Ring closure in actin polymers Supurna Sinha 1 and Sebanti Chattopadhyay 2 1Raman Research Institute, Bangalore 560080, India. 2Doon University, Dehradun 248001, India. (Dated: January 16, 2017) We present an analysis for the ring closure probability of semiflexible polymers within the pure bendWormLikeChain(WLC)model. Theringclosureprobabilitypredictedfromouranalysiscan betested against fluorescent actin cyclization experiments.Wealso discuss theeffect ofringclosure on bend angle fluctuationsin actin polymers. 7 1 PACSnumbers: 87.15.Cc,62.20.de,82.35.-x,87.10.-e 0 2 n I. INTRODUCTION method for solving the wormlike chain model for semi- a flexible polymers to any desired accuracy over the entire J In the past two decades, there has been much interest range of polymer lengths to determine Q˜(~r). The plots 1 in the theoretical study of semiflexible polymer elastic- for Q˜(~r) for various β = L , the ratio of the contour 1 LP ity. These studies are motivated by micromanipulation length L to the persistence length LP, reveal the depen- ] experiments[1–3]onbiopolymers. Inparticular,inrecent dence ofthe endto enddistance vectoronthe rigidityof t f years there have been experiments involving stretching the polymer (See Fig. [4] in [7]). o DNA molecules[1] which give us information about the We outline the theoretical calculation of Q˜(~r) below. s . bend elastic properties of DNA. There have also been (For a detailed exposition please see Appendix A). Con- t a experiments on fluorescently tagged actin filaments[4] sider a situation where the initial and final tangent vec- m wheretheymeasurethebendpersistencelengthofactin. tors(tˆA = dd~xs|s=0 andtˆB = dd~xs|s=L)areheldfixed. Then - More recently, there have been fluorescence experiments Q˜(~r) has the following path integral representation: d on cyclization of actin filaments[5]. In these papers they on analyze the formation of rings in actin polymers and Q˜(~r) = N D[tˆ(s)]exp{− 1 A L(dtˆ)2ds } c study the effect of ring closure on bend angle fluctua- Z kBT 2 Z0 ds [ tions in these polymeric rings. Our interest here is lim- L (cid:2) (cid:3) 1 ited to the process of cyclization itself and therefore in ×δ3(~r− tˆds) (2) v our analysis we restrict to polymers with only bend de- Z0 0 grees of freedom and no twist degree of freedom. Actin HereN isthenormalizationconstantandkBT,thether- 2 cyclization is of interest to biologists [6] who do visual- mal energy at temperature T. As mentioned in [7], we 5 ization studies of actin ring formation in the context of solve for Q˜(~r) by first considering a related end to end 3 0 cell division. distance measure: . 1 P(z)= d~rQ˜(~r)δ(r −z), 0 3 II. RING CLOSURE PROBABILITY 7 Z DISTRIBUTION 1 whichisQ˜(~r)integratedoveraplaneofconstantz. This v: inturnis relatedtoP˜(f), the LaplacetransformofP(z) Our starting point is the pure bend Worm Like Chain i given by: X (WLC) model[7]. In this model, the polymer configura- r tion is viewed as a space curve ~x(s). There is a tangent L a vectorassociatedwith eachpointonthe polymerofcon- P˜(f)= P(z)eLfPz dz (3) tour length L and the energy of configuration is given Z−L by: f, the variable conjugate to z has the interpretation of A L a stretching force and thus P˜(f), can be written as the E[C]= dsκ2 (1) ratioZ(f)/Z(0)ofthepartitionfunctionsinthepresence 2 Z0 and absence of an