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Transient Leadership and Collective Cell Movement in Early Diverged Multicellular Animals

Collective motion of cells is critical to some of the most vital tasks including wound healing, development, and immune response [Friedl and Gilmour 2009; Tokarski et al. 2012; Lee et al. 2012; Beltman et al. 2009], and is common to many pathological processes including cancer cell invasion and teratogenesis [Khalil and Friedl 2010]. The extensive understanding of movement by single cells [Rørth 2011; Insall and Machesky 2011; Houk et al. 2012] is insufficient to predict the behavior of cellular groups [Theveneau et al. 2013; Trepat, X. and Fredberg 2011], and identifying underlying rules of coordination in collective cell migration is still evasive. Few of the supposed benefits of collective motion have ever been tested at the cellular scale. As an example, though collective sensing allows for larger groups to exhibit greater accuracy in navigation [Simons 2004; Berdahl et al. 2013] and group taxis is possible through the leadership of only a few individuals [Couzin et al. 2005], such effects have never been investigated in collective cell migration. We will investigate collective motion and decision-making in a primitive multicellular animal, Trichoplax adhaerens to understand how intercellular coordination affects animal behavior and how migration accuracy scales with cellular group size.

q-bio.CB↗

Emerging Allee effect in tumor growth

Tumor cells develop different features to adapt to environmental conditions. A prominent example is the ability of tumor cells to switch between migratory and proliferative phenotypes, a phenomenon known as go-or-grow mechanism. It is however unclear how this particular phenotypic plasticity affects overall tumor growth. To address this problem, we formulate and study a mathematical model of spatio-temporal tumor dynamics where different responses to local cell density mediate the go-or-grow dichotomy. Our analysis reveals that two dynamic regimes can be distinguished. If cell motility is allowed to increase with local cell density, any tumor cell population will persist in time, irrespective of its initial size. On the contrary, if cell motility is assumed to decrease with respect to local cell density, an Allee effect emerges, so that any tumor population below a certain size threshold eventually extinguishes. These results suggest that strategies aimed at hindering migration, for instance by enhancing contact inhibition, are worth to be explored as alternatives to those mainly focused at checking tumor proliferation.

q-bio.TO↗

Instant Response of Live HeLa Cells to Static Magnetic Field and Its Magnetic Adaptation

We report Static Magnetic Field (SMF) induced altered sub-cellular streaming, which retains even after withdrawal of the field. The observation is statistically validated by differential fluorescence recovery after photo-bleaching (FRAP) studies in presence and absence of SMF, recovery rate being higher in presence of SMF. This instant magneto-sensing by live cells can be explained by inherent diamagnetic susceptibility of cells and alternatively by spin recombination, e.g., by the radical pair mechanism. These arguments are however insufficient to explain the retention of the SMF effect even after field withdrawal. Typically, a relaxation time scale at least of the order of minutes is observed. This long duration of the SMF effect can be explained postulating a field induced coherence that is followed by decoherence after the field withdrawal. A related observation is the emergence of enhanced magnetic susceptibility of cells after magnetic pre-incubation. This implies onset of a new spin equilibrium state as a result of prolonged SMF incubation. Lastly, translation of such altered spin states to a cellular signal that leads to an altered sub-cellular streaming, probable intracellular machineries for this translation being discussed in the text.

q-bio.CB↗

Universal relationship in gene-expression changes for cells in steady-growth state

Cells adapt to different conditions by altering a vast number of components, which is measurable using transcriptome analysis. Given that a cell undergoing steady growth is constrained to sustain each of its internal components, the abundance of all the components in the cell has to be roughly doubled during each cell division event. From this steady-growth constraint, expression of all genes is shown to change along a one-parameter curve in the state space in response to the environmental stress. This leads to a global relationship that governs the cellular state: By considering a relatively moderate change around a steady state, logarithmic changes in expression are shown to be proportional across all genes, upon alteration of stress strength, with the proportionality coefficient given by the change in the growth rate of the cell. This theory is confirmed by transcriptome analysis of Escherichia Coli in response to several stresses.

