Quantifying hopping and jumping in facilitated diffusion of DNA-binding proteins

Stick, Slide, or Bounce: Charge Density Controls Nanoparticle Diffusion

The diffusion and interaction dynamics of charged nanoparticles (NPs) within charged polymer networks are crucial for understanding various biological and biomedical applications. Using a combination of coarse-grained molecular dynamics simulations and experimental diffusion studies, we investigate the effects of the NP size, relative surface charge density (ζ), and concentration on the NP permeation length and time. We propose a scaling law for the relative diffusion of NPs with respect to concentration and ζ, highlighting how these factors influence the NP movement within the network. The analyses reveal that concentration and ζ significantly affect NP permeation length and time, with ζ being critical, as critical as concentration. This finding is corroborated by controlled release experiments. Further, we categorize NP dynamics into sticking, sliding, and bouncing regimes, demonstrating how variations in ζ, concentration, and NP size control these behaviors. Through normalized attachment time (NAT) analyses, we elucidate the roles of electrostatic interactions, steric hindrance, and hydrodynamic forces in governing NP dynamics. These insights provide guidance for optimizing NP design in targeted drug delivery and advanced material applications, enhancing our understanding of NP behavior in complex environments.

Fractional Brownian motion with fluctuating diffusivities

Despite the success of fractional Brownian motion (fBm) in modeling systems that exhibit anomalous diffusion due to temporal correlations, recent experimental and theoretical studies highlight the necessity for a more comprehensive approach of a generalization that incorporates heterogeneities in either the tracers or the environment. This work presents a modification of Lévy's representation of fBm for the case in which the generalized diffusion coefficient is a stochastic process. We derive analytical expressions for the autocovariance function and both ensemble- and time-averaged mean squared displacements. Further, we validate the efficacy of the developed framework in two-state systems, comparing analytical asymptotic expressions with numerical simulations.

Probing the modulation in facilitated diffusion guided by DNA-protein interactions in target search processes

Many fundamental biophysical processes involving gene regulation and gene editing rely, at the molecular level, on an intricate methodology of searching and locating the precise target base pair sequence on the genome by specific binding proteins. A unique mechanism, known as 'facilitated diffusion', which is a combination of 1D sliding along with 3D movement, is considered to be the key step for such events. This also explains the relatively much shorter timescale of the target searching process, compared to other diffusion-controlled biophysical processes. In this work, we aim to probe the modulation of target search dynamics of a protein moiety by estimating the rate of the target search process, and the statistics of the search rounds and timescales accomplished by the 1D and 3D motions, based on first passage time (FPT) calculations. This is studied with its characteristics getting influenced by various given conditions such as, when the DNA is rigid or flexible, and when the target is placed at different locations on the DNA. The current theoretical framework includes a Brownian dynamics simulation setup adopting a straightforward coarse-grained model for a diffusing protein on DNA. Moreover, this theoretical analysis provides insights into the complex target search dynamics by highlighting the significance of the chain dynamics in the mechanistic details of the facilitated diffusion process.

Unconventionally fast transport through sliding dynamics of rodlike particles in macromolecular networks

Transport of rodlike particles in confinement environments of macromolecular networks plays crucial roles in many important biological processes and technological applications. The relevant understanding has been limited to thin rods with diameter much smaller than network mesh size, although the opposite case, of which the dynamical behaviors and underlying physical mechanisms remain unclear, is ubiquitous. Here, we solve this issue by combining experiments, simulations and theory. We find a nonmonotonic dependence of translational diffusion on rod length, characterized by length commensuration-governed unconventionally fast dynamics which is in striking contrast to the monotonic dependence for thin rods. Our results clarify that such a fast diffusion of thick rods with length of integral multiple of mesh size follows sliding dynamics and demonstrate it to be anomalous yet Brownian. Moreover, good agreement between theoretical analysis and simulations corroborates that the sliding dynamics is an intermediate regime between hopping and Brownian dynamics, and provides a mechanistic interpretation based on the rod-length dependent entropic free energy barrier. The findings yield a principle, that is, length commensuration, for optimal design of rodlike particles with highly efficient transport in confined environments of macromolecular networks, and might enrich the physics of the diffusion dynamics in heterogeneous media.

Conformational Change of Transcription Factors from Search to Specific Binding: A lac Repressor Case Study

In a process known as facilitated diffusion, DNA-binding proteins find their target sites by combining three-dimensional diffusion and one-dimensional scanning of the DNA. Following the trade-off between speed and stability, agile exploration of DNA requires loose binding, whereas, at the DNA target site, the searching protein needs to establish tight interactions with the DNA. To enable both efficient search and stable binding, DNA-binding proteins and DNA often switch conformations upon recognition. Here, we study the one-dimensional diffusion and DNA binding of the dimeric lac repressor (LacI), which was reported to adopt two different conformations when binding different conformations of DNA. Using coarse-grained molecular dynamic simulations, we studied the diffusion and the sequence-specific binding of these conformations of LacI, as well as their truncated or monomeric variants, with two DNA conformations: straight and bent. The simulations were compared to experimental observables. This study supports that linear diffusion along DNA combines tight rotation-coupled groove tracking and rotation-decoupled hopping, where the protein briefly dissociates and reassociates just a few base pairs away. Tight groove tracking is crucial for target-site recognition, while hopping speeds up the overall search process. We investigated the diffusion of different LacI conformations on DNA and show how the flexibility of LacI's hinge regions ensures agility on DNA as well as faithful groove tracking. If the hinge regions instead form α-helices at the protein-DNA interface, tight groove tracking is not possible. On the contrary, the helical hinge region is essential for tight binding to bent, specific DNA, for the formation of the specific complex. Based on our study of different encounter complexes, we argue that the conformational change in LacI and DNA bending are somewhat coupled. Our findings underline the importance of two distinct protein conformations for facilitated diffusion and specific binding, respectively.

