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Two-Phase Dynamics of DNA Supercoiling based on DNA Polymer Physics

Biao Wan Beijing Computational Science Research Center, Beijing 100193,China    Jin Yu jin.yu@uci.edu Department of Physics and Astronomy, Department of Chemistry, NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA 92697, USA
Abstract

DNA supercoils are generated in genome regulation processes such as transcription and replication, and provide mechanical feedback to such processes. Under tension, DNA supercoil can present a coexistence state of plectonemic (P) and stretched (S) phases. Experiments have revealed the dynamic behaviors of plectoneme, e.g. diffusion, nucleation and hopping. To represent these dynamics with computational changes, we demonstrated first the fast dynamics on the DNA to reach torque equilibrium within the P and S phases, and then identified the two-phase boundaries as collective slow variables to describe the essential dynamics. According to the time scale separation demonstrated here, we accordingly developed a two-phase model on the dynamics of DNA supercoiling, which can capture physiologically relevant events across time scales of several orders of magnitudes. In this model, we systematically characterized the slow dynamics between the two phases, and compared the numerical results with that from the DNA polymer physics-based worm-like chain model. The supercoiling dynamics, including the nucleation, diffusion, and hopping of plectoneme, have been well represented and reproduced, using the two-phase dynamic model, at trivial computational costs. Our current developments, therefore, can be implemented to explore multi-scale physical mechanisms of the DNA supercoiling-dependent physiological processes.

INTRODUCTION

Supercoiling is ubiquitous in cellular DNA, which results from the topology of double-helical DNA Bates et al. (2005); Fuller (1971); Koster et al. (2010); Lavelle (2014). For eukaryotic DNA, the large structural domains (1\sim 1 Mbb) emerge in the genome as the topologically associating domains (TADs)Dixon et al. (2012); Glinsky (2015); Stadhouders et al. (2019), which are further divided into smaller supercoiling domains(105bp\sim 10^{5}bp)Naughton et al. (2013); Gilbert and Allan (2014); Corless and Gilbert (2016). For the prokaryotic DNA, comparatively large structural domains and smaller supercoiling domains also present (e.g., EE. colicoli with an average domain size, 104\sim 10^{4} bpbp) Postow et al. (2004); Gilbert and Allan (2014). Supercoils are generated in many crucial genetic processes and in turn regulates corresponding processes, including transcription, replication and genome condensationLiu and Wang (1987); Ma et al. (2013); Chong et al. (2014); Bates et al. (2005); Burnier et al. (2008); Schvartzman et al. (2013); Hirano (2000); Strick et al. (2004). During transcription elongation, a RNA polymerase (RNAP) moves along the helical DNA and generates twists, which subsequently create positive supercoiling ahead of the RNAP or downstream along the transcription direction and negative supercoiling behind or upstreamLiu and Wang (1987). The accumulation of the torsional stress can slow down or even stall the transcription elongationMa et al. (2013); Chong et al. (2014). Recent experiments show long-distance cooperative and antagonistic dynamics of multiple RNAPs via supercoilingKim et al. (2019), which justify the role of supercoiling as a long-range mediatorTeves and Henikoff (2014). A previous modeling study pointed out that multiple RNAPs facilitate elongation by reducing collisions or traffic jam by torquesTantale et al. (2016); and another model suggested that multiple RNAPs also induce strong supercoiling to bring significant transcription fluctuationsJing et al. (2018). In addition, supercoiling contributes to the chromosome condensationHirano (2000); Strick et al. (2004), during which the negative supercoils accumulate in the protein-free region of the DNA Kimura and Hirano (1997). Under tension, the accumulative supercoiling presents twisted and interwound coils called plectonemes, which may act as a driving force for compacting the chromatin fiberKimura and Hirano (1997); Swedlow and Hirano (2003).

Supercoil can be partitioned into two parts, twist and writhe, which play distinct roles in genomic processesSeol and Neuman (2016). Underwound DNA (with negative twists) can melt the secondary structures of DNA that can attract regulatory proteinsMa and Wang (2014a, b); Seol and Neuman (2016). In contrast, overwound DNA (with positive twists) can hinder enzymatic activities associated with opening of the DNA duplex, such as in transcription initiation and elongation by RNAPMa et al. (2013); Chong et al. (2014). On the other hand, writhe characterizes spatial crossings of DNA segmentsFuller (1971, 1978), accordingly facilitating distant interactions on DNAParker and Halford (1991); Liu et al. (2001); Huang et al. (2001); Polikanov et al. (2007). Writhe can be in a solenoidal or a plectonemic form, or a combination of both. Under an externally stretching force, supercoiled DNA can present a coexistence state of bothMarko (1997a); Strick et al. (1999); Ghatak and Mahadevan (2005); Marko (2007), in which the plectonemic coils form the plectonemic (P) phase, while the solenoidal coils are almost straightly stretched, forming the stretched (S) phaseMarko (2007); Forte et al. (2019).

DNA supercoiling has been quantitatively studied with single-molecule techniquesMarko and Siggia (1994); Bustamante et al. (1994); Strick et al. (1996, 1998, 1999); Bustamante et al. (2000); Strick et al. (2000); Koster et al. (2005); van Loenhout et al. (2012); Bustamante et al. (2003). The extension-twist curves from experiments reveal a coupling between supercoiling (linking number) and DNA extension under stretching forceMarko and Siggia (1994); Bustamante et al. (1994); Strick et al. (1996). The discontinuities on torque and extension versus linking number were also observed in experimentForth et al. (2008). Experiments with a magnetic tweezers pulling a fluorescently labeled DNA have directly imaged the coexistence phase, and remarkably, measured the time-dependent supercoiling dynamics, e.g., plectoneme diffusion, nucleation and hoppingvan Loenhout et al. (2012). The propagation of plectoneme along DNA via diffusion presents conformational rearrangement of DNA at about hundreds bps per second. The hopping happens comparatively fast and a fastest one observed takes tens of milliseconds for a displacement of thousands of bpsvan Loenhout et al. (2012). The surviving time of the individual plectoneme from nucleation to vanishing, i.e., the plectoneme life-time, spans from milliseconds to several seconds.

In accompany with the experiments, theoretical studies of DNA supercoiling have been developed based on the worm-like chain (WLC) modelMarko and Siggia (1995a, b); Moroz and Nelson (1997); Marko (2007); Phillips et al. (2009). The statistical mechanics of the WLC model of DNA provides a description of the coupling between supercoiling and DNA extensionMoroz and Nelson (1997); Marko (1998), and reveals the pre-plectonemic loops formed by bending DNA, i.e., buckling transitionDaniels and Sethna (2011), which give rise to the discontinuities on torque and extension versus linking number curvesMarko and Neukirch (2012); Emanuel et al. (2013). Further, studies show that under a stretching force, the coexistence of the S and P phases is maintained under a coexistence torque that is a function of the stretching forceMarko (2007).

Nevertheless, the related analytic theories concern mostly the equilibrium and static behaviors, without elucidating the time-dependent dynamic processes. The experiments suggest that the dynamics of plectonemes essentially covers multiple orders of timescalesvan Loenhout et al. (2012). In this study, we focus on building a model to describe these dynamic processes across the time scales.

Apart from the analytic theories, computational simulations and numerical methods have offered effective ways to probe supercoiling dynamics. Atomistic molecular dynamics (MD) simulations offer the finest details of such dynamics. For example, MD simulations of DNA mini-circles (10210^{2} bb) reveal writhe fluctuation and configuration diversityMitchell and Harris (2013); Mitchell et al. (2011); Irobalieva et al. (2015). To improve computational efficiency, a coarse-grained model that treats nucleotides as beads with three interaction sites, called oxDNA, was developedMatek et al. (2015). Furthermore, by unitizing MD and the coarse-grained simulations, the multi-scale dynamics of supercoiling have been studiedSutthibutpong et al. (2016); Hirsh et al. (2013a). Nevertheless, computational costs of these models are high and the simulation time scales are limited by microsecondsDans et al. (2016). The models without considering DNA sequence structure are capable of exceeding such a limit. An elasto-dynamic model (i.e., the Kircholff rod), for example, has been developed, by which DNA is characterized in terms of a continuum rod while omitting thermal fluctuationsGoyal et al. (2005). The corresponding applications were carried out on supercoil removalLillian et al. (2011), and on compressed DNA inside bacteriophage cavity to allow DNA ejectionHirsh et al. (2013b). In particular, for a representative polymer physics model, the numerical approach of the WLC model, i.e., the discrete worm-like chain (dWLC) method, has been widely implemented in simulating DNA with the thermal fluctuations incorporatedVologodskii (2006). For example, the Monte Carlo (MC) simulations of the WLC model have been used in describing DNA thermodynamics, conformation and site juxtapositionVologodskii et al. (1992); Klenin et al. (1991); Polikanov et al. (2007). The Brownian dynamics (BD) simulations, on the other hand, have been applied more widely in studying supercoilingVologodskii (2006); Klenin et al. (1998). Such type of studies successfully show the plectoneme diffusionBell et al. (2012), supercoiling conformations Vologodskii et al. (1992); Babamohammadi and Lillian (2020), buckling transitionDaniels and Sethna (2011); Walker et al. (2018); Ott et al. (2020), modeling a DNA wrapped around a model histoneWocjan et al. (2009), and supercoil removal by nickingIvenso and Lillian (2016). Besides, other semi-flexible polymer models with Lennard-Jones potential have also been utilized to investigate the mechanism for supercoiling by rotating the endsWada and Netz (2009), or using interwoven and braided polymers to produce plectonemesForte et al. (2019).

