Classes of fast and specific search mechanisms for proteins on DNA

Optimal search in E. coli chemotaxis

We study chemotaxis of a single E. coli bacterium in a medium where the nutrient chemical is also undergoing diffusion and its concentration has the form of a Gaussian whose width increases with time. We measure the average first passage time of the bacterium at a region of high nutrient concentration. In the limit of very slow nutrient diffusion, the bacterium effectively experiences a Gaussian concentration profile with a fixed width. In this case we find that there exists an optimum width of the Gaussian when the average first passage time is minimum, i.e., the search process is most efficient. We verify the existence of the optimum width for the deterministic initial position of the bacterium and also for the stochastic initial position, drawn from uniform and steady state distributions. Our numerical simulation in a model of a non-Markovian random walker agrees well with our analytical calculations in a related coarse-grained model. We also present our simulation results for the case when the nutrient diffusion and bacterial motion occur over comparable time scales and the bacterium senses a time-varying concentration field.

Chromatin fiber allostery and the epigenetic code

The notion of allostery introduced for proteins about fifty years ago has been extended since then to DNA allostery, where a locally triggered DNA structural transition remotely controls other DNA-binding events. We further extend this notion and propose that chromatin fiber allosteric transitions, induced by histone-tail covalent modifications, may play a key role in transcriptional regulation. We present an integrated scenario articulating allosteric mechanisms at different scales: allosteric transitions of the condensed chromatin fiber induced by histone-tail acetylation modify the mechanical constraints experienced by the embedded DNA, thus possibly controlling DNA-binding of allosteric transcription factors or further allosteric mechanisms at the linker DNA level. At a higher scale, different epigenetic constraints delineate different statistically dominant subsets of accessible chromatin fiber conformations, which each favors the assembly of dedicated regulatory complexes, as detailed on the emblematic example of the mouse Igf2-H19 gene locus and its parental imprinting. This physical view offers a mechanistic and spatially structured explanation of the observed correlation between transcriptional activity and histone modifications. The evolutionary origin of allosteric control supports to speak of an 'epigenetic code', by which events involved in transcriptional regulation are encoded in histone modifications in a context-dependent way.

A simple model for DNA bridging proteins and bacterial or human genomes: bridging-induced attraction and genome compaction

We present computer simulations of the phase behaviour of an ensemble of proteins interacting with a polymer, mimicking non-specific binding to a piece of bacterial DNA or eukaryotic chromatin. The proteins can simultaneously bind to the polymer in two or more places to create protein bridges. Despite the lack of any explicit interaction between the proteins or between DNA segments, our simulations confirm previous results showing that when the protein-polymer interaction is sufficiently strong, the proteins come together to form clusters. Furthermore, a sufficiently large concentration of bridging proteins leads to the compaction of the swollen polymer into a globular phase. Here we characterise both the formation of protein clusters and the polymer collapse as a function of protein concentration, protein-polymer affinity and fibre flexibility.

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.

RecA-mediated sequence homology recognition as an example of how searching speed in self-assembly systems can be optimized by balancing entropic and enthalpic barriers

Ideally, self-assembly should rapidly and efficiently produce stable correctly assembled structures. We study the tradeoff between enthalpic and entropic cost in self-assembling systems using RecA-mediated homology search as an example. Earlier work suggested that RecA searches could produce stable final structures with high stringency using a slow testing process that follows an initial rapid search of ∼9-15 bases. In this work, we will show that as a result of entropic and enthalpic barriers, simultaneously testing all ∼9-15 bases as separate individual units results in a longer overall searching time than testing them in groups and stages.

Accelerating search kinetics by following boundaries

We derive exact expressions of the mean first-passage time to a bulk target for a random searcher that performs boundary-mediated diffusion in a circular domain. Although nonintuitive for bulk targets, it is found that boundary excursions, if fast enough, can minimize the search time. A scaling analysis generalizes these findings to domains of arbitrary shapes and underlines their robustness. Overall, these results provide a generic mechanism of optimization of search kinetics in interfacial systems, which could have important implications in chemical physics. In the context of animal behavior sciences, it shows that following the boundaries of a domain can accelerate a search process, and therefore suggests that thigmotactism could be a kinetically efficient behavior.