Dynamic and facilitated binding of topoisomerase accelerates topological relaxation

How type 2 Topoisomerase (TopoII) proteins relax and simplify the topology of DNA molecules is one of the most intriguing open questions in genome and DNA biophysics. Most of the existing models neglect the dynamics of TopoII which is expected of proteins searching their targets via facilitated diffusion. Here, we show that dynamic binding of TopoII speeds up the topological relaxation of knotted substrates by enhancing the search of the knotted arc. Intriguingly, this in turn implies that the timescale of topological relaxation is virtually independent of the substrate length. We then discover that considering binding biases due to facilitated diffusion on looped substrates steers the sampling of the topological space closer to the boundaries between different topoisomers yielding an optimally fast topological relaxation. We discuss our findings in the context of topological simplification in vitro and in vivo.

The nanocaterpillar's random walk: diffusion with ligand-receptor contacts

Particles with ligand-receptor contacts bind and unbind fluctuating "legs" to surfaces, whose fluctuations cause the particle to diffuse. Quantifying the diffusion of such "nanoscale caterpillars" is a challenge, since binding events often occur on very short time and length scales. Here we derive an analytical formula, validated by simulations, for the long time translational diffusion coefficient of an overdamped nanocaterpillar, under a range of modeling assumptions. We demonstrate that the effective diffusion coefficient, which depends on the microscopic parameters governing the legs, can be orders of magnitude smaller than the background diffusion coefficient. Furthermore it varies rapidly with temperature, and reproduces the striking variations seen in existing data and our own measurements of the diffusion of DNA-coated colloids. Our model gives insight into the mechanism of motion, and allows us to ask: when does a nanocaterpillar prefer to move by sliding, where one leg is always linked to the surface, and when does it prefer to move by hopping, which requires all legs to unbind simultaneously? We compare a range of systems (viruses, molecular motors, white blood cells, protein cargos in the nuclear pore complex, bacteria such as Escherichia coli, and DNA-coated colloids) and present guidelines to control the mode of motion for materials design.

DNA Looping and DNA Conformational Fluctuations Can Accelerate Protein Target Search

Protein searching and binding to specific sites on DNA is a fundamentally important process that marks the beginning of all major cellular transformations. While the dynamics of protein-DNA interactions in in vitro settings is well investigated, the situation is much more complex for in vivo conditions because the DNA molecules in live cells are packed into chromosomal structures where they are undergoing strong dynamic and conformational fluctuations. In this work, we present a theoretical investigation on the role of DNA looping and DNA conformational fluctuations in the protein target search. It is based on a discrete-state stochastic analysis that allows for explicit calculations of dynamic properties, which is also supplemented by Monte Carlo computer simulations. It is found that for stronger nonspecific interactions between DNA and proteins the search occurs faster on the DNA looped conformation in comparison with the unlooped conformation, and the fastest search is observed when the loop is formed near the target site. It is also shown that DNA fluctuations between the looped and unlooped conformations influence the search dynamics, and this depends on the magnitude of conformational transition rates and on which conformation is more energetically stable. Physical-chemical arguments explaining these observations are presented. Our theoretical study suggests that the geometry and conformational changes in DNA are additional factors that might efficiently control the gene regulation processes.

Dynamics of chromosomal target search by a membrane-integrated one-component receptor

Membrane proteins account for about one third of the cellular proteome, but it is still unclear how dynamic they are and how they establish functional contacts with cytoplasmic interaction partners. Here, we consider a membrane-integrated one-component receptor that also acts as a transcriptional activator, and analyze how it kinetically locates its specific binding site on the genome. We focus on the case of CadC, the pH receptor of the acid stress response Cad system in E. coli. CadC is a prime example of a one-component signaling protein that directly binds to its cognate target site on the chromosome to regulate transcription. We combined fluorescence microscopy experiments, mathematical analysis, and kinetic Monte Carlo simulations to probe this target search process. Using fluorescently labeled CadC, we measured the time from activation of the receptor until successful binding to the DNA in single cells, exploiting that stable receptor-DNA complexes are visible as fluorescent spots. Our experimental data indicate that CadC is highly mobile in the membrane and finds its target by a 2D diffusion and capture mechanism. DNA mobility is constrained due to the overall chromosome organization, but a labeled DNA locus in the vicinity of the target site appears sufficiently mobile to randomly come close to the membrane. Relocation of the DNA target site to a distant position on the chromosome had almost no effect on the mean search time, which was between four and five minutes in either case. However, a mutant strain with two binding sites displayed a mean search time that was reduced by about a factor of two. This behavior is consistent with simulations of a coarse-grained lattice model for the coupled dynamics of DNA within a cell volume and proteins on its surface. The model also rationalizes the experimentally determined distribution of search times. Overall our findings reveal that DNA target search does not present a much bigger kinetic challenge for membrane-integrated proteins than for cytoplasmic proteins. More generally, diffusion and capture mechanisms may be sufficient for bacterial membrane proteins to establish functional contacts with cytoplasmic targets.

Adaptation to changing environments is vital to bacteria and is enabled by sophisticated signal transduction systems. While signal transduction by two-component systems is well studied, the signal transduction of membrane-integrated one-component systems, where one protein performs both sensing and response regulation, are insufficiently understood. How can a membrane-integrated protein bind to specific sites on the genome to regulate transcription? Here, we study the kinetics of this process, which involves both protein diffusion within the membrane and conformational fluctuations of the genomic DNA. A well-suited model system for this question is CadC, the signaling protein of the E. coli Cad system involved in pH stress response. Fluorescently labeled CadC forms visible spots in single cells upon stable DNA-binding, marking the end of the protein-DNA search process. Moreover, the start of the search is triggered by a medium shift exposing cells to pH stress. We probe the underlying mechanism by varying the number and position of DNA target sites. We combine these experiments with mathematical analysis and kinetic Monte Carlo simulations of lattice models for the search process. Our results suggest that CadC diffusion in the membrane is pivotal for this search, while the DNA target site is just mobile enough to reach the membrane.

