DNA dynamically directs its own transcription initiation

Localization of Potential Energy in Hydrogen Bonds of the ATXN2 Gene

It is known that a number of neurodegenerative diseases, also called diseases of waiting, are associated with the expansion of the polyQ tract in the first exon of the ATXN2 gene. In the expanded polyQ tract, the probability of occurrence of non-canonical configurations (hairpins, G-quadruplexes, etc.) is significantly higher than in the normal one. Obviously, for their formation, the occurrence of open states (OSs) is necessary. Calculations were made for these processes using the angular mechanical model of DNA. It has been established that the probability of the large OS zones genesis in a DNA segment depends not only on the "strength" of the nucleotide sequence but also on the factors determining the dynamics of DNA; localization of the energy in the DNA molecule and the potential energy of interaction between pairs of nitrogenous bases also depend on environmental parameters. The potential energy of hydrogen bonds does not remain constant, and oscillatory movements lead to its redistribution and localization. In this case, OSs effectively dissipate the energy of oscillations. Thus, mathematical modeling makes it possible to calculate the localization of mechanical energy, which is necessary for the OSs formation, and to predict the places of their origin, taking into account the mechanical oscillations of the DNA molecule.

Efficient High-Throughput DNA Breathing Features Generation Using Jax-EPBD

DNA breathing dynamics-transient base-pair opening and closing due to thermal fluctuations-are vital for processes like transcription, replication, and repair. Traditional models, such as the Extended Peyrard-Bishop-Dauxois (EPBD), provide insights into these dynamics but are computationally limited for long sequences. We present JAX-EPBD, a high-throughput Langevin molecular dynamics framework leveraging JAX for GPU-accelerated simulations, achieving up to 30x speedup and superior scalability compared to the original C-based EPBD implementation. JAX-EPBD efficiently captures time-dependent behaviors, including bubble lifetimes and base flipping kinetics, enabling genome-scale analyses. Applying it to transcription factor (TF) binding affinity prediction using SELEX datasets, we observed consistent improvements inR 2 values when incorporating breathing features with sequence data. Validating on the 77-bp AAV P5 promoter, JAX-EPBD revealed sequence-specific differences in bubble dynamics correlating with transcriptional activity. These findings establish JAX-EPBD as a powerful and scalable tool for understanding DNA breathing dynamics and their role in gene regulation and transcription factor binding.

Ratio of AT and GC Pairs in the Zones of Open States Genesis in DNA Molecules

BACKGROUND

There is an assumption about the presence of a specific nucleotides sequence in DNA molecule, which contributes to the genesis of open states (OS). In addition, it would be logical to assume that OS zones should form in DNA regions with a large proportion of Adenine-Thymine (AT) pairs, since they contain fewer hydrogen bonds than Guanine- Cytosine (GC) base pairs. However, studies have shown that in areas rich in AT pairs, the probability of open states will not always be higher.

METHODS

In this work, for two genes containing different numbers of regions with a large AT pairs proportion, we calculated the ratio of AT and GC pairs in the OS zones. For calculations, we used a coarse-grained angular mechanical DNA model.

RESULTS

It has been established that small OS zones can appear on any part of the DNA molecule. They mainly consist of AT pairs, but as the size of OS zones increases, the content of AT pairs in them decreases.

CONCLUSIONS

The occurrence of long-length OS zones is "tied" to regions of the DNA molecule with a large proportion of AT pairs; if there are several such areas, then, depending on the magnitude of the torque, OS zones can arise in different areas of the gene. Thus, the genesis probability of large OS zones in a DNA segment depends not only on the "strength" of the nucleotide sequence of this area, but also on the factors determining the dynamics of DNA.

DNA breathing integration with deep learning foundational model advances genome-wide binding prediction of human transcription factors

It was previously shown that DNA breathing, thermodynamic stability, as well as transcriptional activity and transcription factor (TF) bindings are functionally correlated. To ascertain the precise relationship between TF binding and DNA breathing, we developed the multi-modal deep learning model EPBDxDNABERT-2, which is based on the Extended Peyrard-Bishop-Dauxois (EPBD) nonlinear DNA dynamics model. To train our EPBDxDNABERT-2, we used chromatin immunoprecipitation sequencing (ChIP-Seq) data comprising 690 ChIP-seq experimental results encompassing 161 distinct TFs and 91 human cell types. EPBDxDNABERT-2 significantly improves the prediction of over 660 TF-DNA, with an increase in the area under the receiver operating characteristic (AUROC) metric of up to 9.6% when compared to the baseline model that does not leverage DNA biophysical properties. We expanded our analysis to in vitro high-throughput Systematic Evolution of Ligands by Exponential enrichment (HT-SELEX) dataset of 215 TFs from 27 families, comparing EPBD with established frameworks. The integration of the DNA breathing features with DNABERT-2 foundational model, greatly enhanced TF-binding predictions. Notably, EPBDxDNABERT-2, trained on a large-scale multi-species genomes, with a cross-attention mechanism, improved predictive power shedding light on the mechanisms underlying disease-related non-coding variants discovered in genome-wide association studies.

Non-canonical DNA structures in the human ribosomal DNA

Non-canonical structures (NCS) refer to the various forms of DNA that differ from the B-conformation described by Watson and Crick. It has been found that these structures are usual components of the genome, actively participating in its essential functions. The present review is focused on the nine kinds of NCS appearing or likely to appear in human ribosomal DNA (rDNA): supercoiling structures, R-loops, G-quadruplexes, i-motifs, DNA triplexes, cruciform structures, DNA bubbles, and A and Z DNA conformations. We discuss the conditions of their generation, including their sequence specificity, distribution within the locus, dynamics, and beneficial and detrimental role in the cell.

