Physics - Biological Physics Publications (50)


Physics - Biological Physics Publications

Proposal to develop an Improved immunological assay employing primary IgG antibodies and secondary IgM antibodies labeled with quantum dots to amplify antigen detection. Read More

Amyloid beta peptides (A\b{eta}), implicated in Alzheimers disease (AD), interact with the cellular membrane and induce amyloid toxicity. The composition of cellular membranes changes in aging and AD. We designed multi component lipid models to mimic healthy and diseased states of the neuronal membrane. Read More

Stress-induced glucocorticoid elevation is a highly conserved response among vertebrates. This facilitates stress adaptation and the mode of action involves activation of the intracellular glucocorticoid receptor leading to the modulation of target gene expression. However, this genomic effect is slow acting and, therefore, a role for glucocorticoid in the rapid response to stress is unclear. Read More

Thiol self assembled monolayers (SAMs) are widely used in many nano- and bio-technology applications. We report a new approach to create and characterize a thiol SAMs micropattern with alternating charges on a flat goldcoated substrate using atomic force microscopy (AFM) and Kelvin probe force microscopy (KPFM). We produced SAMs patterns made of alternating positively charged, negatively charged, and hydrophobic terminated thiols by an automated AFM assisted manipulation, or nanografting. Read More

Using atomic force microscopy (AFM) we investigated the interaction of amyloid beta (Ab) (1 42) peptide with chemically modified surfaces in order to better understand the mechanism of amyloid toxicity, which involves interaction of amyloid with cell membrane surfaces. We compared the structure and density of Ab fibrils on positively and negatively charged as well as hydrophobic chemically modified surfaces at physiologically relevant conditions. Read More

The link between metals, Alzheimers disease (AD) and its implicated protein, amyloid \b{eta} (A\b{eta}), is complex and highly studied. AD is believed to occur as a result of the misfolding and aggregation of A\b{eta}. The dyshomeostasis of metal ions and their propensity to interact with A\b{eta} has also been implicated in AD. Read More

Superparamagnetic iron oxide nanoparticles (SPIONs), due to their controllable sizes, relatively long in vivo half-life and limited agglomeration, are ideal for biomedical applications such as magnetic labeling, hyperthermia cancer treatment, targeted drug delivery and for magnetic resonance imaging (MRI) as contrast enhancement agents. In order to understand how SPIONs interact with cells and cellular membranes it would be of interest to characterize individual SPIONs at the nanoscale in physiologically relevant conditions without labeling them. We demonstrate that Magnetic Force Microscopy (MFM) can be used to image SPIONs in air as well as in liquid. Read More

Metal ions, including copper and zinc, have been implicated in the pathogenesis of Alzheimers disease through a variety of mechanisms including increased amyloid \b{eta} affinity and redox effects. Recent reports have demonstrated that the amyloid \b{eta} monomer does not necessarily travel through a definitive intermediary en-route to a stable amyloid fibril structure. Rather, amyloid \b{eta} misfolding may follow a variety of pathways resulting in a fibrillar end-product or a variety of oligomeric end-products with a diversity of structures and sizes. Read More

Alzheimer's disease (AD) is a devastating neurodegenerative disorder with no cure and limited treatment solutions that are unable to target any of the suspected causes. Increasing evidence suggests that one of the causes of neurodegeneration is the overproduction of amyloid beta (A\b{eta}) and the inability of A\b{eta} peptides to be cleared from the brain, resulting in self-aggregation to form toxic oligomers, fibrils and plaques. One of the potential treatment options is to target A\b{eta} and prevent self-aggregation to allow for a natural clearing of the brain. Read More

Since the invention of the atomic force microscope (AFM) in 1986, there has been a drive to apply this scanning probe technique or a form of this technique to various disciplines in nanoscale science. Magnetic force microscopy (MFM) is a member of a growing family of scanning probe methods and has been widely used for the study of magnetic materials. In MFM a magnetic probe is used to raster-scan the surface of the sample, of which its magnetic field interacts with the magnetic tip to offer insight into its magnetic properties. Read More