Precise sequencing of single protected-DNA fragment molecules for profiling of protein distribution and assembly on DNA

Multiple DNA-interacting protein molecules are often dynamically distributed and/or assembled along a DNA molecule to adapt to their intricate functions temporally. However, analytical technology for measuring such binding behaviours is still missing. Here, we demonstrate the unique capacity of a supernuclease for a highly efficient cutting of the unprotected-DNA segments and with complete preservation of the protein-occluded DNA segments at near single-nucleotide resolution. By exploring this high-resolution cutting, an unprecedented assay that allows a precise sequencing of single protected-DNA fragment molecules (SPDFMS) was developed. As relevant applications, relevant information was gained on the respective distribution/assembly patterns and coordinated displacement of single-stranded DNA-binding protein and recombinase RecA, two model proteins, on DNA. Benefiting from this assay, we also for the first time provide direct measurement of the length of single RecA nucleofilaments, showing the predominant stoichiometry of 5-7 RecA monomers per RecA nucleofilament under physiologically relevant conditions. This innovative assay appears as a promising analytical tool for studying diverse protein-DNA interactions implicated in DNA replication, transcription, recombination, repair, and gene editing.

Protein-DNA target search relies on quantum walk

Protein-DNA interactions play a fundamental role in all life systems. A critical issue of such interactions is given by the strategy of protein search for specific targets on DNA. The mechanisms by which the protein are able to find relatively small cognate sequences, typically 15-20 base pairs (bps) for repressors, and 4-6 bps for restriction enzymes among the millions of bp of non-specific chromosomal DNA have hardly engaged researchers for decades. Recent experimental studies have generated new insights on the basic processes of protein-DNA interactions evidencing the underlying complex dynamic phenomena involved, which combine three-dimensional and one-dimensional motion along the DNA chain. It has been demonstrated that protein molecules have an extraordinary ability to find the target very quickly on the DNA chain, in some cases, with two orders of magnitude faster than the diffusion limit. This unique property of protein-DNA search mechanism is known as facilitated diffusion. Several theoretical mechanisms have been suggested to describe the origin of facilitated diffusion. However, none of such models currently has the ability to fully describe the protein search strategy. In this paper, we suggest that the ability of proteins to identify consensus sequences on DNA is based on the entanglement of π-π electrons between DNA nucleotides and protein amino acids. The π-π entanglement is based on Quantum Walk (QW), through Coin-position entanglement (CPE). First, the protein identifies a dimer belonging to the consensus sequence, and localize a π on such dimer, hence, the other π electron scans the DNA chain until the sequence is identified. Focusing on the example of recognition of consensus sequences of EcoRV or EcoRI, we will describe the quantum features of QW on protein-DNA complexes during the search strategy, such as walker quadratic spreading on a coherent superposition of different vertices and environment-supported long-time survival probability of the walker. We will employ both discrete- or continuous-time versions of QW. Biased and unbiased classical Random Walk (CRW) have been used for a long time to describe the Protein-DNA search strategy. QW, the quantum version of CRW, has been widely studied for its applications in quantum information applications. In our biological application, the walker (the protein) resides at a vertex in a graph (the DNA structural topology). Differently to CRW, where the walker moves randomly, the quantum walker can hop along the edges in the graph to reach other vertices entering coherently a superposition across different vertices spreading quadratically faster than CRW analogous evidencing the typical speed up features of the QW. When applied to a protein-DNA target search problem, QW gives the possibility to achieve the experimental diffusional motion of proteins over diffusion classical limits experienced along DNA chains exploiting quantum features such as CPE and long-time survival probability supported by the environment. In turn, we come to the conclusion that, under quantum picture, the protein search strategy does not distinguish between one-dimensional (1D) and three-dimensional (3D) cases.

Diffusion of DNA-Binding Species in the Nucleus: A Transient Anomalous Subdiffusion Model

Single-particle tracking experiments have measured escape times of DNA-binding species diffusing in living cells: CRISPR-Cas9, TetR, and LacI. The observed distribution is a truncated power law. Working backward from the experimental results, the observed distribution appears inconsistent with a Gaussian distribution of binding energies. Working forward, the observed distribution leads to transient anomalous subdiffusion, in which diffusion is anomalous at short times and normal at long times, here only mildly anomalous. Monte Carlo simulations are used to characterize the time-dependent diffusion coefficient D(t) in terms of the anomalous exponent α, the crossover time tcross, and the limits D(0) and D(∞) and to relate these quantities to the escape time distribution. The simplest interpretations identify the escape time as the actual binding time to DNA or the period of one-dimensional diffusion on DNA in the standard model combining one-dimensional and three-dimensional search, but a more complicated interpretation may be required. The model has several implications for cell biophysics. 1) The initial anomalous regime represents the search of the DNA-binding species for its target DNA sequence. 2) Non-target DNA sites have a significant effect on search kinetics. False positives in bioinformatic searches of the genome are potentially rate-determining in vivo. For simple binding, the search would be speeded if false-positive sequences were eliminated from the genome. 3) Both binding and obstruction affect diffusion. Obstruction ought to be measured directly, using as the primary probe the DNA-binding species with the binding site inactivated and eGFP as a calibration standard among laboratories and cell types. 4) Overexpression of the DNA-binding species reduces anomalous subdiffusion because the deepest binding sites are occupied and unavailable. 5) The model provides a coarse-grained phenomenological description of diffusion of a DNA-binding species, useful in larger-scale modeling of kinetics, FCS, and FRAP.

CRISPR-Cas9 Genome Interrogation: A Facilitated Subdiffusive Target Search Strategy

The functional application of RNA-guided CRISPR-associated Cas9 protein, a bacterial immune system-based protein complex, via which in vivo, highly specific, and well-regulated, gene-editing processes are being monitored at an unprecedented level, has led to remarkable progress in genetic engineering and technology. The complicated in vivo process of genome interrogation followed by gene editing by the Cas9 complex was recently reported by Knight et al. (Science, 2015, 350, 823-826) using an elegant single-particle tracking method, aided by the two-photon fluorescence correlation spectroscopic technique. In contrast to the usually observed fast target-searching and protein-binding events in biophysical systems, an interesting slow genome-interrogation process by the RNA-guided CRISPR-Cas9 system through a crowded chromatin environment of a mammalian cell has been revealed in Knight et al.'s study. Motivated by this experiment, in this paper, we provide a generalized theoretical framework to capture this particular target-searching mechanism of the CRISPR-Cas9 protein complex. We show that an analysis on the basis of 3D subdiffusion under a cylindrical volume, created by several nonspecific off-target interactions from the DNA strands, can capture the essential details of the process. Moreover, on the basis of this model, we quantify the dynamics of this process and estimate the survival probability, first passage time, and the intensity correlation function of the tagged proteins of the experiment. The results from our theoretical predictions are found to be consistent with the experimental observations, and hence, seem to provide a plausible microscopic picture of the process.

