomic regions bound between closely related mammals, when contrasted with the smaller, quantitative TF binding differences among Drosophila species, illustrate how genome structure and population genetics together shape regulatory evolution.

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Earliest steps of regulatory evolution in mammals captured using five mouse species

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Interspecies differences in TF binding are rarely caused by DNA variation in motifs

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Cobound TFs change their genomic binding cooperatively in closely related mammals

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Genetic knockouts revealed the extent of cooperative stabilization in TF binding clusters

A novel prokaryotic promoter identified in the genome of some monopartite begomoviruses

Geminiviruses are known to exhibit both prokaryotic and eukaryotic features in their genomes, with the ability to express their genes and even replicate in bacterial cells. We have demonstrated previously the existence of unit-length single-stranded circular DNAs of Ageratum yellow vein virus (AYVV, a species in the genus Begomovirus, family Geminiviridae) in Escherichia coli cells, which prompted our search for unknown prokaryotic functions in the begomovirus genomes. By using a promoter trapping strategy, we identified a novel prokaryotic promoter, designated AV3 promoter, in nts 762-831 of the AYVV genome. Activity assays revealed that the AV3 promoter is strong, unidirectional, and constitutive, with an endogenous downstream ribosome binding site and a translatable short open reading frame of eight amino acids. Sequence analyses suggested that the AV3 promoter might be a remnant of prokaryotic ancestors that could be related to certain promoters of bacteria from marine or freshwater environments. The discovery of the prokaryotic AV3 promoter provided further evidence for the prokaryotic origin in the evolutionary history of geminiviruses.

New insights into DNA recognition by zinc fingers revealed by structural analysis of the oncoprotein ZNF217

Classical zinc fingers (ZFs) are one of the most abundant and best characterized DNA-binding domains. Typically, tandem arrays of three or more ZFs bind DNA target sequences with high affinity and specificity, and the mode of DNA recognition is sufficiently well understood that tailor-made ZF-based DNA-binding proteins can be engineered. We have shown previously that a two-zinc finger unit found in the transcriptional coregulator ZNF217 recognizes DNA but with an affinity and specificity that is lower than other ZF arrays. To investigate the basis for these differences, we determined the structure of a ZNF217-DNA complex. We show that although the overall position of the ZFs on the DNA closely resembles that observed for other ZFs, the side-chain interaction pattern differs substantially from the canonical model. The structure also reveals the presence of two methyl-π interactions, each featuring a tyrosine contacting a thymine methyl group. To our knowledge, interactions of this type have not previously been described in classical ZF-DNA complexes. Finally, we investigated the sequence specificity of this two-ZF unit and discuss how ZNF217 might discriminate its target DNA sites in the cell.

Computation of diffusion limited controlled actions for gene regulating repressor particles

Temporal changes in association anddissociation kinetics of the repressor -operator reaction were simulated by a computational approach using MATOLABO on the basis of strict mathematical description. The diffusion equation of a repressor particle has been combinedwith arrival probabilities of therepressor particle. Temporal behaviors of the repressor operator complex have been computed by inverting the Laplace transformed equations. The temporal kinetic data of association anddissociation obtained at differentionic strength and at different DNA length were successfully simulated. Those results could be achieved byregulating diffusion constants inmedium on the DNA, a reaction radius of the repressor and a reaction rate per one repressor on the reaction sphere surface, k value. The reported values of association rate constant ka obtained at different ionic strength were also successfully simulated. Amongthe regulated parameters to get these successful simulations, the reaction rate per one particle on the reaction sphere surface, k value has effectiveinfluences on the association anddissociation kinetics particularly those at varying ionic strength that were induced by high KCl condition. By an electro chemical consideration for thechange of k value in combinationwith the screening effects of counter ions around the repressor particle and the DNA molecule, the most effectivefactor seems to be the Coulombrepulsive forces and or Londondispersion forces. The sliding mechanism for facilitated translocation of a repressor protein ona DNA chain can be described by the present mathematical approach which describes the temporal changes in amounts of the species. To achieve such mechanism in varying ionic strength,the secondary changes in the diffusion constants, the reaction radius and the reaction rate per one particle on thereaction sphere surface k value (anelectro chemical factor) seemed to have important roles.

