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At least 523 records · Page 29Linked to original sources

arXiv2018

Hydrodynamics of Diffusion in Lipid Membrane Simulations

By performing molecular dynamics simulations with up to 132 million coarse-grained particles in half-micron sized boxes, we show that hydrodynamics quantitatively explains the finite-size effects on diffusion of lipids, proteins, and carbon nanotubes in membranes. The resulting Oseen correction allows us to extract infinite-system diffusion coefficients and membrane surface viscosities from membrane simulations despite the logarithmic divergence of apparent diffusivities with increasing box width. The hydrodynamic theory of diffusion applies also to membranes with asymmetric leaflets and embedded proteins, and to a complex plasma-membrane mimetic.

cond-mat.soft↗

arXiv2013

Physics of adherent cells

One of the most unique physical features of cell adhesion to external surfaces is the active generation of mechanical force at the cell-material interface. This includes pulling forces generated by contractile polymer bundles and networks, and pushing forces generated by the polymerization of polymer networks. These forces are transmitted to the substrate mainly by focal adhesions, which are large, yet highly dynamic adhesion clusters. Tissue cells use these forces to sense the physical properties of their environment and to communicate with each other. The effect of forces is intricately linked to the material properties of cells and their physical environment. Here a review is given of recent progress in our understanding of the role of forces in cell adhesion from the viewpoint of theoretical soft matter physics and in close relation to the relevant experiments.

q-bio.CB↗

arXiv2017

Molecular Motor or Molecular Clock: A Question of Load

The output of a motor is work, while the output of a clock is information. Here it is discussed how a molecular motor can produce both, work and information, depending on the load. If the ratio of the backward and forward stepping rates of a molecular motor increases exponentially with load, the change in free energy per step can be used to produce only work (at stall force) or only timing information (at zero force), or anything in between.

physics.chem-ph↗

arXiv2013

Chemical energy in an introductory physics course for the life sciences

Energy is a complex idea that cuts across scientific disciplines. For life science students, an approach to energy that incorporates chemical bonds and chemical reactions is better equipped to meet the needs of life sciences students than a traditional introductory physics approach that focuses primarily on mechanical energy. We present a curricular sequence, or thread, designed to build up students' understanding of chemical energy in an introductory physics course for the life sciences. This thread is designed to connect ideas about energy from physics, biology, and chemistry. We describe the kinds of connections among energetic concepts that we intended to develop to build interdisciplinary coherence, and present some examples of curriculum materials and student data that illustrate our approach.

physics.ed-ph↗

arXiv2013

Elasticity of DNA and the effect of Dendrimer Binding

Negatively charged DNA can be compacted by positively charged dendrimers and the degree of compaction is a delicate balance between the strength of the electrostatic interaction and the elasticity of DNA. We report various elastic properties of short double stranded DNA (dsDNA) and the effect of dendrimer binding using fully atomistic molecular dynamics and numerical simulations. In equilibrium at room temperature, the contour length distribution P(L) and end-to-end distance distribution P(R) are nearly Gaussian, the former gives an estimate of the stretch modulus γ_1 of dsDNA in quantitative agreement with the literature value. The bend angle distribution P(θ) of the dsDNA also has a Gaussian form and allows to extract a persistence length, L_p of 43 nm. When the dsDNA is compacted by positively charged dendrimer, the stretch modulus stays invariant but the effective bending rigidity estimated from the end-to-end distance distribution decreases dramatically due to backbone charge neutralization of dsDNA by dendrimer. We support our observations with numerical solutions of the worm-like-chain (WLC) model as well as using non-equilibrium dsDNA stretching simulations. These results are helpful in understanding the dsDNA elasticity at short length scales as well as how the elasticity is modulated when dsDNA binds to a charged object such as a dendrimer or protein.

physics.bio-ph↗

arXiv2018

Sub-picosecond proton tunnelling in deformed DNA hydrogen bonds under an asymmetric double-oscillator model

We present a model of proton tunnelling across DNA hydrogen bonds, compute the characteristic tunnelling time (CTT) from donor to acceptor and discuss its biological implications. The model is a double oscillator characterised by three geometry parameters describing planar deformations of the H bond, and a symmetry parameter representing the energy ratio between ground states in the individual oscillators. If the symmetry parameter takes its maximum value of 1, then we recover a known model which produced CTTs too large to be biologically relevant; but this is reduced by up to 40 orders of magnitude as the symmetry parameter is decreased. We discover that unless the symmetry parameter is close to 1 or 0, the proton's CTT under any planar deformation is guaranteed to be below one picosecond, which is a biologically relevant time-scale. This supports theories of links between proton tunnelling and biological processes such as spontaneous mutation.