external stretching force f. We do an where C stands for the polymer configuration. A is the eigenspectrumanalysisofP˜(f)anddetermineQ˜(~r)using bending elastic constant and the curvature κ=|dtˆ|. tomographic transformations outlined in [7]. ds One of the key quantities characterizing the elasticity Hereweaddressaquestionwhichisofcurrentinterest of a biopolymer is Q˜(~r), the probability distribution for to application of polymer physics to biology: cyclization the end to end distance vector ~r between the two ends of actin filaments[5]. Within the pure bend Worm Like of the polymer as it gets jiggled around by thermal fluc- Chain (WLC) Model we compute the ring closure prob- tuations in a cellular environment [7]. In [7] we use a ability (RCP) by considering Q˜(~r =~0). 2 III. METHOD In Fig. 4 of [7] we display a family of curves of Q(ρ) versus ρ, with ρ = |~r| for various values of β. Q(ρ) is β a theoretically convenientquantity expressedin terms of scaledunits(ρ~= ~r). Inordertocomputetheringclosure β probabilitydensityQ˜(~r =~0)weneedtochangevariables from ρ= |~r| to |~r|=r. Setting Q˜(~r)=Q , we get: β ~r Q(ρ~)dρ~ = Q d~r (4) ~r Z Z FIG. 1: A plot of the ring closure probability density Q(ρ~= or ~0)= Q(0) versus β, setting LP =1. It has a small value for shortpolymerswhich arehard tobendandform ringsandit has a large value for long polymers which are easy to bend Q(ρ~) d~r = Q d~r (5) and thustheprobability density of ring formation is high. β3 ~r Z Z which in turn implies Q(0) = Q (6) β3 0 We compute Q(0) for a range of values of β using Math- ematica. As we can see from the plot of the ring closure probabilitydensityQ(0)versusβ (Fig. 1),thatQ(0)has a small value for short polymers which are hard to bend and form rings and it has a large value for long poly- FIG.2: Aplotoftheringclosureprobabilitydensityinphys- mers which are easy to bend and thus the probability ical space Q0 = Q(0)/β3, versus β setting LP = 1. Notice density of ring formation is high. We then compute and thatthisfunctionissmallforverysmallandlargeβandpeaks around an intermediate valueβ ≈3. plottheringclosureprobabilitydensityinphysicalspace, Q = Q(0) as a function of β (Fig. 2). The qualitative 0 β3 features of the plot shown in Fig. 2 are in agreement modes which do not contribute, we find that the contri- with our intuition. The ring closure probability density bution from the x−y plane is given by Q in physical space, which is an experimentally mea- 0 1 6 L surable quantity is small for very short and long strands <φ2 >xy = (1− ) (7) ring 12 π2 L of the polymer and peaks around intermediate contour P lengths of L≈3LP (See Fig. 7-41 on page 438 of [8]). We need to add this contribution to the contribution coming from the z direction where the ring closure con- dition is of the form IV. MEAN SQUARED TANGENT ANGLE L FLUCTUATION φ (s)ds=0. z Z0 One of the experimentally relevant quantities of inter- In this case the Fourier expansion for φz(s) can be est is the mean squared tangent angle fluctuation[5]. In expressed as φz(s) = ∞n=2φne2πLins which finally gives Ref. [5] the mean squared tangent angle fluctuation has us P been calculated for a ring and a linear filament in a two 1 6 L dimensional setup. They find good agreement with ex- <φ2 >zring= 12(1− π2)L (8) P perimental measurements. Thus combining Eqs. 7 and 8, the net