Extreme events in stochastic transport on networks

Extreme events are emergent phenomena in multi-particle transport processes on complex networks. In practice, such events could range from power blackouts to call drops in cellular networks to traffic congestion on roads. All the earlier studies of extreme events on complex networks had focused only on the nodal events. If random walks are used to model the transport process on a network, it is known that degree of the nodes determines the extreme event properties. In contrast, in this work, it is shown that extreme events on the edges display a distinct set of properties from that of the nodes. It is analytically shown that the probability for the occurrence of extreme events on an edge is independent of the degree of the nodes linked by the edge and is dependent only on the total number of edges on the network and the number of walkers on it. Further, it is also demonstrated that non-trivial correlations can exist between the extreme events on the nodes and the edges. These results are in agreement with the numerical simulations on synthetic and real-life networks.

eGFRD in all dimensions

Biochemical reactions often occur at low copy numbers but at once in crowded and diverse environments. Space and stochasticity therefore play an essential role in biochemical networks. Spatial-stochastic simulations have become a prominent tool for understanding how stochasticity at the microscopic level influences the macroscopic behavior of such systems. While particle-based models guarantee the level of detail necessary to accurately describe the microscopic dynamics at very low copy numbers, the algorithms used to simulate them typically imply trade-offs between computational efficiency and biochemical accuracy. eGFRD (enhanced Green's Function Reaction Dynamics) is an exact algorithm that evades such trade-offs by partitioning the N-particle system into M ≤ N analytically tractable one- and two-particle systems; the analytical solutions (Green's functions) then are used to implement an event-driven particle-based scheme that allows particles to make large jumps in time and space while retaining access to their state variables at arbitrary simulation times. Here we present "eGFRD2," a new eGFRD version that implements the principle of eGFRD in all dimensions, thus enabling efficient particle-based simulation of biochemical reaction-diffusion processes in the 3D cytoplasm, on 2D planes representing membranes, and on 1D elongated cylinders representative of, e.g., cytoskeletal tracks or DNA; in 1D, it also incorporates convective motion used to model active transport. We find that, for low particle densities, eGFRD2 is up to 6 orders of magnitude faster than conventional Brownian dynamics. We exemplify the capabilities of eGFRD2 by simulating an idealized model of Pom1 gradient formation, which involves 3D diffusion, active transport on microtubules, and autophosphorylation on the membrane, confirming recent experimental and theoretical results on this system to hold under genuinely stochastic conditions.

Disparity in anomalous diffusion of proteins searching for their target DNA sites in a crowded medium is controlled by the size, shape and mobility of macromolecular crowders

Using extensive computer simulations, we analyzed the role of physical properties of molecular crowding agents such as size, shape and mobility in the target search dynamics of DNA binding proteins. Our main result is that the sub-diffusive dynamics of a protein inside a crowded medium strongly depends on the crowder properties and also on the protein's mode of diffusion. For instance, while scanning the DNA one-dimensionally, the protein dynamics does not vary with the change in crowder properties. Conversely, the diffusion exponent varies non-monotonically during 3D diffusion and is maximally affected when the crowders match the protein physically. The investigation shows that the effect stems from the ruggedness of the associated potential energy landscape, which is regulated by the protein-crowder and DNA-crowder interactions. Our findings have broad significance in understanding the target search dynamics of proteins on DNA in crowded cellular milieu and selecting appropriate crowding agents when designing in vitro experiments.

Fluctuations of random walks in critical random environments

Percolation networks have been widely used in the description of porous media but are now found to be relevant to understand the motion of particles in cellular membranes or the nucleus of biological cells. Random walks on the infinite cluster at criticality of a percolation network are asymptotically ergodic. On any finite size cluster of the network stationarity is reached at finite times, depending on the cluster's size. Despite of this we here demonstrate by combination of analytical calculations and simulations that at criticality the disorder and cluster size average of the ensemble of clusters leads to a non-vanishing variance of the time averaged mean squared displacement, regardless of the measurement time. Fluctuations of this relevant experimental quantity due to the disorder average of such ensembles are thus persistent and non-negligible. The relevance of our results for single particle tracking analysis in complex and biological systems is discussed.

The dynamics of the monomeric restriction endonuclease BcnI during its interaction with DNA

Endonucleases that generate DNA double strand breaks often employ two independent subunits such that the active site from each subunit cuts either DNA strand. Restriction enzyme BcnI is a remarkable exception. It binds to the 5΄-CC/SGG-3΄ (where S = C or G, ‘/’ designates the cleavage position) target as a monomer forming an asymmetric complex, where a single catalytic center approaches the scissile phosphodiester bond in one of DNA strands. Bulk kinetic measurements have previously shown that the same BcnI molecule cuts both DNA strands at the target site without dissociation from the DNA. Here, we analyse the BcnI DNA binding and target recognition steps at the single molecule level. We find, using FRET, that BcnI adopts either ‘open’ or ‘closed’ conformation in solution. Next, we directly demonstrate that BcnI slides over long distances on DNA using 1D diffusion and show that sliding is accompanied by occasional jumping events, where the enzyme leaves the DNA and rebinds immediately at a distant site. Furthermore, we quantify the dynamics of the BcnI interactions with cognate and non-cognate DNA, and determine the preferred binding orientation of BcnI to the target site. These results provide new insights into the intricate dynamics of BcnI–DNA interactions.

Unraveling intermittent features in single-particle trajectories by a local convex hull method

We propose a model-free method to detect change points between distinct phases in a single random trajectory of an intermittent stochastic process. The local convex hull (LCH) is constructed for each trajectory point, while its geometric properties (e.g., the diameter or the volume) are used as discriminators between phases. The efficiency of the LCH method is validated for six models of intermittent motion, including Brownian motion with different diffusivities or drifts, fractional Brownian motion with different Hurst exponents, and surface-mediated diffusion. We discuss potential applications of the method for detection of active and passive phases in the intracellular transport, temporal trapping or binding of diffusing molecules, alternating bulk and surface diffusion, run and tumble (or search) phases in the motion of bacteria and foraging animals, and instantaneous firing rates in neurons.