Positive and negative impacts of nonspecific sites during target location by a sequence-specific DNA-binding protein: origin of the optimal search at physiological ionic strength

The inducible transcription factor Egr-1, which recognizes a 9-bp target DNA sequence via three zinc-finger domains, rapidly activates particular genes upon cellular stimuli such as neuronal signals and vascular stresses. Here, using the stopped-flow fluorescence method, we measured the target search kinetics of the Egr-1 zinc-finger protein at various ionic strengths between 40 and 400 mM KCl and found the most efficient search at 150 mM KCl. We further investigated the kinetics of intersegment transfer, dissociation, and sliding of this protein on DNA at distinct concentrations of KCl. Our data suggest that Egr-1's kinetic properties are well suited for efficient scanning of chromosomal DNA in vivo. Based on a newly developed theory, we analyzed the origin of the optimal search efficiency at physiological ionic strength. Target association is accelerated by nonspecific binding to nearby sites and subsequent sliding to the target as well as by intersegment transfer. Although these effects are stronger at lower ionic strengths, such conditions also favor trapping of the protein at distant nonspecific sites, decelerating the target association. Our data demonstrate that Egr-1 achieves the optimal search at physiological ionic strength through a compromise between the positive and negative impacts of nonspecific interactions with DNA.

Coarse-grained modeling of protein unspecifically bound to DNA

There is now a certain consensus that transcription factors (TFs) reach their target sites, where they regulate gene transcription, via a mechanism dubbed facilitated diffusion (FD). In FD, the TF cycles between events of 3D diffusion in solution (jumps), 1D diffusion along DNA (sliding), and small jumps (hopping), achieving association rates higher than for 3D diffusion alone. We investigate the FD phenomenology through molecular dynamics simulations in the framework of coarse-grained modeling. We show that, despite the crude approximations, the model generates, upon varying the equilibrium distance of the DNA-TF interaction, a phenomenology matching a number of experimental and numerical results obtained with more refined models. In particular, focusing on the kinematics of the process, we characterize the geometrical properties of TF trajectories during sliding. We find that sliding occurs via helical paths around the DNA helix, leading to a coupling of translation along the DNA axis with rotation around it. The 1D diffusion constant measured in simulations is found to be interwoven with the geometrical properties of sliding and we develop a simple argument that can be used to quantitatively reproduce the measured values.

FOUNDATIONS FOR MODELING THE DYNAMICS OF GENE REGULATORY NETWORKS: A MULTILEVEL-PERSPECTIVE REVIEW

A promising alternative for unraveling the principles under which the dynamic interactions among genes lead to cellular phenotypes relies on mathematical and computational models at different levels of abstraction, from the molecular level of protein-DNA interactions to the system level of functional relationships among genes. This review article presents, under a bottom–up perspective, a hierarchy of approaches to modeling gene regulatory network dynamics, from microscopic descriptions at the single-molecule level in the spatial context of an individual cell to macroscopic models providing phenomenological descriptions at the population-average level. The reviewed modeling approaches include Molecular Dynamics, Particle-Based Brownian Dynamics, the Master Equation approach, Ordinary Differential Equations, and the Boolean logic abstraction. Each of these frameworks is motivated by a particular biological context and the nature of the insight being pursued. The setting of gene network dynamic models from such frameworks involves assumptions and mathematical artifacts often ignored by the non-specialist. This article aims at providing an entry point for biologists new to the field and computer scientists not acquainted with some recent biophysically-inspired models of gene regulation. The connections promoting intuition between different abstraction levels and the role that approximations play in the modeling process are highlighted throughout the paper.

Obstacles may facilitate and direct DNA search by proteins

DNA recognition by DNA-binding proteins (DBPs), which is a pivotal event in most gene regulatory processes, is often preceded by an extensive search for the correct site. A facilitated diffusion process in which a DBP combines three-dimensional diffusion in solution with one-dimensional sliding along DNA has been suggested to explain how proteins can locate their target sites on DNA much faster than predicted by three-dimensional diffusion alone. Although experimental and theoretical studies have recently advanced understanding of the biophysical principles underlying the search mechanism, the process under in vivo cellular conditions is poorly understood. In this study, we used various computational approaches to explore how the presence of obstacle proteins on the DNA influences search efficiency. At a low obstacle occupancy (i.e., when few obstacles occupy sites on the DNA), sliding by the searching DBP may be confined, which may impair search efficiency. The obstacles, however, can be bypassed during hopping events, and the number of bypasses is larger for higher obstacle occupancies. Dynamism on the part of the obstacles may even further facilitate search kinetics. Our study shows that the nature and efficiency of the search process may be governed not only by the intrinsic properties of the DBP and the salt concentration of the medium, but also by the in vivo association of DNA with other macromolecular obstacles, their location, and occupancy.