mean squared Herewepresentasimilarcalculationinathreedimen- tangent angle fluctuation for a three dimensional ring is sional geometry. Consider a polymer configuration in a given by closed circular ring lying in the x−y plane. Expanding the bend angle fluctuation φ(s) in a Fourier series and 1 6 L <φ2 >3d = (1− ) (9) imposing the ring closure constraint and removing zero ring 6 π2 L P 3 the mean squared tangent angle fluctuation to be tested against future experiments on fluorescently tagged ring like and linear actin filaments in a three dimensional ge- ometry. ACKNOWLEDGEMENT One of us (SC) would like to thank RRI for providing hospitalityduringstayinRamanResearchInstitute asa Visiting Student. FIG. 3: Plots of mean squared tangent angle fluctuation in APPENDIX A: COMPUTATION OF Q0 threedimensionsforaring(dashedline)andalinearfilament (solid line). We have set LP = 1. Notice the suppression of OurgoalistocalculateQ ,theringclosureprobability. fluctuation for a ring filament compared to a linear one. 0 Q is Q˜(~r) for ~r =~0. Q˜(~r), the probability distribution 0 fortheendtoendvector~r forasemiflexiblepolymerhas Asimilarcalculationforalinearfilamentinthreedimen- the following path integral representation: sions gives us 1 A L dtˆ Q˜(~r) = N D[tˆ(s)]exp{− ( )2ds } <φ2 >3lidn= 31LLP (10) Z L kBT(cid:2)2 Z0 ds (cid:3) ×δ3(~r− tˆds) (11) Wehaveplotted(9)and(10)inFig. 3. Thesepredictions Z0 canbetestedagainstfutureexperimentsonfluorescently HereN isthenormalizationconstantandk T,thether- taggedactinfilaments. Noticethat,asinthetwodimen- B mal energy at temperature T. sional case[5], we find that < φ2 > is suppressed for a InsteadofQ˜(~r)itturnsouttobeeasiertofirstconsider ringlike structure compared to a linear filament. This P(z) indicates that cyclization is entropically costly. Also, as expected, the fluctuations are smaller in the two dimen- P(z)= d~rQ˜(~r)δ(r −z), sional geometry compared to the three dimensional ge- 3 ometry. Z which is Q˜(~r) integrated over a plane of constant z. P(z)in turn is relatedto P˜(f), the Laplacetransform V. CONCLUSION of P(z) given by: L Our treatment is an analysis based on the pure bend P˜(f)= P(z)eLfPz dz (12) Worm Like Chain Model. The absence of twist degree Z−L of freedom enables our predictions to be directly tested f, the variable conjugate to z has the interpretation of againstactincyclizationexperimentswherethetwoends a stretching force and thus P˜(f), can be written as the of the polymer come together without any relative twist ratioZ(f)/Z(0)ofthepartitionfunctionsinthepresence between the two ends. This is to be contrasted with and absence of an external stretching force f. analysisof J factor of DNA with twist degreeof freedom Z(f) is given by where the additional twist degree of freedom makes the analysis considerably more cumbersome[9–11]. In [11] aninterpolationformulaispresentedinthe intermediate L L dtˆ 2 rigidity regime. They [11] also presented analytical ex- Z(f)=N D tˆ(s) exp − P ds 2 ds pressions for the ring closure probability density Q in Z ( "Zo (cid:18) (cid:19) #) 0 (cid:2) (cid:3) the limit of β <<1 and β >>1. However, they did not f L ×exp tˆds have an exact expression for the entire range of polymer L 2 " P Z0 # lengths. In contrast, here we present a semianalytical study which gives an essentially exact prediction for Q which in turn can be expressed as 0 fortheentirerangeofrigidity(See Fig. 1andFig. 