q-bio.CB↗

Numerical simulation of growth of Escherichia coli in unsaturated porous media

A model for the aerobic and anaerobic growth of Escherichia coli (HB101 K12 pGLO) depending on the concentration of oxygen and DOC as substrate has been developed based on laboratory batch experiments. Using inverse modelling to obtain optimal sets of parameters, it could be shown that a model based on a modified double Contois kinetic can predict cell densities, organic carbon utilisation, oxygen transfer and utilisation rates for a large number of experiments under aerobic and anaerobic conditions with a single unique set of parameters. The model was extended to describe growth of E. coli in unsaturated porous media, combining diffusion, phase exchange and microbiological growth. Experiments in a Hele-Shaw cell, filled with quartz sand, were conducted to study bacterial growth in the capillary fringe above a saturated porous medium. Cell density profiles in the Hele-Shaw cell were predicted with the growth model and the parameters from the batch experiments without any further calibration. They showed a very good qualitative and quantitative agreement with cell densities determined from samples taken from the Hele-Shaw cell by re-suspension and subsequent counting. Thus it could be shown, that it is possible to successfully transfer growth parameters from batch experiments to porous media for both aerobic and anaerobic conditions.

q-bio.CB↗

Rare event simulation in immune biology: Models of negative selection in T-cell maturation

We present a probabilistic T-cell model that includes negative selection and takes contrasting models of tissue-restricted antigen (TRA) expression in the thymus into account. We start from the basic model of van den Berg, Rand, and Burroughs (2001) and include negative selection via individual-based T-cell modelling, in which each T-cell is defined by its stimulation rates to all relevant self antigens. We present a simulation approach based on partial tilting of the stimulation rates recognized by a single T-cell. We investigate the effects of negative selection for diverging modes of thymic antigen presentation, namely arbitrary TRA presentation, and more or less strict emulation of tissue-specific cell lines. We observe that negative selection leads to truncation of the tail of the distribution of the stimulation rates mature T-cells receive from self antigens, i.e., the self background is reduced. This increases the activation probabilities of single T-cells in the presence of non-self antigens.

q-bio.CB↗

Variation in Microbial Growth under Hypergravity

We report bacterial growth under hypergravitational stress. Cultures of E. coli and B. subtilis were subjected to the gravitational stress (38g) and their growth curves were measured using UV-VIS spectrophotometer. Experiments were also carried out to investigate nutrient consumption under hypergravitational conditions. Our results show considerable difference between samples subjected to hypergravity and normal conditions. This study has importance to understand bacterial response to external stress factors like gravity and changes in bacterial system in order to adapt with stress conditions for its survival.

q-bio.CB↗

Numerical study of cancer cell invasion dynamics using adaptive mesh refinement: the urokinase model

In the present work we investigate the chemotactically and proteolytically driven tissue invasion by cancer cells. The model employed is a system of advection-reaction-diffusion equations that features the role of the serine protease urokinase-type plasminogen activator. The analytical and numerical study of this system constitutes a challenge due to the merging, emerging, and travelling concentrations that the solutions exhibit. Classical numerical methods applied to this system necessitate very fine discretization grids to resolve these dynamics in an accurate way. To reduce the computational cost without sacrificing the accuracy of the solution, we apply adaptive mesh refinement techniques, in particular h-refinement. Extended numerical experiments exhibit that this approach provides with a higher order, stable, and robust numerical method for this system. We elaborate on several mesh refinement criteria and compare the results with the ones in the literature. We prove, for a simpler version of this model, $L^\infty$ bounds for the solutions, we study the stability of its conditional steady states, and conclude that it can serve as a test case for further development of mesh refinement techniques for cancer invasion simulations.

math.NA↗

Transition to diversification by competition for resources in catalytic reaction networks

All life, including cells and artificial protocells, must integrate diverse molecules into a single unit in order to reproduce. Despite expected pressure to evolve a simple system with the fastest replication speed, the mechanism by which the use of the great variety of components, and the coexistence of diverse cell-types with different compositions are achieved is as yet unknown. Here we show that coexistence of such diverse compositions and cell-types is the result of competitions for a variety of limited resources. We find that a transition to diversity occurs both in chemical compositions and in protocell types, as the resource supply is decreased, when the maximum inflow and consumption of resources are balanced.

q-bio.CB↗

Lymphocyte repertoire selection and intracellular self/not-self discrimination: historical overview