Quantitative influence of macromolecular crowding on gene regulation kinetics

We introduce macromolecular crowding quantitatively into the model for kinetics of gene regulation in Escherichia coli. We analyse and compute the specific-site searching time for 180 known transcription factors (TFs) regulating 1300 operons. The time is between 160 s (e.g. for SoxS M_w = 12.91 kDa) and 1550 s (e.g. for PepA₆ of M_w = 329.28 kDa). Diffusion coefficients for one-dimensional sliding are between for large proteins up to for small monomers or dimers. Three-dimensional diffusion coefficients in the cytoplasm are 2 orders of magnitude larger than 1D sliding coefficients, nevertheless the sliding enhances the binding rates of TF to specific sites by 1–2 orders of magnitude. The latter effect is due to ubiquitous non-specific binding. We compare the model to experimental data for LacI repressor and find that non-specific binding of the protein to DNA is activation- and not diffusion-limited. We show that the target location rate by LacI repressor is optimized with respect to microscopic rate constant for association to non-specific sites on DNA. We analyse the effect of oligomerization of TFs and DNA looping effects on searching kinetics. We show that optimal searching strategy depends on TF abundance.

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.

Effect of DNA conformation on facilitated diffusion

Within a living cell, site-specific DNA-binding proteins need to search the whole genome to find a target of ~10-20 bp. That they find the target, and do so quickly, is vital for the correct functioning of the DNA, and of the cell as a whole. The current understanding is that this search is performed via facilitated diffusion, i.e. by combining three-dimensional bulk diffusion within the cytoplasm or nucleoplasm, with one-dimensional diffusion along the DNA backbone, to which the protein binds non-specifically. After reviewing the standard theory of facilitated diffusion, we discuss in the present article the still rather rare direct computer simulations of this process, focusing on the three-dimensional part of the search, and the effect of DNA looping and the general DNA conformation on its efficiency. We close by highlighting some open questions in this field.

Asymmetric DNA-search dynamics by symmetric dimeric proteins

We focus on dimeric DNA-binding proteins from two well-studied families: orthodox type II restriction endonucleases (REs) and transcription factors (TFs). Interactions of the protein's recognition sites with the DNA and, particularly, the contribution of each of the monomers to one-dimensional (1D) sliding along nonspecific DNA were studied using computational tools. Coarse-grained molecular dynamics simulations of DNA scanning by various TFs and REs provide insights into how the symmetry of a homodimer can be broken while they nonspecifically interact with DNA. The characteristics of protein sliding along DNA, such as the average sliding length, partitioning between 1D and 3D search, and the one-dimensional diffusion coefficient D1, strongly depend on the salt concentration, which in turn affects the probability of the two monomers adopting a cooperative symmetric sliding mechanism. Indeed, we demonstrate that maximal DNA search efficiency is achieved when the protein adopts an asymmetric search mode in which one monomer slides while its partner hops. We find that proteins classified as TFs have a higher affinity for the DNA, longer sliding lengths, and an increased probability of symmetric sliding in comparison with REs. Moreover, TFs can perform their biological function over a much wider range of salt concentrations than REs. Our results demonstrate that the different biological functions of DNA-binding proteins are related to the different nonspecific DNA search mechanisms they adopt.

Simplified biased random walk model for RecA-protein-mediated homology recognition offers rapid and accurate self-assembly of long linear arrays of binding sites

Inspired by RecA-protein-based homology recognition, we consider the pairing of two long linear arrays of binding sites. We propose a fully reversible, physically realizable biased random walk model for rapid and accurate self-assembly due to the spontaneous pairing of matching binding sites, where the statistics of the searched sample are included. In the model, there are two bound conformations, and the free energy for each conformation is a weakly nonlinear function of the number of contiguous matched bound sites.

Weak frustration regulates sliding and binding kinetics on rugged protein-DNA landscapes

A fundamental step in gene-regulatory activities, such as repression, transcription, and recombination, is the binding of regulatory DNA-binding proteins (DBPs) to specific targets in the genome. To rapidly localize their regulatory genomic sites, DBPs reduce the dimensionality of the search space by combining three-dimensional (3D) diffusion in solution with one-dimensional (1D) sliding along DNA. However, the requirement to form a thermodynamically stable protein-DNA complex at the cognate genomic target sequence imposes a challenge on the protein because, as it navigates one-dimensionally along the genome, it may come in close contact with sites that share partial or even complete sequence similarity with the functional DNA sequence. This puzzling issue creates a conflict between two basic requirements: finding the cognate site quickly and stably binding it. Here, we structurally assessed the interface adopted by a variety of DBPs to bind DNA specifically and nonspecifically, and found that many DBPs utilize one interface to specifically recognize a DNA sequence and another to assist in propagating along the DNA through nonspecific associations. While these two interfaces overlap each other in some proteins, they present partial overlap in others and frustrate the protein-DNA interface. Using coarse-grained molecular dynamics simulations, we demonstrate that the existence of frustration in DBPs is a compromise between rapid 1D diffusion along other regions in the genome (high frustration smoothens the landscape for sliding) and rapid formation of a stable and essentially active protein-DNA complex (low frustration reduces the free energy barrier for switching between the two binding modes).