Mechanisms by which transcription factors gain access to target sequence elements in chromatin

Transcription factors (TF) bind DNA sequence motifs, but the presence of a consensus DNA element is not sufficient to direct TF binding to chromatin. Recent genomic data have revealed that accessibility, as measured by DNase sensitivity and the presence of active histone marks, is necessary for TF binding. DNA sequence provides the initial specification of the accessibility of DNA elements within chromatin that permits TF binding. In yeast, it is known that poly(dA-dT) tracts directly encode low-nucleosome occupancy at promoters. Recent evidence suggests that CpG islands in mammals are inherently refractory to higher-order chromatin structure and remain accessible, despite favoring nucleosome formation in vitro. Taken together, these studies support a model for how accessibility originates and then propagates throughout regulatory cascades and development.

DNA regions bound at low occupancy by transcription factors do not drive patterned reporter gene expression in Drosophila

In animals, each sequence-specific transcription factor typically binds to thousands of genomic regions in vivo. Our previous studies of 20 transcription factors show that most genomic regions bound at high levels in Drosophila blastoderm embryos are known or probable functional targets, but genomic regions occupied only at low levels have characteristics suggesting that most are not involved in the cis-regulation of transcription. Here we use transgenic reporter gene assays to directly test the transcriptional activity of 104 genomic regions bound at different levels by the 20 transcription factors. Fifteen genomic regions were selected based solely on the DNA occupancy level of the transcription factor Kruppel. Five of the six most highly bound regions drive blastoderm patterns of reporter transcription. In contrast, only one of the nine lowly bound regions drives transcription at this stage and four of them are not detectably active at any stage of embryogenesis. A larger set of 89 genomic regions chosen using criteria designed to identify functional cis-regulatory regions supports the same trend: genomic regions occupied at high levels by transcription factors in vivo drive patterned gene expression, whereas those occupied only at lower levels mostly do not. These results support studies that indicate that the high cellular concentrations of sequence-specific transcription factors drive extensive, low-occupancy, nonfunctional interactions within the accessible portions of the genome.

Influence of decoys on the noise and dynamics of gene expression

Many transcription factors bind to DNA with a remarkable lack of specificity, so that regulatory binding sites compete with an enormous number of nonregulatory "decoy" sites. For an autoregulated gene, we show decoy sites decrease noise in the number of unbound proteins to a Poisson limit that results from binding and unbinding. This noise buffering is optimized for a given protein concentration when decoys have a 1/2 probability of being occupied. Decoys linearly increase the time to approach steady state and exponentially increase the time to switch epigenetically between bistable states.

Operator sequence alters gene expression independently of transcription factor occupancy in bacteria

A canonical quantitative view of transcriptional regulation holds that the only role of operator sequence is to set the probability of transcription factor binding, with operator occupancy determining the level of gene expression. In this work, we test this idea by characterizing repression in vivo and the binding of RNA polymerase in vitro in experiments where operators of various sequences were placed either upstream or downstream from the promoter in Escherichia coli. Surprisingly, we find that operators with a weaker binding affinity can yield higher repression levels than stronger operators. Repressor bound to upstream operators modulates promoter escape, and the magnitude of this modulation is not correlated with the repressor-operator binding affinity. This suggests that operator sequences may modulate transcription by altering the nature of the interaction of the bound transcription factor with the transcriptional machinery, implying a new layer of sequence dependence that must be confronted in the quantitative understanding of gene expression.

