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At least 307 records · Page 17Linked to original sources

arXiv2014

Studies of protein adsorption on implant materials in relation to biofilm formation I. Activity of Pseudomonas aeruginosa on Polypropylene and High density Polyethylene in presence of serum albumin

The surface of biomaterials used as implants are highly susceptible to bacterial colonization and subsequent infection. The amount of protein adsorption on biomaterials, among other factors, can affect the nature and quality of biofilms formed on them. The variation in the adsorption time of the protein on the biomaterial surface produces a phenotypic change in the bacteria by alteration of the production of EPS (exoplysaccharide) matrix. Knowledge of the effects of protein adsorption on implant infection will be very useful in understanding the chemistry of the biomaterial surfaces, which can deter the formation of biofilms. It is observed that the adsorption of BSA on the biomaterial surfaces increases with time and concentration, irrespective of their type and the nature of the EPS matrix of the bacterial biofilm is dependent on the amount of protein adsorbed on the biomaterial surface. The adsorption of protein (BSA) on the biomaterials, polypropylene (PP) and high density polyethylene (HDPE) has been studied and the formation of the biofilms of Pseudomonas aeruginosa on them has been examined.

physics.bio-ph↗

arXiv2014

Activation of effector immune cells promotes tumor stochastic extinction: A homotopy analysis approach

In this article we provide homotopy solutions of a cancer nonlinear model describing the dynamics of tumor cells in interaction with healthy and effector immune cells. We apply a semi-analytic technique for solving strongly nonlinear systems - the Step Homotopy Analysis Method (SHAM). This algorithm, based on a modification of the standard homotopy analysis method (HAM), allows to obtain a one-parameter family of explicit series solutions. By using the homotopy solutions, we first investigate the dynamical effect of the activation of the effector immune cells in the deterministic dynamics, showing that an increased activation makes the system to enter into chaotic dynamics via a period-doubling bifurcation scenario. Then, by adding demographic stochasticity into the homotopy solutions, we show, as a difference from the deterministic dynamics, that an increased activation of the immune cells facilitates cancer clearance involving tumor cells extinction and healthy cells persistence. Our results highlight the importance of therapies activating the effector immune cells at early stages of cancer progression.

nlin.CD↗

arXiv2014

Model for Acid-Mediated Tumour Invasion with Chemotherapy Intervention I: Homogeneous Populations

The acid-mediation hypothesis, that is, the hypothesis that acid produced by tumours, as a result of aerobic glycolysis, provides a mechanism for invasion, has so far been considered as a relatively closed system. The focus has mainly been on the dynamics of the tumour, normal-tissue, acid and possibly some other bodily components, without considering the effect of an external intervention such as a cytotoxic treatment. This article aims to examine the effect that a cytotoxic treatment has on a tumour growing under the acid-mediation hypothesis by using a simple set of ordinary differential equations that consider the interaction between normal-tissue, tumour-tissue, acid and chemotherapy drug.

q-bio.CB↗

arXiv2014

Growth-dependent bacterial susceptibility to ribosome-targeting antibiotics

Bacterial growth environment strongly influences the efficacy of antibiotic treatment, with slow growth often being associated with decreased susceptibility. Yet in many cases the connection between antibiotic susceptibility and pathogen physiology remains unclear. We show that for ribosome-targeting antibiotics acting on Escherichia coli, a complex interplay exists between physiology and antibiotic action; for some antibiotics within this class faster growth indeed increases susceptibility, but for other antibiotics the opposite is true. Remarkably, these observations can be explained by a simple mathematical model that combines drug transport and binding with physiological constraints. Our model reveals that growth-dependent susceptibility is controlled by a single parameter characterizing the `reversibility' of antibiotic transport and binding. This parameter provides a spectrum-classification of antibiotic growth-dependent efficacy that appears to correspond at its extremes to existing binary classification schemes. In these limits the model predicts universal, parameter-free limiting forms for growth inhibition curves. The model also leads to non-trivial predictions for the drug susceptibility of a translation-mutant strain of E. coli, which we verify experimentally. Drug action and bacterial metabolism are mechanistically complex; nevertheless this study illustrates how coarse-grained models can be used to integrate pathogen physiology into drug design and treatment strategies.