Bulk-mediated surface transport in the presence of bias

Surface transport, when the particle is allowed to leave the surface, travel in the bulk for some time, and then return to the surface, is referred to as bulk-mediated surface transport. Recently, we proposed a formalism that significantly simplifies analysis of bulk-mediated surface diffusion [A. M. Berezhkovskii, L. Dagdug, and S. M. Bezrukov, J. Chem. Phys. 143, 084103 (2015)]. Here this formalism is extended to bulk-mediated surface transport in the presence of bias, i.e., when the particle has arbitrary drift velocities on the surface and in the bulk. A key advantage of our approach is that the transport problem reduces to that of a two-state problem of the particle transitions between the surface and the bulk. The latter can be solved with relative ease. The formalism is used to find the Laplace transforms of the first two moments of the particle displacement over the surface in time t at arbitrary values of the particle drift velocities and diffusivities on the surface and in the bulk. This allows us to analyze in detail the time dependence of the effective drift velocity of the particle on the surface, which can be highly nontrivial.

How nonspecifically DNA-binding proteins search for the target in crowded environments

We investigate how a tracer particle searches a target located in DNA modeled by a stiff chain in crowded environments using theoretical analysis and Langevin dynamics simulations. First, we show that the three-dimensional (3D) diffusion coefficient of the tracer only depends on the density of crowders ϕ, while its one-dimensional (1D) diffusion coefficient is affected by not only ϕ but also the nonspecific binding energy ε. With increasing ϕ and ε, no obvious change in the average 3D diffusion time is observed, while the average 1D sliding time apparently increases. We propose theoretically that the 1D sliding of the tracer along the chain could be well captured by the Kramers' law of escaping rather than the Arrhenius law, which is verified directly by the simulations. Finally, the average search time increases monotonously with an increase in ϕ while it has a minimum as a function of ε, which could be understood from the different behaviors of the average number of search rounds with the increasing ϕ or ε. These results provide a deeper understanding of the role of facilitated diffusion in target search of proteins on DNA in vivo.

Rad4 recognition-at-a-distance: Physical basis of conformation-specific anomalous diffusion of DNA repair proteins

Since Robert Brown's first observations of random walks by pollen particles suspended in solution, the concept of diffusion has been subject to countless theoretical and experimental studies in diverse fields from finance and social sciences, to physics and biology. Diffusive transport of macromolecules in cells is intimately linked to essential cellular functions including nutrient uptake, signal transduction, gene expression, as well as DNA replication and repair. Advancement in experimental techniques has allowed precise measurements of these diffusion processes. Mathematical and physical descriptions and computer simulations have been applied to model complicated biological systems in which anomalous diffusion, in addition to simple Brownian motion, was observed. The purpose of this review is to provide an overview of the major physical models of anomalous diffusion and corresponding experimental evidence on the target search problem faced by DNA-binding proteins, with an emphasis on DNA repair proteins and the role of anomalous diffusion in DNA target recognition.

Influence of external potentials on heterogeneous diffusion processes

In this paper we consider heterogeneous diffusion processes with the power-law dependence of the diffusion coefficient on the position and investigate the influence of external forces on the resulting anomalous diffusion. The heterogeneous diffusion processes can yield subdiffusion as well as superdiffusion, depending on the behavior of the diffusion coefficient. We assume that not only the diffusion coefficient but also the external force has a power-law dependence on the position. We obtain analytic expressions for the transition probability in two cases: when the power-law exponent in the external force is equal to 2η-1, where 2η is the power-law exponent in the dependence of the diffusion coefficient on the position, and when the external force has a linear dependence on the position. We found that the power-law exponent in the dependence of the mean square displacement on time does not depend on the external force; this force changes only the anomalous diffusion coefficient. In addition, the external force having the power-law exponent different from 2η-1 limits the time interval where the anomalous diffusion occurs. We expect that the results obtained in this paper may be relevant for a more complete understanding of anomalous diffusion processes.

A matter of time - How transient transcription factor interactions create dynamic gene regulatory networks

Dynamic reprogramming of transcriptional networks enables cells to adapt to a changing environment. Thus, it is crucial not only to understand what gene targets are regulated by a transcription factor (TF) but also when. This review explores the way TFs function with respect to time, paying particular attention to discoveries made in plants - where coordinated, genome-wide responses to environmental change is crucial to the survival of these sessile organisms. We investigate the molecular mechanisms that mediate transient TF-DNA binding, and assess how these rapid and dynamic interactions translate to long-term temporal regulation of genomes. We also discuss how current molecular techniques can catch, and sometimes miss, transient TF-target interactions that underlie dynamic cellular responses. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

Geometry controlled anomalous diffusion in random fractal geometries: looking beyond the infinite cluster

We investigate the ergodic properties of a random walker performing (anomalous) diffusion on a random fractal geometry. Extensive Monte Carlo simulations of the motion of tracer particles on an ensemble of realisations of percolation clusters are performed for a wide range of percolation densities. Single trajectories of the tracer motion are analysed to quantify the time averaged mean squared displacement (MSD) and to compare this with the ensemble averaged MSD of the particle motion. Other complementary physical observables associated with ergodicity are studied, as well. It turns out that the time averaged MSD of individual realisations exhibits non-vanishing fluctuations even in the limit of very long observation times as the percolation density approaches the critical value. This apparent non-ergodic behaviour concurs with the ergodic behaviour on the ensemble averaged level. We demonstrate how the non-vanishing fluctuations in single particle trajectories are analytically expressed in terms of the fractal dimension and the cluster size distribution of the random geometry, thus being of purely geometrical origin. Moreover, we reveal that the convergence scaling law to ergodicity, which is known to be inversely proportional to the observation time T for ergodic diffusion processes, follows a power-law ∼T(-h) with h < 1 due to the fractal structure of the accessible space. These results provide useful measures for differentiating the subdiffusion on random fractals from an otherwise closely related process, namely, fractional Brownian motion. Implications of our results on the analysis of single particle tracking experiments are provided.