Accurate prediction of inducible transcription factor binding intensities in vivo

DNA sequence and local chromatin landscape act jointly to determine transcription factor (TF) binding intensity profiles. To disentangle these influences, we developed an experimental approach, called protein/DNA binding followed by high-throughput sequencing (PB-seq), that allows the binding energy landscape to be characterized genome-wide in the absence of chromatin. We applied our methods to the Drosophila Heat Shock Factor (HSF), which inducibly binds a target DNA sequence element (HSE) following heat shock stress. PB-seq involves incubating sheared naked genomic DNA with recombinant HSF, partitioning the HSF-bound and HSF-free DNA, and then detecting HSF-bound DNA by high-throughput sequencing. We compared PB-seq binding profiles with ones observed in vivo by ChIP-seq and developed statistical models to predict the observed departures from idealized binding patterns based on covariates describing the local chromatin environment. We found that DNase I hypersensitivity and tetra-acetylation of H4 were the most influential covariates in predicting changes in HSF binding affinity. We also investigated the extent to which DNA accessibility, as measured by digital DNase I footprinting data, could be predicted from MNase-seq data and the ChIP-chip profiles for many histone modifications and TFs, and found GAGA element associated factor (GAF), tetra-acetylation of H4, and H4K16 acetylation to be the most predictive covariates. Lastly, we generated an unbiased model of HSF binding sequences, which revealed distinct biophysical properties of the HSF/HSE interaction and a previously unrecognized substructure within the HSE. These findings provide new insights into the interplay between the genomic sequence and the chromatin landscape in determining transcription factor binding intensity.

Comprehensive genome-wide protein-DNA interactions detected at single-nucleotide resolution

Chromatin immunoprecipitation (ChIP-chip and ChIP-seq) assays identify where proteins bind throughout a genome. However, DNA contamination and DNA fragmentation heterogeneity produce false positives (erroneous calls) and imprecision in mapping. Consequently, stringent data filtering produces false negatives (missed calls). Here we describe ChIP-exo, where an exonuclease trims ChIP DNA to a precise distance from the crosslinking site. Bound locations are detectable as peak pairs by deep sequencing. Contaminating DNA is degraded or fails to form complementary peak pairs. With the single bp accuracy provided by ChIP-exo, we show an unprecedented view into genome-wide binding of the yeast transcription factors Reb1, Gal4, Phd1, Rap1, and human CTCF. Each of these factors was chosen to address potential limitations of ChIP-exo. We found that binding sites become unambiguous and reveal diverse tendencies governing in vivo DNA-binding specificity that include sequence variants, functionally distinct motifs, motif clustering, secondary interactions, and combinatorial modules within a compound motif.

Genome-wide mapping of transcription factor binding reveals developmental process integration and a fresh look at evolutionary dynamics

How does evolution forge adaptive responses? Are many changes required or few? Just how complex are the transcriptional networks that control development? Diverse questions like these are being newly addressed by next-generation sequencing-based techniques. Facilitating a mechanistic understanding, these approaches reveal the direct in vivo interactions between transcription factors and their physical targets, combined with genome-scale readouts to comprehensively map adaptive gene regulatory networks (GRNs). Here I focus on pioneering work from the last 3 years that has leveraged these data to investigate diverse aspects of GRN circuitry controlling the reproductive transition in plants. These approaches have revealed surprising new functions for long-investigated key players in developmental programs and laid bare the basis for pleiotropy in many others, suggesting widespread process integration at the transcriptional level. Evolutionary questions begged by the recent deluge of GRN mapping data are being assessed anew, both by emerging work outside Arabidopsis thaliana and novel analyses within. These studies have swiftly exposed the distinctive power and adaptability of genome-wide GRN mapping and illustrate that this unique data type holds tremendous promise for plant biology.

Classes of fast and specific search mechanisms for proteins on DNA

Problems of search and recognition appear over different scales in biological systems. In this review we focus on the challenges posed by interactions between proteins, in particular transcription factors, and DNA and possible mechanisms which allow for fast and selective target location. Initially we argue that DNA-binding proteins can be classified, broadly, into three distinct classes which we illustrate using experimental data. Each class calls for a different search process and we discuss the possible application of different search mechanisms proposed over the years to each class. The main thrust of this review is a new mechanism which is based on barrier discrimination. We introduce the model and analyze in detail its consequences. It is shown that this mechanism applies to all classes of transcription factors and can lead to a fast and specific search. Moreover, it is shown that the mechanism has interesting transient features which allow for stability at the target despite rapid binding and unbinding of the transcription factor from the target.