q-bio.CB↗

arXiv2014

Optimal Observation Time Points in Stochastic Chemical Kinetics

Wet-lab experiments, in which the dynamics within living cells are observed, are usually costly and time consuming. This is particularly true if single-cell measurements are obtained using experimental techniques such as flow-cytometry or fluorescence microscopy. It is therefore important to optimize experiments with respect to the information they provide about the system. In this paper we make a priori predictions of the amount of information that can be obtained from measurements. We focus on the case where the measurements are made to estimate parameters of a stochastic model of the underlying biochemical reactions. We propose a numerical scheme to approximate the Fisher information of future experiments at different observation time points and determine optimal observation time points. To illustrate the usefulness of our approach, we apply our method to two interesting case studies.

q-bio.CB↗

arXiv2014

Cancer Metastasis: Collective Invasion in Heterogeneous Multicellular Systems

Heterogeneity within tumour cell populations is associated with an increase in malignancy and appears to play an important role during cancer metastasis. Using in silico experiments, we study the interplay between collective behaviours and cell motility heterogeneities in a model system. Working with tumour spheroids that contain two non-proliferating cell populations of different motile properties, we explore the conditions required for maximal invasion into surrounding tissues. We show emerging spatial patterns of cellular organisation and invasion which are consistent with in vitro and in vivo observations. This demonstrates that mechanical interactions at the cellular level are sufficient to account for many of the observed morphologies of invasion and that heterogeneity in cell motility can be more important than average mechanical properties in controlling the fate of large cell populations.

q-bio.TO↗

arXiv2015

Yeast caspase 1 suppresses the burst of reactive oxygen species and maintains mitochondrial stability in Saccharomyces cerevisiae

Caspases are a family of cysteine proteases that play essential roles during apoptosis, and we presume some of them may also protect the cell from oxidative stress. We found that the absence of yeast caspase 1(Yca1)in Saccharomyces cerevisiae leads to a more intense burst of mitochondrial reactive oxygen species (ROS) In addition, compared to wild type yeast cells, the ability of yca1 mutant cells to maintain mitochondrial activity is significantly reduced after either oxidative stress treatment or aging. During mitochondrial ROS burst, deletion of the yca1 gene delayed structural damage of a green fluorescent protein (GFP) reporter bound in the inner mitochondrial membrane. This work implies that yeast caspase 1 is closely connected to the oxidative stress response. We speculate that Yca1 can discriminate proteins damaged by oxidation and accelerate their hydrolysis to attenuate the ROS burst.

q-bio.CB↗

arXiv2015

Numerical Model for the Deformation of Nucleated Cells by Optical Stretchers

In this paper, we seek to model the deformation of nucleated cells by single diode-laser bar optical stretchers. We employ a recently developed computational model, the Dynamic Ray-Tracing method, to determine the stress distribution induced by the applied optical forces on a capsule encapsulating a nucleus of different optical properties. These forces are shape dependent and can deform real non-rigid objects; thus resulting in a dynamically changing optical stress distribution with cell and nucleus deformation. Chinese hamster ovary cell is a common biological cell that is of interest to the biomedical community because of their use in recombinant protein therapeutics and is an example of a nucleated cell. To this end, we model chinese hamster ovary cells as two three-dimensional elastic capsules of variable inner capsule size immersed in a fluid where the hydrodynamic forces are calculated using the Immersed Boundary Method. Our results show that the presence of a nucleus has a major effect on the force distribution on the cell surface and the net deformation. Scattering and gradient forces are reported for different nucleus sizes and the effect of nucleus size on the cell deformation is discussed.

physics.bio-ph↗

arXiv2015

Mathematical Modelings for Angiogenesis - A Cellular Automaton Model and its Continuous Model

Based on recent experiments with time-lapse fluorescent imaging, we propose a cellular automaton model for the dynamics of vascular endothelial cells (ECs) in angiogenic morphogenesis. The model successfully reproduces cell mixing behavior, elongation and bifurcation of blood vessels. The results suggest that the two-body interaction between ECs, which is repulsive in short distance and become attractive in moderately long distance, is essential to the dynamics of ECs, in particular, to the cell mixing behavior. The corresponding analytically solvable differential equation model is also proposed.

nlin.CG↗

arXiv2016

An introduction to linear stability analysis for deciphering spatial patterns in signaling networks