The computational costs of the above models are still quite significant for studying the plectoneme dynamics. For example, by employing the dWLC method, simulating the plectoneme dynamics over a second requires weeks of CPU timeIvenso and Lillian (2016); Ott et al. (2020). In this study, we developed a two-phase (S and P phases) dynamic model of DNA supercoiling at trivial computational cost based on the WLC polymer physics model of DNA. In solvent, supercoiled DNA experiences frictional forces on the two phases and the energy gradient that drives the transformation between the S and P phases. Thus the first thing is to identify the fast dynamics comparing to the phase-transformation and possibly integratae them out to reduce the degrees of freedomFasnacht et al. (2004); Zhang and Ma (2010). Here we demonstrate first the dynamics and timescales of the torque transport within S and P phases that define the fast dynamics. Then we choose interphase boundaries as the slow dynamic observables and obtain the associated energetics. Subsequently, we derive the Langevin dynamics of the slow observables. As a result, this implies that DNA supercoil can fast propagate as twist (torque) and slowly propagate as writhe (or plectonemes) along DNA. For calibration and consistency check, we compare the numerical results of the two-phase dynamic model with those from the dWLC method. For applications, we reproduce the supercoil dynamics on plectoneme diffusion, nucleation and vanishing as being measured experimentally, as well as the force/ionic strength-dependent dynamics. Finally, plectoneme hopping and the associated energetics transformations between the two phases are monitored.

RESULTS

Here, we study dynamics of the DNA supercoiling and build a two-phase dynamic model with a focus on DNA of 10310^{3} to 10410^{4} bb. Such sizes of DNAs are widely used in the single-molecule experimentsCrut et al. (2007); van Loenhout et al. (2012); Ma et al. (2013). DNAs shorter than several hundreds bps hardly bend to form a stable plectonmic helix; for DNAs longer than 10410^{4} bb, however, the supercoiling domain may emerge and take overDixon et al. (2012); Glinsky (2015).

Fast torsional equilibrium on the stretched (S) and plectonemic (P) phases

In this section, we describe the dynamics of torque transport reaching to equilibrium within the S and P phases, and show that such dynamics are fast comparing to the transformation between the two phases.

Torque transport on stretched DNA or S phase

We study the dynamics of torque propagation on supercoiled DNA based on the WLC model numerically, i.e., via an implementation of the dWLC method (see Text S1 in the Supporting Material).

In the WLC model, harmonic potentials are used in representing the elasticities of DNABates et al. (2005); Marko and Siggia (1995b); Klenin et al. (1998). The twist energy density is defined as

twist=12kBTlt(ΔθΔu)2\mathcal{E}_{twist}=\frac{1}{2}k_{B}Tl_{t}(\frac{\Delta\theta}{\Delta u})^{2} (A1)

where kBk_{B} is the Boltzmann constant, TT is the room temperature, ltl_{t} is the torsional persistence length, i.e., lt=75nml_{t}=75nm, Δθ\Delta\theta is the twist on the segment Δu\Delta u. We introduce an internal torque TqinT_{q}^{in} as a measure of torsional stress on DNA, TqinkBTltΔθΔuT_{q}^{in}\equiv k_{B}Tl_{t}\frac{\Delta\theta}{\Delta u} (Torque is proportional to twist). Based on the elastic properties of DNA, the torque transport along DNA can be written as (see Text S2),

Tqint=ltkBTζR2Tqinu2\frac{\partial T_{q}^{in}}{\partial t}=\frac{l_{t}k_{B}T}{\zeta_{R}}\frac{\partial^{2}T_{q}^{in}}{\partial u^{2}} (A2)

where drag coefficient for a rotational cylinder ζR=4πR2η\zeta_{R}=4\pi R^{2}\eta, and the radius of DNA R=2nmR=2nm and the viscosity η=0.001kg/m/s)\eta=0.001kg/m/s). A solution to Eq A2 can be seen in Text S2. The characteristic time for torque equilibrium time can be reached at 2.5ζRltkBTL22.5\frac{\zeta_{R}}{l_{t}k_{B}T}L^{2}(about 0.1msms for 3000bp3000bp) (Text S2), independent of stretching force, torque and linking number. For example, a twist pulse starting at one end of the stretched DNA or S phase will spread over 10310^{3} bpbp within 102ms10^{-2}ms and 10410^{4} bpbp within 1ms1ms. Compared with the dynamics of plectoneme of 103\sim 10^{3} bpbp that happens at the time scale from msms to ss, e.g. diffusion and hopping, the torque transport within the S phase is fast.

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Figure 1: Measuring the torque transport on the stretched (S) phase and the plectonemic (P) phase of the supercoiled DNA based on the dWLC, respectively. (a)The schematic shows the torque transport along the S phase following an external torque TqexT_{q}^{ex} promptly applied from 0 pNnmpNnm to 9 pNnmpNnm at t=0t=0. (b) The internal torque of DNA at length of 1500bp1500bp and 3000bp3000bp, T¯qin\bar{T}_{q}^{in} rises to equilibrium (9 pNnmpNnm) within 0.1 msms to follow TqexT_{q}^{ex}. (c) The excess linking number density σS\sigma_{S} reaches to equilibrium σSeq=0.17\sigma_{S}^{eq}=0.17 within 0.1msms. (d) The schematic shows that a pure plectonemic DNA follows an promptly applied torque,TqexT_{q}^{ex} from an initial 8pNnm8pNnm to maintains the plectonemic helix (t<0t<0) to 10pNnm10pNnm at t=0t=0. The internal torque along DNA consequently propagates on plectoneme. (e) The mean torque of DNA at length of 1500bp1500bp and 3000bp3000bp, T¯qin\bar{T}_{q}^{in} reaches to equilibrium (10 pNnmpNnm) within 0.3ms0.3ms. (f) The excess linking number density σP\sigma_{P} reaches to equilibrium value σPeq=0.091\sigma_{P}^{eq}=0.091 within 0.3 msms.

Fig.1 shows the scheme for simulating the torque transport on a stretched DNA using the dWLC method. Under a constant stretching force f=0.4f=0.4 pNpN, DNA is twisted by an external torque Tqex=9pNnmT_{q}^{ex}=9pNnm starting at t=0t=0 (Tqex=0T_{q}^{ex}=0 at t<0t<0). After that, the torque is kept constant and the torsional response of DNA is monitored.

The measurements of the mean internal torque of DNA at lengths of 1500 bpbp and 3000 bpbp are shown in Fig. 1. After being initially twisted, the mean internal torque, T¯qin\bar{T}_{q}^{in}, reaches to equilibrium (9 pNnmpNnm) at about 0.03ms0.03ms for 1500 bpbp and about 0.10.1 msms for 3000 bpbp, consistent with the torque equilibrium time 2.5ζRltkBTL22.5\frac{\zeta_{R}}{l_{t}k_{B}T}L^{2}.