Examining DNA breathing with pyDNA-EPBD

MOTIVATION

The two strands of the DNA double helix locally and spontaneously separate and recombine in living cells due to the inherent thermal DNA motion. This dynamics results in transient openings in the double helix and is referred to as "DNA breathing" or "DNA bubbles." The propensity to form local transient openings is important in a wide range of biological processes, such as transcription, replication, and transcription factors binding. However, the modeling and computer simulation of these phenomena, have remained a challenge due to the complex interplay of numerous factors, such as, temperature, salt content, DNA sequence, hydrogen bonding, base stacking, and others.

RESULTS

We present pyDNA-EPBD, a parallel software implementation of the Extended Peyrard-Bishop-Dauxois (EPBD) nonlinear DNA model that allows us to describe some features of DNA dynamics in detail. The pyDNA-EPBD generates genomic scale profiles of average base-pair openings, base flipping probability, DNA bubble probability, and calculations of the characteristically dynamic length indicating the number of base pairs statistically significantly affected by a single point mutation using the Markov Chain Monte Carlo algorithm.

AVAILABILITY AND IMPLEMENTATION

pyDNA-EPBD is supported across most operating systems and is freely available at https://github.com/lanl/pyDNA_EPBD. Extensive documentation can be found at https://lanl.github.io/pyDNA_EPBD/.

Equilibrium melting probabilities of a DNA molecule with a defect: An exact solution of the Poland-Scheraga model

In this study we derive analytically the equilibrium melting probabilities for basepairs of a DNA molecule with a defect site. We assume that the defect is characterized by a change in the Watson-Crick basepair energy of the defect basepair, and in the associated two stacking energies for the defect, as compared to the remaining parts of the DNA. The defect site could, for instance, occur due to DNA basepair mismatching, cross-linking, or by the chemical modifications when attaching fluorescent labels, such as fluorescent-quencher pairs, to DNA. Our exact solution of the Poland-Scheraga model for DNA melting provides the probability that the labeled basepair, and its neighbors, are open at different temperatures. Our work is of direct importance, for instance, for studies where fluorophore-quencher pairs are used for studying single basepair fluctuations of designed DNA molecules.

Examining DNA Breathing with pyDNA-EPBD

Motivation

The two strands of the DNA double helix locally and spontaneously separate and recombine in living cells due to the inherent thermal DNA motion.This dynamics results in transient openings in the double helix and is referred to as "DNA breathing" or "DNA bubbles." The propensity to form local transient openings is important in a wide range of biological processes, such as transcription, replication, and transcription factors binding. However, the modeling and computer simulation of these phenomena, have remained a challenge due to the complex interplay of numerous factors, such as, temperature, salt content, DNA sequence, hydrogen bonding, base stacking, and others.

Results

We present pyDNA-EPBD, a parallel software implementation of the Extended Peyrard-Bishop- Dauxois (EPBD) nonlinear DNA model that allows us to describe some features of DNA dynamics in detail. The pyDNA-EPBD generates genomic scale profiles of average base-pair openings, base flipping probability, DNA bubble probability, and calculations of the characteristically dynamic length indicating the number of base pairs statistically significantly affected by a single point mutation using the Markov Chain Monte Carlo (MCMC) algorithm.

Bubble Relaxation Dynamics in Homopolymer DNA Sequences

Understanding the inherent timescales of large bubbles in DNA is critical to a thorough comprehension of its physicochemical characteristics, as well as their potential role on helix opening and biological function. In this work, we employ the coarse-grained Peyrard-Bishop-Dauxois model of DNA to study relaxation dynamics of large bubbles in homopolymer DNA, using simulations up to the microsecond time scale. By studying energy autocorrelation functions of relatively large bubbles inserted into thermalised DNA molecules, we extract characteristic relaxation times from the equilibration process for both adenine-thymine (AT) and guanine-cytosine (GC) homopolymers. Bubbles of different amplitudes and widths are investigated through extensive statistics and appropriate fittings of their relaxation. Characteristic relaxation times increase with bubble amplitude and width. We show that, within the model, relaxation times are two orders of magnitude longer in GC sequences than in AT sequences. Overall, our results confirm that large bubbles leave a lasting impact on the molecule's dynamics, for times between 0.5-500 ns depending on the homopolymer type and bubble shape, thus clearly affecting long-time evolutions of the molecule.

Nonlinear physics opens a new paradigm for accurate transcription start site prediction

There is evidence that DNA breathing (spontaneous opening of the DNA strands) plays a relevant role in the interactions of DNA with other molecules, and in particular in the transcription process. Therefore, having physical models that can predict these openings is of interest. However, this source of information has not been used before either in transcription start sites (TSSs) or promoter prediction. In this article, one such model is used as an additional information source that, when used by a machine learning (ML) model, improves the results of current methods for the prediction of TSSs. In addition, we provide evidence on the validity of the physical model, as it is able by itself to predict TSSs with high accuracy. This opens an exciting avenue of research at the intersection of statistical mechanics and ML, where ML models in bioinformatics can be improved using physical models of DNA as feature extractors.

Non-linear Hamiltonian models for DNA

Nucleic acids' physical properties have been investigated by theoretical methods based both on fully atomistic representations and on coarse-grained models, e.g., the worm-like-chain, taken from polymer physics. In this review article, I discuss an intermediate (mesoscopic) approach and show how to build a three-dimensional Hamiltonian model which accounts for the main interactions responsible for the stability of the helical molecules. While the 3D mesoscopic model yields a sufficiently detailed description of the helix at the level of the base pair, it also allows one to predict the thermodynamical and structural properties of molecules in solution. Relying on the idea that the base pair fluctuations can be conceived as trajectories, I have built over the past years a computational method based on the time-dependent path integral formalism to derive the partition function. While the main features of the method are presented, I focus here in particular on a newly developed statistical method to set the maximum amplitude of the base pair fluctuations, a key parameter of the theory. Some applications to the calculation of DNA flexibility properties are discussed together with the available experimental data.

