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At least 253 records · Page 14Linked to original sources
arXiv2013

Distribution of Traction Forces and Intracellular Markers Associated with Shape Changes During Amoeboid Cell Migration

During migration, amoeboid cells perform a cycle of quasi-periodic repetitive events (motility cycle). the cell length and the strain energy exchanged with the substrate oscillate in time with an average frequency, f, on top of which are imposed smaller random fluctuations. the fact that a considerable portion of the changes in cell shape are due to periodic repetitive events enables the use of conditional statistics methods to analyze the network of biochemical processes involved in cell motility. taking advan- tage of this cyclic nature, we apply Principal Component analysis (PCa) and phase- average statistics to analyze the dominant modes of shape change and their association to the activity and localization of molecular motors. We analyze time-lapse measure- ments of cell shape, traction forces and fluorescence from green fluorescent protein (GfP) reporters for f-actin in Dictyostelium cells undergoing guided chemotactic migration. using wild-type cells (wt) as reference, we investigated the contractile and actin crosslinking functions of myosin II by studying myosin II heavy chain null mutant cells (mhcA-) and myosin II essential light chain null cells (mlcE-).

q-bio.CB↗
arXiv2013

High Throughput Screening of Natural Phenolic Compounds Against Migration of Metastatic Triple-Negative Breast Cancer (TNBC) Cells

In this report, we hypothesize that natural phenolic compounds may present a new class of chemotherapeutics against migration of metastatic triple-negative breast cancers (TNBC). In this project we will screen a small library of phenolic compounds to test this hypothesis, identify compounds that show efficacy against TNBC cell migration, and elucidate underlying molecular mechanisms.

q-bio.CB↗
arXiv2013

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We present simulation results of the tumor growth model and discuss tumor properties that favor the proposed high-performance design.

q-bio.QM↗
arXiv2013

Signal transduction and directional sensing in eukaryotes

Control of the cytoskeleton and mechanical contacts with the extracellular environment are essential component of motility in eukaryotic cells. In the absence of signals, cells continuously rebuild the cytoskeleton and periodically extend pseudopods or other protrusions at random membrane locations. Extracellular signals bias the direction of movement by biasing the extension of protrusions, but this involves another layer of biochemical networks for signal detection, transduction, and control of the rebuilding of the cytoskeleton. Here we develop a model for the latter processes that centers on a Ras-based module that adapts to constant extracellular signals and controls the downstream PI3K-PIP3-based module responsible for amplifying a spatial gradient of the signal. The resulting spatial gradient can lead to polarization, which enables cells to move in the preferred direction (up gradient for attractants and down-gradient for repellents). We show that the model can replicate many of the observed characteristics of the responses to cAMP stimulation for Dictyostelium, and analyze how cell geometry and signaling interact to produce the observed localization of some of the key components of the amplification module. We show how polarization can emerge without directional cues, and how it interacts with directional signals and leads to directional persistence. Since other cells such as neutrophils use similar pathways, the model is a generic one for a large class of eukaryotic cells.

q-bio.CB↗
arXiv2015

Colloquium: Mechanical formalisms for tissue dynamics

The understanding of morphogenesis in living organisms has been renewed by tremendous progressin experimental techniques that provide access to cell-scale, quantitative information both on theshapes of cells within tissues and on the genes being expressed. This information suggests that ourunderstanding of the respective contributions of gene expression and mechanics, and of their crucialentanglement, will soon leap forward. Biomechanics increasingly benefits from models, which assistthe design and interpretation of experiments, point out the main ingredients and assumptions, andultimately lead to predictions. The newly accessible local information thus calls for a reflectionon how to select suitable classes of mechanical models. We review both mechanical ingredientssuggested by the current knowledge of tissue behaviour, and modelling methods that can helpgenerate a rheological diagram or a constitutive equation. We distinguish cell scale ("intra-cell")and tissue scale ("inter-cell") contributions. We recall the mathematical framework developpedfor continuum materials and explain how to transform a constitutive equation into a set of partialdifferential equations amenable to numerical resolution. We show that when plastic behaviour isrelevant, the dissipation function formalism appears appropriate to generate constitutive equations;its variational nature facilitates numerical implementation, and we discuss adaptations needed in thecase of large deformations. The present article gathers theoretical methods that can readily enhancethe significance of the data to be extracted from recent or future high throughput biomechanicalexperiments.