Supercoiling can be quantified by the excess linking number ΔLk\Delta Lk or the linking number density σ\sigma (see Text S3). The free energy density of a stretched DNA is, S=12cS(σSeq)2+0\mathcal{F}_{S}=\frac{1}{2}c_{S}(\sigma_{S}^{eq})^{2}+\mathcal{F}_{0}(Text S4), including the contributions from torsion and force stretchingMarko (1998, 2007), where cSc_{S} stands for the torsional stiffness, which is a function of ff, ltl_{t} and lbl_{b} (lb=50nml_{b}=50nm, the DNA persistence length), σSeq\sigma_{S}^{eq} is the equilibrium linking number density of the stretched phase, and0\mathcal{F}_{0} is the free energy density without torsion, representing the stretching of the WLCMarko and Siggia (1995a). At equilibrium, the torque is defined as 1Ω0SσSeq\frac{1}{\Omega_{0}}\frac{\partial\mathcal{F}_{S}}{\partial\sigma_{S}^{eq}}Marko (2007), where the constant Ω0=1.85nm1\Omega_{0}=1.85nm^{-1} is the rotation angle of the DNA backbone per unit lengthBates et al. (2005); Marko (2007). Thus, we have

σSeq=Ω0T¯qincS\sigma_{S}^{eq}=\frac{\Omega_{0}\bar{T}_{q}^{in}}{c_{S}} (A3)

We accordingly measure the excess linking number density of the stretched DNA as shown in Fig. 1. σS\sigma_{S} reaches to the equilibrium value at 0.03msms for 1500 bpbp and 0.1 msms for 3000 bpbp.

Torque transport on plectoneme

A plectoneme can be considered as a pair of rods anti-parallel interwound around each other under an external torqueRybenkov et al. (1997); Marko (2007). Thus, an empirical form of the energy of the plectonemeKlenin et al. (1991); Rybenkov et al. (1997); Marko (2007) can be utilized,

P=12cPσP2,\mathcal{F}_{P}=\frac{1}{2}c_{P}\sigma_{P}^{2}, (A4)

where cPlpkBTΩ02c_{P}\equiv l_{p}k_{B}T\Omega_{0}^{2} is the torsional stiffness of plectoneme, and lpl_{p} is the torsional persistence length of the plectonemic helix, depending on the ionic strength and often taking value of 21 to 27 nmnm Rybenkov et al. (1997), and σP\sigma_{P} is the excess linking number density of the plectonemes. The internal toque is defined similarly as that of the stretched DNA, i.e., Tqin=kBTlpσPT_{q}^{in}=k_{B}Tl_{p}\sigma_{P}. Nevertheless, torque transport on plectoneme can not be described as the twist angle θ\theta propagation on DNA. That is because that the change of twist of the plectomeical helix also influences the writhe, and in turn the writhe change feeds back to the twist propagation. We introduce a plectonemic angle Θ\Theta (see Fig. S1), similar to θ\theta, as Tqin=kBTlpΔΘΔuT_{q}^{in}=k_{B}Tl_{p}\frac{\Delta\Theta}{\Delta u}. Thus we consider the torque transport on plectoneme as the propagation of the plectonemical angle, i.e.,

Tqint=lpkBTζP2Tqinu2,\frac{\partial T_{q}^{in}}{\partial t}=\frac{l_{p}k_{B}T}{\zeta_{P}}\frac{\partial^{2}T_{q}^{in}}{\partial u^{2}}, (A5)

where ζP2πRplect2η\zeta_{P}\approx 2\pi R_{plect}^{2}\eta is the drag coefficient due to motions of the two parallel rods and RplectR_{plect} the radius of plectonemesNeukirch and Marko (2011); van Loenhout et al. (2012), about 2.5 nm. The time for torque equilibrium on plectoneme with contour length LL can be calculated as 2.5ζPlpkBTL242.5\frac{\zeta_{P}}{l_{p}k_{B}T}\frac{L^{2}}{4}, about 2.62.6 times comparing to that on the stretched DNA. i.e, about 0.26 msms for torque equilibrium for 3000 bpbp.

Fig. 1 illustrates the setup of torque transport on a pure plectoneme, which is originally maintained by a pre-existing external torque Tqex=8pNnmT_{q}^{ex}=8pNnm(t<0t<0). Then the external torque jumps to Tqex=10pNnmT_{q}^{ex}=10pNnm at t0t\geqslant 0, and the ensuing torsional response of the plectoneme is monitored.

The measurements of the internal torque of plectonemes at lengths of 1500 bpbp and 3000 bpbp are shown in Fig. 1. Following the torque jumping at t=0t=0, the mean internal torques, T¯qin\bar{T}_{q}^{in} rises from 8pNnm8pNnm to 10pNnm10pNnm at about 0.1 and 0.3 msms for 1500 bpbp and 3000bpbp, respectively, as estimated above.

In equilibrium, Eq. A4 becomes P=12cP(σPeq)2\mathcal{F}_{P}=\frac{1}{2}c_{P}(\sigma_{P}^{eq})^{2}. The equilibrium torque is defined as 1Ω0PσPeq\frac{1}{\Omega_{0}}\frac{\partial\mathcal{F}_{P}}{\partial\sigma_{P}^{eq}}. Thus

σPeq=Ω0T¯qincP\sigma_{P}^{eq}=\frac{\Omega_{0}\bar{T}_{q}^{in}}{c_{P}} (A6)

We also numerically measure the excess linking number density of the plectoneme as shown in Fig. 1. As Eq A6 suggests, σPeq=TqexΩ0cP=0.076\sigma_{P}^{eq}=\frac{T_{q}^{ex}\Omega_{0}}{c_{P}}=0.076 at t<0t<0, where Tqex=8pNnmT_{q}^{ex}=8pNnm. Then σP\sigma_{P} follows the external torque jumping. Subsequently, σP\sigma_{P} reaches a new equilibrium defined by TqexΩ0cP=0.091\frac{T_{q}^{ex}\Omega_{0}}{c_{P}}=0.091 at about 0.10.1 ms for 1500 bpbp and 0.3 ms for 3000 bpbp.

The torque equilibrium (Eqs A3 and A6) can be applied to the coexistence state of S and P phases. The interphase torque equilibrium means the equilibrium at the phase-boundaries, i.e., cPσPeq=cSσSeqc_{P}\sigma_{P}^{eq}=c_{S}\sigma_{S}^{eq}. Next, we show that the phase boundaries can be chosen as the slow observables to quantify the plectoneme dynamics.

Two-phase dynamics of DNA supercoiling

We have demonstrated the comparatively fast dynamics of torque to reach equilibrium within the S and P phases, respectively. The fast dynamics can then be averaged out within the two phases. We show below that the energy gradients at the phase-boundaries drive the transformation between the two phases and thus establish a two-phase dynamic model for describing the DNA supercoiling.

Multiple plectonemes have been observed in the extended DNA supercoil in experimentvan Loenhout et al. (2012). The dynamics of the plectonemes can be described by the boundaries between the S and P phases. We therefore label the plectonemes from the fixed end to the stretching end with α=1,2,\alpha=1,2,.... Without loss of generality, we only focus on the α\alpha-th plectoneme as shown in Fig. 2. 𝐗(Xαl,Xαr){\mathbf{X}}\equiv(X_{\alpha}^{l},X_{\alpha}^{r}) are the boundaries of plectonemes, where the superscripts ll and rr denote the left and right boundaries of the α\alpha-th plectoneme, respectively. Along the axis, Xαl<uXαrX_{\alpha}^{l}<u\leqslant X_{\alpha}^{r} locates the α\alpha-th plectoneme, while Xα1r<u<XαlX_{\alpha-1}^{r}<u<X_{\alpha}^{l} specifies the α\alpha-th section of the S phase. Thus the motion of plectonemes must be accompanied by that of the stretched phase. The formation of plectonemic coils can make DNA compact by bringing distant-site together, i.e., XαlX_{\alpha}^{l} and XαrX_{\alpha}^{r} are in physical contact. Plectoneme propagation corresponds to the movement of XαlX_{\alpha}^{l} and XαrX_{\alpha}^{r} in the same direction. For example, in Fig. 2 if the α\alpha-th plectoneme moves left, the S phase on the left-hand side of XαlX_{\alpha}^{l} is transformed into the P phase while the P phase on the left-hand side of XαrX_{\alpha}^{r} is transformed into the S phase. This process is accompanied with the internal slithering of parallel segments of the plectonemic helix(Fig. 2). Indeed, the velocity of the relative slithering is equal to the velocity of plectoneme motion (see Methods).

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Figure 2: Two-phase dynamic model of DNA supercoiling. (a) The schematic of the α\alpha-th plectoneme among multiple plectonemes, showing the torque equilibrium between the plectoneme and stretched phases. By mapping the P and S phases into a 1-dimensional arc-length parameter space, one introduces u=Xαlu=X_{\alpha}^{l}, the left boundary of the α\alpha-th plectoneme, and u=Xαru=X_{\alpha}^{r}, the right boundary of the α\alpha-th plectoneme. (b) The propagation of the α\alpha-th plectoneme. The slithering of the segments of the plectonemic helix facilitates the recombination of distal sites on DNA (marked by red and black marks). (c)Simulation trajectories based on the WLC model and the two-phase dynamics. The internal torque of a DNA of 4500 bpbp at f=0.5pNf=0.5pN fluctuates around the coexistence torque, TcoT_{co}. The histograms in the inset show the variance of the internal torque obtained from the dWLC simulations (red bars, 50 msms in total) and that from the simulations using the two-phase dynamic model (green bars, 1 ss in total).