Organic material in anoxic sediment represents a globally significant carbon reservoir that acts to stabilize Earth's atmospheric composition. The dynamics by which microbes organize to consume this material remain poorly understood. Here we observe the collective dynamics of a microbial community, collected from a salt marsh, as it comes to steady state in a two-dimensional ecosystem, covered by flowing water and under constant illumination. Read More

We consider the problem of inferring the probability distribution of flux configurations in metabolic network models from empirical flux data. For the simple case in which experimental averages are to be retrieved, data are described by a Boltzmann-like distribution ($\propto e^{F/T}$) where $F$ is a linear combination of fluxes and the `temperature' parameter $T\geq 0$ allows for fluctuations. The zero-temperature limit corresponds to a Flux Balance Analysis scenario, where an objective function ($F$) is maximized. Read More

We present a method of detecting sequence defects by supercoiling DNA with magnetic tweezers. The method is sensitive to a single mismatched base pair in a DNA sequence of several thousand base pairs. We systematically compare DNA molecules with 0 to 16 adjacent mismatches at 1 M monovalent salt and 3. Read More

We employ Real-Time Time-Dependent Density Functional Theory to study hole oscillations within a B-DNA monomer (one base pair) or dimer (two base pairs). Placing the hole initially at any of the bases which make up a base pair, results in THz oscillations, albeit of negligible amplitude. Placing the hole initially at any of the base pairs which make up a dimer is more interesting: For dimers made of identical monomers, we predict oscillations with frequencies in the range $f \approx$ 20-80 THz, with a maximum transfer percentage close to 1. Read More

A multi-scale framework was recently proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent, where we formulated the physical model and developed a numerical fluid dynamics integrator. In this study, we incorporated the fluid dynamics integrator with the Amber simulation engine to conduct atomistic simulations of biomolecules. At this stage of the development, only nonelectrostatic interactions, i. Read More

We investigate the effective two- and three-body interactions mediated between non-active colloidal inclusions immersed in an active bath of chiral or non-chiral self-propelled particles (swimmers). We perform Brownian Dynamics simulations within a standard model comprising hard inclusions and swimmers in two spatial dimensions. In the absence of chirality, we corroborate previous findings by showing that strong, repulsive, two-body forces of medium range (up to surface separations of a few swimmer radii) emerge between colloidal inclusions in the active bath. Read More

We evaluate the practical performance of the zero-multiple summation method (ZMM), a method for approximately calculating electrostatic interactions in molecular dynamics simulations. The performance of the ZMM is compared with that of the smooth particle mesh Ewald method (SPME). Even though the ZMM uses a larger cutoff distance than the SPME does, the performance of the ZMM is found to be comparable to or better than that of the SPME. Read More

Quantitative nuclear magnetic resonance imaging (MRI) shifts more and more into the focus of clinical research. Especially determination of relaxation times without/and with contrast agents becomes the foundation of tissue characterization, e.g. Read More

Single-molecule biophysics has transformed our understanding of the fundamental molecular processes involved in living biological systems, but also of the fascinating physics of life. Far more exotic than a collection of exemplars of soft matter behaviour, active biological matter lives far from thermal equilibrium, and typically covers multiple length scales from the nanometre level of single molecules up several orders of magnitude to longer length scales in emergent structures of cells, tissues and organisms. Biological molecules are often characterized by an underlying instability, in that multiple metastable free energy states exist which are separated by energy levels of typically just a few multiples of the thermal energy scale of kBT, where kB is the Boltzmann constant and T the absolute temperature, implying complex, dynamic inter-conversion kinetics across this bumpy free energy landscape in the relatively hot, wet environment of real, living biological matter. Read More