physics.bio-ph↗

arXiv2013

Dynamics of ions in the selectivity filter of the KcsA channel: Towards a coupled Brownian particle description

The statistical and dynamical properties of ions in the selectivity filter of the KcsA ion channel are considered on the basis of molecular dynamics (MD) simulations of the KcsA protein embedded in a lipid membrane surrounded by an ionic solution. A new approach to the derivation of a Brownian dynamics (BD) model of ion permeation through the filter is discussed, based on unbiased MD simulations. It is shown that depending on additional assumptions, ion's dynamics can be described either by under-damped Langevin equation with constant damping and white noise or by Langevin equation with a fractional memory kernel. A comparison of the potential of the mean force derived from unbiased MD simulations with the potential produced by the umbrella sampling method demonstrates significant differences in these potentials. The origin of these differences is an open question that requires further clarifications.

physics.bio-ph↗

arXiv2014

Viral Evolution and Adaptation as a Multivariate Branching Process

In the present work we analyze the problem of adaptation and evolution of RNA virus populations, by defining the basic stochastic model as a multivariate branching process in close relation with the branching process advanced by Demetrius, Schuster and Sigmund ("Polynucleotide evolution and branching processes", Bull. Math. Biol. 46 (1985) 239-262), in their study of polynucleotide evolution. We show that in the absence of beneficial forces the model is exactly solvable. As a result it is possible to prove several key results directly related to known typical properties of these systems like (i) proof, in the context of the theory of branching processes, of the lethal mutagenesis criterion proposed by Bull, Sanjuán and Wilke ("Theory of lethal mutagenesis for viruses", J. Virology 18 (2007) 2930-2939); (ii) a new proposal for the notion of relaxation time with a quantitative prescription for its evaluation and (iii) the quantitative description of the evolution of the expected values in four distinct regimes: transient, "stationary" equilibrium, extinction threshold and lethal mutagenesis. Moreover, new insights on the dynamics of evolving virus populations can be foreseen.

q-bio.PE↗

arXiv2013

On Kinetic Equations Modeling Evolution of Systems in Mathematical Biology

We develop a rigorous formalism for the description of the kinetic evolution of interacting entities modeling systems in mathematical biology within the framework of the evolution of marginal observables. For this purpose we construct the mean field asymptotic behavior of a solution of the Cauchy problem of the dual BBGKY hierarchy for marginal observables of the dynamical systems based on the Markov jump processes, exhibiting the intrinsic properties of the living entities. The constructed scaling limit is governed by the set of recurrence evolution equations, namely by the dual Vlasov-type hierarchy. Moreover, the relationships of the dual Vlasov hierarchy for the limit marginal observables with the Vlasov-type kinetic equation is established.

math-ph↗

arXiv2012

The statistical properties of protein folding in the ϕ^4 theory

The statistical properties of protein folding within the ϕ^4 model are investigated. The calculation is performed using statistical mechanics and path integral method. In particular, the evolution of heat capacity in term of temperature is given for various levels of the nonlinearity of source and the strength of interaction between protein backbone and nonlinear source. It is found that the nonlinear source contributes constructively to the specific heat especially at higher temperature when it is weakly interacting with the protein backbone. This indicates increasing energy absorption as the intensity of nonlinear sources are getting greater. The simulation of protein folding dynamics within the model is also refined.

physics.bio-ph↗

arXiv2013

Effective viscosity of non-gravitactic Chlamydomonas Reinhardtii microswimmer suspensions

Active microswimmers are known to affect the macroscopic viscosity of suspensions in a more complex manner than passive particles. For puller-like microswimmers an increase in the viscosity has been observed. It has been suggested that the persistence of the orientation of the microswimmers hinders the rotation that is normally caused by the vorticity. It was previously shown that some sorts of algaes are bottom-heavy swimmers, i.e. their centre of mass is not located in the centre of the body. In this way, the algae affects the vorticity of the flow when it is perpendicular oriented to the axis of gravity. This orientation of gravity to vorticity is given in a rheometer that is equipped with a cone-plate geometry. Here we present measurements of the viscosity both in a cone-plate and a Taylor-Couette cell. The two set-ups yielded the same increase in viscosity although the axis of gravitation in the Taylor-Couette cell is parallel to the direction of vorticity. In a complementary experiment we tested the orientation of the direction of swimming through microscopic observation of single \textit{Chlamydomonas reinhardtii} and could not identify a preferred orientation, i. e. our specific strain of \textit{Chlamydomonas reinhardtii} are not bottom-heavy swimmers. We thus conclude that bottom heaviness is not a prerequisite for the increase of viscosity and that the effect of gravity on the rheology of our strain of \textit{Chlamydomonas reinhardtii} is negligible. This finding reopens the question of whether origin of persistence in the orientation of cells is actually responsible for the increased viscosity of the suspension.