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.

Speed-selectivity paradox in the protein search for targets on DNA: is it real or not?

Protein search for targets on DNA starts all major biological processes. Although significant experimental and theoretical efforts have been devoted to investigation of these phenomena, mechanisms of protein-DNA interactions during the search remain not fully understood. One of the most surprising observations is known as a speed-selectivity paradox. It suggests that experimentally observed fast findings of targets require smooth protein-DNA binding potentials, while the stability of the specific protein-DNA complex imposes a large energy gap which should significantly slow down the protein molecule. We developed a discrete-state stochastic approach that allowed us to investigate explicitly target search phenomena and to analyze the speed-selectivity paradox. A general dynamic phase diagram for different search regimes is constructed. The effect of the target position on search dynamics is investigated. Using experimentally observed parameters, it is found that slow protein diffusion on DNA does not lead to an increase in the search times. Thus, our theory resolves the speed-selectivity paradox by arguing that it does not exist. It is just an artifact of using approximate continuum theoretical models for analyzing protein search in the region of the parameter space beyond the range of validity of these models. In addition, the presented method, for the first time, provides an explanation for fast target search at the level of single protein molecules. Our theoretical predictions agree with all available experimental observations, and extensive Monte Carlo computer simulations are performed to support analytical calculations.

In vivo facilitated diffusion model

Under dilute in vitro conditions transcription factors rapidly locate their target sequence on DNA by using the facilitated diffusion mechanism. However, whether this strategy of alternating between three-dimensional bulk diffusion and one-dimensional sliding along the DNA contour is still beneficial in the crowded interior of cells is highly disputed. Here we use a simple model for the bacterial genome inside the cell and present a semi-analytical model for the in vivo target search of transcription factors within the facilitated diffusion framework. Without having to resort to extensive simulations we determine the mean search time of a lac repressor in a living E. coli cell by including parameters deduced from experimental measurements. The results agree very well with experimental findings, and thus the facilitated diffusion picture emerges as a quantitative approach to gene regulation in living bacteria cells. Furthermore we see that the search time is not very sensitive to the parameters characterizing the DNA configuration and that the cell seems to operate very close to optimal conditions for target localization. Local searches as implied by the colocalization mechanism are only found to mildly accelerate the mean search time within our model.

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.

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.

Geometry-induced bursting dynamics in gene expression

In prokaryotes and eukaryotes, genes are transcribed stochastically according to various temporal patterns that range from simple first-order kinetics to marked bursts, resulting in temporal and cell-to-cell variations of mRNA and protein levels. Here, we consider the effect of the transport of regulatory molecules on the noise in gene expression by taking into account explicitly the dynamics of a finite number of transcription factors confined in the cell. We calculate analytically time-dependent correlation functions of mRNA levels for a wide range of transport mechanisms and find that in the limit of small-transcription-factor copy number, the results differ significantly from standard approaches, which ignore confinement. It is shown how such dynamical quantities, which can now be obtained experimentally, can be used to identify the underlying mechanisms of transcription. Of particular importance, it is demonstrated that the geometry of transcription-factor trajectories in the cellular environment plays a key role in transcription kinetics, and can intrinsically generate the observed various transcription patterns ranging from simple first-order kinetics to bursts.

Facilitated diffusion on confined DNA

In living cells, proteins combine three-dimensional bulk diffusion and one-dimensional sliding along the DNA to reach a target faster. This process is known as facilitated diffusion and we investigate its dynamics in the physiologically relevant case of confined DNA. The confining geometry and DNA elasticity are key parameters: We find that facilitated diffusion is most efficient inside an isotropic volume and on a flexible polymer. By considering the typical copy numbers of proteins in vivo, we show that the speedup due to sliding becomes insensitive to fine tuning of parameters, rendering facilitated diffusion a robust mechanism to speed up intracellular diffusion-limited reactions. The parameter range we focus on is relevant for in vitro systems and for facilitated diffusion on yeast chromatin.