Bubble lifetimes in DNA gene promoters and their mutations affecting transcription

Relative lifetimes of inherent double stranded DNA openings with lengths up to ten base pairs are presented for different gene promoters and corresponding mutants that either increase or decrease transcriptional activity in the framework of the Peyrard-Bishop-Dauxois model. Extensive microcanonical simulations are used with energies corresponding to physiological temperature. The bubble lifetime profiles along the DNA sequences demonstrate a significant reduction of the average lifetime at the mutation sites when the mutated promoter decreases transcription, while a corresponding enhancement of the bubble lifetime is observed in the case of mutations leading to increased transcription. The relative difference in bubble lifetimes between the mutated and wild type promoters at the position of mutation varies from 20% to more than 30% as the bubble length decreases.

Exploiting SERS sensitivity to monitor DNA aggregation properties

In the last decades, DNA has been considered far more than the system carrying the essential genetic instructions. Indeed, because of the remarkable properties of the base-pairing specificity and thermoreversibility of the interactions, DNA plays a central role in the design of innovative architectures at the nanoscale. Here, combining complementary DNA strands with a custom-made solution of silver nanoparticles, we realize plasmonic aggregates to exploit the sensitivity of Surface Enhanced Raman Spectroscopy (SERS) for the identification/detection of the distinctive features of DNA hybridization, both in solution and on dried samples. Moreover, SERS allows monitoring the DNA aggregation process by following the temperature variation of a specific spectroscopic marker associated with the Watson-Crick hydrogen bond formation. This temperature-dependent behavior enables us to precisely reconstruct the melting profile of the selected DNA sequences by spectroscopic measurements only.

Distributions of bubble lifetimes and bubble lengths in DNA

We investigate the distribution of bubble lifetimes and bubble lengths in DNA at physiological temperature, by performing extensive molecular dynamics simulations with the Peyrard-Bishop-Dauxois (PBD) model, as well as an extended version (ePBD) having a sequence-dependent stacking interaction, emphasizing the effect of the sequences' guanine-cytosine (GC)/adenine-thymine (AT) content on these distributions. For both models we find that base pair-dependent (GC vs AT) thresholds for considering complementary nucleotides to be separated are able to reproduce the observed dependence of the melting temperature on the GC content of the DNA sequence. Using these thresholds for base pair openings, we obtain bubble lifetime distributions for bubbles of lengths up to ten base pairs as the GC content of the sequences is varied, which are accurately fitted with stretched exponential functions. We find that for both models the average bubble lifetime decreases with increasing either the bubble length or the GC content. In addition, the obtained bubble length distributions are also fitted by appropriate stretched exponential functions and our results show that short bubbles have similar likelihoods for any GC content, but longer ones are substantially more likely to occur in AT-rich sequences. We also show that the ePBD model permits more, longer-lived, bubbles than the PBD system.

Towards spectrally selective catastrophic response

We study the large-amplitude response of classical molecules to electromagnetic radiation, showing the universality of the transition from linear to nonlinear response and breakup at sufficiently large amplitudes. We demonstrate that a range of models, from the simple harmonic oscillator to the successful Peyrard-Bishop-Dauxois type models of DNA, which include realistic effects of the environment (including damping and dephasing due to thermal fluctuations), lead to characteristic universal behavior: formation of domains of dissociation in driving force amplitude-frequency space, characterized by the presence of local boundary minima. We demonstrate that by simply following the progression of the resonance maxima in this space, while gradually increasing intensity of the radiation, one must necessarily arrive at one of these minima, i.e., a point where the ultrahigh spectral selectivity is retained. We show that this universal property, applicable to other oscillatory systems, is a consequence of the fact that these models belong to the fold catastrophe universality class of Thom's catastrophe theory. This in turn implies that for most biostructures, including DNA, high spectral sensitivity near the onset of the denaturation processes can be expected. Such spectrally selective molecular denaturation could find important applications in biology and medicine.

Discrete-breather-assisted charge transport along DNA-like molecular wires

Mobile discrete breathers (MDBs) are here suggested as localized excitations underlying the trapping and transport of charged particles (electron or hole) along a DNA-like molecular wire with anchored ends such as attached to two electrodes. For illustration the Peyrard-Bishop-Dauxois-Holstein (PBDH) model is used. MDBs are excited by imposing appropriate disturbances to velocities or space positions of adjacent nucleotide pairs or lattice units of the wire. They can be directed either towards or away from the wire hence transverse to it. Numerical computer simulations show that a rather stable quasiparticle MDB + electron is possible when just a few of the nucleotide pairs near one of the fixed ends of the wire are excited. For the process to be effective, the charge, e.g., the electron, must be initially placed around the disturbed region of the molecule. Once the MDB + electron quasiparticle is formed it may be transported to quite a long distance up to ca. 60-70 nm in real space. Our findings show that such process does not demand intervention of an externally applied electric field and hence it may be considered as alternative to the polaron transport process.

Heterogeneity and chaos in the Peyrard-Bishop-Dauxois DNA model

We discuss the effect of heterogeneity on the chaotic properties of the Peyrard-Bishop-Dauxois nonlinear model of DNA. Results are presented for the maximum Lyapunov exponent and the deviation vector distribution. Different compositions of adenine-thymine (AT) and guanine-cytosine (GC) base pairs are examined for various energies up to the melting point of the corresponding sequence. We also consider the effect of the alternation index, which measures the heterogeneity of the DNA chain through the number of alternations between different types (AT or GC) of base pairs, on the chaotic behavior of the system. Biological gene promoter sequences have been also investigated, showing no distinct behavior of the maximum Lyapunov exponent.