physics.bio-ph↗

arXiv2013

Pair quenched mean-field theory for the susceptible-infected-susceptible model on complex networks

We present a quenched mean-field (QMF) theory for the dynamics of the susceptible-infected-susceptible (SIS) epidemic model on complex networks where dynamical correlations between connected vertices are taken into account by means of a pair approximation. We present analytical expressions of the epidemic thresholds in the star and wheel graphs and in random regular networks. For random networks with a power law degree distribution, the thresholds are numerically determined via an eigenvalue problem. The pair and one-vertex QMF theories yield the same scaling for the thresholds as functions of the network size. However, comparisons with quasi-stationary simulations of the SIS dynamics on large networks show that the former is quantitatively much more accurate than the latter. Our results demonstrate the central role played by dynamical correlations on the epidemic spreading and introduce an efficient way to theoretically access the thresholds of very large networks that can be extended to dynamical processes in general.

physics.bio-ph↗

arXiv2014

Can scale-freeness offset delayed signal detection in neuronal networks?

First spike latency following stimulus onset is of significant physiological relevance. Neurons transmit information about their inputs by transforming them into spike trains, and the timing of these spike trains is in turn crucial for effectively encoding that information. Random processes and uncertainty that underly neuronal dynamics have been shown to prolong the time towards the first response in a phenomenon dubbed noise-delayed decay. Here we study whether Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise might have shorter response times to external stimuli just above threshold if placed on a scale-free network. We show that the heterogeneity of the interaction network may indeed eradicate slow responsiveness, but only if the coupling between individual neurons is sufficiently strong. Increasing the average degree also favors a fast response, but it is less effective than increasing the coupling strength. We also show that noise-delayed decay can be offset further by adjusting the frequency of the external signal, as well as by blocking a fraction of voltage-gated sodium or potassium ion channels. For certain conditions, we observe a double peak in the response time depending on the intensity of intrinsic noise, indicating competition between local and global effects on the neuronal dynamics.

physics.bio-ph↗

arXiv2014

Shape-dependent bounds on cell growth rates

I consider how cell shape and environmental geometry affect the rate of nutrient capture and the consequent maximum growth rate of a cell, focusing on rod-like species like \textit{E.\ coli}. Simple modeling immediately implies that it is the elongated profiles of such cells that allows for them to grow -- as observed -- at exponential rates in nutrient-rich media. Growth is strongly suppressed when nutrient capture is diffusion-limited: In three dimensions, the length is bounded by $\log L \lesssim t^{1/2}$, and in lower dimensions growth is algebraic. Similar bounds are easily obtained for other cell geometries, groups of cells, \textit{etc}. Fits of experimental growth curves to such bounds can be used to estimate various quantities of interest, including generalized metabolic rates.

physics.bio-ph↗

arXiv2014

Stochastic Dynamics of Electrical Membrane with Voltage-Dependent Ion Channel Fluctuations

Brownian ratchet like stochastic theory for the electrochemical membrane system of Hodgkin-Huxley (HH) is developed. The system is characterized by a continuous variable $Q_m(t)$, representing mobile membrane charge density, and a discrete variable $K_t$ representing ion channel conformational dynamics. A Nernst-Planck-Nyquist-Johnson type equilibrium is obtained when multiple conducting ions have a common reversal potential. Detailed balance yields a previously unknown relation between the channel switching rates and membrane capacitance, bypassing Eyring-type explicit treatment of gating charge kinetics. From a molecular structural standpoint, membrane charge $Q_m$ is a more natural dynamic variable than potential $V_m$; our formalism treats $Q_m$-dependent conformational transition rates $λ_{ij}$ as intrinsic parameters. Therefore in principle, $λ_{ij}$ vs. $V_m$ is experimental protocol dependent,e.g., different from voltage or charge clamping measurements. For constant membrane capacitance per unit area $C_m$ and neglecting membrane potential induced by gating charges, $V_m=Q_m/C_m$, and HH's formalism is recovered. The presence of two types of ions, with different channels and reversal potentials, gives rise to a nonequilibrium steady state with positive entropy production $e_p$. For rapidly fluctuating channels, an expression for $e_p$ is obtained.