physics.bio-ph↗
arXiv2013

Spatial anisotropy and heterogeneity in contractility and adhesion distribution may contribute to cell steering during migration

Transition from random to persistent cell motility requires spatiotemporal organization of the cytoskeleton and focal adhesions. The influence of these two structures on cell steering can also be gleaned from trypsin de-adhesion experiments, wherein cells exposed to trypsin round up, exhibiting a combination of rotation and translation. Here, we present a model to evaluate the contributions of contractility and bond distribution to experimentally observed de-adhesion. We show that while asymmetry in bond distribution causes only cell translation, a combination of asymmetric bond distribution and non-uniform contractility are required for translation and rotation, and may guide cell migration.

q-bio.CB↗
arXiv2013

Application of CellDesigner to the Selection of Anticancer Drug Targets: Test Case using P53

Cancer is a disease involving many genes, consequently it has been difficult to design anticancer drugs that are efficacious over a broad range of cancers. The robustness of cellular responses to gene knockout and the need to reduce undesirable side effects also contribute to the problem of effective anti-cancer drug design. To promote the successful selection of drug targets, each potential target should be subjected to a systems biology scrutiny to locate effective and specific targets while minimizing undesirable side effects. The gene p53 is considered a good candidate for such a target because it has been implicated in 50% of all cancers and is considered to encode a hub protein that is highly connected to other proteins. Using P53 as a test case, this paper explores the capacity of the systems biology tool, CellDesigner, to aid in the selection of anticancer drug targets and to serve as a teaching resource for human resource development.

q-bio.CB↗
arXiv2013

Study on Antibody-Virus Interaction using Molecular Dynamics: Two Dimensional Simulation on Immunoglobulin Reaction against Human Papillomavirus

Human Papillomavirus (HPV) has been known as one of the cause of virus-induced cancer such as cervical cancer and carcinoma. Among other types of cancer, this type has higher chance in being prevented earlier. The main idea is to eradicate the virus as soon as it enters the body by marking it with antibodies; signaling the immune system to dispose of it. However, the antibodies must be trained to recognize the virus. They can be trained by inserting an object similar to the virus allowing them to learn to recognize and surround the inserted object. In response to this, molecular dynamics simulation was chosen to study the antibody-virus interaction. In this work, two-dimensional case that involves HPV and immunoglobulin (Ig) was studied and observed. Two types of objects will be defined; one stands for HPV while another stands for antibodies. The interaction between the two objects will be governed by two forces; Coulomb force and repulsive contact force. Through the definition of some rules and condition, the antibodies' motion was observed. The influence of antibody concentration, and the antibody's type and their appearance sequence were observed both quantitatively and visually. Keywords: antibody-virus interaction, molecular dynamics, HPV, immunoglobulin.

q-bio.CB↗
arXiv2013

Sepsis is a syndrome with hyperactivity of TH17-like innate immunity and hypoactivity of adaptive immunity

Currently, there are two major theories for the pathogenesis of sepsis: hyperimmune and hypoimmune. Hyperimmune theory suggests that cytokine storm causes the symptoms of sepsis. On the contrary, hypoimmune theory suggests that immunosuppression causes the manifestations of sepsis. By using microarray study, this study implies that hyperactivity of TH17-like innate immunity and failure of adaptive immunity are noted in sepsis patients. I find out that innate immunity related genes are significantly up-regulated including CD14, TLR1,2,4,5,8, HSP70, CEBP proteins, AP1(JUNB, FOSL2), TGF-β, IL-6, TGF-α, CSF2 receptor, TNFRSF1A, S100A binding proteins, CCR2, formyl peptide receptor2, amyloid proteins, pentraxin, defensins, CLEC5A, whole complement machinery, CPD, NCF, MMP, neutrophil elastase, caspases, IgG and IgA Fc receptors(CD64, CD32), ALOX5, PTGS, LTB4R, LTA4H, and ICAM1. Majority of adaptive immunity genes are down-regulated including MHC related genes, TCR genes, granzymes/perforin, CD40, CD8, CD3, TCR signaling, BCR signaling, T & B cell specific transcription factors, NK killer receptors, and TH17 helper specific transcription factors(STAT3, RORA, REL). In addition, Treg related genes are up-regulated including TGFβ, IL-15, STAT5B, SMAD2/4, CD36, and thrombospondin. Thus, both hyperimmune and hypoimmune play important roles in the pathophysiology of sepsis.