2). It would be interesting to see how our predictions quanti- β 1 dtˆ 2 tativelycomparewithfuturecyclizationprobabilitydata Z(f)=N D tˆ(τ) exp − dτ −ftˆ z for actin filaments. We also expect our predictions for Z ( Zo "2(cid:18)dτ(cid:19) #) (cid:2) (cid:3) 4 which has the interpretation of the kernel of a quantum Z=M[[1,1]]; particle on the surface of a sphere at an inverse tem- L=Append[L,Z]] perature β. We now exploit the analogy between time L=Re[L]; imaginary quantum mechanics and classical statistical Pz={}; mechanics to re-express Z(f) as follows: P1z={} For[l=-2,l¡1200,l++, xi=.001*l; Z(f)= e−[βEn]ψn tˆA ψn tˆβ P=(h*beta/Pi)*Sum[L[[n]]*Cos[(n- Xn (cid:0) (cid:1) (cid:0) (cid:1) 1)*h*xi*beta],n,1,Nmax]; where{ψ tˆ }isacompletesetofnormalizedeigen- Pz=Append[Pz,xi,P]; n A P1z=Append[P1z,P]]; statesoftheHamiltonianH =−∇2−fcosθandE are (cid:0) (cid:1) f 2 n V=P1z; the corresponding eigenstates. For free boundary condi- QR1=; tions for the end tangent vectors we can express Z(f) L1=Drop[V,2] as L2=Drop[V,-2] LPR=(L1-L2)/(.001*2); Z(f)=ho|exp−βH |oi f LPR=Drop[LPR,1]; TheHamiltonianH =−∇2−fcosθ istheHamiltonian (*Computation of S(r)*) f 2 QR = Table[LPR[[i]] ∗ 1/((i − 1) ∗ .001) ∗ [−1/(2 ∗ of a rigid rotor in a potential and |0 > is the ground stateofthefreeHamiltonianH =−∇2. Wenumerically Pi)],i,2,1199]; 0 2 (*Computation of Q(r)*) evaluate Z(f) by choosing a suitable basis in which H f QR1=Table[(i−1)∗.001,LPR[[i]]∗(1/(i−1))∗ has a tridiagonal symmetric matrix structure with 1/((i−1)∗.001)∗[−1/(2∗Pi)],i,2,2]; ListPlot[QR1] l(l+1) H = ll 2 Program for computing Q0 H =f(l+1) 1/[(2l+1)(2l+3)] ll+1 ClearAll[h, f, Z, lmax, H, beta, Nmax, L1, L2, LPR, p To summarize, after casting the problem analytically PR] we use Mathematica programs to sequentially compute lmax = 10; Z(f) and P˜(f), then P(z), then S(r)=−2rdP(r)/dr = h = .005; 4πr2Q˜(r) and finally Q˜(~r). We then consider the scaled final = {}; variable ρ~ = ~r. Q(0) is then computed by considering β For[k = 0, k <50, k++, Q(ρ~) at ρ~ =~0 and plotting it as a function of β. Q0 = beta = .25*k + 1; Q(0). BelowwedisplaytheprogramsforcomputingQ(ρ~) Nmax = Piecewise[90000,beta <=3, 9000, beta >3]; β3 andQ . We haveinsertedsome comments as partofthe L = {}; 0 programs for clarity. For[n = 0, n<Nmax+1, n++, f = h*n*I; H =Table[Switch[i−j,−1,f ∗(i+1)/Sqrt[ (2i+1)(2i+3)],0,i(i+1)/2,1,f∗(i)/Sqrt[(2i−1)(2i+ Program for computing Q(ρ~) 1)], 0],i,0,lmax,j,0,lmax]; , M = MatrixExp[-beta*H]; ClearAll[h,f,Z,lmax,H,beta,L1,L2,LPR,PR] Z = M[[1, 1]]; lmax=10; L = Append[L, Z]] Nmax=3000; L = Re[L]; beta=3; Pz = {}; h=.005; P1z = {}; L={}; For[l=−2,l<1200,l++,xi=.001∗l; For[n=0,n<Nmax+1,n++, P = (h*beta/Pi)*Sum[L[[n]]*Cos[(n - 1)*h*xi*beta], n, f=h*n*I; 1, Nmax]; H =Table[Switch[i−j,−1,f ∗(i+1)/Sqrt[ Pz = Append[Pz, xi, P]; (2i+1)(2i+3)],0,i(i+1)/2,1,f∗(i)/Sqrt[(2i−1)(2i+ P1z = Append[P1z, P]]; 1)], 0],i,0,lmax,j,0,lmax]; V = P1z; , M=MatrixExp[-beta*H]; QR1 = {}; (*Computation of Z(f)*) L1 = Drop[V, 2]; 5 L2 = Drop[V, -2]; [4] A. Ott, M. Magnasco, A. Simon, and A. Libch- LPR = (L1 - L2)/(.001*2); aber, Phys. Rev. E 48, R1642 (1993), URL LPR = Drop[LPR, 1]; http://link.aps.org/doi/10.1103/PhysRevE.48.R1642. [5] T. Sanchez, I. M. Kulic, and Z. 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