Toward a Universal Structural and Energetic Model for Prokaryotic Promoters

With almost no consensus promoter sequence in prokaryotes, recruitment of RNA polymerase (RNAP) to precise transcriptional start sites (TSSs) has remained an unsolved puzzle. Uncovering the underlying mechanism is critical for understanding the principle of gene regulation. We attempted to search the hidden code in ∼16,500 promoters of 12 prokaryotes representing two kingdoms in their structure and energetics. Twenty-eight fundamental parameters of DNA structure including backbone angles, basepair axis, and interbasepair and intrabasepair parameters were used, and information was extracted from x-ray crystallography data. Three parameters (solvation energy, hydrogen-bond energy, and stacking energy) were selected for creating energetics profiles using in-house programs. DNA of promoter regions was found to be inherently designed to undergo a change in every parameter undertaken for the study, in all prokaryotes. The change starts from some distance upstream of TSSs and continues past some distance from TSS, hence giving a signature state to promoter regions. These signature states might be the universal hidden codes recognized by RNAP. This observation was reiterated when randomly selected promoter sequences (with little sequence conservation) were subjected to structure generation; all developed into very similar three-dimensional structures quite distinct from those of conventional B-DNA and coding sequences. Fine structural details at important motifs (viz. -11, -35, and -75 positions relative to TSS) of promoters reveal novel to our knowledge and pointed insights for RNAP interaction at these locations; it could be correlated with how some particular structural changes at the -11 region may allow insertion of RNAP amino acids in interbasepair space as well as facilitate the flipping out of bases from the DNA duplex.

Direct Observation of Activated Kinetics and Downhill Dynamics in DNA Dehybridization

We have studied two model DNA oligonucleotide sequences that display contrasting degrees of heterogeneous melting using an optical temperature jump to trigger dehybridization and a nonlinear infrared (IR) spectroscopy probe to track the response of the helix ensemble. This approach offers base-sensitive structural insight through the unique vibrational fingerprint characteristic of each nucleobase as well as time resolution capable of following unfolding across nanoseconds to milliseconds. We observe predissociation unzipping of the helical termini, loss of final dimer contacts, and rehybridization of the dissociated strands all in a single measurement. Complete dissociation of the dimer is found to be well described by Arrhenius kinetics for both sequences, with dissociation barriers in the range of 160-190 kJ/mol. A sequence with terminal adenine-thymine (AT) base pairs and a guanine-cytosine core returns a large-amplitude fast response ranging from 70 to 170 ns, originating only from the AT base pairs. Variable temperature jump ( T-jump) experiments in which the final temperature ( T_f) is fixed and the initial temperature ( T_i) is varied such that different starting ensembles all evolve on the same final free-energy surface were employed to explore the features of the underlying potential that dictates hybridization. These experiments reveal that the unzipping of the AT termini is an essentially barrierless process and that both activated and downhill events are necessary to describe the dehybridization mechanism. Although our results are largely consistent with the classic nucleation-zipper picture, new insights regarding the nature of base pair zippering refine the mechanistic details of the fastest DNA hybridization dynamics.

Evaluating the role of coherent delocalized phonon-like modes in DNA cyclization

The innate flexibility of a DNA sequence is quantified by the Jacobson-Stockmayer's J-factor, which measures the propensity for DNA loop formation. Recent studies of ultra-short DNA sequences revealed a discrepancy of up to six orders of magnitude between experimentally measured and theoretically predicted J-factors. These large differences suggest that, in addition to the elastic moduli of the double helix, other factors contribute to loop formation. Here, we develop a new theoretical model that explores how coherent delocalized phonon-like modes in DNA provide single-stranded "flexible hinges" to assist in loop formation. We combine the Czapla-Swigon-Olson structural model of DNA with our extended Peyrard-Bishop-Dauxois model and, without changing any of the parameters of the two models, apply this new computational framework to 86 experimentally characterized DNA sequences. Our results demonstrate that the new computational framework can predict J-factors within an order of magnitude of experimental measurements for most ultra-short DNA sequences, while continuing to accurately describe the J-factors of longer sequences. Further, we demonstrate that our computational framework can be used to describe the cyclization of DNA sequences that contain a base pair mismatch. Overall, our results support the conclusion that coherent delocalized phonon-like modes play an important role in DNA cyclization.

Observation of coherent delocalized phonon-like modes in DNA under physiological conditions

Underdamped terahertz-frequency delocalized phonon-like modes have long been suggested to play a role in the biological function of DNA. Such phonon modes involve the collective motion of many atoms and are prerequisite to understanding the molecular nature of macroscopic conformational changes and related biochemical phenomena. Initial predictions were based on simple theoretical models of DNA. However, such models do not take into account strong interactions with the surrounding water, which is likely to cause phonon modes to be heavily damped and localized. Here we apply state-of-the-art femtosecond optical Kerr effect spectroscopy, which is currently the only technique capable of taking low-frequency (GHz to THz) vibrational spectra in solution. We are able to demonstrate that phonon modes involving the hydrogen bond network between the strands exist in DNA at physiologically relevant conditions. In addition, the dynamics of the solvating water molecules is slowed down by about a factor of 20 compared with the bulk.

Fast Prediction of DNA Melting Bubbles Using DNA Thermodynamic Stability

DNA melting bubbles are the basis of many DNA-protein interactions, such as those in regulatory DNA regions driving gene expression, DNA replication and bacterial horizontal gene transfer. Bubble formation is affected by DNA duplex stability and thermally induced duplex destabilization (TIDD). Although prediction of duplex stability with the nearest neighbor (NN) method is much faster than prediction of TIDD with the Peyrard-Bishop-Dauxois (PBD) model, PBD predicted TIDD defines regulatory DNA regions with higher accuracy and detail. Here, we considered that PBD predicted TIDD is inherently related to the intrinsic duplex stabilities of destabilization regions. We show by regression modeling that NN duplex stabilities can be used to predict TIDD almost as accurately as is predicted with PBD. Predicted TIDD is in fact ascribed to non-linear transformation of NN duplex stabilities in destabilization regions as well as effects of neighboring regions relative to destabilization size. Since the prediction time of our models is over six orders of magnitude shorter than that of PBD, the models present an accessible tool for researchers. TIDD can be predicted on our webserver at http://tidd.immt.eu.

