Polymer translocation through a nanopore under an applied external field

We investigate the dynamics of polymer translocation through a nanopore under an externally applied field using the 2D fluctuating bond model with single-segment Monte Carlo moves. We concentrate on the influence of the field strength $E$, length of the chain $N$, and length of the pore $L$ on forced translocation. As our main result, we find a crossover scaling for the translocation time $\tau$ with the chain length from $\tau \sim N^{2\nu}$ for relatively short polymers to $\tau \sim N^{1 + \nu}$ for longer chains, where $\nu$ is the Flory exponent. We demonstrate that this crossover is due to the change in the dependence of the translocation velocity v on the chain length. For relatively short chains $v \sim N^{- \nu}$, which crosses over to $v \sim N^{- 1}$ for long polymers. The reason for this is that with increasing $N$ there is a high density of segments near the exit of the pore, which slows down the translocation process due to slow relaxation of the chain. For the case of a long nanopore for which $R_\parallel$, the radius of gyration $R_{g}$ along the pore, is smaller than the pore length, we find no clear scaling of the translocation time with the chain length. For large $N$, however, the asymptotic scaling $\tau \sim N^{1 + \nu}$ is recovered. In this regime, $\tau$ is almost independent of $L$. We have previously found that for a polymer, which is initially placed in the middle of the pore, there is a minimum in the escape time for $R_\parallel \approx L$. We show here that this minimum persists for a weak fields $E$ such that $EL$ is less than some critical value, but vanishes for large values of $EL$.Comment: 25 Pages, 10 figures. Submitted to J. Chem. Phys. J. Chem. Phys. 124, in press (2006

Probing molecular free energy landscapes by periodic loading

Single molecule pulling experiments provide information about interactions in biomolecules that cannot be obtained by any other method. However, the reconstruction of the molecule's free energy profile from the experimental data is still a challenge, in particular for the unstable barrier regions. We propose a new method for obtaining the full profile by introducing a periodic ramp and using Jarzynski's identity for obtaining equilibrium quantities from non-equilibrium data. Our simulated experiments show that this method delivers significant more accurate data than previous methods, under the constraint of equal experimental effort.Comment: 4 pages, 3 figure

Molecular Spiders in One Dimension

Molecular spiders are synthetic bio-molecular systems which have "legs" made of short single-stranded segments of DNA. Spiders move on a surface covered with single-stranded DNA segments complementary to legs. Different mappings are established between various models of spiders and simple exclusion processes. For spiders with simple gait and varying number of legs we compute the diffusion coefficient; when the hopping is biased we also compute their velocity.Comment: 14 pages, 2 figure

Mechanochemical action of the dynamin protein

Dynamin is a ubiquitous GTPase that tubulates lipid bilayers and is implicated in many membrane severing processes in eukaryotic cells. Setting the grounds for a better understanding of this biological function, we develop a generalized hydrodynamics description of the conformational change of large dynamin-membrane tubes taking into account GTP consumption as a free energy source. On observable time scales, dissipation is dominated by an effective dynamin/membrane friction and the deformation field of the tube has a simple diffusive behavior, which could be tested experimentally. A more involved, semi-microscopic model yields complete predictions for the dynamics of the tube and possibly accounts for contradictory experimental results concerning its change of conformation as well as for plectonemic supercoiling.Comment: 17 pages, 4 figures; typos corrected, reference adde

Genetic noise control via protein oligomerization

Gene expression in a cell entails random reaction events occurring over disparate time scales. Thus, molecular noise that often results in phenotypic and population-dynamic consequences sets a fundamental limit to biochemical signaling. While there have been numerous studies correlating the architecture of cellular reaction networks with noise tolerance, only a limited effort has been made to understand the dynamic role of protein-protein interactions. Here we have developed a fully stochastic model for the positive feedback control of a single gene, as well as a pair of genes (toggle switch), integrating quantitative results from previous in vivo and in vitro studies. We find that the overall noise-level is reduced and the frequency content of the noise is dramatically shifted to the physiologically irrelevant high-frequency regime in the presence of protein dimerization. This is independent of the choice of monomer or dimer as transcription factor and persists throughout the multiple model topologies considered. For the toggle switch, we additionally find that the presence of a protein dimer, either homodimer or heterodimer, may significantly reduce its random switching rate. Hence, the dimer promotes the robust function of bistable switches by preventing the uninduced (induced) state from randomly being induced (uninduced). The specific binding between regulatory proteins provides a buffer that may prevent the propagation of fluctuations in genetic activity. The capacity of the buffer is a non-monotonic function of association-dissociation rates. Since the protein oligomerization per se does not require extra protein components to be expressed, it provides a basis for the rapid control of intrinsic or extrinsic noise

Stochastic Eulerian Lagrangian Methods for Fluid-Structure Interactions with Thermal Fluctuations