physics.bio-ph↗

arXiv2013

In situ ore formation experiment: Amino acids and amino sugars trapped in artificial chimneys on deep-sea hydrothermal systems at Suiyo Seamount, Izu-Bonin Arc, Pacific Ocean

The present study reports on the bio-organic composition of a deep-sea venting hydrothermal system originating from arc volcanism; the origin of the particulates in hydrothermal fluids from the Suiyo Seamount in the southern Izu-Bonin (Ogasawara) Arc is discussed with regard to amino compounds. Chimney samples on deep-sea hydrothermal systems and core samples at Suiyo Seamount were determined for amino acids, and occasionally amino sugars. Two types of chimney samples were obtained from active hydrothermal systems by submersible vehicles: one was natural chimney (NC) on a hydrothermal natural vent; the other was artificial chimneys (AC), mainly formed by the growth and deposition of sulfide-rich particulate components in a Kuwabara-type in situ incubator (KI incubator). Total hydrolyzed amino acids (THAA) and hydrolyzed hexosamines (HA) in AC ranged from 10.7 nmol/g to 64.0 nmol/g and from 0 nmol/g to 8.1 nmol/g, respectively, while THAA in hydrothermally altered core samples ranged from 26.0 nmol/g to 107.4 nmol/g-rock. The THAA was thus of the same order of magnitude in AC and core samples. The representative biochemical indicator ratios of β-alanine/aspartic acid and γ-aminobutyric acid/glutamic acid were low. This is consistent with a large microbial population and labile subterranean biogenic organic compounds. A micro energy dispersive X-ray spectrometer (μEDX) was used to show that the formation of massive pyrite- and chalcopyrite-ores, the major matrixes of the natural chimney structures, were processed during hydrothermal activity. These data suggest that labile particulate organic matter (POM) and/or dissolved organic matter (DOM) from hydrothermal fluid were continuously trapped to form concentrated organic matter in a sulfide-rich matrix.

physics.bio-ph↗

arXiv2014

Tracking individual nanodiamonds in Drosophila melanogaster embryos

Tracking the dynamics of fluorescent nanoparticles during embryonic development allows insights into the physical state of the embryo and, potentially, molecular processes governing developmental mechanisms. In this work, we investigate the motion of individual fluorescent nanodiamonds micro-injected into Drosophila melanogaster embryos prior to cellularisation. Fluorescence correlation spectroscopy and wide-field imaging techniques are applied to individual fluorescent nanodiamonds in blastoderm cells during stage 5 of development to a depth of ~40 μm. The majority of nanodiamonds in the blastoderm cells during cellularisation exhibit free diffusion with an average diffusion coefficient of (6 $\pm$ 3) x 10$^{-3}$ μm$^2$/s, (mean $\pm$ SD). Driven motion in the blastoderm cells was also observed with an average velocity of 0.13 $\pm$ 0.10 μm/s (mean $\pm$ SD) μm/s and an average applied force of 0.07 $\pm$ 0.05 pN (mean $\pm$ SD). Nanodiamonds in the periplasm between the nuclei and yolk were also found to undergo free diffusion with a significantly larger diffusion coefficient of (63 $\pm$ 35) x10$^{-3}$ μm$^2$/s (mean $\pm$ SD). Driven motion in this region exhibited similar average velocities and applied forces compared to the blastoderm cells indicating the transport dynamics in the two cytoplasmic regions are analogous.

physics.bio-ph↗

arXiv2013

Effective harmonic potentials: insights into the internal cooperativity and sequence-specificity of protein dynamics

The proper biological functioning of proteins often relies on the occurrence of coordinated fluctuations around their native structure, or of wider and sometimes highly elaborated motions. Coarse-grained elastic-network descriptions are known to capture essential aspects of conformational dynamics in proteins, but have so far remained mostly phenomenological, and unable to account for the chemical specificities of amino acids. Here, we propose a method to derive residue- and distance-specific effective harmonic potentials from the statistical analysis of an extensive dataset of NMR conformational ensembles. These potentials constitute dynamical counterparts to the mean-force statistical potentials commonly used for static analyses of protein structures. In the context of the elastic network model, they yield a strongly improved description of the cooperative aspects of residue motions, and give the opportunity to systematically explore the influence of sequence details on protein dynamics.

q-bio.BM↗