Allostery through DNA drives phenotype switching

Quantification and potential functional relevance of binding cooperativity of adjacent transcription factors on DNA

In eukaryotes, the expression of specific genes is regulated by a combination of transcription factors (TFs) bound on regulatory regions of the genomic DNA (promoters and enhancers). Recent advances in genomic sequencing technology have enabled the measurements of TFs' footprints and binding affinities on DNA at the single-molecule level, facilitating the probing of binding cooperativity among adjacent TFs. This necessitates quantitative descriptions of TFs' binding cooperativity and understanding of its potential functional relevance. In this study, we show that the binding cooperativities between two adjacent TFs can be quantified by the [Formula: see text] coefficient, which can be experimentally determined. Under thermodynamic equilibrium, the binding affinities of two TFs can either increase together (positive cooperativity) or decrease together (negative cooperativity), but not in opposing directions (one increases while the other decreases). Within the framework of thermodynamics, we investigate the functional relevance of cooperativity. The functional relevance of positive cooperativity, which has been extensively discussed in the literature, is the sigmoidal binding curve around a TF concentration threshold (analogous to oxygen binding to hemoglobin), whereas the functional relevance of negative cooperativity is twofold. First, mutual exclusion of the two TFs enables bidirectional gene switching, akin to the CI-Cro system in phage [Formula: see text]. Second, while TFs often exhibit intranuclear concentration fluctuations, negative binding cooperativity assures fast TF dissociation from DNA and hence rapid response for gene expression regulation. Furthermore, the nonequilibrium steady states of living cells can lead to either positive or negative cooperativity, which can also be quantified by the [Formula: see text] coefficient.

Deciphering Allosteric Modulation of Cancer-Associated Histone Missense Mutations

Histone mutations have been implicated in various cancers, but their mechanistic effects on chromatin dynamics remain largely unexplored. In this study, we investigated allosteric modulation effects induced by 40 cancer-associated histone missense mutations. By combining computational approaches with experimental evidence, we assessed the allosteric and functional impact of these mutations. Our results reveal that the allosteric effects of histone mutations are position-specific, with mutations near the H3 and H4 histone N-terminal tails exhibiting the strongest long-range perturbations. Notably, we predicted seven mutations with significant allosteric effects, potentially altering nucleosome interactions. Experimental verification of H2BS64Y and H2BS64F mutations demonstrated that they disrupted normal histone function, altered H2BK120 ubiquitination levels and genome stability, findings suggestive of their potential carcinogenic effects. Collectively, these results show that allostery may serve as a critical mechanism underlying the oncogenic potential of some histone mutations, highlighting the need for further exploration of allosteric pathways in cancer epigenetics.

Thermodynamic principles link in vitro transcription factor affinities to single-molecule chromatin states in cells

The molecular details governing transcription factor (TF) binding and the formation of accessible chromatin are not yet quantitatively understood - including how sequence context modulates affinity, how TFs search DNA, the kinetics of TF occupancy, and how motif grammars coordinate binding. To resolve these questions for a human TF, erythroid Krüppel-like factor (eKLF/KLF1), we quantitatively compare, in high throughput, in vitro TF binding rates and affinities with in vivo single molecule TF and nucleosome occupancies across engineered DNA sequences. We find that 40-fold flanking sequence effects on affinity are consistent with distal flanks tuning TF search parameters and captured by a linear energy model. Motif recognition probability, rather than time in the bound state, drives affinity changes, and in vitro and in nuclei measurements exhibit consistent, minutes-long TF residence times. Finally, pairing in vitro biophysical parameters with thermodynamic models accurately predicts in vivo single-molecule chromatin states for unseen motif grammars.