DNA is an essential molecule central to the survival and propagation of life, it was imperative to investigate possible electromagnetic properties inherent to it, such as the existence of any non-trivial interactions of this molecule with electromagnetic fields (beyond the usual dielectric response and damage by ionizing gamma radiations). Extensive investigations were carried out with both prokaryotic and eukaryotic purified DNA samples utilizing some of the most sensitive and precision instrumentation and methods available, while scanning the whole spectral region from 1Hz to 100KHz (in the low frequencies) and all the way to the high-frequency region of 100MHz (including investigations on the effects of 100MHz high-frequency fields as well as 2.4GHz microwave fields on the DNA). Read More

Membrane proteins constitute a large portion of the human proteome and perform a variety of important functions as membrane receptors, transport proteins, enzymes, signaling proteins, and more. The computational studies of membrane proteins are usually much more complicated than those of globular proteins. Here we propose a new continuum model for Poisson-Boltzmann calculations of membrane channel proteins. Read More

Active dynamic processes of cells are largely driven by the cytoskeleton, a complex and adaptable semiflexible polymer network, motorized by mechanoenzymes. Small dimensions, confined geome- tries and hierarchical structures make it challenging to probe dynamics and mechanical response of such networks. Embedded semiflexible probe polymers can serve as non-perturbing multi-scale probes to detect force distributions in active polymer networks. Read More

Membrane proteins and lipids can self-assemble into membrane protein polyhedral nanoparticles (MPPNs). MPPNs have a closed spherical surface and a polyhedral protein arrangement, and may offer a new route for structure determination of membrane proteins and targeted drug delivery. We develop here a general analytic model of how MPPN self-assembly depends on bilayer-protein interactions and lipid bilayer mechanical properties. Read More

In this work we study how a viral capsid can change conformation using techniques of Large Deviations Theory for stochastic differential equations. The viral capsid is a model of a complex system in which many units - the proteins forming the capsomers - interact by weak forces to form a structure with exceptional mechanical resistance. The destabilization of such a structure is interesting both per se, since it is related either to infection or maturation processes, and because it yields insights into the stability of complex structures in which the constitutive elements interact by weak attractive forces. Read More

Collective cell migration is a highly regulated process involved in wound healing, cancer metastasis and morphogenesis. Mechanical interactions among cells provide an important regulatory mechanism to coordinate such collective motion. Using a Self-Propelled Voronoi (SPV) model that links cell mechanics to cell shape and cell motility, we formulate a generalized mechanical inference method to obtain the spatio-temporal distribution of cellular stresses from measured traction forces in motile tissues and show that such traction-based stresses match those calculated from instantaneous cell shapes. Read More

A computational framework integrating optimization algorithms, parallel computing and plant physiology was developed to explore crop ideotype design. The backbone of the framework is a plant physiology model that accurately tracks water use (i.e. Read More

We are concerned with the dynamical description of the motion of a stochastic micro-swimmer with constant speed and fluctuating orientation in the long time limit by adiabatic elimination of the orientational variable. Starting with the corresponding full set of Langevin equations, we eliminate the memory in the stochastic orientation and obtain a stochastic equation for the position alone in the overdamped limit. An equivalent procedure based on the Fokker-Planck equation is presented as well. Read More

Biochemical reaction networks frequently consist of species evolving on multiple timescales. Stochastic simulations of such networks are often computationally challenging and therefore various methods have been developed to obtain sensible stochastic approximations on the timescale of interest. One of the rigorous and popular approaches is the multiscale approximation method for continuous time Markov processes. Read More

The activity of a neuronal network, characterized by action potentials (spikes) is constrained by the intrinsic properties of neurons and their interactions. When a neuronal network is submitted to external stimuli, the statistics of spikes changes, and becomes difficult to disentangle the influence of the stimuli from the intrinsic dynamics. Using the formalism of Gibbs distributions we analyze this problem in a specific model (Conductance-based Integrate-and-Fire), where the neuronal dynamics depends on the history of spikes of the network. Read More