q-bio.GN↗
arXiv2013

Oscillations in a neurite growth model with extracellular feedback

We take into account the influence of extracellular signalling on neurite elongation in a model of neurite growth mediated by building proteins (e.g. tubulin). Tubulin production dynamics was supplied by a function describing the influence of the extracellular signalling that can promote or depress the elongation. We found that such extracellular feedback can generate neurite length oscillations with periodic sequence of elongations and retractions. The oscillations prevent further outgrowth of the neurite which becomes trapped in the non-uniform extracellular field. We analyzed the characteristics of the elongation process for different distributions of attracting and repelling sources of the extracellular signal molecules. The model predicts three different scenarios of the neurite development in the extracellular field including monotonic and oscillatory outgrowth, localized limit cycle oscillations and complete depression of the growth.

q-bio.CB↗
arXiv2013

Unstable Angina is a syndrome correlated to mixed Th17 and Th1 immune disorder

Unstable angina is common clinical manifestation of atherosclerosis. However, the detailed pathogenesis of unstable angina is still not known. Here, I propose that unstable angina is a mixed TH17 and TH1 immune disorder. By using microarray analysis, I find out that TH1 and TH17 related cytokine, cytokine receptor, chemokines, complement, immune-related transcription factors, anti-bacterial genes, Toll-like receptors, and heat shock proteins are all up-regulated in peripheral leukocytes of unstable angina. In addition, H-ATPase, glycolytic genes, platelet and RBC related genes are also up-regulated in peripheral leukocytes of during unstable angina. It also implies that atherosclerosis is a mixed TH17 and TH1 autoimmune disease. If we know the etiology of unstable angina as well as atherosclerosis better, we can have better methods to control and prevent this detrimental illness.

q-bio.CB↗
arXiv2013

Parameter identification problems in the modelling of cell motility

We present a novel parameter identification algorithm for the estimation of parameters in models of cell motility using imaging data of migrating cells. Two alternative formulations of the objective functional that measures the difference between the computed and observed data are proposed and the parameter identification problem is formulated as a minimisation problem of nonlinear least squares type. A Levenberg-Marquardt based optimisation method is applied to the solution of the minimisation problem and the details of the implementation are discussed. A number of numerical experiments are presented which illustrate the robustness of the algorithm to parameter identification in the presence of large deformations and noisy data and parameter identification in three dimensional models of cell motility. An application to experimental data is also presented in which we seek to identify parameters in a model for the monopolar growth of fission yeast cells using experimental imaging data.

math.NA↗
arXiv2013

Model for tumour growth with treatment by continuous and pulsed chemotherapy

In this work we investigate a mathematical model describing tumour growth under a treatment by chemotherapy that incorporates time-delay related to the conversion from resting to hunting cells. We study the model using values for the parameters according to experimental results and vary some parameters relevant to the treatment of cancer. We find that our model exhibits a dynamical behaviour associated with the suppression of cancer cells, when either continuous or pulsed chemotherapy is applied according to clinical protocols, for a large range of relevant parameters. When the chemotherapy is successful, the predation coefficient of the chemotherapic agent acting on cancer cells varies with the infusion rate of chemotherapy according to an inverse relation. Finally, our model was able to reproduce the experimental results obtained by Michor and collaborators [Nature, 435, 1267 (2005)] about the exponential decline of cancer cells when patients are treated with the drug glivec.