Unravelling the Role of the F55 Regulator in the Transition from Lysogeny to UV Induction of Sulfolobus Spindle-Shaped Virus 1

Sulfolobus spindle-shaped virus 1 represents a model for studying virus-host interaction in harsh environments, and it is so far the only member of the family Fuselloviridae that shows a UV-inducible life cycle. Although the virus has been extensively studied, mechanisms underpinning the maintenance of lysogeny as well as those regulating the UV induction have received little attention. Recently, a novel SSV1 transcription factor, F55, was identified. This factor was able to bind in vitro to several sequences derived from the early and UV-inducible promoters of the SSV1 genome. The location of these binding sites together with the differential affinity of F55 for these sequences led to the hypothesis that this protein might be involved in the maintenance of the SSV1 lysogeny. Here, we report an in vivo survey of the molecular events occurring at the UV-inducible region of the SSV1 genome, with a focus on the binding profile of F55 before and after the UV irradiation. The binding of F55 to the target promoters correlates with transcription repression, whereas its dissociation is paralleled by transcription activation. Therefore, we propose that F55 acts as a molecular switch for the transcriptional regulation of the early viral genes.

IMPORTANCE

Functional genomic studies of SSV1 proteins have been hindered by the lack of similarity with other characterized proteins. As a result, few insights into their in vivo roles have been gained throughout the last 3 decades. Here, we report the first in vivo investigation of an SSV1 transcription regulator, F55, that plays a key role in the transition from the lysogenic to the induced state of SSV1. We show that F55 regulates the expression of the UV-inducible as well as the early genes. Moreover, the differential affinity of this transcription factor for these targets allows a fine-tuned and temporal coordinated regulation of transcription of viral genes.

A statistical thermodynamic model for investigating the stability of DNA sequences from oligonucleotides to genomes

We describe the development and testing of a simple statistical mechanics methodology for duplex DNA applicable to sequences of any composition and extensible to genomes. The microstates of a DNA sequence are modeled in terms of blocks of basepairs that are assumed to be fully closed (paired) or open. This approach generates an ensemble of bubblelike microstates that are used to calculate the corresponding partition function. The energies of the microstates are calculated as additive contributions from hydrogen bonding, basepair stacking, and solvation terms parameterized from a comprehensive series of molecular dynamics simulations including solvent and ions. Thermodynamic properties and nucleotide stability constants for DNA sequences follow directly from the partition function. The methodology was tested by comparing computed free energies per basepair with the experimental melting temperatures of 60 oligonucleotides, yielding a correlation coefficient of -0.96. The thermodynamic stability of genic/nongenic regions was tested in terms of nucleotide stability constants versus sequence for the Escherichia coli K-12 genome. It showed clear differentiation of the genes from promoters and captures genic regions with a sensitivity of 0.94. The statistical thermodynamic model presented here provides a seemingly new handle on the challenging problem of interpreting genomic sequences.

Mesoscopic model and free energy landscape for protein-DNA binding sites: analysis of cyanobacterial promoters

The identification of protein binding sites in promoter sequences is a key problem to understand and control regulation in biochemistry and biotechnological processes. We use a computational method to analyze promoters from a given genome. Our approach is based on a physical model at the mesoscopic level of protein-DNA interaction based on the influence of DNA local conformation on the dynamics of a general particle along the chain. Following the proposed model, the joined dynamics of the protein particle and the DNA portion of interest, only characterized by its base pair sequence, is simulated. The simulation output is analyzed by generating and analyzing the Free Energy Landscape of the system. In order to prove the capacity of prediction of our computational method we have analyzed nine promoters of Anabaena PCC 7120. We are able to identify the transcription starting site of each of the promoters as the most populated macrostate in the dynamics. The developed procedure allows also to characterize promoter macrostates in terms of thermo-statistical magnitudes (free energy and entropy), with valuable biological implications. Our results agree with independent previous experimental results. Thus, our methods appear as a powerful complementary tool for identifying protein binding sites in promoter sequences.

Binding of specific proteins to particular sites in the DNA sequence is a fundamental issue for gene regulation in molecular biology and genetic engineering. A deep understanding of cell physiology requires the analysis of a plethora of genes involving characterization of their promoter architectures that determine their regulation and gene transcription. In order to locate the promoter elements of a given gene, experimental determination of its transcription start site (TSS) is required. This is an expensive, time-consuming task that, depending on our requirements, could be simplified using computational analysis as a first approach. Nevertheless, most computational methods lack a physical basis on the protein-DNA interaction mechanism. We adopt here this strategy, by using a simple model for protein-DNA interaction to find TSS in a bunch of cyanobacteria promoters. We make use of physical tools to characterize these TSS and to relate them with biological properties as the relative strength of the promoter. Our study shows how a model based on a coarse-grained description of a biomolecule can give valuable insight on its biological function.