Immunological self/not-self discrimination is conventionally seen as an extracellular event, involving interactions been receptors on T cells pre-educated to discriminate, and peptides bound to major histocompatibility complex proteins (pMHCs). Mechanisms by which not-self peptides might first be sorted intracellularly to distinguish them from the vast excess of self-peptides have long been called for. Recent demonstrations of endogenous peptide-specific clustering of pMHCs on membrane rafts are indicative of intracellular enrichment before surface display. The clustering could follow the specific aggregation of a foreign protein that exceeded its solubility limit in the crowded intracellular environment. Predominantly entropy-driven, this homoaggregation would co-localize identical peptides, so facilitating their collective presentation. Concentrations of self-proteins are fine-tuned over evolutionary time to avoid this. Disparate observations, such as pyrexia, and female susceptibility to autoimmune disease, can be explained in terms of the need to cosegregate cognate pMHC complexes internally prior to extracellular display.

q-bio.CB↗

Bacterial fitness shapes the population dynamics of antibiotic-resistant and -susceptible bacteria in a model of combined antibiotic and anti-virulence treatment

Bacterial resistance to antibiotic treatment is a huge concern: introduction of any new antibiotic is shortly followed by the emergence of resistant bacterial isolates in the clinic. This issue is compounded by a severe lack of new antibiotics reaching the market. The significant rise in clinical resistance to antibiotics is especially problematic in nosocomial infections, where already vulnerable patients may fail to respond to treatment, causing even greater health concern. A recent focus has been on the development of anti-virulence drugs as a second line of defence in the treatment of antibiotic-resistant infections. This treatment, which weakens bacteria by reducing their virulence rather than killing them, should allow infections to be cleared through the body's natural defence mechanisms. In this way there should be little to no selective pressure exerted on the organism and, as such, a predominantly resistant population would be unlikely to emerge. However, much controversy surrounds this approach with many believing it would not be powerful enough to clear existing infections, restricting its potential application to prophylaxis. We have developed a mathematical model that provides a theoretical framework to reveal the circumstances under which anti-virulence drugs may or may not be successful. We demonstrate that by harnessing and combining the advantages of antibiotics with those provided by anti-virulence drugs, given infection-specific parameters, it is possible to identify treatment strategies that would efficiently clear bacterial infections, while preventing the emergence of resistant subpopulations. Our findings strongly support the continuation of research into anti-virulence drugs and demonstrate that their applicability may reach beyond infection prevention.

q-bio.CB↗

Modeling the dynamics of hypoxia inducible factor-1α (HIF-1α) within single cells and 3D cell culture systems

HIF (Hypoxia Inducible Factor) is an oxygen-regulated transcription factor that mediates the intracellular response to hypoxia in human cells. There is increasing evidence that cell signaling pathways encode temporal information, and thus cell fate may be determined by the dynamics of protein levels. We have developed a mathematical model to describe the transient dynamics of the HIF-1α protein measured in single cells subjected to hypoxic shock. The essential characteristics of these data are modeled with a system of differential equations describing the feedback inhibition between HIF-1α and Prolyl Hydroxylases (PHD) oxygen sensors. Heterogeneity in the single-cell data is accounted for through parameter variation in the model. We previously identified the PHD2 isoform as the main PHD responsible for controlling the HIF-1α transient response, and make here testable predictions regarding HIF-1α dynamics subject to repetitive hypoxic pulses. The model is further developed to describe the dynamics of HIF-1α in cells cultured as 3D spheroids, with oxygen dynamics parameterized using experimental measurements of oxygen within spheroids. We show that the dynamics of HIF-1α and transcriptional targets of HIF-1α display a non-monotone response to the oxygen dynamics. Specifically we demonstrate that the dynamic transient behavior of HIF-1α results in differential dynamics in transcriptional targets.

q-bio.CB↗

Remodeling of Fibrous Extracellular Matrices by Contractile Cells: Predictions from Discrete Fiber Network Simulations

Contractile forces exerted on the surrounding extracellular matrix (ECM) lead to the alignment and stretching of constituent fibers within the vicinity of cells. As a consequence, the matrix reorganizes to form thick bundles of aligned fibers that enable force transmission over distances larger than the size of the cells. Contractile force-mediated remodeling of ECM fibers has bearing on a number of physiologic and pathophysiologic phenomena. In this work, we present a computational model to capture cell-mediated remodeling within fibrous matrices using finite element based discrete fiber network simulations. The model is shown to accurately capture collagen alignment, heterogeneous deformations, and long-range force transmission observed experimentally. The zone of mechanical influence surrounding a single contractile cell and the interaction between two cells are predicted from the strain-induced alignment of fibers. Through parametric studies, the effect of cell contractility and cell shape anisotropy on matrix remodeling and force transmission are quantified and summarized in a phase diagram. For highly contractile and elongated cells, we find a sensing distance that is ten times the cell size, in agreement with experimental observations.

q-bio.CB↗

Why so many sperm cells?