Profiling signaling mediators for cell-cell interactions and communications with microfluidics-based single-cell analysis tools

Cell-cell interactions and communication represent the fundamental cornerstone of cells' collaborative efforts in executing diverse biological processes. A profound understanding of how cells interface through various mediators is pivotal across a spectrum of biological systems. Recent strides in microfluidic technologies have significantly bolstered the precision and prowess in capturing and manipulating cells with exceptional spatial and temporal resolution. These advanced methodologies converge with multi-signal mediator detection systems, furnishing potent, high-throughput platforms for dissecting cell-cell interactions at the single-cell level. This approach empowers researchers to delve into intricate cellular dynamics with unprecedented accuracy and efficiency. Here, we present a critical evaluation of the latest advancements in microfluidics-driven techniques for detecting signal mediators involved in cell-cell interactions and communication at the single-cell level. We underscore notable biological applications that have benefited from these technologies and identify pressing challenges that must be addressed in future endeavors leveraging microfluidic tools for single-cell interaction studies.

Dynamic Features Driven by Stochastic Collisions in a Nanopore for Precise Single-Molecule Identification

Nanopore technology holds great potential for single-molecule identification. However, extracting meaningful features from ionic current signals and understanding the molecular mechanisms underlying the specific features remain unresolved. In this study, we uncovered a distinctive ionic current pattern in a K238Q aerolysin nanopore, characterized by transient spikes superimposed on two stable transition states. By employing a neural network model, we demonstrated that these previously overlooked dynamic spike features exhibit superior discriminative power, improving the accuracy from 44% to 93%. We identified that the stable transition states result from simultaneous interactions of ssDNA with the two sensitive sites of the nanopore. The proposed stochastic collision model offers a mechanistic framework for interpreting the generation of the dynamic spike features. This model indicates that the continuous transitions facilitate iterative, comprehensive snapshots of molecular interactions by nanopores. Our findings introduce a new approach for optimizing nanopore technology to capture complex dynamic features and substantially improve the accuracy of single-molecule identification.

Stacking correlation length in single-stranded DNA

Base stacking is crucial in nucleic acid stabilization, from DNA duplex hybridization to single-stranded DNA (ssDNA) protein binding. While stacking energies are tiny in ssDNA, they are inextricably mixed with hydrogen bonding in DNA base pairing, making their measurement challenging. We conduct unzipping experiments with optical tweezers of short poly-purine (dA and alternating dG and dA) sequences of 20-40 bases. We introduce a helix-coil model of the stacking-unstacking transition that includes finite length effects and reproduces the force-extension curves. Fitting the model to the experimental data, we derive the stacking energy per base, finding the salt-independent value $\Delta G_0^{ST}=0.14(3)$ kcal/mol for poly-dA and $\Delta G_0^{ST}=0.07(3)$ kcal/mol for poly-dGdA. Stacking in these polymeric sequences is predominantly cooperative with a correlation length of ∼4 bases at zero force . The correlation length reaches a maximum of ∼10 and 5 bases at the stacking-unstacking transition force of ∼10 and 20 pN for poly-dA and poly-dGdA, respectively. The salt dependencies of the cooperativity parameter in ssDNA and the energy of DNA hybridization are in agreement, suggesting that double-helix stability is primarily due to stacking. Analysis of poly-rA and poly-rC RNA sequences shows a larger stacking stability but a lower stacking correlation length of ∼2 bases.

An efficient EPR spin-labeling method enables insights into conformational changes in DNA

Electron paramagnetic resonance (EPR) is a powerful tool for elucidating both static and dynamic conformational alterations in macromolecules. However, to effectively utilize EPR for such investigations, the presence of paramagnetic centers, known as spin labels, is required. The process of spin labeling, particularly for nucleotides, typically demands intricate organic synthesis techniques. In this study, we introduce a unique addition-elimination reaction method with a simple spin-labeling process, facilitating the monitoring of structural changes within nucleotide sequences. Our investigation focuses on three distinct labeling positions with a DNA sequence, allowing the measurement of distance between two spin labels. The experimental mean distances obtained agreed with the calculated distances, underscoring the efficacy of this straightforward spin-labeling approach in studying complex biological processes such as transcription mechanism using EPR measurements.