Torsion-mediated interaction between adjacent genes

DNA torsional stress is generated by virtually all biomolecular processes involving the double helix, in particular transcription where a significant level of stress propagates over several kilobases. If another promoter is located in this range, this stress may strongly modify its opening properties, and hence facilitate or hinder its transcription. This mechanism implies that transcribed genes distant of a few kilobases are not independent, but coupled by torsional stress, an effect for which we propose the first quantitative and systematic model. In contrast to previously proposed mechanisms of transcriptional interference, the suggested coupling is not mediated by the transcription machineries, but results from the universal mechanical features of the double-helix. The model shows that the effect likely affects prokaryotes as well as eukaryotes, but with different consequences owing to their different basal levels of torsion. It also depends crucially on the relative orientation of the genes, enhancing the expression of eukaryotic divergent pairs while reducing that of prokaryotic convergent ones. To test the in vivo influence of the torsional coupling, we analyze the expression of isolated gene pairs in the Drosophila melanogaster genome. Their orientation and distance dependence is fully consistent with the model, suggesting that torsional gene coupling may constitute a widespread mechanism of (co)regulation in eukaryotes.

A proposed mechanism of the influence of gold nanoparticles on DNA hybridization

A combination of gold nanoparticles (AuNPs) and nucleic acids has been used in biosensing applications. However, there is a poor fundamental understanding of how gold nanoparticle surfaces influence the DNA hybridization process. Here, we measured the rate constants of the hybridization and dehybridization of DNA on gold nanoparticle surfaces to enable the determination of activation parameters using transition state theory. We show that the target bases need to be detached from the gold nanoparticle surfaces before zipping. This causes a shift of the rate-limiting step of hybridization to the mismatch-sensitive zipping step. Furthermore, our results propose that the binding of gold nanoparticles to the single-stranded DNA segments (commonly known as bubbles) in the duplex DNA stabilizes the bubbles and accelerates the dehybridization process. We employ the proposed mechanism of DNA hybridization/dehybridization to explain the ability of 5 nm diameter gold nanoparticles to help discriminate between single base-pair mismatched DNA molecules when performed in a NanoBioArray chip. The mechanistic insight into the DNA-gold nanoparticle hybridization/dehybridization process should lead to the development of new biosensors.

Twisting and bending stress in DNA minicircles

The interplay between bending of the molecule axis and appearance of disruptions in circular DNA molecules, with ∼100 base pairs, is addressed. Three minicircles with different radii and almost equal contents of AT and GC pairs are investigated. The DNA sequences are modeled by a mesoscopic Hamiltonian which describes the essential interactions in the helix at the level of the base pair and incorporates twisting and bending degrees of freedom. Helix unwinding and bubble formation patterns are consistently computed by a path integral method that sums over a large number of molecule configurations compatible with the model potential. The path ensembles are determined, as a function of temperature, by minimizing the free energy of the system. Fluctuational openings appear along the helix to release the stress due to the bending of the molecule backbone. In agreement with the experimental findings, base pair disruptions are found with larger probability in the smallest minicircle of 66 bps whose bending angle is ∼6°. For this minicircle, a sizeable untwisting is obtained with the helical repeat showing a step-like increase at T = 315 K. The method can be generalized to determine the bubble probability profiles of open ends linear sequences.

ProMT: effective human promoter prediction using Markov chain model based on DNA structural properties

The core promoters play significant and extensive roles for the initiation and regulation of DNA transcription. The identification of core promoters is one of the most challenging problems yet. Due to the diverse nature of core promoters, the results obtained through existing computational approaches are not satisfactory. None of them considered the potential influence on performance of predictive approach resulted by the interference between neighboring TSSs in TSS clusters. In this paper, we sufficiently considered this main factor and proposed an approach to locate potential TSS clusters according to the correlation of regional profiles of DNA and TSS clusters. On this basis, we further presented a novel computational approach (ProMT) for promoter prediction using Markov chain model and predictive TSS clusters based on structural properties of DNA. Extensive experiments demonstrated that ProMT can significantly improve the predictive performance. Therefore, considering interference between neighboring TSSs is essential for a wider range of promoter prediction.

Breathing dynamics based parameter sensitivity analysis of hetero-polymeric DNA

We study the parameter sensitivity of hetero-polymeric DNA within the purview of DNA breathing dynamics. The degree of correlation between the mean bubble size and the model parameters is estimated for this purpose for three different DNA sequences. The analysis leads us to a better understanding of the sequence dependent nature of the breathing dynamics of hetero-polymeric DNA. Out of the 14 model parameters for DNA stability in the statistical Poland-Scheraga approach, the hydrogen bond interaction ε(hb)(AT) for an AT base pair and the ring factor ξ turn out to be the most sensitive parameters. In addition, the stacking interaction ε(st)(TA-TA) for an TA-TA nearest neighbor pair of base-pairs is found to be the most sensitive one among all stacking interactions. Moreover, we also establish that the nature of stacking interaction has a deciding effect on the DNA breathing dynamics, not the number of times a particular stacking interaction appears in a sequence. We show that the sensitivity analysis can be used as an effective measure to guide a stochastic optimization technique to find the kinetic rate constants related to the dynamics as opposed to the case where the rate constants are measured using the conventional unbiased way of optimization.

Single-molecule FRET and linear dichroism studies of DNA breathing and helicase binding at replication fork junctions

DNA "breathing" is a thermally driven process in which base-paired DNA sequences transiently adopt local conformations that depart from their most stable structures. Polymerases and other proteins of genome expression require access to single-stranded DNA coding templates located in the double-stranded DNA "interior," and it is likely that fluctuations of the sugar-phosphate backbones of dsDNA that result in mechanistically useful local base pair opening reactions can be exploited by such DNA regulatory proteins. Such motions are difficult to observe in bulk measurements, both because they are infrequent and because they often occur on microsecond time scales that are not easy to access experimentally. We report single-molecule fluorescence experiments with polarized light, in which tens-of-microseconds rotational motions of internally labeled iCy3/iCy5 donor-acceptor Förster resonance energy transfer fluorophore pairs that have been rigidly inserted into the backbones of replication fork constructs are simultaneously detected using single-molecule Förster resonance energy transfer and single-molecule fluorescence-detected linear dichroism signals. Our results reveal significant local motions in the ∼100-μs range, a reasonable time scale for DNA breathing fluctuations of potential relevance for DNA-protein interactions. Moreover, we show that both the magnitudes and the relaxation times of these backbone breathing fluctuations are significantly perturbed by interactions of the fork construct with a nonprocessive, weakly binding bacteriophage T4-coded helicase hexamer initiation complex, suggesting that these motions may play a fundamental role in the initial binding, assembly, and function of the processive helicase-primase (primosome) component of the bacteriophage T4-coded DNA replication complex.