Such observables always evolve slowly comparing to the torque transport, independently of the contour-length (Text S5). A collective observable 𝐗\mathbf{X} is associated with a certain amount of free energy, with its gradient along 𝐗\mathbf{X} as a driving force to reach the free energy minimaWeinan (2011). Based on this idea we derive below the free energy and the dynamic equations associated with the slow variable 𝐗\mathbf{X}.

Free energy associated with the slow observables

As the torque equilibrium is reached, i.e., Ω0T¯qin=cPσPeq\Omega_{0}\overline{T}_{q}^{in}=c_{P}\sigma_{P}^{eq}. The torque equilibrium at the boundaries means cPσPeq=cSσSeqc_{P}\sigma_{P}^{eq}=c_{S}\sigma_{S}^{eq}. Accordingly, every plectenome carries the equal σPeq\sigma_{P}^{eq}. The free energy density of each plectoneme is therefore represented as P(𝐗)=12cP(σPeq)2\mathcal{F}_{P}(\mathbf{X})=\frac{1}{2}c_{P}(\sigma_{P}^{eq})^{2}Klenin et al. (1991); Rybenkov et al. (1997).

The translational displacement of the α\alpha-th section of the S phase is subjected to the viscous drag along it. At u<Xαru<X_{\alpha}^{r} and >Xαl>X_{\alpha}^{l} , the tension imposed on DNA is fuf_{u}, and at the stretching end, f|u=L=ff|_{u=L}=f. As the torque equilibrium is reached, the local free energy density (or force) is represented by S(u,𝐗)=12cS(σSeq)2+0\mathcal{F}_{S}(u,\mathbf{X})=\frac{1}{2}c_{S}(\sigma_{S}^{eq})^{2}+\mathcal{F}_{0}Marko (1998, 2007).

The free energy associated with 𝐗{\mathbf{X}} can be written as the contributions from the S and P phases

Φ0(𝐗)=α=0XαrXα+1lS(u,𝐗)𝑑u+Xα+1lXα+1rP(𝐗)𝑑u.\Phi_{0}(\mathbf{X})=\sum_{\alpha=0}\int_{X_{\alpha}^{r}}^{X_{\alpha+1}^{l}}\mathcal{F}_{S}(u,\mathbf{X})du+\int_{X_{\alpha+1}^{l}}^{X_{\alpha+1}^{r}}\mathcal{F}_{P}(\mathbf{X})du. (B1)

Langevin dynamics

The free energy gradient along 𝐗\mathbf{X} serves as a driving force, which drives the transformation between S and P phases. The variable 𝐗\mathbf{X} thus follows the Langevin equations γ1𝐗˙=𝐗Φ0(𝐗)+2kBTγ1dt𝐖˙\gamma_{1}\mathbf{\dot{X}}=-\nabla_{\mathbf{X}}\Phi_{0}(\mathbf{X})+\sqrt{\frac{2k_{B}T\gamma_{1}}{dt}}\mathbf{\dot{W}}, where γ1\gamma_{1} denotes the drag coefficent for the growth or shrinkage of plectonemes, and W˙\dot{W} is the white noise. Specifically, the left/right boundaries of the α\alpha-plectoneme follow

X˙αl/r=1γαXαl/rΦ0(𝐗)+2kBTγαW˙,\dot{X}_{\alpha}^{l/r}=-\frac{1}{\gamma_{\alpha}}\nabla_{X_{\alpha}^{l/r}}\Phi_{0}(\mathbf{X})+\sqrt{\frac{2k_{B}T}{\gamma_{\alpha}}}\dot{W}, (B2)

where γα\gamma_{\alpha} is drag coefficient for the growth or shrinkage of the α\alpha-th plectoneme (see Methods).

It should be noted that Eq B2 should be completed with two constraints: the first one is the topology constraint (ΔLk=ΔLkS+ΔLkP.\Delta Lk=\Delta Lk_{S}+\Delta Lk_{P}.), and the second one is in-extensibility of DNA model (L=LS+LPL=L_{S}+L_{P})(see Methods).

The equilibrium point, i.e., Xαl/rΦ0(𝐗)=0\nabla_{X_{\alpha}^{l/r}}\Phi_{0}(\mathbf{X})=0 leads to the coexistence torque Tco=1Ω0(2cP(fkBTflb)1cP/cS)12T_{co}=\frac{1}{\Omega_{0}}(\frac{2c_{P}(f-\sqrt{\frac{k_{B}Tf}{l_{b}}})}{1-c_{P}/c_{S}})^{\frac{1}{2}}Marko (2007). Actually, the dynamics of the slow variable 𝐗\mathbf{X} accompanies with a time-dependent torque, Tqin(t)cPσPeq(t)ΩoT_{q}^{in}(t)\equiv\frac{c_{P}\sigma_{P}^{eq}(t)}{\Omega_{o}} (Fig. 2). The internal torque of a DNA at length of 4500 bpbp under f=0.5pNf=0.5pN fluctuates around the coexistence torque, TcoT_{co}. The two-phase dynamic model can be regarded as a smoothed version of the dWLC method. Although the fluctuations faster than the torque equilibrium have been averaged out, the mean and the variance of the torque are still consistent with that obtained from the dWLC method(inset in Fig. 2).

Supercoil with a given linking number is analogous to the classical gas (van der Waals) confined inside a fixed volume (NVT ensemble)Mattis and Swendsen (2008). A DNA twisted under a constant torque TqexT_{q}^{ex}, however, is analogous to the classical gas under a fixed pressure (isobaric ensemble). Its free energy densities can be obtained through the Legendre’s transformation S/P(Tqex)=S/PΩ0Tqexσeq\mathcal{F}_{S/P}(T_{q}^{ex})=\mathcal{F}_{S/P}-\Omega_{0}T_{q}^{ex}\sigma^{eq}. The free energy densities of the plectonemes and the stretched phase are therefore P=12(Ω0Tqex)2cP\mathcal{F}_{P}=-\frac{1}{2}\frac{(\Omega_{0}T_{q}^{ex})^{2}}{c_{P}} and S=12(Ω0Tqex)2cSfu+kBTfulb\mathcal{F}_{S}=-\frac{1}{2}\frac{(\Omega_{0}T_{q}^{ex})^{2}}{c_{S}}-f_{u}+\sqrt{\frac{k_{B}Tf_{u}}{l_{b}}}, respectively. Inserting them into Eq B1 and Eq B2 we obtained the dynamic model of extended DNA supercoiling under constant torque.

Generally speaking, the stretching force, ff in Eq B1 or B2 is not necessarily constant. The force can be time-dependent as long as it dose not break the interphase torque equilibrium. For example, one can impose an instantaneous force. Similarly, ΔLk\Delta Lk can be time-dependent as well if it does not break the interphase torque equilibrium.

Comparing with the WLC model

In this section, by employing the dWLC method, we compare and calibrate the two-phase dynamic model via two examples. One is the supercoiling accumulation at a constantly twisting rate. The other one is supercoiling accumulation under a constant torque. In the first example, the system reaches to a two phase-coexistent state at equilibrium. We show that the two-phase dynamic model at trivial computational costs provides consistent results with the dWLC method, which demands a significant amount of computational time. In the second case, plectonemes finally dominate the supercoiling state under an external torque larger than TcoT_{co}. This non-equilibrium process helps determine the slithering drag coefficient by calibration.

Supercoil accumulation and buckling transition at a constant rate

An extended DNA undergoes linking number accumulation when one end of the DNA is rotated while the other end is kept fixed, as shown in Fig.3. The stretching force f=0.5pNf=0.5pN, the rotation angle Ω=ωt\Omega=\omega t and the angular velocity ω=20π/s\omega=20\pi/s, equivalent to ΔLk=10\Delta Lk=10 per second (i.e., comparable to polymerase enzyme unwinding and synthesizing at  100 nucleotide or nt per second)Thomen et al. (2005); Jing et al. (2018). At first, the extended DNA is twisted, and then it undergoes a buckling transition (discontinuities on torque and extension curves) followed by plectoneme formationForth et al. (2008).