Role of Shape Deformation of DNA-Binding Sites in Regulating the Efficiency and Specificity in Their Recognition by DNA-Binding Proteins

Accurate transcription of genetic information is crucial, involving precise recognition of the binding motifs by DNA-binding proteins. While some proteins rely on short-range hydrophobic and hydrogen bonding interactions at binding sites, others employ a DNA shape readout mechanism for specific recognition. In this mechanism, variations in DNA shape at the binding motif resulted from either inherent flexibility or binding of proteins at adjacent sites are sensed and capitalized by the searching proteins to locate them specifically. Through extensive computer simulations, we investigate both scenarios to uncover the underlying mechanism and origin of specificity in the DNA shape readout mechanism. Our findings reveal that deformation in shape at the binding motif creates an entropy funnel, allowing information about altered shapes to manifest as fluctuations in minor groove widths. This signal enhances the efficiency of nonspecific search of nearby proteins by directing their movement toward the binding site, primarily driven by a gain in entropy. We propose this as a generic mechanism for DNA shape readout, where specificity arises from the alignment between the molecular frustration of the searching protein and the ruggedness of the entropic funnel governed by molecular features of the protein and arrangement of the DNA bases at the binding site, respectively.

Skipping events impose repeated binding attempts: profound kinetic implications of protein-DNA conformational changes

The kinetics of protein-DNA recognition, along with its thermodynamic properties, including affinity and specificity, play a central role in shaping biological function. Protein-DNA recognition kinetics are characterized by two key elements: the time taken to locate the target site amid various nonspecific alternatives; and the kinetics involved in the recognition process, which may necessitate overcoming an energetic barrier. In this study, we developed a coarse-grained (CG) model to investigate interactions between a transcription factor called the sex-determining region Y (SRY) protein and DNA, in order to probe how DNA conformational changes affect SRY-DNA recognition and binding kinetics. We find that, not only does a requirement for such a conformational DNA transition correspond to a higher energetic barrier for binding and therefore slower kinetics, it may further impede the recognition kinetics by increasing unsuccessful binding events (skipping events) where the protein partially binds its DNA target site but fails to form the specific protein-DNA complex. Such skipping events impose the need for additional cycles protein search of nonspecific DNA sites, thus significantly extending the overall recognition time. Our results highlight a trade-off between the speed with which the protein scans nonspecific DNA and the rate at which the protein recognizes its specific target site. Finally, we examine molecular approaches potentially adopted by natural systems to enhance protein-DNA recognition despite its intrinsically slow kinetics.

Recovering true FRET efficiencies from smFRET investigations requires triplet state mitigation

Single-molecule fluorescence resonance energy transfer (smFRET) methods employed to quantify time-dependent compositional and conformational changes within biomolecules require elevated illumination intensities to recover robust photon emission streams from individual fluorophores. Here we show that outside the weak-excitation limit, and in regimes where fluorophores must undergo many rapid cycles of excitation and relaxation, non-fluorescing, excitation-induced triplet states with lifetimes orders of magnitude longer lived than photon-emitting singlet states degrade photon emission streams from both donor and acceptor fluorophores resulting in illumination-intensity-dependent changes in FRET efficiency. These changes are not commonly taken into consideration; therefore, robust strategies to suppress excited state accumulations are required to recover accurate and precise FRET efficiency, and thus distance, estimates. We propose both robust triplet state suppression and data correction strategies that enable the recovery of FRET efficiencies more closely approximating true values, thereby extending the spatial and temporal resolution of smFRET.

Insights into elastic properties of coarse-grained DNA models: q-stiffness of cgDNA vs cgDNA

Coarse-grained models have emerged as valuable tools to simulate long DNA molecules while maintaining computational efficiency. These models aim at preserving interactions among coarse-grained variables in a manner that mirrors the underlying atomistic description. We explore here a method for testing coarse-grained vs all-atom models using stiffness matrices in Fourier space (q-stiffnesses), which are particularly suited to probe DNA elasticity at different length scales. We focus on a class of coarse-grained rigid base DNA models known as cgDNA and its most recent version, cgDNA+. Our analysis shows that while cgDNA+ closely follows the q-stiffnesses of the all-atom model, the original cgDNA shows some deviations for twist and bending variables, which are rather strong in the q → 0 (long length scale) limit. The consequence is that while both cgDNA and cgDNA+ give a suitable description of local elastic behavior, the former misses some effects that manifest themselves at longer length scales. In particular, cgDNA performs poorly on twist stiffness, with a value much lower than expected for long DNA molecules. Conversely, the all-atom and cgDNA+ twist are strongly length scale dependent: DNA is torsionally soft at a few base pair distances but becomes more rigid at distances of a few dozen base pairs. Our analysis shows that the bending persistence length in all-atom and cgDNA+ is somewhat overestimated.