Molecular motors are nonequilibrium open systems that convert chemical energy to mechanical work. Here we investigate the nonequilibrium energetics of a single molecule kinesin by measuring the motion of an attached probe particle and its response to external forces with optical tweezers. The sum of the heat dissipation estimated from the violation of the fluctuation-response relation and the output power was inconsistent with the input free energy rate, implying that internal dissipation is dominant. Read More

Contact between particles and motile cells underpins a wide variety of biological processes, from nutrient capture and ligand binding, to grazing, viral infection and cell-cell communication. The window of opportunity for these interactions is ultimately determined by the physical mechanism that enables proximity and governs the contact time. Jeanneret et al. Read More

Optogenetics is an emerging field of neuroscience where neurons are genetically modified to express light-sensitive receptors that enable external control over when the neurons fire. Given the prominence of neuronal signaling within the brain and throughout the body, optogenetics has significant potential to improve the understanding of the nervous system and to develop treatments for neurological diseases. This paper uses a simple optogenetic model to compare the timing distortion between a randomly-generated target spike sequence and an externally-stimulated neuron spike sequence. Read More

Recent experiments have revealed that the diffusivity of exothermic and fast enzymes is enhanced when they are catalytically active, and different physical mechanisms have been explored and quantified to account for this observation. We perform measurements on the endothermic and relatively slow enzyme aldolase, which also shows substrate-induced enhanced diffusion. We propose a new physical paradigm, which reveals that the diffusion coefficient of a model enzyme hydrodynamically coupled to its environment increases significantly when undergoing changes in conformational fluctuations in a substrate-dependent manner, and is independent of the overall turnover rate of the underlying enzymatic reaction. Read More

Here we report a method for visualization of volumetric structural information of live biological samples with no exogenous contrast agents. The process is made possible through a technique that involves generation, synthesis and analysis of three-dimensional (3D) Fourier components of light diffracted by the sample. This leads to the direct recovery of quantitative cellular morphology with no iterative procedures for reduced computational complexity. Read More

It is known that the eye's scotopic photodetectors, rhodopsin molecules and their associated phototransduction mechanism leading to light perception, are efficient single photon counters. We here use the photon counting principles of human rod vision to propose a secure quantum biometric identification based on the quantum-statistical properties of retinal photon detection. The photon path along the human eye until its detection by rod cells is modeled as a filter having a specific transmission coefficient. Read More

For quantitative phase imaging (QPI) based on transport-of-intensity equation (TIE), partially coherent illumination provides speckle-free imaging, compatibility with brightfield microscopy, and transverse resolution beyond coherent diffraction limit. Unfortunately, in a conventional microscope with circular illumination aperture, partial coherence tends to diminish the phase contrast, exacerbating the inherent noise-to-resolution tradeoff in TIE imaging, resulting in strong low-frequency artifacts and compromised imaging resolution. Here, we demonstrate how these issues can be effectively addressed by replacing the conventional circular illumination aperture with an annular one. Read More

We derive a Ito stochastic differential equation for entropy production in nonequilibrium Langevin processes. Introducing a stochastic time, entropy production obeys a one-dimensional drift-diffusion equation, independent of the underlying physical model. This time transformation allows us to identify generic properties of entropy production. Read More

The intrinsic stochasticity of gene expression can give rise to large fluctuations and rare events that drive phenotypic variation in a population of genetically identical cells. Characterizing the fluctuations that give rise to such rare events motivates the analysis of large deviations in stochastic models of gene expression. Recent developments in non-equilibrium statistical mechanics have led to a framework for analyzing Markovian processes conditioned on rare events and for representing such processes by conditioning-free driven Markovian processes. Read More

Gene drives have the potential to rapidly replace a harmful wild-type allele with a gene drive allele engineered to have desired functionalities. However, an accidental or premature release of a gene drive construct to the natural environment could damage an ecosystem irreversibly. Thus, it is important to understand the spatiotemporal consequences of the super-Mendelian population genetics prior to potential applications. Read More

In a standard bifurcation of a dynamical system, the stationary points (or more generally attractors) change qualitatively when varying a control parameter. Here we describe a novel unusual effect, when the change of a parameter, e.g. Read More