A new approach to the problem of bulk-mediated surface diffusion

This paper is devoted to bulk-mediated surface diffusion of a particle which can diffuse both on a flat surface and in the bulk layer above the surface. It is assumed that the particle is on the surface initially (at t = 0) and at time t, while in between it may escape from the surface and come back any number of times. We propose a new approach to the problem, which reduces its solution to that of a two-state problem of the particle transitions between the surface and the bulk layer, focusing on the cumulative residence times spent by the particle in the two states. These times are random variables, the sum of which is equal to the total observation time t. The advantage of the proposed approach is that it allows for a simple exact analytical solution for the double Laplace transform of the conditional probability density of the cumulative residence time spent on the surface by the particle observed for time t. This solution is used to find the Laplace transform of the particle mean square displacement and to analyze the peculiarities of its time behavior over the entire range of time. We also establish a relation between the double Laplace transform of the conditional probability density and the Fourier-Laplace transform of the particle propagator over the surface. The proposed approach treats the cases of both finite and infinite bulk layer thicknesses (where bulk-mediated surface diffusion is normal and anomalous at asymptotically long times, respectively) on equal footing.

Molecular crowding effect on dynamics of DNA-binding proteins search for their targets

DNA-binding proteins locate and bind their target sequences positioned on DNA in crowded environments, but the molecular crowding effect on this search process is not clear. Using analytical techniques and Langevin dynamics simulations in two dimensions (2D), we find that the essential physics for facilitated diffusion in 2D search and 3D search is the same. We observe that the average search times have minima at the same optimal nonspecific binding energy for the cases with and without the crowding particle. Moreover, the molecular crowding increases the search time by increasing the average search rounds and the one-dimensional (1D) sliding time of a round, but almost not changing the average 2D diffusion time of a round. In addition, the fraction of 1D sliding time out of the total search time increases with increasing the concentration of crowders. For 2D diffusion, the molecular crowding decreases the jumping length and narrows its distribution due to the cage effect from crowders. These results shed light on the role of facilitated diffusion in DNA targeting kinetics in living cells.

Method for the analysis of contribution of sliding and hopping to a facilitated diffusion of DNA-binding protein: Application to in vivo data

DNA-binding protein searches for its target, a specific site on DNA, by means of diffusion. The search process consists of many recurrent steps of one-dimensional diffusion (sliding) along the DNA chain and three-dimensional diffusion (hopping) after dissociation of a protein from the DNA chain. Here we propose a computational method that allows extracting the contribution of sliding and hopping to the search process in vivo from the measurements of the kinetics of the target search by the lac repressor in Escherichia coli [P. Hammar et al., Science 336, 1595 (2012)]. The method combines lattice Monte Carlo simulations with the Brownian excursion theory and includes explicitly steric constraints for hopping due to the helical structure of DNA. The simulation results including all experimental data reveal that the in vivo target search is dominated by sliding. The short-range hopping to the same base pair interrupts one-dimensional sliding while long-range hopping does not contribute significantly to the kinetics of the search of the target in vivo.

Analytical representations of the spread harmonic measure density

We study the spread harmonic measure that characterizes the spatial distribution of reaction events on a partially reactive surface. For Euclidean domains in which Brownian motion can be split into independent lateral and transverse displacements, we derive analytical formulas for the spread harmonic measure density and analyze its asymptotic behavior. This analysis is applicable to slab domains, general cylindrical domains, and a half-space. We investigate the spreading effect due to multiple reflections on the surface, and the underlying role of finite reactivity. We discuss further extensions and applications of analytical results to describe Laplacian transfer phenomena such as permeation through semipermeable membranes, secondary current distribution on partially blocking electrodes, and surface relaxation in nuclear magnetic resonance.

What matters for lac repressor search in vivo--sliding, hopping, intersegment transfer, crowding on DNA or recognition?

We have investigated which aspects of transcription factor DNA interactions are most important to account for the recent in vivo search time measurements for the dimeric lac repressor. We find the best agreement for a sliding model where non-specific binding to DNA is improbable at first contact and the sliding LacI protein binds at high probability when reaching the specific O_sym operator. We also find that the contribution of hopping to the overall search speed is negligible although physically unavoidable. The parameters that give the best fit reveal sliding distances, including hopping, close to what has been proposed in the past, i.e. ∼40 bp, but with an unexpectedly high 1D diffusion constant on non-specific DNA sequences. Including a mechanism of inter-segment transfer between distant DNA segments does not bring down the 1D diffusion to the expected fraction of the in vitro value. This suggests a mechanism where transcription factors can slide less hindered in vivo than what is given by a simple viscosity scaling argument or that a modification of the model is needed. For example, the estimated diffusion rate constant would be consistent with the expectation if parts of the chromosome, away from the operator site, were inaccessible for searching.

Weak ergodicity breaking and ageing in anomalous diffusion

Modern single particle tracking techniques and many large scale simulations produce time series r(t) of the position of a tracer particle. Standardly these are evaluated in terms of the time averaged mean squared displacement. For ergodic processes such as Brownian motion, one can interpret the results of such an analysis in terms of the known theories for the corresponding ensemble averaged mean squared displacement, if only the measurement time is sufficiently long. In anomalous diffusion processes, that are widely observed over many orders of magnitude, the equivalence between (long) time and ensemble averages may be broken (weak ergodicity breaking). In such cases the time averages may no longer be interpreted in terms of ensemble theories. Here we collect some recent results on weakly non-ergodic systems with respect to the time averaged mean squared displacement and the inherent irreproducibility of individual measurements. We also address the phenomenon of ageing, the dependence of physical observables on the time span between initial preparation of the system and the start of the measurement.

Search by proteins for their DNA target site: 2. The effect of DNA conformation on the dynamics of multidomain proteins

Multidomain transcription factors, which are especially abundant in eukaryotic genomes, are advantageous to accelerate the search kinetics for target site because they can follow the intersegment transfer via the monkey-bar mechanism in which the protein forms a bridged intermediate between two distant DNA regions. Monkey-bar dynamics highly depends on the properties of the multidomain protein (the affinity of each of the constituent domains to the DNA and the length of the linker) and the DNA molecules (their inter-distance and inter-angle). In this study, we investigate using coarse-grained molecular dynamics simulations how the local conformation of the DNA may affect the DNA search performed by a multidomain protein Pax6 in comparison to that of the isolated domains. Our results suggest that in addition to the common rotation-coupled translation along the DNA major groove, for curved DNA the tethered domains may slide in a rotation-decoupled sliding mode. Furthermore, the multidomain proteins move by longer jumps on curved DNA compared with those performed by the single domain protein. The long jumps originate from the DNA curvature bringing two sequentially distant DNA sites into close proximity with each other and they suggest that multidomain proteins may move on highly curved DNA faster than linear DNA.