Mechanism of RGD-conjugated nanodevice binding to its target protein integrin αVβ3 by atomistic molecular dynamics and machine learning

Active targeting strategies have been proposed to enhance the selective uptake of nanoparticles (NPs) by diseased cells, and recent experimental findings have proven the effectiveness of this approach. However, no mechanistic studies have yet revealed the atomistic details of the interactions between ligand-activated NPs and integrins. As a case study, here we investigate, by means of advanced molecular dynamics simulations (MD) and machine learning methods (namely equilibrium MD, binding free energy calculations and training of self-organized maps), the interaction of a cyclic-RGD-conjugated PEGylated TiO2 NP (the nanodevice) with the extracellular segment of integrin αVβ3 (the target), the latter experimentally well-known to be over-expressed in several solid tumors. Firstly, we proved that the cyclic-RGD ligand binding to the integrin pocket is established and kept stable even in the presence of the cumbersome realistic model of the nanodevice. In this respect, the unsupervised machine learning analysis allowed a detailed comparison of the ligand/integrin binding in the presence and in the absence of the nanodevice, which unveiled differences in the chemical features. Then, we discovered that unbound cyclic RGDs conjugated to the NP largely contribute to the interactions between the nanodevice and the integrin. Finally, by increasing the density of cyclic RGDs on the PEGylated TiO2 NP, we observed a proportional enhancement of the nanodevice/target binding. All these findings can be exploited to achieve an improved targeting selectivity and cellular uptake, and thus a more successful clinical outcome.

Electrostatics and hydrophobicity in the dynamics of intrinsically disordered proteins

Internal friction is a major contribution to the dynamics of intrinsically disordered proteins (IDPs). Yet, the molecular origin of internal friction has so far been elusive. Here, we investigate whether attractive electrostatic interactions in IDPs modulate internal friction differently than the hydrophobic effect. To this end, we used nanosecond fluorescence correlation spectroscopy (nsFCS) and single-molecule Förster resonance energy transfer (FRET) to quantify the conformation and dynamics of the disordered DNA-binding domains Myc, Max and Mad at different salt concentrations. We find that internal friction effects are stronger when the chain is compacted by electrostatic attractions compared to the hydrophobic effect. Although the effect is moderate, the results show that the heteropolymeric nature of IDPs is reflected in their dynamics.

Mechanisms of DNA-Mediated Allostery

Proteins often regulate their activities via allostery-or action at a distance-in which the binding of a ligand at one binding site influences the affinity for another ligand at a distal site. Although less studied than in proteins, allosteric effects have been observed in experiments with DNA as well. In these experiments two or more proteins bind at distinct DNA sites and interact indirectly with each other, via a mechanism mediated by the linker DNA molecule. We develop a mechanical model of DNA/protein interactions which predicts three distinct mechanisms of allostery. Two of these involve an enthalpy-mediated allostery, while a third mechanism is entropy driven. We analyze experiments of DNA allostery and highlight the distinctive signatures allowing one to identify which of the proposed mechanisms best fits the data.

Distinguishing between concerted, sequential and barrierless conformational changes: Folding versus allostery

Characterization of transition and intermediate states of reactions provides insights into their mechanisms and is often achieved through analysis of linear free energy relationships. Such an approach has been used extensively in protein folding studies but less so for analyzing allosteric transitions. Here, we point out analogies in ways to characterize pathways and intermediates in folding and allosteric transitions. Achieving an understanding of the mechanisms by which proteins undergo allosteric switching is important in many cases for obtaining insights into how they function.

All over or overall - Do we understand allostery?