GENOME WIDE IDENTIFICATION OF DNA BINDING MOTIFS OF NodD-FACTOR IN SINORHIZOBIUM MELILOTI AND MESORHIZOBIUM LOTI

NodD transcription factor is a regulatory protein of nitrogen fixing bacteria, which activates expression of nod genes participating in nodulation during interaction with its symbiont legumes. It's DNA binding motifs have been characterized and reported in Sinorhizobium meliloti and this pattern information has been used in our theoretical analyses to detect its novel regulated genes in genomes of S. meliloti and Mesorhizobium loti. M. loti, a symbiont to model legume plant Lotus japonicus, showed presence of these regulatory motifs in upstream sequences of nod and other functionally related genes. The methodology involved comparative potential weight matrix construction through GIBBS SAMPLER (RSAT) and MEME tools, using information of conserved upstream sequences of nine genes including nod and neighboring genes of both genomes possessing nod-box like motif. The resultant DNA consensus sequence had highly conserved nod-box like 17 bp long motif consensus sequence pattern for binding of detected NodD transcription factors as analyzed by homologous clustering method and therefore the genome wide predictions were considered highly accurate since confirmed by operon delineation method and the described methodology can be used in other nitrogen fixing bacteria to pursue the study in detail.

The nuclear pore complex mediates binding of the Mig1 repressor to target promoters

All eukaryotic cells alter their transcriptional program in response to the sugar glucose. In Saccharomyces cerevisiae, the best-studied downstream effector of this response is the glucose-regulated repressor Mig1. We show here that nuclear pore complexes also contribute to glucose-regulated gene expression. NPCs participate in glucose-responsive repression by physically interacting with Mig1 and mediating its function independently of nucleocytoplasmic transport. Surprisingly, despite its abundant presence in the nucleus of glucose-grown nup120Δ or nup133Δ cells, Mig1 has lost its ability to interact with target promoters. The glucose repression defect in the absence of these nuclear pore components therefore appears to result from the failure of Mig1 to access its consensus recognition sites in genomic DNA. We propose that the NPC contributes to both repression and activation at the level of transcription.

In vivo tests of thermodynamic models of transcription repressor function

One emphasis of the Gibbs Conference on Biothermodynamics is the value of thermodynamic measurements for understanding behaviors of biological systems. In this study, the correlation between thermodynamic measurements of in vitro DNA binding affinity with in vivo transcription repression was investigated for two transcription repressors. In the first system, which comprised an engineered LacI/GalR homolog, mutational changes altered the equilibrium constant for binding DNA. Changes correlated with altered repression, but estimates of in vivo repressor concentration suggest a ≥25-fold discrepancy with in vitro conditions. In the second system, changes in ligand binding to BirA altered dimerization and subsequent DNA occupancy. Again, these changes correlate with altered in vivo repression, but comparison with in vitro measurements reveals a ~10-fold discrepancy. Further analysis of each system suggests that the observed discrepancies between in vitro and in vivo results reflect the contributions of additional equilibria to the transcription repression process.

The cell in an era of systems biology

The increasing use of high-throughput technologies and computational modeling is revealing new levels of biological function and organization. How are these features of systems biology influencing our view of the cell?

DNA binding restricts the intrinsic conformational flexibility of methyl CpG binding protein 2 (MeCP2)

Mass spectrometry-based hydrogen/deuterium exchange (H/DX) has been used to define the polypeptide backbone dynamics of full-length methyl CpG binding protein 2 (MeCP2) when free in solution and when bound to unmethylated and methylated DNA. Essentially the entire MeCP2 polypeptide chain underwent H/DX at rates faster than could be measured (i.e. complete exchange in ≤10 s), with the exception of the methyl DNA binding domain (MBD). Even the H/DX of the MBD was rapid compared with that of a typical globular protein. Thus, there is no single tertiary structure of MeCP2. Rather, the full-length protein rapidly samples many different conformations when free in solution. When MeCP2 binds to unmethylated DNA, H/DX is slowed several orders of magnitude throughout the MBD. Binding of MeCP2 to methylated DNA led to additional minor H/DX protection, and only locally within the N-terminal portion of the MBD. H/DX also was used to examine the structural dynamics of the isolated MBD carrying three frequent mutations associated with Rett syndrome. The effects of the mutations ranged from very little (R106W) to a substantial increase in conformational sampling (F155S). Our H/DX results have yielded fine resolution mapping of the structure of full-length MeCP2 in the absence and presence of DNA, provided a biochemical basis for understanding MeCP2 function in normal cells, and predicted potential approaches for the treatment of a subset of RTT cases caused by point mutations that destabilize the MBD.