We propose a fully cooperative coinfection model in which singly infected individuals are more likely to acquire a second disease than those who are susceptible, and doubly infected individuals are also assumed to be more contagious than those infected with one disease. The dynamics of such fully cooperative coinfection model between two interacting infectious diseases is investigated through well-mixed and network-based approaches. We show that the former approach exhibits three types of hysteresis, namely, $C$, $S_l$ and $S_r$ types, where the last two types have not been identified before. Read More

We introduce a self-consistent multi-species kinetic theory based on the structure of the narrow voltage-gated potassium channel. Transition rates depend on a complete energy spectrum with contributions including the dehydration amongst species, interaction with the dipolar charge of the filter and, bulk solution properties. It displays high selectivity between species coexisting with fast conductivity, and Coulomb blockade phenomena, and it fits well to data. Read More

The biophysical analysis of dynamically formed multi-protein complexes in solution presents a formidable technical challenge. Sedimentation velocity (SV) analytical ultracentrifugation achieves strongly size-dependent hydrodynamic resolution of different size species, and can be combined with multi-component detection by exploiting different spectral properties or temporally modulated signals from photoswitchable proteins. Coexisting complexes arising from self- or hetero-associations that can be distinguished in SV allow measurement of their stoichiometry, affinity, and cooperativity. Read More

Magnetic nanoparticles are promising systems for biomedical applications and in particular for Magnetic Fluid Hyperthermia, a promising therapy that utilizes the heat released by such systems to damage tumor cells. We present an experimental study of the physical properties that influences the capability of heat release, i.e. Read More

Electrostatic interactions play crucial roles in biophysical processes such as protein folding and molecular recognition. Poisson-Boltzmann equation (PBE)-based models have emerged as widely used in modeling these important processes. Though great efforts have been put into developing efficient PBE numerical models, challenges still remain due to the high dimensionality of typical biomolecular systems. Read More

The observed spatio-temporal ciliary beat patterns on multiciliated epithelia are suspected to be the result of self-organizing processes on various levels. Here, we present an abstract epithelium model at the pluricellular level, which intends to make the self-organization of ciliary beating patterns as well as of the associated fluid transport across the airway epithelium plausible. Ciliated cells are modeled in terms of locally interacting oscillating two-state actuators. Read More

Cells receive signaling molecules by receptors and relay the information via sensory networks so that they can respond properly depending on the type of signals. Recent studies show that cells can extract multi-dimensional information from dynamical concentration patterns of signaling molecules. Here we study how cells generally and optimally process multi-dimensional information embedded in dynamical patterns through biochemical networks. Read More

We study a large number of physically-plausible arrangements of chromophores, generated via a computational method involving stochastic real-space transformations of a naturally occurring `reference' structure, illustrating our methodology using the well-studied Fenna-Matthews-Olsen complex (FMO). To explore the idea that the natural structure has been tuned for the efficient transport of excitons, we use an atomic transition charge method to calculate the excitonic couplings of each generated structure and a Lindblad master equation to study the quantum transport of an exciton from a `source' to a `drain' chromophore. We find statistically significant correlations between structure and transport efficiency: High-performing structures tend to be more compact and, among those, the best structures display a certain orientation of the chromophores, particularly the chromophore closest to the source-to-drain vector. Read More

The notion of entropy is shared between statistics and thermodynamics, and is fundamental to both disciplines. This makes statistical problems particularly suitable for reaction network implementations. In this paper we show how to perform a statistical operation known as Information Projection or E projection with stochastic mass-action kinetics. Read More

Surface molecules, distributed in diverse patterns and clusters on cell membranes, influence vital functions of living cells. It is therefore important to understand their molecular surface organisation under different physiological and pathological conditions. Here, we present a model-free, quantitative method to determine the distribution of cell surface molecules based on TIRF illumination and super-resolution optical fluctuation imaging (SOFI). Read More