Mathematical modeling is now used commonly in the analysis of signaling networks. With advances in high resolution microscopy, the spatial location of different signaling molecules and the spatio-temporal dynamics of signaling microdomains are now widely acknowledged as key features of biochemical signal transduction. Reaction-diffusion mechanisms are commonly used to model such features, often with a heavy reliance on numerical simulations to obtain results. However, simulations are parameter dependent and may not be able to provide an understanding of the full range of the system responses. Analytical approaches on the other hand provide a framework to study the entire phase space. In this tutorial, we provide a largely analytical method for studying reaction-diffusion models and analyzing their stability properties. Using two representative biological examples, we demonstrate how this approach can guide experimental design.

q-bio.SC↗

arXiv2015

Maximum velocity of self-propulsion for an active segment

The motor part of a crawling eukaryotic cell can be represented schematically as an active continuum layer. The main active processes in this layer are protrusion, originating from non-equilibrium polymerization of actin fibers, contraction, induced by myosin molecular motors and attachment due to active bonding of trans-membrane proteins to a substrate. All three active mechanisms are regulated by complex signaling pathways involving chemical and mechanical feedback loops whose microscopic functioning is still poorly understood. In this situation, it is instructive to take a reverse engineering approach and study a problem of finding the spatial organization of standard active elements inside a crawling layer ensuring an optimal cost-performance trade-off. In this paper we assume that (in the range of interest) the energetic cost of self-propulsion is velocity independent and adopt, as an optimality criterion, the maximization of the overall velocity. We then choose a prototypical setting, formulate the corresponding variational problem and obtain a set of bounds suggesting that radically different spatial distributions of adhesive complexes would be optimal depending on the domineering active mechanism of self-propulsion. Thus, for contraction-dominated motility, adhesion has to cooperate with 'pullers' which localize at the trailing edge of the cell, while for protrusion-dominated motility it must conspire with 'pushers' concentrating at the leading edge of the cell. Both types of crawling mechanisms were observed experimentally.

physics.bio-ph↗

arXiv2015

An Extended Filament Based Lamellipodium Model Produces Various Moving Cell Shapes in the Presence of Chemotactic Signals

The Filament Based Lamellipodium Model (FBLM) is a two-phase two-dimensional continuum model, describing the dynamcis of two interacting families of locally parallel actin filaments (C.Schmeiser and D.Oelz, How do cells move? Mathematical modeling of cytoskeleton dynamics and cell migration. Cell mechanics: from single scale-based models to multiscale modeling. Chapman and Hall, 2010). It contains accounts of the filaments' bending stiffness, of adhesion to the substrate, and of cross-links connecting the two families. An extension of the model is presented with contributions from nucleation of filaments by branching, from capping, from contraction by actin-myosin interaction, and from a pressure-like repulsion between parallel filaments due to Coulomb interaction. The effect of a chemoattractant is described by a simple signal transduction model influencing the polymerization speed. Simulations with the extended model show its potential for describing various moving cell shapes, depending on the signal transduction procedure, and for predicting transients between nonmoving and moving states as well as changes of direction.

q-bio.CB↗

arXiv2015

First Passage processes in cellular biology

Often sharp changes in cellular behavior are triggered by thresholded events, i.e., by the attainment of a threshold value of a relevant cellular or molecular dynamical variable. Since the governing variable itself typically undergoes noisy or stochastic dynamics, there is a corresponding variability in the times when the same change occurs in each cell of a population. This time is called the "first passage" time and the corresponding process is a "first passage" (FP) process, referring to the event when a random variable first passes the threshold value. In this review we first present and elucidate fundamentals of the FP formalism within a unified conceptual framework, which naturally integrates the existing techniques. We then discuss applications thereof, with emphasis on the practical use of FP techniques in biophysical systems. Our focus here is on covering a diverse set of analytical techniques; the number of reviewed biological applications is thus limited, out of necessity. We focus on three specific areas: channel transport; receptor binding and adhesion; and single-cell growth and division.

cond-mat.stat-mech↗

arXiv2015

A model of calcium-mediated coupling between membrane activity and clock gene expression in neurons of the suprachiasmatic nucleus