We performed BD simulations of such a supercoil accumulation based on the dWLC method. In Fig. 3, the relative extension z/Lz/L almost remains unchanged before 0.6 s while the torque gradually builds up, suggesting that the extended DNA is twisted. The buckling at about 0.6 s marks the starting-point of the phase-coexistence. The buckling transition indicates a competition between pre-plectonemic loops and stretched phaseMarko and Neukirch (2012); Mielke et al. (2004). After 0.6 s, the torque drops and converges as torsional stress on DNA is relieved, indicating the twist is transformed into writhe. These discontinuities have previously been observed in single-molecule experimentForth et al. (2008). The coexistence torque TqcoT_{q}^{co} remains unchanged when more linking number is injected. Note that multiple plectonemes can co-exist in the process. The representative snapshots are also shown in Fig. 3. The unchanged torque curves or the linearly decreased extension after buckling transition suggest that the process remains quasi-static.

It should be noted here that we obtained the curves in Fig. 3 from four BD simulation trajectories using the dWLC method, and each of the trajectories requires several weeks of CPU time. The calculation of the electrostatics interaction between the charged points on segments of the dWLC model indeed dominates the computational cost (see Text S6). According to our analyses, the computational cost of the dWLC in the plectonemic phase is still significant and grows linearly with the contour-length. For example, in Fig. 1, simulating a stretched DNA of 3000 bpbp in 10 msms costs 3 hours while simulating a pure plectoneme of the same contour length costs one day(i.e., the CPU time). The two-phase dynamic model, however, enables us to reduce the computational cost to trivial by dealing only with the essential variables with slow dynamics. In Fig. 3, the torque and extension curves generated from the two-phase dynamic model (using tens of seconds of computation time) well reproduce those in Fig.3(b) from the dWLC method and also consistent with previous experimental and computational studiesForth et al. (2008); Ott et al. (2020).

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Figure 3: Buckling transition and measurements of the extensions of the DNA during supercoil accumulation. (a)Injecting supercoil (i.e., increasing linking number) at constant rate to the DNA of 3000 bpbp within 1 ss. The rotation rate ω\omega is 20 π\pi per second. (b)The relative extension z/Lz/L (black curve) and torque (red curve) obtained from the BD simulations based on the dWLC as the DNA is gradually twisted. (c)The torque and extension curves from (b) are reproduced using the two-phase dynamic model. (d) Injecting supercoil under a constant external torque, Tqex=9pNnmT_{q}^{ex}=9pNnm. (e)The relative extension from the BD simulations based on the dWLC with various DNA lengths. (f) The results from (e) are reproduced using the two-phase dynamic model. The curves in (e) and (f) are the fitting functions 1+λt\sqrt{1+\lambda t} (see Text S7).

Supercoil accumulation under a constant torque

We also performed simulations of supercoiling generation under a constant torque. Fig.3 illustrates an extended supercoil under a constant torque, Tqex=9pNnmT_{q}^{ex}=9pNnm (comparable to 5\sim11 pNnmpNnm torque exerted by polymerasesMa et al. (2013)), and a constant stretching force f=0.4pNf=0.4pN. Since the external torque is larger than TcoT_{co} (i.e., 6.5pNnm6.5pNnm that maintains the coexistence state under 0.4 pNpN), plectonemes are created and the ultimate equilibrium state is dominated by plectonemes. Consequently, plectonemic coils are building up until all stretched DNA is interwound to plectonemical coils.

Using the dWLC method, we can capture the dynamics of the plectoneme growth. Fig. 3 shows the measurements of the relative extensions z/Lz/L of DNAs at 1500 bpbp (black solid squares), 3000 bpbp, 6000 bpbp and 9000 bpbp. Indeed, the shrinking extensions indicate the growth of plectonemes. The fitting curves are generated using zLz0L11+λt\frac{z}{L}-\frac{z_{0}}{L}\propto 1-\sqrt{1+\lambda t}, where λ\lambda is a fitting parameter. In the two-phase dynamic model, all but the slithering drag coefficients are given based on the hydrodynamics (see Methods). The slithering drag μslt\mu_{slt} is to be determined in the two-phase model by calibrating results with the dWLC method. We performed the simulations using the two-phase dynamic model shown in Fig. 3. The slithering drag μslt\mu_{slt} was then determined via fitting parameter λ\lambda Text S7). Consequently, we can then reproduce the plectoneme dynamics.

Reproducing experimentally measured plectoneme dynamics

Previous experimental studies show that the plectonemes on the extended supercoiled DNA can diffuse, vanish and re-emerge, and their dynamics depend on the stretching force and ionic strengthvan Loenhout et al. (2012).

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Figure 4: Obtaining plectoneme dynamics using the two-phase dynamic model. (a) The kymograph of the plectonemes of a 21-kbp (7μm\mu m) under an constant stretching f=0.8pNf=0.8pN and with a constant linking number ΔLk=70\Delta Lk=70. (b)The diffusion coefficients of a single plectoneme under different forces obtained from the simulation of the two-phase model (the dots). The green curve is directly from the Einstein relation. (c) Large stretching force ff makes more compact plectonemic helices (smaller radius of the plecotnemic helix). (d) Increased salt concentration makes more compact plecotnemic helices. (e) Buckling transition. A portion of stretched DNA is bent to form a loop during nucleation, which is associated with an energy barrier. The reversed process (red arrow, a plectoneme degenerates to a loop) to the nucleation (blue arrow) is also illustrated. (f) Nucleation rate of the plectonemes as a function of force obtained from the two-phase model simulations. The black, red and blue curve and error bars are the results for (lp=25nml_{p}=25nm), (lp=23nml_{p}=23nm) and

(lp=21nml_{p}=21nm) corresponding to the low, regular and high salt concentrations, respectively. (d) The mean lifetime of the individual plectoneme as a function of force and salt concentration. Note that only a single plectoneme is captured at lp=21nml_{p}=21nm and f=3.2pNf=3.2pN in simulations (nucleation and annihilation, however, need multiple plectonemes). (h) A typical hopping event of a displacement of plectoneme for nearly 4 μm\mu m in a time interval about 0.1s0.1s, corresponding to 12 kbp. (i) Energetic conversion during hopping ( nucleation is, e.g, at 80 msms). The total energy changes of hopping (black line) and the reversed (complementary to hopping) process (dashed line) are also shown in the inset.

In particular, the experiments also captured plectoneme hopping, in which a plectoneme vanishes at one position and a new one immediately emerges by nucleation at another remote position. By employing the two-phase dynamic model, we reproduced the plectoneme dynamics, including plectoneme diffusion, nucleation and hopping. Notably, we captured the plectoneme hoppings with significant energetic changes, which facilitate such rapid processes.

Reproducing plectoneme diffusion

The inter-phase boundaries in the two-phase dynamic model can be used to directly monitor the plectoneme dynamics. Fig. 4 shows a kymograph, i.e., the spatial vs time evolution process of the plectonemes of a 21-kbp (7μm\mu m) DNA (extended under a force f=0.8pNf=0.8pN and with ΔLk=70\Delta Lk=70), illustrating the coexistence of multiple plectonemes, and the plectoneme nucleating and vanishing.

The simulations of a plectoneme with 1/41/4 of the DNA contour length under different forces were performed. To estimate the diffusion constant, we measured the mean square displacement (MSD) Δx2(t)¯\overline{\Delta x^{2}(t)} of the plectoneme. As shown in Fig. 4, we obtained the diffusion constants via DΔx2(t)¯2tD\equiv\frac{\overline{\Delta x^{2}(t)}}{2t} under different stretching forces. For consistency check, we also compared the results with the Einstein relation, i.e., D=kBTζdiffD=\frac{k_{B}T}{\zeta_{diff}} where ζdiff\zeta_{diff} as a sum of the viscous drags for the transverse displacement of the plectoneme (see Methods). The diffusion constant of the plectoneme is about 101μm2/s10^{-1}\mu m^{2}/s.

Reproducing nucleation and Measuring plectoneme life time

To compare the dynamics of the plectonemes at different stretching forces and ionic strengths, simulations of the P phase with 1/41/4 of the DNA contour length were performed in the conditions where the stretching forces were 0.40.4, 0.80.8, 1.61.6 and 3.23.2 pNpN. Large stretching force ff results in more compact plectonemes, i.e., reduces the radius of the plectonemic helix(Fig 4). Indeed, in the coexistence state of DNA supercoiling, the equilibrium excess linking number density of the P phase is σPeq=1cP(2cP(fkBTflb)1cP/cS)12f/lp\sigma_{P}^{eq}=\frac{1}{c_{P}}(\frac{-2c_{P}(f-\sqrt{\frac{k_{B}Tf}{l_{b}}})}{1-c_{P}/c_{S}})^{\frac{1}{2}}\sim\sqrt{f/l_{p}}Marko (2007), which suggests that σPeq\sigma_{P}^{eq} increases with ff.