Allostery is probably the most important concept in the regulation of cellular processes. Models to explain allostery are plenty. Each sheds light on different aspects but their entirety conveys an ambiguous feeling of comprehension and disappointment. Here, I discuss the most popular allostery models, their roots, similarities, and limitations. All of them are thermodynamic models. Naturally this bears a certain degree of redundancy, which forms the center of this review. After sixty years, many questions remain unanswered, mainly because our human longing for causality as base for understanding is not satisfied by thermodynamics alone. A description of allostery in terms of pathways, i.e., as a temporal chain of events, has been-, and still is-, a missing piece of the puzzle.

A new twist on PIFE: photoisomerisation-related fluorescence enhancement

PIFE was first used as an acronym for protein-induced fluorescence enhancement, which refers to the increase in fluorescence observed upon the interaction of a fluorophore, such as a cyanine, with a protein. This fluorescence enhancement is due to changes in the rate ofcis/transphotoisomerisation. It is clear now that this mechanism is generally applicable to interactions with any biomolecule. In this review, we propose that PIFE is thereby renamed according to its fundamental working principle as photoisomerisation-related fluorescence enhancement, keeping the PIFE acronym intact. We discuss the photochemistry of cyanine fluorophores, the mechanism of PIFE, its advantages and limitations, and recent approaches to turning PIFE into a quantitative assay. We provide an overview of its current applications to different biomolecules and discuss potential future uses, including the study of protein-protein interactions, protein-ligand interactions and conformational changes in biomolecules.

Bacterial toxin-antitoxin systems: Novel insights on toxin activation across populations and experimental shortcomings

The alarming rise in hard-to-treat bacterial infections is of great concern to human health. Thus, the identification of molecular mechanisms that enable the survival and growth of pathogens is of utmost urgency for the development of more efficient antimicrobial therapies. In challenging environments, such as presence of antibiotics, or during host infection, metabolic adjustments are essential for microorganism survival and competitiveness. Toxin-antitoxin systems (TASs) consisting of a toxin with metabolic modulating activity and a cognate antitoxin that antagonizes that toxin are important elements in the arsenal of bacterial stress defense. However, the exact physiological function of TA systems is highly debatable and with the exception of stabilization of mobile genetic elements and phage inhibition, other proposed biological functions lack a broad consensus. This review aims at gaining new insights into the physiological effects of TASs in bacteria and exploring the experimental shortcomings that lead to discrepant results in TAS research. Distinct control mechanisms ensure that only subsets of cells within isogenic cultures transiently develop moderate levels of toxin activity. As a result, TASs cause phenotypic growth heterogeneity rather than cell stasis in the entire population. It is this feature that allows bacteria to thrive in diverse environments through the creation of subpopulations with different metabolic rates and stress tolerance programs.

Mechanical codes of chemical-scale specificity in DNA motifs

In gene transcription, certain sequences of double-stranded (ds)DNA play a vital role in nucleosome positioning and expression initiation. That dsDNA is deformed to various extents in these processes leads us to ask: Could the genomic DNA also have sequence specificity in its chemical-scale mechanical properties? We approach this question using statistical machine learning to determine the rigidity between DNA chemical moieties. What emerges for the polyA, polyG, TpA, and CpG sequences studied here is a unique trigram that contains the quantitative mechanical strengths between bases and along the backbone. In a way, such a sequence-dependent trigram could be viewed as a DNA mechanical code. Interestingly, we discover a compensatory competition between the axial base-stacking interaction and the transverse base-pairing interaction, and such a reciprocal relationship constitutes the most discriminating feature of the mechanical code. Our results also provide chemical-scale understanding for experimental observables. For example, the long polyA persistence length is shown to have strong base stacking while its complement (polyAc) exhibits high backbone rigidity. The mechanical code concept enables a direct reading of the physical interactions encoded in the sequence which, with further development, is expected to shed new light on DNA allostery and DNA-binding drugs.

The architecture of binding cooperativity between densely bound transcription factors

The binding of transcription factors (TFs) along genomes is restricted to a subset of sites containing their preferred motifs. TF-binding specificity is often attributed to the co-binding of interacting TFs; however, apart from specific examples, this model remains untested. Here, we define dependencies among budding yeast TFs that localize to overlapping promoters by profiling the genome-wide consequences of co-depleting multiple TFs. We describe unidirectional interactions, revealing Msn2 as a central factor allowing TF binding at its target promoters. By contrast, no case of mutual cooperation was observed. Particularly, Msn2 retained binding at its preferred promoters upon co-depletion of fourteen similarly bound TFs. Overall, the consequences of TF co-depletions were moderate, limited to a subset of promoters, and failed to explain the role of regions outside the DNA-binding domain in directing TF-binding preferences. Our results call for re-evaluating the role of cooperative interactions in directing TF-binding preferences.