Rhythms in electrical activity in the membrane of cells in the suprachiasmatic nucleus (SCN) are crucial for the function of the circadian timing system, which is characterized by the expression of the so-called clock genes. Intracellular Ca$^{2+}$ ions seem to connect, at least in part, the electrical activity of SCN neurons with the expression of clock genes. In this paper, we introduce a simple mathematical model describing the linking of membrane activity to the transcription of one gene by means of a feedback mechanism based on the dynamics of intracellular calcium ions.

physics.bio-ph↗

arXiv2015

Single-cell protein dynamics reproduce universal fluctuations in cell populations

Protein variability in single cells has been studied extensively in populations, but little is known about temporal protein fluctuations in a single cell over extended times. We present here traces of protein copy number measured in individual bacteria over multiple generations and investigate their statistical properties, comparing them to previously measured population snapshots. We find that temporal fluctuations in individual traces exhibit the same universal features as those previously observed in populations. Scaled fluctuations around the mean of each trace exhibit the same universal distribution shape as found in populations measured under a wide range of conditions and in two distinct microorganisms. Additionally, the mean and variance of the traces over time obey the same quadratic relation. Analyzing the temporal features of the protein traces in individual cells, reveals that within a cell cycle protein content increases as an exponential function with a rate that varies from cycle to cycle. This leads to a compact description of the protein trace as a 3-variable stochastic process - the exponential rate, the cell-cycle duration and the value at the cycle start - sampled once each cell cycle. This compact description is sufficient to preserve the universal statistical properties of the protein fluctuations, namely, the protein distribution shape and the quadratic relationship between variance and mean. Our results show that the protein distribution shape is insensitive to sub-cycle intracellular microscopic details and reflects global cellular properties that fluctuate between generations.

physics.bio-ph↗

arXiv2015

The extrinsic noise effect on lateral inhibition differentiation waves

Multipotent differentiation, where cells adopt one of several cell fates, is a determinate and orchestrated procedure that often incorporates stochastic mechanisms in order to diversify cell types. How these stochastic phenomena interact to govern cell fate are poorly understood. Nonetheless, cell fate decision making procedure is mainly regulated through the activation of differentiation waves and associated signaling pathways. In the current work, we focus on the Notch/Delta signaling pathway which is not only known to trigger such waves but also is used to achieve the principle of lateral inhibition, i.e. a competition for exclusive fates through cross-signaling between neighboring cells. Such a process ensures unambiguous stochastic decisions influenced by intrinsic noise sources, e.g.~as ones found in the regulation of signaling pathways, and extrinsic stochastic fluctuations, attributed to micro-environmental factors. However, the effect of intrinsic and extrinsic noise on cell fate determination is an open problem. Our goal is to elucidate how the induction of extrinsic noise affects cell fate specification in a lateral inhibition mechanism. Using a stochastic Cellular Automaton with continuous state space, we show that extrinsic noise results in the emergence of steady-state furrow patterns of cells in a "frustrated/transient" phenotypic state.

q-bio.CB↗

arXiv2015

On the Mechanism of Light Transmission by Müller Cells

We report that Müller cells contain bundles of long specialized intermediate filaments about 10 nm in diameter; most likely, these filaments are the channels providing light transmission to photoreceptor cells in mammalian and avian retinas. We interpret transmission of light in such channels using the notions of quantum confinement, describing energy transport in structures with electro-conductive walls and diameter much smaller than the wavelength of the respective photons. Model calculations produce photon transmission efficiency in such channels exceeding 0.8, in optimized geometry. We infer that protein molecules make up the channels, proposing a qualitative mechanism of light transmission by such structures.

physics.optics↗

arXiv2015

Optimal chemotaxis in animal cell intermittent migration

Animal cells can sense chemical gradients without moving, and are faced with the challenge of migrating towards a target despite noisy information on the target position. Here we discuss optimal search strategies for a chaser that moves by switching between two phases of motion ("run" and "tumble"), reorienting itself towards the target during tumble phases, and performing a persistent random walk during run phases. We show that the chaser average run time can be adjusted to minimize the target catching time or the spatial dispersion of the chasers. We obtain analytical results for the catching time and for the spatial dispersion in the limits of small and large ratios of run time to tumble time, and scaling laws for the optimal run times. Our findings have implications for optimal chemotactic strategies in animal cell migration.

physics.bio-ph↗