A key limiting step in fertility is the search for the oocyte by spermatozoa. Initially, there are tens of millions of sperm cells, but a single one will make it to the oocyte. This may be one of the most severe selection processes designed by evolution, whose role is yet to be understood. Why is it that such a huge redundancy is required and what does that mean for the search process? we propose to discuss here these questions and consequently a new line of interdisciplinary research needed to find possible answers.

q-bio.CB↗

Hydrodynamical random walker with chemotactic memory

A three-dimensional hydrodynamical model for a micro random walker is combined with the idea of chemotactic signaling network of E. coli. Diffusion exponents, orientational correlation functions and their dependence on the geometrical and dynamical parameters of the system are analyzed numerically. Because of the chemotactic memory, the walker shows superdiffusing displacements in all directions with the largest diffusion exponent for a direction along the food gradient. Mean square displacements and orientational correlation functions show that the chemotactic memory washes out all the signatures due to the geometrical asymmetry of the walker and statistical properties are asymmetric only with respect to the direction of food gradient. For different values of the memory time, the Chemotactic index (CI) is also calculated.

cond-mat.soft↗

Cellular Uptake and Biocompatibility of Bismuth Ferrite Harmonic Advanced Nanoparticles

Bismuth Ferrite (BFO) nanoparticles (BFO-NP) display interesting optical (nonlinear response) and magnetic properties which make them amenable for bio-oriented applications as intra- and extra membrane contrast agents. Due to the relatively recent availability of this material in well dispersed nanometric form, its biocompatibility was not known to date. In this study, we present a thorough assessment of the effects of in vitro exposure of human adenocarcinoma (A549), lung squamous carcinoma (NCI-H520), and acute monocytic leukemia (THP-1) cell lines to uncoated and poly(ethylene glycol)-coated BFO-NP in the form of cytotoxicity, haemolytic response and biocompatibility. Our results support the attractiveness of the functional-BFO towards biomedical applications focused on advanced diagnostic imaging.

q-bio.CB↗

Replicator Dynamics of of Cancer Stem Cell; Selection in the Presence of Differentiation and Plasticity

Stem cells have the potential to produce lineages of non-stem cell populations (differentiated cells) via a ubiquitous hierarchal division scheme. Differentiation of a stem cell into (partially) differentiated cells can happen either symmetrically or asymmetrically. The selection dynamics of a mutant cancer stem cell should be investigated in the light of a stem cell proliferation hierarchy and presence of a non-stem cell population. By constructing a three-compartment Moran-type model composed of normal stem cells, mutant (cancer) stem cells and differentiated cells, we derive the replicator dynamics of stem cell frequencies where asymmetric differentiation and differentiated cell death rates are included in the model. We determine how these new factors change the conditions for a successful mutant invasion and discuss the variation on the steady state fraction of the population as different model parameters are changed. By including the phenotypic plasticity/dedifferentiation, in which a progenitor/differentiated cell can transform back into a cancer stem cell, we show that the effective fitness of mutant stem cells is not only determined by their proliferation and death rates but also according to their dedifferentiation potential. By numerically solving the model we derive the phase diagram of the advantageous and disadvantageous phases of cancer stem cells in the space of proliferation and dedifferentiation potentials. The result shows that at high enough dedifferentiation rates even a previously disadvantageous mutant can take over the population of normal stem cells. This observation has implications in different areas of cancer research including experimental observations that imply metastatic cancer stem cell types might have lower proliferation potential than other stem cell phenotypes while showing much more phenotypic plasticity and can undergo clonal expansion.

q-bio.CB↗

Colored Correlated Noises in Growth Model of Tumor

Stochastic resonance induced by external factor is considering to investigate the complex dynamics of tumor. The surrounding environment and the treatment effects on the tumor growth are considered as additive and multiplicative noises in growth model. The adaptability of tumor to treatment is presented by correlation of these two noises. The Fokker-Plank equation is deduced to study the probability distribution function and mean number of tumor cells in different conditions. The mean number of tumor cells can be controlled by the correlation and intensity of noises.

q-bio.CB↗