An integrated model of transcription factor diffusion shows the importance of intersegmental transfer and quaternary protein structure for target site finding

We present a computational model of transcription factor motion that explains both the observed rapid target finding of transcription factors, and how this motion influences protein and genome structure. Using the Smoldyn software, we modelled transcription factor motion arising from a combination of unrestricted 3D diffusion in the nucleoplasm, sliding along the DNA filament, and transferring directly between filament sections by intersegmental transfer. This presents a fine-grain picture of the way in which transcription factors find their targets two orders of magnitude faster than 3D diffusion alone allows. Eukaryotic genomes contain sections of nucleosome free regions (NFRs) around the promoters; our model shows that the presence and size of these NFRs can be explained as their acting as antennas on which transcription factors slide to reach their targets. Additionally, our model shows that intersegmental transfer may have shaped the quaternary structure of transcription factors: sequence specific DNA binding proteins are unusually enriched in dimers and tetramers, perhaps because these allow intersegmental transfer, which accelerates target site finding. Finally, our model shows that a ‘hopping’ motion can emerge from 3D diffusion on small scales. This explains the apparently long sliding lengths that have been observed for some DNA binding proteins observed in vitro. Together, these results suggest that transcription factor diffusion dynamics help drive the evolution of protein and genome structure.

Solution structure and intramolecular exchange of methyl-cytosine binding domain protein 4 (MBD4) on DNA suggests a mechanism to scan for mCpG/TpG mismatches

Unlike other members of the methyl-cytosine binding domain (MBD) family, MBD4 serves as a potent DNA glycosylase in DNA mismatch repair specifically targeting ^mCpG/TpG mismatches arising from spontaneous deamination of methyl-cytosine. The protein contains an N-terminal MBD (MBD4_MBD) and a C-terminal glycosylase domain (MBD4_GD) separated by a long linker. This arrangement suggests that the MBD4_MBD either directly augments enzymatic catalysis by the MBD4_GD or targets the protein to regions enriched for ^mCpG/TpG mismatches. Here we present structural and dynamic studies of MBD4_MBD bound to dsDNA. We show that MBD4_MBD binds with a modest preference for^mCpG as compared to mismatch, unmethylated and hydroxymethylated DNA. We find that while MBD4_MBD exhibits slow exchange between molecules of DNA (intermolecular exchange), the domain exhibits fast exchange between two sites in the same molecule of dsDNA (intramolecular exchange). Introducing a single-strand defect between binding sites does not greatly reduce the intramolecular exchange rate, consistent with a local hopping mechanism for moving along the DNA. These results support a model in which the MBD4_MBD4 targets the intact protein to ^mCpG islands and promotes scanning by rapidly exchanging between successive ^mCpG sites which facilitates repair of nearby ^mCpG/TpG mismatches by the glycosylase domain.

Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets

Background

The global effort to annotate the non-coding portion of the human genome relies heavily on chromatin immunoprecipitation data generated with high-throughput DNA sequencing (ChIP-seq). ChIP-seq is generally successful in detailing the segments of the genome bound by the immunoprecipitated transcription factor (TF), however almost all datasets contain genomic regions devoid of the canonical motif for the TF. It remains to be determined if these regions are related to the immunoprecipitated TF or whether, despite the use of controls, there is a portion of peaks that can be attributed to other causes.

Results

Analyses across hundreds of ChIP-seq datasets generated for sequence-specific DNA binding TFs reveal a small set of TF binding profiles for which predicted TF binding site motifs are repeatedly observed to be significantly enriched. Grouping related binding profiles, the set includes: CTCF-like, ETS-like, JUN-like, and THAP11 profiles. These frequently enriched profiles are termed ‘zingers’ to highlight their unanticipated enrichment in datasets for which they were not the targeted TF, and their potential impact on the interpretation and analysis of TF ChIP-seq data. Peaks with zinger motifs and lacking the ChIPped TF’s motif are observed to compose up to 45% of a ChIP-seq dataset. There is substantial overlap of zinger motif containing regions between diverse TF datasets, suggesting a mechanism that is not TF-specific for the recovery of these regions.

Conclusions

Based on the zinger regions proximity to cohesin-bound segments, a loading station model is proposed. Further study of zingers will advance understanding of gene regulation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0412-4) contains supplementary material, which is available to authorized users.

Androgen receptor complexes probe DNA for recognition sequences by short random interactions

Owing to the tremendous progress in microscopic imaging of fluorescently labeled proteins in living cells, the insight into the highly dynamic behavior of transcription factors has rapidly increased over the past decade. However, a consistent quantitative scheme of their action is still lacking. Using the androgen receptor (AR) as a model system, we combined three different fluorescence microscopy assays: single-molecule microscopy, photobleaching and correlation spectroscopy, to provide a quantitative model of the action of this transcription factor. This approach enabled us to distinguish two types of AR-DNA binding: very brief interactions, in the order of a few hundred milliseconds, and hormone-induced longer-lasting interactions, with a characteristic binding time of several seconds. In addition, freely mobile ARs were slowed down in the presence of hormone, suggesting the formation of large AR-co-regulator complexes in the nucleoplasm upon hormone activation. Our data suggest a model in which mobile hormone-induced complexes of transcription factors and co-regulators probe DNA by briefly binding at random sites, only forming relatively stable transcription initiation complexes when bound to specific recognition sequences.