At high salt concentration, the screening of the Coulomb repulsion potential reduces the effective repulsive DNA diameter, leading to the shorter torsional persistence length of the plectoneme lpl_{p} and smaller radius of the plectonemic helixRybenkov et al. (1997). Meanwhile, based on the coexistence state relation σPeqf/lp\sigma_{P}^{eq}\propto\sqrt{f/l_{p}}, lowering lpl_{p} increases the σP\sigma_{P}, i.e., making the plectonemes more compact (Fig. 4). Accordingly, we adjusted the torsional persistence length of plectoneme lpl_{p} to represent the impacts from the ionic strengthRybenkov et al. (1997), specifically, lp=25l_{p}=25, 2323 and 2121 nmnm to represent the low, regular and high salt concentrations, respectively.

According to Kramers’ reaction-rate theory, the nucleation rate is knucexp(βϵnuc)k_{nuc}\propto exp(-\beta\epsilon_{nuc}) Daniels and Sethna (2011), where the energy barrier ϵnucf\epsilon_{nuc}\propto\sqrt{f}, which incorporates the bending energy of the loop and the loss of the elastic energy stored originally in the stretched DNA(Fig. 4)Marko and Neukirch (2012). Therefore, the large forces can lower the nucleation rate. Again, according to the relation σPeqf/lp\sigma_{P}^{eq}\propto\sqrt{f/l_{p}}, large force and small lpl_{p} (high salt concentration) have a similar effect on the nucleation rate. Indeed, the nucleation rates obtained from simulations (Fig. 4) suggest that large stretching forces ff and the high salt concentrations (small lpl_{p}) can suppress the nucleation events. We derived the nucleation relation (Text S8)

knucexp(2fC(lplp)),k_{nuc}\propto exp(-2\sqrt{f}C(l_{p}^{\star}-l_{p})), (D1)

where 2C2C and lpl_{p}^{\star} are fitting parameters (dashed curves in Fig. 4). As lplpl_{p}\rightarrow l_{p}^{\star} (salt concentration decreases), the nucleation rate increases. That is because low salt concentration increases the radius of the plectonemic helices i.e.,RplectRloopR_{plect}\rightarrow R_{loop} (bending energy of DNA in plectonemes increases), then lower the energy barrier from plectonemic helix to loop (reversed buckling transition, red arrow in Fig. 4). By fitting, we obtained lp=27nml_{p}^{\star}=27nm.

The results above indicate that the plectonemes frequently vanish and re-emerge (via nucleation), which lead to the hopping. The surviving time of the individual plectoneme from nucleation to vanishing is defined as plectoneme life-time. Fig. 4 shows that the mean life-time τplec\tau_{plec} depends on stretching force and salt concentration. The large ff or small lpl_{p} increases the plectoneme life-time. As discussed above, large ff or small lpl_{p} lowers the plectonemes nucleation and also leads to more compact plectonemes. The resulting compactness stabilizes existing plectonemes, which means long mean life-time of the individual plectonemes. By obtaining the balance between the plectoneme nucleation and vanishing, we can derive a mean life time of the individual plectoneme (see Text S8)

τplec(2ltlp)fexp(Cf(lplp)).\tau_{plec}\propto(2l_{t}-l_{p})fexp(C\sqrt{f}(l_{p}^{\star}-l_{p})). (D2)

where CC and lpl_{p}^{\star} are the same as those in Eq D1.

Plectoneme hopping and the associated energetic changes

An example of hopping over10kbpover10kbp within about 0.1s0.1s is shown in Fig.4. Plectoneme hopping is a special case of the DNA conformational rearrangementvan Loenhout et al. (2012). As addressed above, plectoneme diffusion happens comparatively slowly, only hundreds of bps per second (2Dt\sim\sqrt{2Dt}). Hopping , however, is a rapid process, potentially, facilitating fast site-specific recombination and enhancer activated expressionSheinin and Wang (2012). Since plectoneme hopping is related to nucleation, the large forces inhibiting the nucleation thus repress the hopping.

We also found that plectoneme hopping is associated with significant energetic changes between the two phases. We identify the nucleation as the starting point of a hopping event. Then we collected numerous simulations (5000) that contain the hopping events and aligned the starting points of the hopping events together for averaging the energetics. The energy change of the S phase accumulates up to about 20kBT20k_{B}T before the nucleation, while that of the P phase falls down to about 20kBT20k_{B}T. These significant energetic changes facilitate the abrupt nucleating-vanishing processes (Fig. 4). After the formation of the new plectoneme by nucleation, the energetic changes rapidly converge to 0. The energetic offsets between the two phases thus makes the total energy change smaller as thermal fluctuations, i.e.,1kBT1k_{B}T(inset of Fig. 4). It should be noted that there is no persistent energetic injection into the system. Thus the energy change must be compensated by the complementary reversed processes (one of the multiple plectonemes vanishes, corresponding to reversed buckling transition shown in Fig. 4).

Methods

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Figure 5: The variables and tentative loops in the two-phase dynamics. (a) The phase boundaries Xαl/rX_{\alpha}^{l/r} describe the phase-transformation between the stretched phase and the α\alpha-th plectoneme, which involve the transverse displacement of the α\alpha-th plectoneme described by zαz_{\alpha}, the displacement of the α\alpha-th section of the stretched phase and the slithering motion of parallel segments of the plectoneme described by vslt,αv_{slt,\alpha}. (b) The algorithm and the integrations are conducted in the discrete bins along the DNA axes. The tentative loops occupy the bins.

The DNA topology and in-extensibility constraints

The Brownian dynamics Eq.B2 is completed with addition of two constraints. The first one is the topology of supercoiling and the second one is the in-extensibility of the model DNA. The DNA topology constraint, i.e., ΔLk=const.\Delta Lk=const., gives the allocation,

ΔLk=ΔLkS+ΔLkP,\Delta Lk=\Delta Lk_{S}+\Delta Lk_{P}, (M1)

where ΔLkS\Delta Lk_{S} and ΔLkP\Delta Lk_{P} are the excess linking numbers of S and P phases, respectively. They can be written as the functions of XX and σS/Peq\sigma_{S/P}^{eq}, i.e., ΔLkS=α=0Ω02πXαrXα+1lσSeq(u,𝐗)𝑑u\Delta Lk_{S}=\sum_{\alpha=0}\frac{\Omega_{0}}{2\pi}\int_{X_{\alpha}^{r}}^{X_{\alpha+1}^{l}}\sigma_{S}^{eq}(u,\mathbf{X})du and ΔLkP=α=0Ω02πXα+1lXα+1rσPeq(𝐗)𝑑u\Delta Lk_{P}=\sum_{\alpha=0}\frac{\Omega_{0}}{2\pi}\int_{X_{\alpha+1}^{l}}^{X_{\alpha+1}^{r}}\sigma_{P}^{eq}(\mathbf{X})du, where σSeq\sigma_{S}^{eq} and σPeq\sigma_{P}^{eq} satisfy the torque equilibrium cSσSeq(u,𝐗)=cPσPeq(X)=Tqinc_{S}\sigma_{S}^{eq}(u,\mathbf{X})=c_{P}\sigma_{P}^{eq}(X)=T_{q}^{in}.