Cooperativity and interaction energy threshold effects in recognition of the -10 promoter element by bacterial RNA polymerase

RNA polymerase (RNAP) melts promoter DNA to form transcription-competent open promoter complex (RPo). Interaction of the RNAP σ subunit with non-template strand bases of a conserved -10 element (consensus sequence T-12A-11T-10A-9A-8T-7) is an important source of energy-driving localized promoter melting. Here, we used an RNAP molecular beacon assay to investigate interdependencies of RNAP interactions with -10 element nucleotides. The results reveal a strong cooperation between RNAP interactions with individual -10 element non-template strand nucleotides and indicate that recognition of the -10 element bases occurs only when free energy of the overall RNAP -10 element binding reaches a certain threshold level. The threshold-like mode of the -10 element recognition may be related to the energetic cost of attaining a conformation of the -10 element that is recognizable by RNAP. The RNAP interaction with T/A-12 base pair was found to be strongly stimulated by RNAP interactions with other -10 element bases and with promoter spacer between the -10 and -35 promoter elements. The data also indicate that unmelted -10 promoter element can impair RNAP interactions with promoter DNA upstream of the -11 position. We suggest that cooperativity and threshold effects are important factors guiding the dynamics and selectivity of RPo formation.

A composite method based on formal grammar and DNA structural features in detecting human polymerase II promoter region

An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG) can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques.

Modeling the interaction of DNA with alternating fields

We study the influence of a terahertz field on thermal properties of DNA molecules. A Peyrard-Bishop-Dauxois model with the inclusion of a solvent interaction term is considered. The terahertz field is included as a sinusoidal driven force in the equation of motion. We show how under certain field and system parameters, the melting transition and bubble formation are modified.

Specificity and heterogeneity of terahertz radiation effect on gene expression in mouse mesenchymal stem cells

We report that terahertz (THz) irradiation of mouse mesenchymal stem cells (mMSCs) with a single-frequency (SF) 2.52 THz laser or pulsed broadband (centered at 10 THz) source results in irradiation specific heterogenic changes in gene expression. The THz effect depends on irradiation parameters such as the duration and type of THz source, and on the degree of stem cell differentiation. Our microarray survey and RT-PCR experiments demonstrate that prolonged broadband THz irradiation drives mMSCs toward differentiation, while 2-hour irradiation (regardless of THz sources) affects genes transcriptionally active in pluripotent stem cells. The strictly controlled experimental environment indicates minimal temperature changes and the absence of any discernable response to heat shock and cellular stress genes imply a non-thermal response. Computer simulations of the core promoters of two pluripotency markers reveal association between gene upregulation and propensity for DNA breathing. We propose that THz radiation has potential for non-contact control of cellular gene expression.

Can we model DNA at the mesoscale?

Modelling DNA is useful for understanding its properties better but it is also challenging because many of these properties involve hundreds of base pairs or more, or time scales which are much longer than the time scales accessible to molecular dynamics. It is therefore necessary to develop models at a mesoscale, which include enough details to describe the properties of interest, for instance the biological sequence, while staying sufficiently simple and realistic.We discuss here two examples: a dynamical model to study the mechanical denaturation of DNA, which probes the sequence on various scales, and a model for the self assembly of DNA which describes the formation of hairpins and allows us to study its kinetics.

Binding of nucleoid-associated protein fis to DNA is regulated by DNA breathing dynamics

Physicochemical properties of DNA, such as shape, affect protein-DNA recognition. However, the properties of DNA that are most relevant for predicting the binding sites of particular transcription factors (TFs) or classes of TFs have yet to be fully understood. Here, using a model that accurately captures the melting behavior and breathing dynamics (spontaneous local openings of the double helix) of double-stranded DNA, we simulated the dynamics of known binding sites of the TF and nucleoid-associated protein Fis in Escherichia coli. Our study involves simulations of breathing dynamics, analysis of large published in vitro and genomic datasets, and targeted experimental tests of our predictions. Our simulation results and available in vitro binding data indicate a strong correlation between DNA breathing dynamics and Fis binding. Indeed, we can define an average DNA breathing profile that is characteristic of Fis binding sites. This profile is significantly enriched among the identified in vivo E. coli Fis binding sites. To test our understanding of how Fis binding is influenced by DNA breathing dynamics, we designed base-pair substitutions, mismatch, and methylation modifications of DNA regions that are known to interact (or not interact) with Fis. The goal in each case was to make the local DNA breathing dynamics either closer to or farther from the breathing profile characteristic of a strong Fis binding site. For the modified DNA segments, we found that Fis-DNA binding, as assessed by gel-shift assay, changed in accordance with our expectations. We conclude that Fis binding is associated with DNA breathing dynamics, which in turn may be regulated by various nucleotide modifications.