Comparing binding site information to binding affinity reveals that Crp/DNA complexes have several distinct binding conformers

We show that the cAMP receptor protein (Crp) binds to DNA as several different conformers. This situation has precluded discovering a high correlation between any sequence property and binding affinity for proteins that bend DNA. Experimentally quantified affinities of Synechocystis sp. PCC 6803 cAMP receptor protein (SyCrp1), the Escherichia coli Crp (EcCrp, also CAP) and DNA were analyzed to mathematically describe, and make human-readable, the relationship of DNA sequence and binding affinity in a given system. Here, sequence logos and weight matrices were built to model SyCrp1 binding sequences. Comparing the weight matrix model to binding affinity revealed several distinct binding conformations. These Crp/DNA conformations were asymmetrical (non-palindromic).

The role of chromatin accessibility in directing the widespread, overlapping patterns of Drosophila transcription factor binding

Background

In Drosophila embryos, many biochemically and functionally unrelated transcription factors bind quantitatively to highly overlapping sets of genomic regions, with much of the lowest levels of binding being incidental, non-functional interactions on DNA. The primary biochemical mechanisms that drive these genome-wide occupancy patterns have yet to be established.

Results

Here we use data resulting from the DNaseI digestion of isolated embryo nuclei to provide a biophysical measure of the degree to which proteins can access different regions of the genome. We show that the in vivo binding patterns of 21 developmental regulators are quantitatively correlated with DNA accessibility in chromatin. Furthermore, we find that levels of factor occupancy in vivo correlate much more with the degree of chromatin accessibility than with occupancy predicted from in vitro affinity measurements using purified protein and naked DNA. Within accessible regions, however, the intrinsic affinity of the factor for DNA does play a role in determining net occupancy, with even weak affinity recognition sites contributing. Finally, we show that programmed changes in chromatin accessibility between different developmental stages correlate with quantitative alterations in factor binding.

Conclusions

Based on these and other results, we propose a general mechanism to explain the widespread, overlapping DNA binding by animal transcription factors. In this view, transcription factors are expressed at sufficiently high concentrations in cells such that they can occupy their recognition sequences in highly accessible chromatin without the aid of physical cooperative interactions with other proteins, leading to highly overlapping, graded binding of unrelated factors.

Genome-wide transcription factor binding: beyond direct target regulation

The binding of transcription factors to specific DNA target sequences is the fundamental basis of gene regulatory networks. Chromatin immunoprecipitation combined with DNA tiling arrays or high-throughput sequencing (ChIP-chip and ChIP-seq, respectively) has been used in many recent studies that detail the binding sites of various transcription factors. Surprisingly, data from a variety of model organisms and tissues have demonstrated that transcription factors vary greatly in their number of genomic binding sites, and that binding events can significantly exceed the number of known or possible direct gene targets. Thus, current understanding of transcription factor function must expand to encompass what role, if any, binding might have outside of direct transcriptional target regulation. In this review, we discuss the biological significance of genome-wide binding of transcription factors and present models that can account for this phenomenon.

Quantitative models of the mechanisms that control genome-wide patterns of transcription factor binding during early Drosophila development

Transcription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ∼0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6-0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription factor binding may be used to predict the binding landscape of any animal transcription factor with significant precision.