Time-resolved burst variance analysis

Quantifying biomolecular dynamics has become a major task of single-molecule fluorescence spectroscopy methods. In single-molecule Förster resonance energy transfer (smFRET), kinetic information is extracted from the stream of photons emitted by attached donor and acceptor fluorophores. Here, we describe a time-resolved version of burst variance analysis that can quantify kinetic rates at microsecond to millisecond timescales in smFRET experiments of diffusing molecules. Bursts are partitioned into segments with a fixed number of photons. The FRET variance is computed from these segments and compared with the variance expected from shot noise. By systematically varying the segment size, dynamics at different timescales can be captured. We provide a theoretical framework to extract kinetic rates from the decay of the FRET variance with increasing segment size. Compared to other methods such as filtered fluorescence correlation spectroscopy, recurrence analysis of single particles, and two-dimensional lifetime correlation spectroscopy, fewer photons are needed to obtain reliable timescale estimates, which reduces the required measurement time.

Structural insights into the DNA recognition mechanism by the bacterial transcription factor PdxR

Specificity in protein-DNA recognition arises from the synergy of several factors that stem from the structural and chemical signatures encoded within the targeted DNA molecule. Here, we deciphered the nature of the interactions driving DNA recognition and binding by the bacterial transcription factor PdxR, a member of the MocR family responsible for the regulation of pyridoxal 5'-phosphate (PLP) biosynthesis. Single particle cryo-EM performed on the PLP-PdxR bound to its target DNA enabled the isolation of three conformers of the complex, which may be considered as snapshots of the binding process. Moreover, the resolution of an apo-PdxR crystallographic structure provided a detailed description of the transition of the effector domain to the holo-PdxR form triggered by the binding of the PLP effector molecule. Binding analyses of mutated DNA sequences using both wild type and PdxR variants revealed a central role of electrostatic interactions and of the intrinsic asymmetric bending of the DNA in allosterically guiding the holo-PdxR-DNA recognition process, from the first encounter through the fully bound state. Our results detail the structure and dynamics of the PdxR-DNA complex, clarifying the mechanism governing the DNA-binding mode of the holo-PdxR and the regulation features of the MocR family of transcription factors.

An intrinsically disordered transcription activation domain increases the DNA binding affinity and reduces the specificity of NFκB p50/RelA

Many transcription factors contain intrinsically disordered transcription activation domains (TADs), which mediate interactions with coactivators to activate transcription. Historically, DNA-binding domains and TADs have been considered as modular units, but recent studies have shown that TADs can influence DNA binding. Whether these results can be generalized to more TADs is not clear. Here, we biophysically characterized the NFκB p50/RelA heterodimer including the RelA TAD and investigated the TAD's influence on NFκB-DNA interactions. In solution, we show the RelA TAD is disordered but compact, with helical tendency in two regions that interact with coactivators. We determined that the presence of the TAD increased the stoichiometry of NFκB-DNA complexes containing promoter DNA sequences with tandem κB recognition motifs by promoting the binding of NFκB dimers in excess of the number of κB sites. In addition, we measured the binding affinity of p50/RelA for DNA containing tandem κB sites and single κB sites. While the presence of the TAD enhanced the binding affinity of p50/RelA for all κB sequences tested, it also increased the affinity for nonspecific DNA sequences by over 10-fold, leading to an overall decrease in specificity for κB DNA sequences. In contrast, previous studies have generally reported that TADs decrease DNA-binding affinity and increase sequence specificity. Our results reveal a novel function of the RelA TAD in promoting binding to nonconsensus DNA, which sheds light on previous observations of extensive nonconsensus DNA binding by NFκB in vivo in response to strong inflammatory signals.