Physical constraints determine the logic of bacterial promoter architectures

Site-specific transcription factors (TFs) bind to their target sites on the DNA, where they regulate the rate at which genes are transcribed. Bacterial TFs undergo facilitated diffusion (a combination of 3D diffusion around and 1D random walk on the DNA) when searching for their target sites. Using computer simulations of this search process, we show that the organization of the binding sites, in conjunction with TF copy number and binding site affinity, plays an important role in determining not only the steady state of promoter occupancy, but also the order at which TFs bind. These effects can be captured by facilitated diffusion-based models, but not by standard thermodynamics. We show that the spacing of binding sites encodes complex logic, which can be derived from combinations of three basic building blocks: switches, barriers and clusters, whose response alone and in higher orders of organization we characterize in detail. Effective promoter organizations are commonly found in the E. coli genome and are highly conserved between strains. This will allow studies of gene regulation at a previously unprecedented level of detail, where our framework can create testable hypothesis of promoter logic.

Anomalous diffusion models and their properties: non-stationarity, non-ergodicity, and ageing at the centenary of single particle tracking

This Perspective summarises the properties of a variety of anomalous diffusion processes and provides the necessary tools to analyse and interpret recorded anomalous diffusion data.

Binding-rebinding dynamics of proteins interacting nonspecifically with a long DNA molecule

We investigate how nonspecific interactions and unbinding-rebinding events give rise to a length- and conformation-dependent enhancement of the "macroscopic" dissociation time of proteins from a DNA, or in general for the release of ligands initially bound to a long polymer. By numerically simulating the release of ligands from polymers of different conformations, we show that the total dissociation time increases logarithmically with polymer length for an extended conformation, and as a power law for self-avoiding and compact conformations. For the latter two cases, the presence of self-avoidance acting between the diffusing ligands affects the power-law exponents. Our results are important in relating kinetic measurements of protein on- and off-rates for large DNAs to equilibrium affinities for a single binding site.

Intracellular facilitated diffusion: searchers, crowders, and blockers

In bacteria, regulatory proteins search for a specific DNA-binding target via "facilitated diffusion": a series of rounds of three-dimensional diffusion in the cytoplasm, and one-dimensional (1D) linear diffusion along the DNA contour. Using large scale Brownian dynamics simulations we find that each of these steps is affected differently by crowding proteins, which can either be bound to the DNA acting as a road block to the 1D diffusion, or freely diffusing in the cytoplasm. Macromolecular crowding can strongly affect mechanistic features such as the balance between three-dimensional and 1D diffusion, but leads to surprising robustness of the total search time.

Distance matters: the impact of gene proximity in bacterial gene regulation

Following recent discoveries of colocalization of downstream-regulating genes in living cells, the impact of the spatial distance between such genes on the kinetics of gene product formation is increasingly recognized. We here show from analytical and numerical analysis that the distance between a transcription factor (TF) gene and its target gene drastically affects the speed and reliability of transcriptional regulation in bacterial cells. For an explicit model system, we develop a general theory for the interactions between a TF and a transcription unit. The observed variations in regulation efficiency are linked to the magnitude of the variation of the TF concentration peaks as a function of the binding site distance from the signal source. Our results support the role of rapid binding site search for gene colocalization and emphasize the role of local concentration differences.

Optical Methods to Study Protein-DNA Interactions in Vitro and in Living Cells at the Single-Molecule Level

The maintenance of intact genetic information, as well as the deployment of transcription for specific sets of genes, critically rely on a family of proteins interacting with DNA and recognizing specific sequences or features. The mechanisms by which these proteins search for target DNA are the subject of intense investigations employing a variety of methods in biology. A large interest in these processes stems from the faster-than-diffusion association rates, explained in current models by a combination of 3D and 1D diffusion. Here, we present a review of the single-molecule approaches at the forefront of the study of protein-DNA interaction dynamics and target search in vitro and in vivo. Flow stretch, optical and magnetic manipulation, single fluorophore detection and localization as well as combinations of different methods are described and the results obtained with these techniques are discussed in the framework of the current facilitated diffusion model.

Computational models for large-scale simulations of facilitated diffusion

The binding of site-specific transcription factors to their genomic target sites is a key step in gene regulation. While the genome is huge, transcription factors belong to the least abundant protein classes in the cell. It is therefore fascinating how short the time frame is that they require to home in on their target sites. The underlying search mechanism is called facilitated diffusion and assumes a combination of three-dimensional diffusion in the space around the DNA combined with one-dimensional random walk on it. In this review, we present the current understanding of the facilitated diffusion mechanism and identify questions that lack a clear or detailed answer. One way to investigate these questions is through stochastic simulation and, in this manuscript, we support the idea that such simulations are able to address them. Finally, we review which biological parameters need to be included in such computational models in order to obtain a detailed representation of the actual process.

Facilitated diffusion on mobile DNA: configurational traps and sequence heterogeneity

We present Brownian dynamics simulations of the facilitated diffusion of a protein, modeled as a sphere with a binding site on its surface, along DNA, modeled as a semiflexible polymer. We consider both the effect of DNA organization in three dimensions and of sequence heterogeneity. We find that in a network of DNA loops, which are thought to be present in bacterial DNA, the search process is very sensitive to the spatial location of the target within such loops. Therefore, specific genes might be repressed or promoted by changing the local topology of the genome. On the other hand, sequence heterogeneity creates traps which normally slow down facilitated diffusion. When suitably positioned, though, these traps can, surprisingly, render the search process much more efficient.

Demethylation initiated by ROS1 glycosylase involves random sliding along DNA

Active DNA demethylation processes play a critical role in shaping methylation patterns, yet our understanding of the mechanisms involved is still fragmented and incomplete. REPRESSOR OF SILENCING 1 (ROS1) is a prototype member of a family of plant 5-methylcytosine DNA glycosylases that initiate active DNA demethylation through a base excision repair pathway. As ROS1 binds DNA non-specifically, we have critically tested the hypothesis that facilitated diffusion along DNA may contribute to target location by the enzyme. We have found that dissociation of ROS1 from DNA is severely restricted when access to both ends is obstructed by tetraloops obstacles. Unblocking any end facilitates protein dissociation, suggesting that random surface sliding is the main route to a specific target site. We also found that removal of the basic N-terminal domain of ROS1 significantly impairs the sliding capacity of the protein. Finally, we show that sliding increases the catalytic efficiency of ROS1 on 5-meC:G pairs, but not on T:G mispairs, thus suggesting that the enzyme achieves recognition and excision of its two substrate bases by different means. A model is proposed to explain how ROS1 finds its potential targets on DNA.