Cellular transcription factors (TFs) are proteins that regulate gene expression, and thereby cellular activity and fate, by binding to specific DNA segments. The physicochemical determinants of protein-DNA binding specificity are not completely understood. Here, we report that the propensity of transient opening and re-closing of the double helix, resulting from thermal fluctuations, aka “DNA breathing” or “DNA bubbles,” can be associated with binding affinity in the case of Fis, a well-studied nucleoid-associated protein in Escherichia coli. We found that a particular breathing profile is characteristic of high-affinity Fis binding sites and that DNA fragments known to bind Fis in vivo are statistically enriched for this profile. Furthermore, we used simulations of DNA breathing dynamics to guide design of gel-shift experiments aimed at testing the idea that local breathing influences Fis binding. As a result, we show that via nucleotide modifications but without modifying nucleotides that directly contact Fis, we were able to transform a low-affinity Fis binding site into a high-affinity site and vice versa. The nucleotide modifications were designed only based on DNA breathing simulations. Our study suggests that strong Fis-DNA binding depends on DNA breathing - a novel physicochemical characteristic that could be used for prediction and rational design of TF binding sites.

Mesoscopic model for free-energy-landscape analysis of DNA sequences

A mesoscopic model which allows us to identify and quantify the strength of binding sites in DNA sequences is proposed. The model is based on the Peyrard-Bishop-Dauxois model for the DNA chain coupled to a Brownian particle which explores the sequence interacting more importantly with open base pairs of the DNA chain. We apply the model to promoter sequences of different organisms. The free energy landscape obtained for these promoters shows a complex structure that is strongly connected to their biological behavior. The analysis method used is able to quantify free energy differences of sites within genome sequences.

Mechanism of homology recognition in DNA recombination from dual-molecule experiments

In E. coli homologous recombination, a filament of RecA protein formed on DNA searches and pairs a homologous sequence within a second DNA molecule with remarkable speed and fidelity. Here, we directly probe the strength of the two-molecule interactions involved in homology search and recognition using dual-molecule manipulation, combining magnetic and optical tweezers. We find that the filament's secondary DNA-binding site interacts with a single strand of the incoming double-stranded DNA during homology sampling. Recognition requires opening of the helix and is strongly promoted by unwinding torsional stress. Recognition is achieved upon binding of both strands of the incoming dsDNA to each of two ssDNA-binding sites in the filament. The data indicate a physical picture for homology recognition in which the fidelity of the search process is governed by the distance between the DNA-binding sites.

Hysteresis in pressure-driven DNA denaturation

In the past, a great deal of attention has been drawn to thermal driven denaturation processes. In recent years, however, the discovery of stress-induced denaturation, observed at the one-molecule level, has revealed new insights into the complex phenomena involved in the thermo-mechanics of DNA function. Understanding the effect of local pressure variations in DNA stability is thus an appealing topic. Such processes as cellular stress, dehydration, and changes in the ionic strength of the medium could explain local pressure changes that will affect the molecular mechanics of DNA and hence its stability. In this work, a theory that accounts for hysteresis in pressure-driven DNA denaturation is proposed. We here combine an irreversible thermodynamic approach with an equation of state based on the Poisson-Boltzmann cell model. The latter one provides a good description of the osmotic pressure over a wide range of DNA concentrations. The resulting theoretical framework predicts, in general, the process of denaturation and, in particular, hysteresis curves for a DNA sequence in terms of system parameters such as salt concentration, density of DNA molecules and temperature in addition to structural and configurational states of DNA. Furthermore, this formalism can be naturally extended to more complex situations, for example, in cases where the host medium is made up of asymmetric salts or in the description of the (helical-like) charge distribution along the DNA molecule. Moreover, since this study incorporates the effect of pressure through a thermodynamic analysis, much of what is known from temperature-driven experiments will shed light on the pressure-induced melting issue.

Charge transport in DNA: dependence of diffusion coefficient on temperature and electron-phonon coupling constant

The diffusion coefficient is calculated for a charge propagating along a double-stranded DNA, while it interacts with the nonlinear fluctuational openings of base pairs. The latter structural dynamics of DNA is described by the Peyrard-Bishop-Dauxois model [T. Dauxois, M. Peyrard, and A. R. Bishop, Phys Rev. E 47 R44 (1993)], which represents essential anharmonicities of base-pair stretchings. The dependence of the diffusion coefficient on the temperature and the electron-phonon coupling constant is presented. The diffusion coefficient decreases when either the temperature or the electron-phonon coupling increases. Analytical expressions are provided that describe the temperature dependence of the diffusion coefficient. The variation of the parameters of these expressions with the electron-phonon coupling constant is also discussed. These results quantitatively demonstrate how DNA structural nonlinear dynamics affects macroscopic charge transport properties.

The Physics of Life and Quantum Complex Matter: A Case of Cross-Fertilization

Progress in the science of complexity, from the Big Bang to the coming of humankind, from chemistry and biology to geosciences and medicine, and from materials engineering to energy sciences, is leading to a shift of paradigm in the physical sciences. The focus is on the understanding of the non-equilibrium process in fine tuned systems. Quantum complex materials such as high temperature superconductors and living matter are both non-equilibrium and fine tuned systems. These topics have been subbjects of scientific discussion in the Rome Symposium on the “Quantum Physics of Living Matter”.

An ANN-GA model based promoter prediction in Arabidopsis thaliana using tilling microarray data

Identification of promoter region is an important part of gene annotation. Identification of promoters in eukaryotes is important as promoters modulate various metabolic functions and cellular stress responses. In this work, a novel approach utilizing intensity values of tilling microarray data for a model eukaryotic plant Arabidopsis thaliana, was used to specify promoter region from non-promoter region. A feed-forward back propagation neural network model supported by genetic algorithm was employed to predict the class of data with a window size of 41. A dataset comprising of 2992 data vectors representing both promoter and non-promoter regions, chosen randomly from probe intensity vectors for whole genome of Arabidopsis thaliana generated through tilling microarray technique was used. The classifier model shows prediction accuracy of 69.73% and 65.36% on training and validation sets, respectively. Further, a concept of distance based class membership was used to validate reliability of classifier, which showed promising results. The study shows the usability of micro-array probe intensities to predict the promoter regions in eukaryotic genomes.