The second constraint originates from the in-extensibility of the model DNA. Eq B2 describes the phase-transformation motion perpendicular to the stretching direction. As shown in Fig. 5, Xαl,rX_{\alpha}^{l,r} specify the α\alpha-th plectoneme, and also involve the displacements of α\alpha-th and α+1\alpha+1-th sections of the stretched phase. This connectivity between the plectonemic and stretched phases additionally confines the translational displacements parallel to the stretching direction. Plectonemes and stretched phase are subjected to the tensions at boundaries fu|u=Xαl/rf_{u}|_{u=X_{\alpha}^{l/r}}, on which potential Φ0(𝐗)\Phi_{0}(\mathbf{X}) depends. The components of motion parallel to the stretching direction, involve the linear combinations of Xαl/rX_{\alpha}^{l/r}. Notice that the coordinate of the α\alpha-th plectoneme is zα=Xαl1α1lplect,αz_{\alpha}=X_{\alpha}^{l}-\sum_{1}^{\alpha-1}l_{plect,\alpha’}, where lplect,α=XαrXαll_{plect,\alpha’}=X_{\alpha’}^{r}-X_{\alpha’}^{l} is the contour length of the α\alpha’-th plectoneme. The velocity of the α\alpha-th stretched section is defined as z˙αX˙αl\dot{z}_{\alpha}-\dot{X}_{\alpha}^{l}. The internal slithering velocity of the parallel segments of the plectoneme vslt,α=12(X˙αl+X˙αr)v_{slt,\alpha}=\frac{1}{2}(\dot{X}_{\alpha}^{l}+\dot{X}_{\alpha}^{r}). The constraints on parallel components result in mechanical balances on the stretching direction

fu|u=Xαrfu|u=Xαlμsltvslt,α=γ2,αz˙α+2β1γ2,αW˙3fu|u=Xαlfu|u=Xα1r=γ3,α(z˙αX˙αl)+2β1γ3,αW˙4,\begin{split}&f_{u}|_{u=X_{\alpha}^{r}}-f_{u}|_{u=X_{\alpha}^{l}}-\mu_{slt}v_{slt,\alpha}=\gamma_{2,\alpha}\dot{z}_{\alpha}+\sqrt{2\beta^{-1}\gamma_{2,\alpha}}\dot{W}_{3}\\ &f_{u}|_{u=X_{\alpha}^{l}}-f_{u}|_{u=X_{\alpha-1}^{r}}=\gamma_{3,\alpha}(\dot{z}_{\alpha}-\dot{X}_{\alpha}^{l})+\sqrt{2\beta^{-1}\gamma_{3,\alpha}}\dot{W}_{4}\end{split}, (M2)

where μslt\mu_{slt} is slithering drag coefficient and γ2,α\gamma_{2,\alpha} is the drag coefficient for the transverse displacement of the α\alpha-th plectoneme, W˙3\dot{W}_{3} is the white noises on the displacement, γ3,α\gamma_{3,\alpha} the drag coefficient for translational displacement of α\alpha-th stretched section, W˙4\dot{W}_{4} is the white noises on the motion of the α\alpha-th stretched section. The first relation in Eq M2 describes the constraints on the transverse displacement of the α\alpha-th plectoneme, and the second one describes constraints between the α1\alpha-1 and α\alpha-th plectonemes. In the dWLC method, the effective viscous drags is 6πηRH6\pi\eta R_{H} for each segment. Thus γ1,α=6πηRHlplect,αl0×12=0.6πηlplect,α\gamma_{1,\alpha}=6\pi\eta R_{H}\frac{l_{plect,\alpha}}{l_{0}}\times\frac{1}{2}=0.6\pi\eta l_{plect,\alpha} where we have used RHl00.2\frac{R_{H}}{l_{0}}\simeq 0.2 and 12\frac{1}{2} means a half of plectoneme contour length in Eq B2, γ2,α=1.2πηlplect,α\gamma_{2,\alpha}=1.2\pi\eta l_{plect,\alpha} and γ3,α=1.2πη(XαlXα1r)\gamma_{3,\alpha}=1.2\pi\eta(X_{\alpha}^{l}-X_{\alpha-1}^{r}).

Neverthless, the friction coefficient μslt\mu_{slt} for slithering is unknown. According to a relation of the slithering drag, μsltlplect,αln(RplectR)\mu_{slt}\propto\frac{l_{plect,\alpha}}{ln(\frac{R_{plect}}{R})}Marko and Siggia (1994), where the plectoneme radius Rplectχ1ln(χ2f)R_{plect}\approx\chi_{1}ln(\frac{\chi_{2}}{f}) and χ1=0.4nm\chi_{1}=0.4nm and χ2=360pN\chi_{2}=360pNvan Loenhout et al. (2012). Calibration of the two-phase model with the dWLC method gives μslt=0.4lplect,αln(RplectR)\mu_{slt}=\frac{0.4l_{plect,\alpha}}{ln(\frac{R_{plect}}{R})}. For supercoiling with a single plectoneme, on average, z˙=vslt\dot{z}=v_{slt}, and then the viscous drag is γ1,1+γ2,1+μslt,1\gamma_{1,1}+\gamma_{2,1}+\mu_{slt,1}. According to the Einstein relation, the diffusion coefficient of individual plectoneme is D=kBTγ1,1+γ2,1+μslt,1D=\frac{k_{B}T}{\gamma_{1,1}+\gamma_{2,1}+\mu_{slt,1}}.

The routine for simulating the two-phase dynamics

ii. Generating the conformation {Xαl/r,σS/Peq}\{X_{\alpha}^{l/r},\sigma_{S/P}^{eq}\}.

The model DNA is discretized as bins with a size 5nm5nm, on which the integrations are numerically conducted (Fig. 5). The observable 𝐗\mathbf{X} follows Eq B2 under constraints Eqs M1 and M2. We select the time-step as dt=2.5ζRL2kBTltdt=2.5\frac{\zeta_{R}L^{2}}{k_{B}Tl_{t}}, specifically, Δt=0.1,0.2,0.4,0.9\Delta t=0.1,0.2,0.4,0.9 and 5ms5ms for 3,4.5,6,93,4.5,6,9 and 21kb21kb, respectively. At each time-step, Eq B2 and constraints Eqs M1 and M2 together constitute the self-consistent equations that can be numerically solved with iteration procedure. Take 20 iteration cycles at each time-step, and the convergence (relative deviation of σS/P<0.001\sigma_{S/P}<0.001) is achieved within 10 iteration cycles.

iiii. Sampling new plectonemes. The energy of the supercoiled DNA with n tentative loops for nucleation is

Φn(𝐗)=Φ0(𝐗)+inEloop,i,\Phi_{n}(\mathbf{X})=\Phi_{0}(\mathbf{X})+\sum_{i}^{n}E_{loop,i}, (M3)

where Eloop,i=8kBTlbfukBTE_{loop,i}=8k_{B}T\sqrt{\frac{l_{b}f_{u}}{k_{B}T}} is the energy penalty for looping at location uuMarko and Neukirch (2012). The excess linking number of the nn tentative loops is ΔLkl=n+12πΔθΔuLloop,i\Delta Lk_{l}=n+\frac{1}{2\pi}\frac{\Delta\theta}{\Delta u}\sum L_{loop,i}, where the relative twist is proportional to torque, i.e., ΔθΔu=TqinkBTlt\frac{\Delta\theta}{\Delta u}=\frac{T_{q}^{in}}{k_{B}Tl_{t}}. The time-scale for looping is on microsecondsDaniels and Sethna (2011), much shorter than dtdt. We thus assume that a portion of ΔLkS\Delta Lk_{S} is stored in loops, then the tentative state follows the two constraints LS=LS+Lloop,iL_{S}=L_{S}’+\sum L_{loop,i} and ΔLkS=ΔLkS+ΔLkl\Delta Lk_{S}=\Delta Lk_{S}’+\Delta Lk_{l} where LSL_{S}’ and LkSLk_{S}’ are the contour length and linking number of the S phase of the tentative state, respectively, and the contour length of a loop is Lloop,i=2π2kBTlb/fuL_{loop,i}=\sqrt{2\pi^{2}}\sqrt{k_{B}Tl_{b}/f_{u}} Marko and Neukirch (2012).

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Figure 6: Flow chart of simulation routine.

The loops along the stretched DNA can be regarded as hard-core particles occupying a 1-dimensional discrete bins (Fig. 5), where each bin characterizes the size of the thermal fluctuations of the DNA. The length of each bin dbin5nmd_{bin}\approx 5nm, defined as the transverse amplitude of the fluctuationsMarko and Siggia (1995b); Marko and Neukirch (2012). Define a partition function of the tentative state with n loops,