We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for operators coupling these descriptions. Stochastic driving fields for the formalism are derived using principles from statistical mechanics. The stochastic differential equations of the formalism are found to exhibit significant stiffness in some physical regimes. To cope with this issue, we derive reduced stochastic differential equations for several physical regimes. We also present stochastic numerical methods for each regime to approximate the fluid-structure dynamics and to generate efficiently the required stochastic driving fields. To validate the methodology in each regime, we perform analysis of the invariant probability distribution of the stochastic dynamics of the fluid-structure formalism. We compare this analysis with results from statistical mechanics. To further demonstrate the applicability of the methodology, we perform computational studies for spherical particles having translational and rotational degrees of freedom. We compare these studies with results from fluid mechanics. The presented approach provides for fluid-structure systems a set of rather general computational methods for treating consistently structure mechanics, hydrodynamic coupling, and thermal fluctuations.Comment: 24 pages, 3 figure

Expression quantitative trait loci are highly sensitive to cellular differentiation state

Blood cell development from multipotent hematopoietic stem cells to specialized blood cells is accompanied by drastic changes in gene expression for which the triggers remain mostly unknown. Genetical genomics is an approach linking natural genetic variation to gene expression variation, thereby allowing the identification of genomic loci containing gene expression modulators (eQTLs). In this paper, we used a genetical genomics approach to analyze gene expression across four developmentally close blood cell types collected from a large number of genetically different but related mouse strains. We found that, while a significant number of eQTLs (365) had a consistent “static” regulatory effect on gene expression, an even larger number were found to be very sensitive to cell stage. As many as 1,283 eQTLs exhibited a “dynamic” behavior across cell types. By looking more closely at these dynamic eQTLs, we show that the sensitivity of eQTLs to cell stage is largely associated with gene expression changes in target genes. These results stress the importance of studying gene expression variation in well-defined cell populations. Only such studies will be able to reveal the important differences in gene regulation between different ce

A Connection between Obscuration and Star Formation in Luminous Quasars

We present a measurement of the star formation properties of a uniform sample of mid-IR selected, unobscured and obscured quasars (QSO1s and QSO2s) in the Bo\ otes survey region. We use an spectral energy distribution (SED) analysis for photometric data spanning optical to far-IR wavelengths to decompose AGN and host galaxy components. We find that when compared to a matched sample of QSO1s, the QSO2s have higher far-IR detection fractions, far-IR fluxes and infrared star formation luminosities (LSFIR) by a factor of ∼2. Correspondingly, we show that the AGN obscured fraction rises from 0.3 to 0.7 between 4−40×1011L⊙. We also find evidence associating the absorption in the X-ray emission with the presence of far-IR emitting dust. Overall, these results are consistent with galaxy evolution models in which quasar obscurations can be associated with a dust-enshrouded starburst galaxie

Single-molecule experiments in biological physics: methods and applications

I review single-molecule experiments (SME) in biological physics. Recent technological developments have provided the tools to design and build scientific instruments of high enough sensitivity and precision to manipulate and visualize individual molecules and measure microscopic forces. Using SME it is possible to: manipulate molecules one at a time and measure distributions describing molecular properties; characterize the kinetics of biomolecular reactions and; detect molecular intermediates. SME provide the additional information about thermodynamics and kinetics of biomolecular processes. This complements information obtained in traditional bulk assays. In SME it is also possible to measure small energies and detect large Brownian deviations in biomolecular reactions, thereby offering new methods and systems to scrutinize the basic foundations of statistical mechanics. This review is written at a very introductory level emphasizing the importance of SME to scientists interested in knowing the common playground of ideas and the interdisciplinary topics accessible by these techniques. The review discusses SME from an experimental perspective, first exposing the most common experimental methodologies and later presenting various molecular systems where such techniques have been applied. I briefly discuss experimental techniques such as atomic-force microscopy (AFM), laser optical tweezers (LOT), magnetic tweezers (MT), biomembrane force probe (BFP) and single-molecule fluorescence (SMF). I then present several applications of SME to the study of nucleic acids (DNA, RNA and DNA condensation), proteins (protein-protein interactions, protein folding and molecular motors). Finally, I discuss applications of SME to the study of the nonequilibrium thermodynamics of small systems and the experimental verification of fluctuation theorems. I conclude with a discussion of open questions and future perspectives.Comment: Latex, 60 pages, 12 figures, Topical Review for J. Phys. C (Cond. Matt

Monte Carlo Simulations of HIV Capsid Protein Homodimer

Capsid protein (CA) is the building block of virus coats. To help understand how the HIV CA proteins self-organize into large assemblies of various shapes, we aim to computationally evaluate the binding affinity and interfaces in a CA homodimer. We model the N- and C-terminal domains (NTD and CTD) of the CA as rigid bodies and treat the five-residue loop between the two domains as a flexible linker. We adopt a transferrable residue-level coarse-grained energy function to describe the interactions between the protein domains. In seven extensive Monte Carlo simulations with different volumes, a large number of binding/unbinding transitions between the two CA proteins are observed, thus allowing a reliable estimation of the equilibrium probabilities for the dimeric vs monomeric forms. The obtained dissociation constant for the CA homodimer from our simulations, 20–25 μM, is in reasonable agreement with experimental measurement. A wide range of binding interfaces, primarily between the NTDs, are identified in the simulations. Although some observed bound structures here closely resemble the major binding interfaces in the capsid assembly, they are statistically insignificant in our simulation trajectories. Our results suggest that although the general purpose energy functions adopted here could reasonably reproduce the overall binding affinity for the CA homodimer, further adjustment would be needed to accurately represent the relative strength of individual binding interfaces