q-bio.TO↗
arXiv2013

Mathematical Model of Colorectal Cancer with Monoclonal Antibody Treatments

We present a new mathematical model of colorectal cancer growth and its response to monoclonal-antibody (mAb) therapy. Although promising, most mAb drugs are still in trial phases, and the possible variations in the dosing schedules of those currently approved for use have not yet been thoroughly explored. To investigate the effectiveness of current mAb treatment schedules, and to test hypothetical treatment strategies, we have created a system of nonlinear ordinary differential equations (ODE) to model colorectal cancer growth and treatment. The model includes tumor cells, elements of the host's immune response, and treatments. Model treatments include the chemotherapy agent irinotecan and one of two monoclonal antibodies - cetuximab, which is FDA-approved for colorectal cancer, and panitumumab, which is still being evaluated in clinical trials. The model incorporates patient-specific parameters to account for individual variations in immune system strength and in medication efficacy against the tumor. We have simulated outcomes for groups of virtual patients on treatment protocols for which clinical trial data are available, using a range of biologically reasonable patient-specific parameter values. Our results closely match clinical trial results for these protocols. We also simulated experimental dosing schedules, and have found new schedules which, in our simulations, reduce tumor size more effectively than current treatment schedules. Additionally, we examined the system's equilibria and sensitivity to parameter values. In the absence of treatment, tumor evolution is most affected by the intrinsic tumor growth rate and carrying capacity. When treatment is introduced, tumor growth is most affected by drug-specific PK/PD parameters.

q-bio.CB↗
arXiv2013

Analysis and Simulation of the Three-Component Model of HIV Dynamics

Mathematical modeling of biological systems is crucial to effectively and efficiently developing treatments for medical conditions that plague humanity. Often, systems of ordinary differential equations are a traditional tool used to describe the spread of disease within the body. We consider the dynamics of the Human Immunodeficiency Virus (HIV) in vivo during the initial stage of infection. In particular, we examine the well-known three-component model and prove the existence, uniqueness, and boundedness of solutions. Furthermore, we prove that solutions remain biologically meaningful, i.e., are positivity preserving, and perform a thorough, local stability analysis for the equilibrium states of the system. Finally, we incorporate random coefficients within the model and obtain numerical results to predict the probability of infection given the transmission of the virus to a new individual.

math.CA↗
arXiv2013

Towards slime mould colour sensor: Recognition of colours by Physarum polycephalum

Acellular slime mould Physarum polycephalum is a popular now user-friendly living substrate for designing of future and emergent sensing and computing devices. P. polycephalum exhibits regular patterns of oscillations of its surface electrical potential. The oscillation patterns are changed when the slime mould is subjected to mechanical, chemical, electrical or optical stimuli. We evaluate feasibility of slime-mould based colour sensors by illuminating Physarum with red, green, blue and white colours and analysing patterns of the slime mould's electrical potential oscillations. We define that the slime mould recognises a colour if it reacts to illumination with the colour by a unique changes in amplitude and periods of oscillatory activity. In laboratory experiments we found that the slime mould recognises red and blue colour. The slime mould does not differentiate between green and white colours. The slime mould also recognises when red colour is switched off. We also map colours to diversity of the oscillations: illumination with a white colour increases diversity of amplitudes and periods of oscillations, other colours studied increase diversity either of amplitude or period.

cs.ET↗
arXiv2013

Comment on Masanari Asano et al. A model of epigenetic evolution based on theory of open quantum systems. Syst Synth Biol, 2013

The comment mostly concerns mis-representation of my position on Quantum Biology, by stating that I am 'reducing cell's behavior to quantum particles inside the cell'. I contrast my position with that of McFadden-Al-Khalili, as well as with the position of Asano et al. I also advertise an idea, described in our latest paper (Bordonaro, Ogryzko. Quantum Biology at the Cellular level - elements of the research program, BioSystems, 2013), for the need of synthetic biology in testing some predictions that follow from our approach.

q-bio.CB↗