𝒫n=I1<I2<<Inexp[βΦn(𝐗)],\mathcal{P}_{n}=\sum_{I_{1}<I_{2}<\cdot\cdot\cdot<I_{n}}exp[-\beta\Phi_{n}(\mathbf{X})], (M4)

where IiI_{i} denotes the location of the i-th tentative loop. Accordingly, P0=𝒫0i𝒫iP_{0}=\frac{\mathcal{P}_{0}}{\sum_{i}\mathcal{P}_{i}} is the probability of the supercoiling without tentative loops and Pn=𝒫ni𝒫iP_{n}=\frac{\mathcal{P}_{n}}{\sum_{i}\mathcal{P}_{i}} is the probability of supercoiling with nn tentative loops. According to the kinetic Monte Carlo methodVan Santen and Sautet (2015), generate a random \mathcal{R} in (0,1). The range (0,1) is divided into (0,P0](0,P_{0}], (P0,P0+P1](P_{0},P_{0}+P_{1}],\cdot\cdot\cdot,(i𝒩1Pi,i𝒩Pi],(\sum_{i}^{\mathcal{N}-1}P_{i},\sum_{i}^{\mathcal{N}}P_{i}],\cdot\cdot\cdot, where 𝒩+1Pi0\sum_{\mathcal{N}+1}^{\infty}P_{i}\simeq 0 and i𝒩Pi1\sum_{i}^{\mathcal{N}}P_{i}\simeq 1 (often 𝒩2\mathcal{N}\leqslant 2). If \mathcal{R} lies in (iN1Pi,iNPi](\sum_{i}^{N-1}P_{i},\sum_{i}^{N}P_{i}], the state with n loops is sampled. The same procedure is applied to locate the nn loops according to the distribution exp[βΦn(𝐗)]𝒫n\frac{exp[-\beta\Phi_{n}(\mathbf{X})]}{\mathcal{P}_{n}}. (For a fully stretched DNA, distribution Eq.M4 implies an entropy brought by nn loops, i.e., Sn=kBnln(LnLloopdbin)kBln(n!)S_{n}=k_{B}nln(\frac{L-nL_{loop}}{d_{bin}})-k_{B}ln(n!), the LnLloopdbin\frac{L-nL_{loop}}{d_{bin}} bins occupied by nn identical particles Marko and Neukirch (2012).)

iiiiii. Removing plectonemes

If 𝒩\mathcal{N}’ plectonemes satisfy lplect,α<2π2kBTf/lbl_{plect,\alpha}<\sqrt{2\pi^{2}}\sqrt{k_{B}Tf/l_{b}} (often 𝒩2\mathcal{N}’\leqslant 2). Similar to iiii, remove the plectonemes according to the distribution exp[βΦn(𝐗)]exp[-\beta\Phi_{n}(\mathbf{X})]. iiii and iiiiii generate and remove plectonemes according to the Boltzmann distribution.

Update the conformation {Xαl/r,σS/Peq}\{X_{\alpha}^{l/r},\sigma_{S/P}^{eq}\}, and then repeat ii, iiii and iiiiii. All the steps can be organized as the flow chart (Fig. 6).

Discussion and Conclusion

In this study, based on the polymer physics or the WLC model of DNA, we have constructed a two-phase dynamic model of the DNA supercoiling. To establish such a model, we demonstrate the fast dynamics of torque equilibrium within the S and P (plectonemic) phases, identify the phase boundaries as slow observables, and derive the energetics associated with the slow observables. By comparing with the WLC model, we have shown that the two-phase dynamic model provides a physically justified and efficient way in representing DNA supercoiling dynamics. The model is particularly suited for studying the plectoneme dynamics from milliseconds to seconds. Correspondingly, we have demonstrated the plectoneme diffusion, nucleation, and hopping, consistently with measurements from single molecule experimentsShashkova and Leake (2017); Sheinin and Wang (2012); van Loenhout et al. (2012).

In order to probe the time-scale separation, we have investigated the dynamics of torque approaching to equilibrium within the pure S and P phases, respectively. Based on the WLC model, the internal torque transports as twist angle propagates. Similarly, by introducing an effective twist angle of the plectonemic helix, the internal torque propagation within the P phase can be described, comparably. Such derivations are confirmed by numerical simulations based on the dWLC, which consistently show that the torque transport is fast, i.e., on either the S or P phase of the supercoiled DNA.

Accordingly, we choose the the boundaries of the S and P phases as observables to describe the slow dynamics. Based on the interphase torque equilibrium, one can then derive the free energy associated with the collective phase boundaries, and the corresponding equation of motion via the Langevin dynamics.

To compare torsional responses from the two-phase model with that from the WLC model, we tested at a constant rate of supercoil accumulation, ΔLk=10\Delta Lk=10 per second, comparable to the RNA polymerization rate during transcription elongation (i.e.,\sim 100 bp per sec), in which ΔLk=0.1\Delta Lk=0.1 is injected into DNA for the RNA polymerase enzyme unwinding to synthesize one nucleotideThomen et al. (2005); Jing et al. (2018). The discontinuities on torque and extension curves are reproduced by the two-phase dynamic model, which reflect the buckling transition during plectoneme nucleationForth et al. (2008); Marko and Neukirch (2012); Emanuel et al. (2013); Daniels and Sethna (2011); Walker et al. (2018); Ott et al. (2020). The torque and extension versus linking number curves suggest that the non-equilibrium effect of the supercoiling accumulation (from the growth of the plectonemic phase) induced by RNAP is constantly relaxed during each polymerization step or elongation cycle. Hence, such an RNA elongation process can be regarded as quasi-steady state. An obvious advantage of the currently developed two-phase dynamic model of DNA supercoiling comes from its trivial computational cost as we only deal with the slow degrees of freedom of the system. Besides, we performed simulations of the plectonemes growth under a constant torque since some studies also regarded RNAPs as a torsional motor which imposes a constant torqueMielke et al. (2004). We accordingly determined frictional coefficient due to slithering in plectoneme by calibrating with the WLC model.

With the two-phase dynamic model we described the DNA supercoiling dynamics and particularly reproduced the plectoneme diffusion, nucleation and hopping. The plectoneme diffusion coefficient is about 0.1 to 0.2μm2/s\mu m^{2}/s, decreasing slightly with the stretching force. Large force indeed makes the plectoneme more compact, which increases the friction for the slithering of parallel segments of the plecoenemes. Consequently, the large force reduces the diffusive capability of plectoneme. Large stretching force also suppresses the nucleation rate, as the force increases the energy penalty for forming a loop. The ability of salt concentration to screen the electrostatic repulsion between opposing segments in plectonemes also affects the radius of plectonemic helixRybenkov et al. (1997); van Loenhout et al. (2012). Similar to large stretching force, strong ionic strength results in compact plectonemes. The resulting compact plectonemes require higher energy penalty to fluctuate, i.e., large stretching force or strong ionic strength can thus stabilize plectonemes. Accordingly, large force or strong ionic strength can prolong the mean life-time of the individual plectoneme. We also observed that a plectoneme can perform a long distance hopping. Specifically, the abruptly conformational change is accompanied by significant energetic changes. However, the total energetic change of the two phase is trivial or as small as thermal fluctuations.

Recent experiments reveal the long-distance cooperative and antagonistic dynamics between multiple RNAPsKim et al. (2019). The experimental evidences suggest that the superpcoil cancellation between adjacent RNAPs makes similar apparent transcription elongation rate. However, upon promoter repression or divergently transcribed genes, RNAPs switch their behavior from collaborative to antagonistic due to the build-up supercoils. There are two important dynamic behaviors that are incorporated in our two-phase model. First, RNAPs can be sensitive to the torque close to the stalling condition (5\sim11 pNpN nmnm)Ma et al. (2013, 2019). A static coexistence torque may not slow down or even stall the transcription elongation, but the torque fluctuation (time-dependent) may. Thus time-dependent torque may induce effects on the long-distance cooperative behaviors of RNAPs. Second, supercoil can fast propagate as twist (torque transport) or slowly propagate as writhe (e.g, plectoneme diffusion). These two kinds of supercoiling propagations are often confounded in modeling supercoiling-dependent dynamics. During transcription elongation, the build-up supercoil can be stored in writhe and can be transmitted as twist that can be felt by RNAPs as the torsional stressMa et al. (2019); Ma and Wang (2014b, a); Ma et al. (2013). The two-phase dynamic model of DNA supercoiling is expected to be applied to improve understanding the supercoiling-dependent transcription.

DNA supercoiling facilitates the site juxtaposition of two distal DNA sites by slithering opposing segments of the interwound superhelix or bending DNA to coilOram et al. (1997); Polikanov et al. (2007); Parker and Halford (1991); Marko (1997b), it then promotes protein binding or enhance the gene expressionvan den Broek et al. (2008); Liu et al. (2001); Lomholt et al. (2009). As we have seen, slithering motion of the segments in a plectomeic helix is accompanied with plectoneme diffusion. However, the diffusion may not offer an efficient mechanism for site juxtaposition. An efficient mechanism for achieving site juxtaposition is combining plectoneme diffusion and hopping. These mechanisms can be efficiently explored by employing the two phase dynamics of the DNA supercoiling which is physical justified and computationally trivial.

Acknowledgements

This work has been supported by NSFC Grant #11775016\#11775016 and #11635002\#11635002. JY has been supported by the CMCF of UCI via NSF DMS 1763272 and the Simons Foundation grant #594598\#594598 and start-up fund from UCI. We acknowledge the computational support from the Beijing Computational Science Research Center (CSRC). Thanks Dr Xinliang Xu for discussions on the work.

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