Diffusion-based DNA target colocalization by thermodynamic mechanisms

In eukaryotic cell nuclei, a variety of DNA interactions with nuclear elements occur, which, in combination with intra- and inter-chromosomal cross-talks, shape a functional 3D architecture. In some cases they are organized by active, i.e. actin/myosin, motors. More often, however, they have been related to passive diffusion mechanisms. Yet, the crucial questions on how DNA loci recognize their target and are reliably shuttled to their destination by Brownian diffusion are still open. Here, we complement the current experimental scenario by considering a physics model, in which the interaction between distant loci is mediated by diffusing bridging molecules. We show that, in such a system, the mechanism underlying target recognition and colocalization is a thermodynamic switch-like process (a phase transition) that only occurs if the concentration and affinity of binding molecules is above a threshold, or else stable contacts are not possible. We also briefly discuss the kinetics of this `passive-shuttling' process, as produced by random diffusion of DNA loci and their binders, and derive predictions based on the effects of genomic modifications and deletions.

Transcription factor binding variation in the evolution of gene regulation

Transcription factor interactions with DNA are one of the primary mechanisms by which expression is modulated, yet their evolution remains poorly understood. Chromatin immunoprecipitation followed by microarray (ChIP-chip) or sequencing (ChIP-Seq) has revolutionized the study of protein-DNA interactions. However, only recently has attention focused on determining to what extent these regulatory interactions vary between species across entire genomes. A series of recent studies have compared in vivo binding data across a range of evolutionary distances. Binding events diverge rapidly, indicating gene regulation is an evolutionarily flexible process.

Quantitative analysis of the Drosophila segmentation regulatory network using pattern generating potentials

A new computational method uses gene expression databases and transcription factor binding specificities to describe regulatory elements in the Drosophila A/P patterning network in unprecedented detail.

Cis-regulatory modules that drive precise spatial-temporal patterns of gene expression are central to the process of metazoan development. We describe a new computational strategy to annotate genomic sequences based on their “pattern generating potential” and to produce quantitative descriptions of transcriptional regulatory networks at the level of individual protein-module interactions. We use this approach to convert the qualitative understanding of interactions that regulate Drosophila segmentation into a network model in which a confidence value is associated with each transcription factor-module interaction. Sequence information from multiple Drosophila species is integrated with transcription factor binding specificities to determine conserved binding site frequencies across the genome. These binding site profiles are combined with transcription factor expression information to create a model to predict module activity patterns. This model is used to scan genomic sequences for the potential to generate all or part of the expression pattern of a nearby gene, obtained from available gene expression databases. Interactions between individual transcription factors and modules are inferred by a statistical method to quantify a factor's contribution to the module's pattern generating potential. We use these pattern generating potentials to systematically describe the location and function of known and novel cis-regulatory modules in the segmentation network, identifying many examples of modules predicted to have overlapping expression activities. Surprisingly, conserved transcription factor binding site frequencies were as effective as experimental measurements of occupancy in predicting module expression patterns or factor-module interactions. Thus, unlike previous module prediction methods, this method predicts not only the location of modules but also their spatial activity pattern and the factors that directly determine this pattern. As databases of transcription factor specificities and in vivo gene expression patterns grow, analysis of pattern generating potentials provides a general method to decode transcriptional regulatory sequences and networks.

The developmental program specifying segmentation along the anterior-posterior axis of the Drosophila embryo is one of the best studied examples of transcriptional regulatory networks. Previous work has identified the location and function of dozens of DNA segments called cis-regulatory “modules” that regulate several genes in precise spatial patterns in the early embryo. In many cases, transcription factors that interact with such modules have also been identified. We present a novel computational framework that turns a qualitative and fragmented understanding of modules and factor-module interactions into a quantitative, systems-level view. The formalism utilizes experimentally characterized binding specificities of transcription factors and gene expression patterns to describe how multiple transcription factors (working as activators or repressors) act together in a module to determine its regulatory activity. This formalism can explain the expression patterns of known modules, infer factor-module interactions and quantify the potential of an arbitrary DNA segment to drive a gene's expression. We have also employed databases of gene expression patterns to find novel modules of the regulatory network. As databases of binding motifs and gene expression patterns grow, this new approach provides a general method to decode transcriptional regulatory sequences and networks.

MyoD, a lesson in widespread DNA binding

There is growing recognition that animal transcription factors bind in vivo to far more genomic regions than generally assumed earlier. In this issue of Developmental Cell, Cao et al. show that the muscle specification factor MyoD binds to regions near most genes and modifies chromatin states at these sites.