FOXL2 and FOXA1 cooperatively assemble on the TP53 promoter in alternative dimer configurations

Although both the p53 and forkhead box (FOX) family proteins are key transcription factors associated with cancer progression, their direct relationship is unknown. Here, we found that FOX family proteins bind to the non-canonical homotypic cluster of the p53 promoter region (TP53). Analysis of crystal structures of FOX proteins (FOXL2 and FOXA1) bound to the p53 homotypic cluster indicated that they interact with a 2:1 stoichiometry accommodated by FOX-induced DNA allostery. In particular, FOX proteins exhibited distinct dimerization patterns in recognition of the same p53-DNA; dimer formation of FOXA1 involved protein-protein interaction, but FOXL2 did not. Biochemical and biological functional analyses confirmed the cooperative binding of FOX proteins to the TP53 promoter for the transcriptional activation of TP53. In addition, up-regulation of TP53 was necessary for FOX proteins to exhibit anti-proliferative activity in cancer cells. These analyses reveal the presence of a discrete characteristic within FOX family proteins in which FOX proteins regulate the transcription activity of the p53 tumor suppressor via cooperative binding to the TP53 promoter in alternative dimer configurations.

Binding of the transcription activator-like effector augments transcriptional regulation by another transcription factor

DNA transcription is regulated by a range of diverse mechanisms and primarily by transcription factors that recruit the RNA polymerase complex to the promoter region on the DNA. Protein binding to DNA at nearby or distant sites can synergistically affect this process in a variety of ways, but mainly through direct interactions between DNA-binding proteins. Here we show that a Transcription Activator-Like Effector (TALE), which lacks an activation domain, can enhance transcription in mammalian cells when it binds in the vicinity of and without direct interaction with several different dimeric or monomeric transcription factors. This effect was observed for several TALEs regardless of the recognition sequences and their DNA-bound orientation. TALEs can exert an effect over the distance of tens of nucleotides and it also potentiated KRAB-mediated repression. The augmentation of transcriptional regulation of another transcription factor is characteristic of TALEs, as it was not observed for dCas9/gRNA, zinc finger, or Gal4 DNA-binding domains. We propose that this mechanism involves an allosteric effect exerted on DNA structure or dynamics. This mechanism could be used to modulate transcription but may also play a role in the natural context of TALEs.

Quantifying the regulatory role of individual transcription factors in Escherichia coli

Gene regulation often results from the action of multiple transcription factors (TFs) acting at a promoter, obscuring the individual regulatory effect of each TF on RNA polymerase (RNAP). Here we measure the fundamental regulatory interactions of TFs in E. coli by designing synthetic target genes that isolate individual TFs' regulatory effects. Using a thermodynamic model, each TF's regulatory interactions are decoupled from TF occupancy and interpreted as acting through (de)stabilization of RNAP and (de)acceleration of transcription initiation. We find that the contribution of each mechanism depends on TF identity and binding location; regulation immediately downstream of the promoter is insensitive to TF identity, but the same TFs regulate by distinct mechanisms upstream of the promoter. These two mechanisms are uncoupled and can act coherently, to reinforce the observed regulatory role (activation/repression), or incoherently, wherein the TF regulates two distinct steps with opposing effects.

Folding dynamics of polymorphic G-quadruplex structures

G-quadruplexes (G4), found in numerous places within the human genome, are involved in essential processes of cell regulation. Chromosomal DNA G4s are involved for example, in replication and transcription as first steps of gene expression. Hence, they influence a plethora of downstream processes. G4s possess an intricate structure that differs from canonical B-form DNA. Identical DNA G4 sequences can adopt multiple long-lived conformations, a phenomenon known as G4 polymorphism. A detailed understanding of the molecular mechanisms that drive G4 folding is essential to understand their ambivalent regulatory roles. Disentangling the inherent dynamic and polymorphic nature of G4 structures thus is key to unravel their biological functions and make them amenable as molecular targets in novel therapeutic approaches. We here review recent experimental approaches to monitor G4 folding and discuss structural aspects for possible folding pathways. Substantial progress in the understanding of G4 folding within the recent years now allows drawing comprehensive models of the complex folding energy landscape of G4s that we herein evaluate based on computational and experimental evidence.